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                     UNITED STATES OF AMERICA

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                   FOOD AND DRUG ADMINISTRATION

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          CENTER FOR DEVICES AND RADIOLOGICAL HEALTH

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                 MEDICAL DEVICES ADVISORY COMMITTEE

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                    MICROBIOLOGY DEVICES PANEL

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                                MEETING
                             OPEN SESSION

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                                 FRIDAY

                          OCTOBER 12, 2001

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                   The   panel     met    in    Salons   A-C    of      the

Gaithersburg Hilton, 620 Perry Parkway, Gaithersburg,

Maryland, at 9:00 a.m., Dr. Michael L. Wilson, Chairman,

presiding.

PRESENT:

MICHAEL L. WILSON, M.D., Chairman

ELLEN JO BARON, Ph.D., Temporary Voting Member

KATHLEEN G. BEAVIS, M.D., Member

KAREN C. CARROLL, M.D., Consultant


                              NEAL R. GROSS
                      COURT REPORTERS AND TRANSCRIBERS
                          1323 RHODE ISLAND AVE., N.W.
(202) 234-4433           WASHINGTON, D.C. 20005-3701     www.nealrgross.com
                                                                         2
PRESENT (continued):

PATRICIA CHARACHE, M.D., Consultant

FRANKLIN R. COCKERILL III, M.D., Consultant

DAVID T. DURACK, M.D., Ph.D., Industry Representative

JANINE JANOSKY, Ph.D., Consultant

DAVID M. LEWINSOHN, M.D., Ph.D., Guest

VALERIE L. NG, Ph.D., Member

FREDERICK C. NOLTE, Ph.D., Temporary Voting Member

L. BARTH RELLER, M.D., Temporary Voting Member

STANLEY M. REYNOLDS, Consumer Representative

NATALIE L. SANDERS, M.D., M.P.H., M.B.A., Member

FREDDIE M. POOLE, Executive Secretary




                         NEAL R. GROSS
                 COURT REPORTERS AND TRANSCRIBERS
                     1323 RHODE ISLAND AVE., N.W.
(202) 234-4433      WASHINGTON, D.C. 20005-3701     www.nealrgross.com
                                                                         3
                      C-O-N-T-E-N-T-S


Opening Remarks .................................... 5


Introductions ...................................... 5


Presentation by Manufacturer, Cellestis Limited

   Introductions ................................... 10
     Dr. Jim Rothel

   TB Diagnosis: Current Situation and
   Medical Need .................................... 14
     Dr. Antonino Catanzaro

   Scientific Basis of the Test .................... 23
     Dr. Paul Wood

   Development and Clinical Studies ................ 30
     Dr. Jim Rothel

Questions from Panel Members ...................... 46



Presentation by FDA

   QFT Performance Characterization ................ 85
     Roxanne G. Shively
     Senior Scientific Reviewer
     Bacteriology Devices Branch
     Division of Clinical Laboratory Devices

   Clinical Use of QFT Results ..................... 97
     Leonard V. Sacks, M.D.
     Senior Staff Fellow
     Divisions of Special Pathogens and
     Immunologic Drug Products
     CDER

   Statistical Analysis of Data ................... 111
     John L. Dawson, MS, JD
     Mathematical Statistician
     Division of Biostatistics
     Office of Surveillance and Biometrics
     CDRH


                         NEAL R. GROSS
                 COURT REPORTERS AND TRANSCRIBERS
                     1323 RHODE ISLAND AVE., N.W.
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                                                                           4
                 C-O-N-T-E-N-T-S (Continued)



Questions from Panel Members ..................... 120


Public Comments

   JAMES B McAULEY ................................ 132
   Medical Director, Cermak
   Cook County Jail, Illinois

   STANLEY H. REYNOLDS ............................ 142
   State Department of Health
   Laboratory in Pennsylvania
   On Behalf of:
   William Barry
   Director, TB Control Program
   Commonwealth of Pennsylvania


Open Committee Discussion ........................ 144

Open Public Hearing .............................. 193

Industry Response ................................ 194

FDA Response ..................................... 195

Final Recommendations and Vote ................... 208

Adjournment ...................................... 211




                           NEAL R. GROSS
                   COURT REPORTERS AND TRANSCRIBERS
                       1323 RHODE ISLAND AVE., N.W.
(202) 234-4433        WASHINGTON, D.C. 20005-3701     www.nealrgross.com
                                                                                   5
1                              P-R-O-C-E-E-D-I-N-G-S

2                                  OPEN SESSION

3                                                             (9:00 a.m.)

4                        CHAIRMAN WILSON:      I'd like everyone to take

5    their seats at this time, please, so we can begin.

6                        Good morning.     I'd like to welcome everyone

7    to the meeting of the Microbiology Devices Panel this

8    morning.         I'm Dr. Michael Wilson.         I'm the Chair of the

9    panel from the University of Colorado and Denver Health

10   Medical Center.

11                       I'd like to begin the meeting this morning

12   by having the panel members introduce themselves.                        If

13   we could go around, just please state your name and your

14   affiliation.         We could start with Dr. Durack.

15                       DR.   DURACK:      Good morning.        I'm David

16   Durack.          I'm the industry representative on the panel,

17   and I'm affiliated with Beckon Dickinson and also with

18   Duke University.

19                       MR. REYNOLDS:      Good morning.      I'm Stanley

20   Reynolds.         I'm the consumer representative on the panel.

21    I'm Supervisor of Immunology and Virology for the

22   Pennsylvania State Public Health Laboratory.

23                       DR. CHARACHE:      I'm Patricia Charache.           I'm

24   affiliated with Johns Hopkins University, a former panel

25   member, and a consultant for this panel.

                                    NEAL R. GROSS
                           COURT REPORTERS AND TRANSCRIBERS
                               1323 RHODE ISLAND AVE., N.W.
     (202) 234-4433           WASHINGTON, D.C. 20005-3701     www.nealrgross.com
                                                                                      6
1                      DR. BARON:         I'm Ellen Jo Baron with the

2    Department        of    Pathology      and     Medicine    at     Stanford

3    University, and I am the Director of the Microbiology

4    and Virology Laboratory, Stanford University Medical

5    Center.

6                      DR. CARROLL:           Good morning.          I'm Karen

7    Carroll.         I'm Associate Professor of Pathology at the

8    University of Utah School of Medicine and the Director

9    of Microbiology Laboratories at ARUP Labs, Incorporated,

10   in Salt Lake City.

11                     DR. SANDERS:         Good morning.        I'm Natalie

12   Sanders, a general internist with Southern California

13   Permanente Medical Group, also known as Kaiser, and I

14   am on the clinical faculty at the University of Southern

15   California.

16                     DR. NG:     Good morning.        I'm Valerie Ng.         I'm

17   Professor        and    Interim     Chair     of   the    Department        of

18   Laboratory Medicine at UC-San Francisco.                   I'm also the

19   Director of the clinical laboratories at San Francisco

20   General Hospital.

21                     MS. POOLE:       I'm Freddie Poole, the Executive

22   Secretary and Branch Chief for Bacteriology Devices.

23                     DR. BEAVIS:         Good morning.        I'm Kathleen

24   Beavis, the Director of the Microbiology and Virology

25   Laboratories at Cook County Hospital in Chicago.

                                    NEAL R. GROSS
                            COURT REPORTERS AND TRANSCRIBERS
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                                                                                         7
1                         DR. JANOSKY:         Janine Janosky, Associate

2    Professor, Division of Biostatistics, Department of

3    Family           Medicine   and    Clinical       Epidemiology,        at     the

4    University of Pittsburgh.

5                         DR. NOLTE:      Good morning.         Frederick Nolte,

6    Emory University School of Medicine, Department of

7    Pathology and Laboratory Medicine, where I'm Director

8    of the Clinical Micrology and Molecular Diagnostics Lab.

9                         DR. RELLER:        Barth Reller, Professor of

10   Medicine, Pathology, Division of Infectious Diseases,

11   and Director of Clinical Microbiology, Duke University

12   Medical Center.

13                        DR. LEWINSOHN:          I'm David Lewinsohn.             I'm

14   an     Assistant        Professor       at    Oregon       Health     Sciences

15   University and have a laboratory that's focused on TB

16   T-cell immunology.

17                        DR.    COCKERILL:          I'm    Frank        Cockerill,

18   Professor and Chair of Microbiology at Mayo Clinic, also

19   Professor of Medicine and Infectious Disease Specialist

20   at Mayo Clinic.

21                        DR. GUTMAN:      I'm Steve Gutman.        I'm Director

22   of the Division of Clinical Laboratory Devices, FDA.

23                        CHAIRMAN WILSON:         Thank you.

24                        At this time I would like to have Ms. Poole

25   read the conflict-of-interest statements.

                                       NEAL R. GROSS
                             COURT REPORTERS AND TRANSCRIBERS
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                                                                                       8
1                      MS. POOLE:        Good morning.

2                      The     following          announcement        addresses

3    conflicts-of-interest              issues       associated     with       this

4    meeting and is made a part of the record to preclude even

5    the         appearance        of        an      impropriety.                The

6    conflict-of-interest               statute        prohibits         special

7    government employees from participating in matters that

8    could        affect   their    or       their    employees'      financial

9    interest.        To determine if any conflict exists, the

10   agency reviewed the submitted agenda and all financial

11   interests reported by the Committee participants.                           The

12   agency has no conflicts to report.

13                     In the event that the discussions involve

14   any other products or firms not already on the agenda

15   for which an FDA participant has a financial interest,

16   the participant should excuse him or herself from such

17   involvement, and the exclusion will be noted for the

18   record.

19                     With respect to all other participants, we

20   ask that in the interest of fairness all persons making

21   statements or presentations disclose any current or

22   previous financial involvement with any firm whose

23   products they may wish to comment upon.

24                     CHAIRMAN WILSON:           Thank you.

25                     A   couple       of    brief    housekeeping        items:

                                   NEAL R. GROSS
                           COURT REPORTERS AND TRANSCRIBERS
                               1323 RHODE ISLAND AVE., N.W.
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                                                                                             9
1    Please, if you have a cell phone, a pager, or any other

2    device that makes noise, I'd ask you to turn it off during

3    the meeting, so as not to distract the proceedings.

4                          The other thing is that, because of the time

5    required to get to the airports now, several panel members

6    reported they have to leave right at or in the middle

7    of the afternoon session.                   So we're going to try to keep

8    on schedule as much as we can today.                        Otherwise, we may

9    lose our quorum late in the afternoon.

10                         The other thing is, when you come to the

11   microphone            to    speak,     if     you   could      please    identify

12   yourself.

13                         The item of new business today is a pre-market

14   approval application from Cellestis Limited for the

15   QuantiFERON-TB.               This is an in vitro diagnostic device

16   for measuring the release of gamma interferon from

17   sensitized lymphocytes in PPD-stimulated whole blood.

18   This product is intended as an aid in the diagnosis of

19   latent           TB   infection       and     to    aid   in     evaluation        of

20   individuals            suspected         of     having      M.    tuberculosis

21   infection.

22                         I would ask all the panel members to hold

23   their questions until after the four presentations by

24   the sponsor.               I would like to remind the members of the

25   audience that only the panel can ask questions of the

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                                                                             10
1    speakers.

2                     So at this time I would like to have Dr. Rothel

3    begin.

4                     DR. ROTHEL:       Hi.     I'm Jim Rothel.          I am

5    employed by Cellestis Limited as the Chief Scientific

6    Officer and Executive Director, and I own stock in

7    Cellestis Limited.

8                     I'd first like to take this opportunity to

9    thank the panel members for coming today, but especially

10   those that had to fly here in these turbulent times.

11   It's not a great experience just at the moment.

12                    This first slide is to give you an outline

13   of our presentation today.             I'm going to give a brief

14   introduction, and then Professor Tony Catanzaro is going

15   to talk about the current diagnostic methods for TB and

16   limitations of those methods.            Then Professor Paul Wood

17   will get up and talk about the scientific basis behind

18   the QuantiFERON technology, and we'll also talk about

19   the bovine model of the QuantiFERON test.              Then I'll come

20   back and talk about the development studies and the

21   clinical studies that we're using to base the PMA

22   submission on.

23                    First, this next slide gives us a history

24   of the development of the test.                   It was initially

25   developed in the mid to late eighties by the Australian

                                 NEAL R. GROSS
                         COURT REPORTERS AND TRANSCRIBERS
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                                                                                 11
1    Government's research body, CSRO, for the detection of

2    TB in cattle.      At that time CSRO got an Australian company

3    called CSL Limited as a commercial partner, and they went

4    on to successfully develop this product into a commercial

5    product which is now sold around the world.

6                     Given the success of the bovine test, they

7    then went on to develop a human version of the test, which

8    is called QuantiFERON-TB.             There's a large amount of

9    pre-clinical       and     clinical       studies      in       Australia

10   establishing the test cutoffs and the various parameters

11   of the test.

12                    Then the large-scale, pivotal studies that

13   we're using to support our PMA application were conducted

14   by two U.S. Government bodies, the CDC and the Walter

15   Reed Army Institute of Research, which I'll refer to as

16   WRAIR from now on for simplicity.                We'll present that

17   later.

18                    I should say the technology is now owned by

19   Cellestis Limited.

20                    This slide is a very simple schematic of the

21   methodology of the test.           It's simple because the test

22   is simple.       How the test is conducted is a heparinized

23   blood sample is collected from individuals and four 1

24   ml aliquots of blood are pipetted into four different

25   wells of a 24-well culture tray.

                                 NEAL R. GROSS
                         COURT REPORTERS AND TRANSCRIBERS
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                                                                                      12
1                       Then      this      whole      blood     --      it's        not

2    diluted -- we add the antigens to it.                 The first antigen

3    is a negative control, which is basically PBS.                      The second

4    well is tuberculin from Mycobacterium tuberculosis, and

5    we'll refer to that as human PPD from now on.                        The third

6    well is tuberculin from Mycobacterium avium, and we'll

7    call       that     avian     PPD.         The     fourth        well      is         a

8    mitogen-positive control for each individual, and that

9    consists of a submaximal amount of phyto hemagglutinin.

10                      Once these antigens are added to the blood,

11   the plate is put in an incubator overnight at 37 degrees

12   for 16 to 24 hours.            During this period if there are any

13   T-cells          present     in     that   blood     that        respond         to

14   mycobacterial antigens -- i.e., if the person has been

15   exposed to mycobacteria -- they're responding in many

16   different ways.            But the main one that we're talking about

17   is the secretion of gamma interferon into the plasma.

18                      The next day the red cells are settled down

19   in the 24 wells, and what you simply have is the plasma

20   off the top and then assay for the presence of gamma

21   interferon produced in each of those four plasma samples

22   by a rapid EIA for gamma interferon.                  We're saying it's

23   rapid.           There's only one incubation step where you

24   incubate the plasma and the conjugate at the same time

25   following by a washing step and adding substrate.

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                                                                                    13
1                           This slide just depicts the type of test

2    interpretation profile we should get.                       We'll go into

3    detail a little bit later exactly how the test is

4    interpreted.

5                           But an individual who is negative in the

6    QuantiFERON test will not respond to the nil antigen,

7    to the human PPD, or to the avian PPD to any substantial

8    amount           and    will   have    a    robust     response       to      the

9    mitogen-positive control.

10                          A person in whom the test indicates MTG

11   infection will have a strong response to human PPD and

12   also some response to avian PPD, but to a lesser extent.

13    This       is     due    to   the    cross-reactive        nature     of     the

14   tuberculin antigens in general between the two species.

15    And, again, a response to mitogen.

16                          The person who has reactivity to atypical

17   mycobacteria or mycobacteria other than tuberculosis,

18   or MTRs we'll refer to them throughout the talk, will

19   have the inverse of that response, where the predominant

20   response to the PPD's will be against avian PPD.

21                          The mitogen-positive control also serves as

22   a control for the quality of the blood sample to be able

23   to produce gamma interferon or also energy perhaps.                            An

24   individual in whom a mitogen response is not detectable,

25   a test result cannot be obtained for that individual.

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                                                                                14
1    That's a very rare event.

2                        So I'll just leave you with the intended use

3    and put it upfront. The QuantiFERON test is intended as

4    an aid, and that's an aid in the detection of infection

5    with Mycobacterium tuberculosis.

6                        After that brief introduction, I would like

7    to pass it over to Tony Catanzaro to talk about the current

8    diagnostic methods.

9                        DR. CATANZARO:        Good morning.      My name is

10   Tony Catanzaro.          I'm with the University of California

11   at San Diego.         I've been working on tuberculosis for over

12   30 years, since my introduction to TB in the TB Branch

13   of CDC.          Since then, I have been working with CDC on a

14   number of projects.

15                       One of the projects that I did with CDC

16   recently was to work on QuantiFERON.                 Because of my work

17   with QuantiFERON, Cellestis asked me to join the Board

18   of Directors, and I'm now a stockholder in the company

19   Cellestis and want to disclose that.

20                       But I'm here to talk to you about the clinical

21   aspects of tuberculosis.               I want to start by pointing

22   out that the prestigious Institute of Medicine recently

23   published a very important report.                 In that report they

24   cite that the greatest need in the control of tuberculosis

25   in the United States is a new diagnostic tool to account

                                    NEAL R. GROSS
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                                                                               15
1    for individuals who have latent tuberculosis.

2                       The reason they focused on that is that CDC

3    has led the charge, and that charge has been joined by

4    the public health community in general, pointing out the

5    way that the identification and treatment of latent

6    tuberculosis infection is the best way to interrupt the

7    transmission of tuberculosis, by preventing active cases

8    from developing from those latent infections.

9                       The diagnosis of latent tuberculosis is not

10   a particularly simple task.             People have said over and

11   over       in    talking   about    this     particular     test,        the

12   QuantiFERON test, that there's no gold standard, and I'm

13   not exactly convinced of that.               It's true there's not

14   a gold standard from a diagnostic or a device point of

15   view, but clinicians are, in fact, able to diagnose latent

16   tuberculosis.

17                      They do this by taking into account the

18   history of the patient and the possible exposure of that

19   patient, the epidemiologic status, socioeconomic status,

20   and clinical findings -- all that together with the

21   cell-mediated immune response to tuberculosis.                     That's

22   what we're talking about here today, one aspect of the

23   diagnosis,         specifically,      the     cell-mediated        immune

24   response to tuberculin.

25                      That cell-mediated immune response or that

                                  NEAL R. GROSS
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                                                                                     16
1    TB sensitivity has been measured for 100 years now by

2    the tuberculin skin test, initially developed by Robert

3    Koch and made better by George Comstock and the CDC by

4    a very specific algorithm that's been used.                       That's the

5    basis that clinicians use to diagnosis tuberculin skin

6    test sensitivity.

7                           However, researchers have been very busy for

8    the past couple of decades developing other aspects, other

9    approaches              to      identifying        T-cell       reactivity;

10   specifically,                lymphocyte     proliferation,          cytotoxic

11   lymphocyte assays, and the measurement of cytokine

12   expression.

13                          When we look at the tuberculin skin test,

14   I think that the community has done a great job of taking

15   a very old and imprecise technique and really learning

16   how to use it.           But I think when we compare the tuberculin

17   skin test with the QuantiFERON-TB, we have to keep in

18   mind the fact that the tuberculin skin test is a very,

19   very complex thing with a lot of little points that a

20   lot of attention has to be paid to.

21                          You    have   to    be   careful      about     antigen

22   handling, about antigen deposition in the skin, about

23   reading          the    tuberculin        delay-type        hypersensitivity

24   response, which is inherently an inflammatory response

25   locally.         It peaks at 48 to 72 hours.                The patient has

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                                                                                 17
1    to return for interpretation, and there are almost always

2    reactions to the antigen.              That's what it's all about.

3     That       reaction    is    what    you   read,     and   occasionally

4    vesiculation and necrosis occur.                    So there are some

5    adverse effects from that antigen preparation.

6                     We've learned to use the tuberculin skin test

7    to a good effect in identifying people who have latent

8    tuberculosis.          I think it's important to recognize that

9    there are some shortcomings from a false negative point

10   of view specifically when we come to the diagnosis of

11   active tuberculosis.             Ten to 15        percent of cases of

12   active tuberculosis have a negative tuberculin skin test,

13   giving us a sensitivity not of 100 percent, but in fact

14   closer to 50 or 90 percent -- in part, because tuberculosis

15   is itself an immunosuppressive disease and in part because

16   of some inherent deficiencies of the tuberculin skin test.

17                    Some of those deficiencies revolve around

18   the application.           Again, you have to apply it just to

19   the intradermal layer.               If it's too deep, the antigen

20   is picked up by blood flow and it's not there 48 hours

21   later for a delayed-type hypersensitivity reaction to

22   occur with.

23                    There are also problems with the handling

24   and storage of PPD.            Finally, the immune status of the

25   patient, even patients who appear to be immuno-intact,

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                                                                              18
1    may be immunosuppressed to some extent.               All these cause

2    false negative reactions.

3                     But the major problems with tuberculin skin

4    tests are in another area.           Specifically, the test has

5    to be given and patients need to return for a reading.

6     That's a problem.        In many settings -- myself, I'm at

7    UCSD Med Center and I run the TB control Lab and I run

8    the skin testing lab.       We have well-trained technicians,

9    highly motivated individuals.            About 30 percent of our

10   patients do not return for their reading of the tuberculin

11   skin test.

12                    So the antigen is placed.             All the costs

13   involved in that are undertaken, but the information is

14   not harvested.       That's not a unique experience.                  That

15   happens in many situations.           Patients do not return for

16   tuberculosis skin test reading.

17                    Some people say, well, gee, you know, if

18   you're only using it to identify latent TB and they can't

19   come back for the reading, are they going to come back

20   for the treatment?       Well, that is a problem, but that's

21   only part of the problem.        There's also the epidemiology.

22    There's also understanding how much is tuberculosis a

23   problem in this population.            You simply don't know if

24   30 percent of the readings aren't made.               Not to mention

25   the cost implications of not only applying the skin test,

                                NEAL R. GROSS
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                                                                                  19
1    but followup and re-followup.                These are major problems.

2                         There are a number of inaccuracies in the

3    measurement of induration.                 Measuring the size of a bump

4    in the skin is inherently imprecise.                       Often we have

5    inexperienced operators.                Anybody feels they can read

6    the amount induration, but to read it accurately, to read

7    it within the limits that CDC would like of plus or minus

8    2 millimeters is not so easy.

9                         But even under the best of circumstances,

10   a 2-millimeter difference is a significant difference.

11    That imparts another problem, which is subjectivity.

12   There's a lot of subjectivity in reading a skin test.

13   This has been demonstrated.                    There are a number of

14   preferences.           Some of these biases are conscious and some

15   of the biases are unconscious and very difficult to

16   control.

17                        There are also false positive tuberculin skin

18   tests due to BCG, mycobacteria other than tuberculosis,

19   particularly avium.                These are very common in the

20   populations that we're trying to deal with latent TB.

21                        The whole southeastern United States has a

22   tremendous problem with hypersensitivity to mycobacteria

23   avium.           BCG is very commonly used in many countries from

24   which        immigrants      come     to    the   United    States,         and

25   tuberculosis or reactivation of tuberculosis in the

                                     NEAL R. GROSS
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1    immigrant population is a major problem in the U.S. today.

2     At least 50 percent of the new active cases develop in

3    immigrant populations.          So this is the target of the

4    latent TB focus and this is a problem for the reading

5    of      identification     of    patients       who   have      latent

6    tuberculosis infection.

7                     I want to talk about the discordance.                I'd

8    like to direct your attention to this slide because it's

9    really quite important.           We have two products on the

10   market that are approved by the FDA for tuberculin skin

11   test antigens, specifically Tubersol and Aplisol.                   They

12   were recently studied by Dr. Villarino from the CDC, and

13   a publication in JAMA describes that these two antigens

14   are equivalent and can be used both to measure tuberculin

15   skin test reactivity.

16                    But look at the results that were obtained

17   here initially in a low-risk population, 1,555 patients.

18    This is with equivalence.         We have 10 who had a positive

19   to     Aplisol   and   a   positive     to   tuberculin,     and      the

20   discordance was 3 and 18 with a Kappa of 0.48.                    Under

21   most circumstances one would be a little bit concerned

22   about saying that those are equivalent, but in fact they

23   are.

24                    The   reason    they     are    is   because       it's

25   recognized by the manufacturers, by the FDA, by the

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1    scientific community, that the tuberculin skin test is

2    not a precise measurement.              You cannot get 100 percent

3    agreement.           This,   a   Kappa     of    .48,    is     considered

4    agreement.

5                       The same thing is true in another population

6    of patients with current tuberculosis.                   The Kappa there

7    was 0.5.         I only point this out to help you understand

8    that, yes, tuberculin skin test is the best we have, but

9    there's a lot of room for improvement there.

10                      So I'd like to point out to you the advantages

11   that I, as a clinician, see for the QuantiFERON-TB test.

12    I see us moving from the tuberculin skin test to an

13   objective measurement which is controlled laboratory

14   test, which has a lot of precision built into it and has

15   the opportunity for much better quality control than the

16   whole setup of tuberculin skin test provides for us.

17                      It offers the advantage of a single patient

18   contact.         We'll be able to get the information as to what

19   the tuberculin skin test reactivity in our population

20   is with one visit.

21                      There are no adverse reactions to tuberculin,

22   and this may seem trivial, but in the patients who are

23   reactive to tuberculin they always get pain, discomfort,

24   irritation, whatever.

25                      Finally, the test has a built-in control for

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1    reactivity to mycobacteria other than tuberculosis, and

2    I think that's a tremendous clinical advantage.

3                      So, in conclusion, the tuberculin skin test

4    is the only currently approved method to identify T-cell

5    reactivity to tuberculin.           QuantiFERON-TB solves several

6    important limitations of the tuberculin skin test.

7    QuantiFERON-TB provides an additional tool for clinicians

8    for       the    identification        of     T-cell    reactivity        to

9    tuberculin.

10                     Finally, clinicians need to have all the

11   available        information      to        interpret   the     clinical

12   significance of T-cell reactivity to tuberculin.                    I want

13   to emphasize that the diagnosis of latent tuberculosis

14   infection is an exercise in clinical medicine, and by

15   definition it requires incorporation of the patient's

16   history, the patient's membership in epidemiologic and

17   socioeconomic status, the physical examination, and an

18   evaluation of tuberculin skin test sensitivity, which

19   can be done classically with a regular skin test and,

20   alternatively, what we're here to talk about today, the

21   QuantiFERON-TB test.

22                     Thank you for your attention.            I'd like to

23   turn the podium over now to my colleague, Paul Wood, who

24   will talk about the scientific basis of the QuantiFERON-TB

25   test.

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1                       DR. WOOD:     Thank you, Tony.

2                       My name is Paul Wood.           I was the original

3    inventor of the technology behind QuantiFERON when I

4    worked for CSRO back in the 1990's.                 I now work for CSL

5    Limited, and through them I act as a consultant to

6    Cellestis, and I have stock in the company.

7                       I want to take you back a bit to when we

8    started.         What do we know about mycobacterial infections?

9     Well, one of the things we know is that they induce very

10   strong T-cell responses, one of the distinctions about

11   mycobacterial infections.                This is the reason that

12   tuberculin or the tuberculin skin test has been used so

13   many years.         We also know that that T-cell reactivity

14   is generated fairly early in infection, and generally

15   maintained for the life of the infection.

16                      On the other hand, we know that antibody tends

17   to come up light in infection and it's more mirrored with

18   the mycobacterial load.             So when we started off it was

19   obvious for us to look for another measure T-cell-mediated

20   immunity, in this case to look for an in vitro assay.

21                      Bovine TB is a very good model for human TB.

22    This is a natural infection, respiratory infection, of

23   an organism in bovis closely related to M. tuberculosis,

24   and, of course, in the early part of the last century,

25   a major infectious disease of humans.               The immunoresponse

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1    in cattle is very similar to what we see in human,

2    predominantly a cellular response.

3                           Most cattle that we see now, if you class

4    it as having a disease or an infection like LTB, we seldom

5    see generalized TB in animals.                        The majority of the

6    animals that we detect have single lesions in a lymph

7    node.

8                           Similar to what you see in humans, we do see

9    active           TB.        Often    it's    in    older       animals     and     in

10   undernourished animals.                   The tuberculin test has also

11   been used in cattle for over 100 years.                           In this case

12   we use in bovis PPD.                 It's injected intradermally.                  In

13   Australia we use the caudal fold.

14                          In Europe, in particular, because of the

15   rates of exposure to other mycobacteria, avium is used

16   in comparative tests.                So it's comparative testing that's

17   used extensively in Europe.                       So I contend that we've

18   actually got a very good model for human TB.

19                          So    why    choose     interferon        gamma     as     the

20   molecule we're going to measure?                       One of the tasks we

21   were given is to find a test that you could test 500 to

22   1,000 animals a day.                So, obviously, we needed something

23   we use very rapidly.                We know, as I said, that TB induces

24   a strong T-cell response.                   We know that interferon gamma

25   is a classical CMI cytokine.                    For those of you familiar

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1    with the type I/type II complex of T-cells, you know that

2    interferon gamma is a classical Type I cytokine.

3                     We also know it's produced in vitro in

4    response-specific            antigens,       and    it's     created         in

5    measurable       and     stable     amounts.        Very     importantly,

6    because we wanted to use whole blood, because, again,

7    as I said, we're looking to test lots of animals in a

8    single day, that it's absent from the normal circulation.

9     There's an extensive literature which is growing all

10   the time showing the importance of interferon gamma in

11   TB infection.

12                    The assay in cattle, which we call Govigam,

13   is very similar to what Jim has just described.                      It uses

14   heparinized whole blood.               In this case we substitute

15   bovine PPD for M. tuberculosis PPD.                   We use avian PPD

16   as a comparator, and we don't use the mitogen.                  As I said,

17   this was the earlier version and we were testing whole

18   cattle, and you classify TB in cattle on the basis of

19   herd diagnosis.

20                    So you incubate overnight, and again if there

21   are specific cells there, they respond and secrete

22   interferon gamma, which we harvest the next day and use

23   a sensitive enzyme immunoassay detect.                    In this case the

24   monoclonal antibodies are detecting bovine interferon

25   gamma as distinct from human interferon gamma, as is the

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1    case with QuantiFERON.

2                       Let me show you some basic raw data.                        This

3    is the data we generated early, and we got three good

4    animals here.            In control animals you see no response

5    or very little response to the PPD's in either of the

6    control, as you can see in the first two animals there.

7     However, with M. avium-infected animals, you see a

8    distinct response to the M. avium PPD.                      These are just

9    raw OD's I'm showing you here.                   It's greater than what

10   we see to the bovine response.                   Of course, if you have

11   M. bovis-infected animals, you see the reverse of that

12   response.

13                      As you can see there, this also shows, the

14   point that Jim made, the cross-reactive nature of these

15   antigens in the sense even in the M. bovis animals you

16   can see quite a strong response to the M. avium.                           That's

17   why we used this comparative.                  So it's basically an in

18   vitro comparative assay.

19                      This is the major study that we did in

20   Australia.         So in the study we had over 6,000 animals.

21    All      of     these     animals     were    tested       and     eventually

22   slaughtered.         The beauty of the cattle model is that we

23   are able to post mortem our animals and collect extensive

24   tissues and culture.              So our gold standard here was M.

25   bovis culture from those animals.                    In this case we had

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1    125 culture-positive animals.

2                     As you can see from that data, the interferon

3    gamma assay was significantly more sensitive than the

4    skin test.       The figure there -- we got a 65.6 for the

5    skin test -- was equivalent to studies that Francis did

6    in the seventies, where he came up with a figure of about

7    70 percent.

8                     When we combine the results of the two assays,

9    we      slightly    increase      the     sensitivity,      but       not

10   significantly over and above what we saw with the bovine

11   interferon gamma line.         But I point out again that we're

12   able to actually have a gold standard in this trial.

13                    More importantly as a scientist, I'm pleased

14   to say that our studies have been consumed my numerous

15   publications.       There's over now 20 published studies in

16   11 different countries.           We have 150,000 animals that

17   have been tested in those studies.             We're coming up with

18   an overall sensitivity of approximately 90 percent with

19   a good specificity.

20                    What we see in those studies, people have

21   used different cutoffs because people's programs around

22   the world change.       So if you're looking for eradication,

23   which is what we did in Australia, then we maximize

24   sensitivity and we sacrifice a little bit in specificity.

25    In other circumstances where you want high specificity,

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1    then you can adjust your cutoffs.                But, overall, all of

2    these studies confirm the results we saw in the Australian

3    trials.

4                       So what are the lessons we've learned from

5    the bovine assay?         Well, in the bovine assay we have found

6    that in general it's more sensitive than skin testing.

7     It's able to detect animals early in the infection.

8    We did in our studies in Brosboteland in New Zealand and

9    also the British now have shown that generally within

10   four weeks of infection -- this is with a low dose,

11   10-to-the-4 CFU -- you see a positive response.                       It's

12   maintained for a significant period.               We followed animals

13   for three years, and although the actual level varies,

14   they remain positive for all of those three years.

15                      It's now used in a variety of countries,

16   including here in the USA.                With the white-tail deer

17   problem in Michigan and the spread to cattle, it's now

18   being used in the USA.

19                      So, in conclusion, I believe that the whole

20   blood interferon gamma assay is applicable to other

21   mammals.         We've now spread it, the technology.            We have

22   a primate-based assay that's going through finalization.

23    We've developed a celine assay we call Cervigam.                       You

24   see a thing coming through there.                  And people are now

25   developing it for other species.

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                                                                            29
1                     But, importantly, what you'll hear today is

2    to hear about the human assay.               The QuantiFERON assay

3    uses exactly the same technology that I've just gone

4    through in the bovine.          It's my belief that the bovine

5    data gives us a good start and extensive validation of

6    the technology.

7                     I'll now hand it over to Jim Rothel, who will

8    take you through the clinical data on the QuantiFERON

9    assay.

10                    DR. ROTHEL:      Thanks, Paul.

11                    Tony's gone through the current situation

12   with TB diagnosis, and Paul's just given us a nice overview

13   of the scientific basis of the test in the bovine model.

14    I'm now going to talk about the initial clinical studies

15   that were conducted largely in Australia and then move

16   on to the pivotal studies, the CDC and the WRAIR studies

17   which were using as the basis for a PMA application.

18                    A large amount of work was done by CSL in

19   characterizing the performance of the QuantiFERON test,

20   and I'll just go over these points here.               The limit of

21   the detection of the test was found to be 1.5 international

22   units of gamma interferon above the nil control for any

23   individual set of plasma samples.               That is, a nil for

24   a person, we can detect in a stimulated plasma sample

25   site with a PPD, we can significantly detect 1.5 units

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1    above the value in the nil.

2                        The linear range of the EIA is on the order

3    of     200       international    units     per    ml.       Looking         at

4    reproducibility of the test, which is an important aspect,

5    we looked initially at the blood culture phase, the first

6    phase of the test.            Looking at replicate cultures, we

7    found the intraclass correlation coefficient to be

8    greater than .95, indicating excellent reproducibility

9    between the blood culture phase.

10                       Looking     just   at   the    EIA     phase,       again

11   interferon ELISA, that was found to be highly reproducible

12   as demonstrated by both within-plate and between-plate

13   coefficients of variation being less than 10 percent.

14                       Looking at the test overall, looking between

15   blood samples collected and sent to different sites and

16   assayed by different operators, the ICC statistic again

17   was        found     to    be     .948,       indicating         excellent

18   reproducibility.

19                       So after establishing these test parameters,

20   the initial trial we did was that reported by Streeton,

21   et al., in the IITLD journal.               This trial was set up to

22   establish the cutoff for the test.                       We enrolled 407

23   individuals who were deemed by the ATS/CDC guidelines

24   as being uninfected with TB -- that is class not

25   individuals by those guidelines -- and 182 individuals

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1    deemed as having latent TB infection by those same

2    guidelines.

3                        After testing blood from those individuals

4    in the QuantiFERON assay, we then analyzed the data by

5    ROC curves.           This established that the appropriate

6    measure of cutoff is this thing we've called "percentage

7    human response" here, and I'll explain that in a little

8    bit more detail later.             We established that should be

9    set at 15 percent.         Using this cutoff on that data -- and

10   this data was used to generate the cutoff, but we'll point

11   it out to you anyway -- specificity was found to be 97.6

12   percent and sensitivity 89.6 percent.

13                       We talked earlier about having avian PPD as

14   well as human PPD in the tests, so it's a comparative-type

15   assay.           We have to determine the optimal method of

16   distinguishing between TB infection and reactivity to

17   MAC in this case or MOTT, using MAC as a representative

18   of a MOTT mycobacteria.

19                       For   this    we    obtained         blood    from       50

20   individuals with culture-confirmed TB infection and 10

21   individuals with culture-confirmed MAC lymphadenitis.

22   This graph there on the bottom, which is hard to see no

23   doubt, but you can get the feeling, up the side here is

24   the second cutoff we've chosen -- I hope I don't zap you

25   with this laser pointer over there -- is the percent avian

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1    difference, which is the second cutoff we've chosen.

2    Again, I'll explain it in a minute.

3                     These individuals here are TB patients.

4    These are the patients with MAC infection.                 The line

5    across there, which is set at minus 10 percent, was chosen

6    as the optimal cutoff to discriminate between those with

7    TB infections and those with reactivity to MOTT.

8                     So just to go through how those two cutoffs

9    are chosen, the percentage human response is the response

10   of an individual to human PPD expressed as a percentage

11   of their response to the mitogen control well.                   These

12   values are both corrected for nil.

13                    The percent avian difference is calculated

14   by subtracting the response to avian PPD from that to

15   human PPD and expressing that as a percentage of the

16   response to human PPD, again corrected for nil.                    That

17   sounds a little complicated, but it's a very simple

18   calculation.       But what that essentially says is, what

19   is the predominant response to?             Is it to human PPD or

20   to avian PPD?

21                    One other or two other factors have to be

22   included in the cutoffs used for the tests.               As I told

23   you earlier, the limit of sensitivity for the QuantiFERON

24   EIA is 1.5 units per ml.       So, therefore, to obtain a valid

25   test result for any individual, their mitogen response

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1    has to be at least 1.5 international units above the nil

2    sample for that individual.                       If it's not, that's an

3    invalid test and we can't obtain a test result for that

4    person.          Again, that's a rare event.               Similarly, seeing

5    the sensitivity of the EIA is 1.5 units above nil, the

6    human PPD minus nil has to be greater than that level

7    to obtain a positive response in TB.

8                           So    now    that    we   have    established         these

9    cutoffs, we went ahead and did some clinical trials, some

10   more clinical trials.                 What we would have loved to have

11   done is to look at the response of individuals before

12   being infected with M. tuberculosis and then following

13   MTB infection, but ethically that's a very difficult

14   experiment to do.               So we did the next best thing and used

15   an MTB complex organism, albeit very attenuative, which

16   is in bovis BCG.

17                          We recruited 53 low-risk TB individuals, that

18   being medical students in Australia who are routinely

19   BCG vaccinated, at this university at least, and tested

20   them with QuantiFERON both before BCG vaccination and

21   then five months after BCG vaccination.                        The data showed

22   that 92 percent of these medical students showed an

23   increase          in    their       QuantiFERON       response      after        BCG

24   vaccination, and the amount of this increase was threefold

25   above that found prior to BCG.                      I should add here that

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1    the vast majority of these were still below the 15 percent

2    cutoff that was established for the QuantiFERON-TB assay,

3    but that would be expected, knowing the BCG is a highly

4    attenuated MTB complex organism.

5                     First, we feel that this study demonstrates

6    that an increase in QuantiFERON-TB response is generated

7    following MTB infection.          We have now established from

8    the Streeton study and from these other studies that the

9    majority of people who are not infected with TB don't

10   respond in their QuantiFERON-TB test, and the majority

11   of people that have latent TB infection give a positive

12   response in QuantiFERON-TB.           But what about those with

13   active TB disease?

14                    To look at this, we conducted a multi-center

15   study in Australia, nine different hospitals around

16   Australia,       and    recruited       129     individuals        with

17   culture-confirmed TB disease.              Eighty-one percent of

18   these patients were found to be QuantiFERON-positive,

19   and this established that the test works in cases of active

20   TB disease, where commonly the immune response is quite

21   depressed to tuberculin.

22                    That's a brief outline of the clinical

23   studies that were conducted in Australia.               Let's move

24   on to the pivotal studies that were conducted by the CDC

25   and Walter Reed.

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1                       First, I want to talk about the constraints

2    of running clinical trials of any test for latent TB

3    infection.         There's no gold standard for latent TB.            Tony

4    told us about it before, and there just isn't a standard

5    for it.          Now TST is an aid to detecting tuberculosis

6    infection.          As Tony eloquently put, it's not a gold

7    standard.         It's definitely not a definitive indicator

8    for LTB.         So, therefore, we didn't have a gold standard.

9     What do we do?

10                      So the data analysis method we used was to

11   recruit individuals with no known risk factors for TB

12   infection and then use these to determine what are termed

13   apparent specificity.           We called it apparent specificity

14   because we cannot guarantee that some of those individuals

15   did not have latent TB infection, although the chance

16   of that is very low.

17                      To determine the sensitivity of the test for

18   active TB disease, we do have a gold standard.                        It's

19   culture of the organism.              So for that, we can recruit

20   culture-confirmed TB cases.

21                      But the last group there on that slide is

22   looking at the sensitivity of the test for latent TB

23   infection.         Without a gold standard, all we can do is

24   recruit individuals with identified risk factors for

25   latent TB infection and look at the concordance with this

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1    suboptimal standard TST.            That's the best available to

2    us.

3                       So the CDC study recruited 1,500 subjects,

4    or that was the goal.           There were five different sites

5    across the U.S., which was San Francisco, San Diego,

6    Baltimore, Newark, and Boston.             The main aim was to look

7    for a concordance between QuantiFERON and the TST.

8                       The four groups enrolled:            a low-risk group,

9    98 individuals, and that was to look for specificity of

10   the test; a medium to high-risk group that included

11   contacts of active TB cases, immigrants from high-risk

12   countries, homeless people, et cetera; TB suspects,

13   people suspected of having active TB disease.                   And these

14   three groups represent the intended population for

15   QuantiFERON TB.

16                      The fourth group that was included in the

17   CDC        study     were     those      individuals          that         had

18   culture-confirmed TB in the past and had completed their

19   therapy for that within the previous two years.                    They're

20   not in the intended population.              For many reasons, they

21   are not appropriate for us to study and we are not

22   presenting any data from those.

23                      For the Walter Reed study, there was nearly

24   1,700 recruits at the Great Lakes Navy Station in

25   Illinois.        These were stratified into three groups, the

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1    first group being 397 individuals with no identified risk

2    factors for TB.

3                     The second group had one limited risk factor,

4    which is they were born in or recruited into the Navy

5    from a U.S. state that had a TB rate of 10 per 100,000

6    or greater.        This is a very low risk factor, I'll

7    acknowledge that.          What we were trying to do here was

8    to make group one as TB risk-factor-free as we possibly

9    could, but I'll acknowledge that group two is a very low

10   respecter as well.

11                    Group three individuals were those who had

12   identified respecters.            The majority of them were born

13   overseas, although there were some recruits that reported

14   contact with active TB in the past.

15                    Adverse events, there were no adverse events

16   reported in the CDC study for the QuantiFERON-TB, where

17   there was 9.4 percent of individuals in the CDC study

18   reported an adverse event for the TST.

19                    Looking     at    the    sensitivity      first        of

20   QuantiFERON-TB for active TB disease, there were 94 people

21   enrolled into the CDC study group three.                They're the

22   TB suspects group.         After culture was performed, 54 of

23   these were found to be MTB culture-positive.              Forty-four

24   of these, or 81.5 percent, were QuantiFERON-TB-positive,

25   indicating that the sensitivity for QuantiFERON-TB, using

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1    that trial 15 percent cutoff we had established, was 81.5

2    percent.

3                     Now this has to be the minimum sensitivity

4    of the test for latent TB as well, because it's well

5    acknowledged in the scientific literature that people

6    with culture-confirmed TB disease often have depressed

7    cellular immune responses, including gamma interferon

8    responses.

9                     We now look at the apparent specificity of

10   QuantiFERON-TB, look at the three low-risk groups, one

11   from the CDC and two from the WRAIR study.                Using the

12   TST at 10 millimeters and the QuantiFERON at a trial cutoff

13   of 15 percent, we found the specificity of the TST 95.9

14   in the WRAIR study compared to 91.8, 98.7, 95.5 for the

15   WRAIR low-risk group and 98 compared to 93.4 for the

16   limited-risk.

17                    But    these       individuals,      group          one

18   individuals, are not recommended by the CDC ATS guidelines

19   to be screened for TB.            In reality, they are.             The

20   military is a prime example of an institution that

21   routinely screens individuals with no risk factors.                   So

22   it's important to be able to have a test that works for

23   them.

24                    For the TST, a stratified cutoff of 15

25   millimeters is used for these individuals.               We can do

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1    exactly the same thing with the QuantiFERON test, and

2    we have established that a 30 percent cutoff is the optimal

3    cutoff to use in individuals like this with no identified

4    risk factors.

5                        So if we look now at the specificities for

6    these three groups, three study groups, using the TST

7    at the stratified 15 millimeters or QuantiFERON at a

8    proposed           30   percent     stratified        cutoff      for       such

9    individuals, you can see that the specificities in general

10   are 98 percent.

11                       Now we're looking at individuals at risk of

12   being infected with latent TB.               This is a two-by-two table

13   obviously comparing QuantiFERON with TST.                  We're looking

14   here at individuals from the CDC study recruited into

15   group one or group two.              That's low-risk or high-risk.

16                       For the TST we're using a risk-stratified

17   cutoff where the individuals in group one, we use a

18   15-millimeter cutoff for the TST, and for group two we

19   use      a       10-millimeter     cutoff.         This    is      comparing

20   QuantiFERON-TB to the trial cutoff of 15 percent.

21                       You can see that concordance is quite good

22   with 85 percent of the individuals having concordant

23   results with the TST, although there are a significant

24   number of individuals that have discordant results on

25   both sides of the diagonal.                     Kappa here was .554,

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1    indicating moderate, verging on good, agreement.

2                     But if we use a stratified cutoff that we're

3    proposed for group one individuals, what happens to the

4    data?        For groups one's, we use the 30 percent human

5    response cutoff for QuantiFERON and 15 millimeter for

6    TST, and group two we use 15 percent cutoff that was

7    established in the Australian trials and a 10-millimeter

8    cutoff for the TST.

9                     We find that the sensitivity of the test is

10   maintained.       The only people that have moved in that

11   two-by-two table are those individuals that were in group

12   one, the low respecters, and we're assumed that they're

13   all negative, that they don't have TB infection.

14                    Kappa for this was .561, again indicating

15   moderate to good agreement.           I would point out again that

16   this is a similar, slightly better Kappa than that

17   attained when comparing Aplisol to Tubersol both in

18   low-risk and TB-infected individuals.

19                    So what are the potential reasons for the

20   discordance we've just seen?              It was random variation

21   as you'd expect to see; again, as the Tubersol versus

22   Aplisol story.       If we look at the individuals that were

23   positive in the TST but negative in the QuantiFERON test,

24   13 out of 80 of them demonstrated MOTT reactivity by the

25   QuantiFERON test, and MOTT is a well-known source, MOTT

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1    reactivity is a well-known source of false positive TST

2    reactions.

3                           There was a significant association with

4    individuals            being       BCG-vaccinated        having     that       same

5    response,             being     TST-positive,        QuantiFERON-negative,

6    suggesting that perhaps the TST is more affected by BCG

7    vaccination than is QuantiFERON-TB.

8                           Two other factors were found, age and gender,

9    and we really don't have any explanation for why they

10   should be associated with discordance.

11                          So    now    we've    shown     that     QuantiFERON-TB

12   detects          M.     tuberculosis-specific            T-cell     responses.

13   We've       demonstrated           with     people    that     don't    have      TB

14   infection the vast majority are negative in the test,

15   98 percent of them.                 We've shown that individuals that

16   definitely have TB disease, as demonstrated by culture,

17   81.5 percent were found to be positive.                              And we've

18   demonstrated good concordance with the TST at 85 percent

19   in those at risk of LTBI.

20                          But although we can explain some of the

21   discordant             results      found      by    MOTT      reactivity,        as

22   demonstrated by QuantiFERON in those TST-positive, what's

23   the best way of demonstrating this?                      It's looking back,

24   I believe, at the extensive data from the bovine animal

25   model, which is an excellent model for TB for humans.

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1                     This slide shows two-by-two tables.               The top

2    table here is the data that you've seen before for the

3    CDC group one and two individuals combined.                     The data

4    down below is a study from the Wood, et al., paper, the

5    key publication that Paul Wood referred to earlier with

6    86,000 cattle tested.

7                     What I want you to focus on here are the

8    numbers, the percentages in brackets.                  These percentage

9    values are the percentage of individuals, or in this case

10   individuals, who are positive to one or both of the tests.

11    So 48 percent of individuals were positive to both of

12   the tests as compared to positive to any.

13                    The same thing down here for the animals,

14   the cattle in that study.           You'll see there very strong

15   similarity between the percentages of discordant values

16   found between the human test and the bovine test.                          So

17   the same level of discordance is found in the bovine assay.

18                    But the big thing about the bovine test is

19   that we could kill the animals, we could take out extensive

20   tissues out of these animals, slaughter them in the

21   laboratory, and culture for M. tuberculosis disease,

22   looking for foci of infection.

23                    If you now look at the data based on culture,

24   stratified by positive culture, you'll see that the

25   animals that were positive to both tests, the TST and

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1    the bovine equivalent of QuantiFERON, 87 percent of those

2    doubly positive were found to be culture-positive.                     But

3    for those that were positive just in the TST and negative

4    by the QuantiFERON or the bovine version of it, 53 of

5    them, only two of them were found to be culture-positive.

6     So 4 percent.

7                     So the sensitivity of the TST, when it was

8    positive only by itself, it was very low.                   Conversely,

9    if we look at the animals that were positive by the bovine

10   gamma interferon assay and negative in the TST, 55 percent

11   of them were found to be culture-positive.

12                    Paul showed you these figures before, but

13   the TST sensitivity from this study was 65.6 and for the

14   gamma interferon assay it was 93.6 percent.                    So it's

15   reasonable to assume, to extrapolate from this bovine

16   model, that for discordance results in the human test

17   it's        reasonable    to      suggest      that    those       gamma

18   interferon-positive         are    more     likely     to    be    truly

19   TB-infected.

20                    Just to go through the conclusions, Tony told

21   us there definitely is a medical need for an improved

22   diagnostic test for latent TB, as indicated by the IoM

23   report that came out last year.                 Paul told us about

24   technology,        and     it's      based       on    sound,        very

25   well-established         scientific     principles.          Hopefully,

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1    I've just shown to you that QuantiFERON is a very sensitive

2    test and highly specific for the protection of TB

3    infection.

4                         QuantiFERON has a major logistic advantage

5    over TST, and that is people don't have to come back to

6    get a result.           As Tony told you, 30 percent, or in many

7    cases many more than 30 percent, of individuals you don't

8    get a result when using the TST.                  With the QuantiFERON

9    test, you will get a result close to 100 percent of people.

10                        QuantiFERON           is          a       controlled,

11   laboratory-based           test.       It's     not    subject    to     those

12   subjective issues that TST is well-known for.                                 It

13   accounts for activity in the MOTT, and the initial data

14   says that it appears to be less affected by BCG than is

15   the TST.

16                        I'd just like to conclude by showing this

17   slide.           We believe the data provide reasonable assurance

18   of the safety and efficacy of QuantiFERON-TB as an aid

19   in     the        detection    of   infection         with   mycobacterium

20   tuberculosis.

21                        Thank you for your attention.

22                        CHAIRMAN WILSON:        Thank you.

23                        At this time I would like to invite the panel

24   members to begin asking questions.                    Dr. Durack?

25                        DR. DURACK:     Several short questions for Dr.

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1    Rothel.          If this test becomes widely used, which I'm sure

2    you'd be pleased to see, what is the story about the supply

3    of        mitogens?             Is     it      adequate,       reliable,

4    quality-controlled, and would there be enough for an

5    extensive application of this test?

6                        DR. ROTHEL:      Yes, the mitogen is a commercial

7    product that I bought from Streeton -- I'm just trying

8    to think who -- but it's commercially available and

9    there's no problem with supply of it.

10                       DR. DURACK:      Standardized and reproducible?

11                       DR.   ROTHEL:           Standardized      and       it's

12   standardized in-house as well.

13                       DR.   DURACK:       A question about the nil

14   response:          Do you see much variation in the nil response?

15    What's the range?

16                       DR. ROTHEL:       The general range of the nil

17   response would be from an optical density, if we talk

18   optical densities, from zero to about .07.

19                       DR. DURACK:      Okay.

20                       DR. ROTHEL:       Occasionally, you do get an

21   individual that has a higher response in the nil, and

22   this is due to competing factors such as heterophile

23   antibodies that are common when you're using an ELISA

24   that uses unique plasma samples.                     The assay, again

25   interferon EIA, is heavily formatted to reduce it for

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1    all antibody activity, but occasionally perhaps some

2    person has very high reactivity there and we don't compute

3    it all out.       But, again, it doesn't affect the result

4    of the test because that variable is subtracted from all

5    the other plasma sample wells.

6                     DR. DURACK:     A question regarding the human

7    versus the avian test:         How often do you see an equivocal

8    response, if you like, where they're about equal?                 Would

9    you comment on that?           Does it happen?        How would you

10   interpret it?

11                    DR. ROTHEL:       The cutoff has been fairly

12   extensively backed up by the data we've seen, I must say.

13    In the vast majority of cases -- and this is all

14   off-the-top-of-my-head stuff without having the data in

15   front of me to show you -- but in the vast majority of

16   cases a person who is infected with TB, such as a

17   culturally-confirmed TB case, the response to human PPD

18   I would guess would be at least twice that to avian PPD,

19   and the inverse in the few individuals who are seen that

20   have had MAC infection.

21                    DR. DURACK:     Have you seen examples where

22   the response is about equal?

23                    DR. ROTHEL:    Off the top of my head, I'm sure

24   we have, but I can't come up because I don't really know

25   any of them.      I can't think of any specific examples.

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1                     DR. DURACK:       Right.      One last question:

2    You've touched I think several times on this, but the

3    degree of the response, the quantitative response, can

4    you comment on the correlation between active disease

5    versus latent disease and the correlation coefficient?

6                     DR. ROTHEL:     Yes, quite often people with

7    active TB disease you get very low responses within the

8    sensitivity of the test to both mitogen and to the human

9    PPD, but they still come out positive, whereas, typically,

10   individuals who would be suspected of having latent TB

11   infection, the responses are much more robust.

12                    DR. DURACK:     Thank you.

13                    CHAIRMAN WILSON:       Dr. Cockerill?

14                    DR. COCKERILL:      Yes, a couple of questions.

15    I know that the datasets are limited, but in the studies

16   you've done and in the studies reported, is there any

17   information regarding the test when applied to children?

18                    DR. ROTHEL:      We've excluded, limited our

19   tests to not cover children, but, yes, there is a large

20   body of data available in Australia from specifically

21   one physician, Jonathan Streeton, that original paper,

22   who has been using the test for many years.           He routinely

23   uses it in children in contact situations, and that has

24   got excellent results.          But we realize we have to do

25   studies in children to be able to gain approval for use

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1    in that population.

2                       DR. COCKERILL:       And among the patients you

3    studied or other studies that have been done, patients

4    who were leukopenic, any information regarding the

5    validity of the testing in those patients?

6                       DR. ROTHEL:       Again, excluded from there,

7    labeled on things, but, yes, we have done studies in

8    HIV-infected individuals both in Kenya -- and I think

9    there was attached to your panel packet a summary of that

10   study.           Also, some studies have been initiated in

11   Australia looking at the response to mitogen relative

12   to CD-4 counts in HIV patients.

13                      It's actually quite surprising; quite a

14   number of individuals with CD-4 counts less than 50 give

15   quite strong responses to the mitogen still.                            Then,

16   again, others don't.          But generally, if they're over 200

17   CD counts, 200 per ml., they do have a measurable response.

18    Less than that, it gets a bit equivocal.

19                      CHAIRMAN WILSON:        Dr. Reller?

20                      DR. RELLER:     Dr. Wood, in the schema you used

21   blood collected in tubes with heparin.                   What about other

22   anticoagulants and the effect on the test:                              EDTA,

23   citrate, SBS, et cetera?

24                      DR. RADFORD:      Yes, we tried sodium citrate,

25   one or two other anticoagulants.               None of them actually

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1    work.        When you look at it, because we're using whole

2    blood, they actually interfere with the interaction

3    between the antigen-presenting cell and the T-cell.                    So

4    heparin is the only anticoagulant that will work in the

5    system.

6                     DR. ROTHEL:      That's also been validated in

7    the human assay.

8                     CHAIRMAN WILSON:        Dr. Charache?

9                     DR. CHARACHE:       I didn't tell you what I do

10   at Hopkins, but I am an infectious disease consultant

11   as well as a microbiologist, and I'm telling you this

12   to give you my orientation, which is to say that I very

13   strongly agree with the advantages of a laboratory test

14   as opposed to a skin test.

15                    I do see some very basic questions here in

16   its current formulation, not what else may we do, but

17   I think perhaps I can show it best if we look at the

18   concordance.        I was, as an example, looking at the

19   concordance in the WRAIR study of all tests.             In our book

20   it's on page 77.

21                    Now the WRAIR group does not match the TB

22   population that we usually look at, which is much more

23   diverse in terms of age and underlying pathology, but

24   it has the advantage of being young, Navy recruits, so

25   it can get a good look at the lower-risk group.                   If we

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1    look at all comers in the WRAIR group, looking at the

2    positives, because to me it's the positives that are

3    important, not the negatives, because we're looking for

4    latent disease, there are 18 in which there's concordance.

5     There's 105 in which the QuantiFERON is positive and

6    the latent is not.                So, clearly, they're measuring

7    different things.            There's a tenfold difference.

8                       We do know that this group includes the

9    low-risk which has a high percent false positives on the

10   tuberculin test, meaning that many of the 18 that were

11   in the low-risk population are false positives.                         That

12   raises the very serious question about the false positives

13   with this test.

14                      If we look on the next page at the low-risk

15   group using the 10-millimeter cutoff -- I think it's two

16   pages        --   the    moderate-risk        category,    primary-risk

17   individuals, we similarly see a skewing, not quite as

18   bad in this one, but you end up with a 15.1 percent positive

19   rate for the QuantiFERON.               Now if we translate that 15

20   percent into positive per 100,000, which is the way it's

21   expressed generally, that group should have 10 patients

22   or 10 subjects per 100,000 individuals which is positive.

23    If this test were correct, it would come out to something

24   like 15,000 patients per 100,000 positive.

25                      And the same is true as you look at the others.

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1     The number that would be called positive, if we use this

2    particular test, particularly in the low-risk population,

3    would be between -- well, in the CDC study it would be

4    8,300 per 100,000.        That's way out of line with what all

5    the epidemiologic studies have said it should be.                     And

6    your slide used the number 10 per 100,000 for your category

7    two.       This comes out, when you add the zeroes, to 15,000.

8                     So I think it's going to be very important

9    that we understand why this is calling so many more people

10   positive or we're going to have a very abrupt jump in

11   our incidence of tuberculosis in the United States that

12   we're going to have to explain.

13                    DR. ROTHEL:     Sure.      Can I reply to the last

14   bit first, get that out of the way?              The 10 per 100,000

15   is the rate for active TB cases per 100,000 individuals.

16    We're looking at latent TB infection, which is meant

17   to be at least 10 to 100 times higher than that for active

18   TB cases.

19                    Did I understand your question wrong?                 Is

20   it that --

21                    DR. CHARACHE:       Actually, the numbers don't

22   come out quite like that from the literature which I saw.

23                    DR. ROTHEL:      Yes.

24                    DR. CHARACHE:      But, in any event, what we're

25   seeing is that for those at lower risk the QuantiFERON

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1    has eight to ten times the number of positives as the

2    skin test does.

3                      DR. ROTHEL:      Sure, sure.

4                      DR. CHARACHE:       And then we know that it's

5    not as sensitive as the skin test when we get to the active

6    TB model, where it's less sensitive.               So I'm questioning

7    what       this   problem   is    that    we're     seeing    with       the

8    discrepancies between these tests that is so striking

9    and how do we adjust for them.

10                     I'm   interested       in     knowing      what      your

11   discordance effects of age and gender are, and in the

12   CDC study they noted there was discordance differences

13   in results according to the particular study site that

14   did the evaluation, in their table, that it mattered

15   whether you were in site E or site A in terms of results.

16    So I'm wondering if you can help us understand some of

17   the factors that we then could modify or adjust, as you

18   have       considered    adjusting       your     criteria     for       the

19   lower-risks, and so on.

20                     DR. ROTHEL:      There's a lot of questions in

21   what you have just asked me.              I hope I can remember to

22   answer them all.

23                     The first one, if we go back in order, as

24   far as the sensitivity in the low-risk WRAIR individuals,

25   we're proposing to use a 30 percent cutoff in those

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1    individuals.        We're not proposing to use the 15 percent

2    cutoff.          That large number you're talking about of

3    individuals positive in QuantiFERON/negative in TST

4    largely disappears if we use a 30 percent cutoff.

5                       What we can assume in those individuals is

6    none of them are truly infected.               That's the assumption

7    we make, and that was the basis of the study.              So a similar

8    number of falsely positive by TST is falsely positive

9    by QFT, would be my response to that.

10                      DR.   CHARACHE:       Now    wouldn't     that       same

11   propensity for false positives perhaps be carried over

12   into the other populations?             They're just hidden?

13                      DR. ROTHEL:    Sure, sure, and there's wobble

14   in any biological test like this.                That's the range of

15   variables I was talking about in my presentation.                     We're

16   always going to get false positives in any test.                        It's

17   the nature of biological tests.

18                      Now where were we?

19                      DR. RADFORD:      I think Tony's actually got

20   a comment to make to this topic.                So I would just ask

21   him to speak.

22                      DR. CATANZARO:      I just wanted to talk about

23   the purpose of screening in the Navy, for example.

24   Obviously, you and I are both clinicians, and we're

25   interested in patients with disease.              But in that setting

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1    the purpose is actually to find individuals who are

2    completely free of any suspicion of disease.

3                         So the fact that a large number of Navy

4    recruits were correctly identified as being free of

5    tuberculin sensitivity is the object of the exercise.

6    Now I grant you that this presents more workload to the

7    clinician to look at these people who are reactors to

8    tuberculin and figure out whether that reactivity is due

9    to tuberculosis disease or due to some other immunologic

10   phenomenon.

11                        But I think as a public health person, and

12   particularly as someone who's going to put young men on

13   a Navy submarine, for example, the fact that you've

14   identified a huge number of individuals who are clearly

15   free of tuberculin reactivity is the purpose of the

16   exercise.

17                        DR. CHARACHE:     I'm concerned about how it's

18   going to be used and the toxicity of the drugs that will

19   be applied, if we have false positives.                   So I'd like to

20   see if we can't get rid of some of them.

21                        DR. CATANZARO:       I think you're absolutely

22   right.           That was the purpose of my presentation saying

23   that a positive reaction to tuberculin skin test or, for

24   that matter, to QuantiFERON does not result necessarily

25   in the application of therapy.                    There's a clinician

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1    between the two who plays a very important role.                 There

2    are many people who have tuberculin sensitivity with the

3    tuberculin skin test who are not candidates for INH

4    prophylaxis, and the same will be true for QuantiFERON.

5                     DR.   CHARACHE:       If you have a positive

6    QuantiFERON, knowing that there may be a very high false

7    positive rate, based on the low-risk group where we can

8    perhaps see it best, what would you tell the doctor to

9    do to prove there was or wasn't latent TB?                Would you

10   suggest they do a skin test or --

11                    DR. CATANZARO:      No.

12                    DR. CHARACHE:     -- how else would you decide

13   whether to use antibiotics or not?

14                    DR. CATANZARO:         No.     First of all, we

15   propose the gradation of having a 15 percent cutoff and

16   a 30 percent cutoff.          This is analogous to what we do

17   with the tuberculin skin test:             a 10-millimeter cutoff

18   in certain situations, a 15-millimeter cutoff in other

19   situations.

20                    But   what    I    would     recommend    to      that

21   individual, just like I do with tuberculin skin test

22   reactivity -- and I've been doing this for the past 30

23   years, and you have as well -- you see an individual who's

24   got a 10-millimeter tuberculin reaction.                  You get a

25   history.

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1                      If that person has, for example, been brought

2    up in Peru and been given BCG three times as he was growing

3    up and now is 25 years old, it's likely that that

4    10-millimeter        reaction        was    due    to    BCG.         If     that

5    individual was raised in Atlanta in a low socioeconomic

6    -- excuse me -- was raised in Atlanta, had a 10-millimeter

7    reaction, chances are that it well be avium.                    On the other

8    hand, if that person was raised in California, the son

9    of a mother with active tuberculosis when he was 10 years

10   old, that 10-millimeter reaction is most likely due to

11   tuberculosis.

12                     So you have to apply, I think, clinical

13   judgment to the tuberculin reactivity with tuberculin

14   skin tests and the same is required by QuantiFERON.                                  I

15   do think that there are a large number of false positives.

16    I think that this wobble effect of getting a different

17   reaction to QuantiFERON than you do with tuberculin skin

18   test is exactly the same as we see with the tuberculin

19   using Tubercol versus Aplisol.                    I don't think you'd

20   identify one of those as false positives, just different.

21                     DR. CHARACHE:            Well, yes, I think that

22   obviously        suggests   that      the    product      has       different

23   antigenic        properties     in    terms       of    stimulating          your

24   immunity.        Here we have a very different mechanism.                      I'm

25   satisfied, I think, as all of us are, that if we have

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1    a simple test that can be done effectively to screen for

2    experience with the mycobacterium tuberculosis, it wold

3    be used very widely.          I certainly favor this.

4                      I'm questioning how to make it more precise,

5    because when we do the math in its current form, we would

6    have statistics that are quite disparate from past

7    experience.

8                      DR. CATANZARO:         I want to make one more

9    comment, if I may, regarding the question you asked,

10   "Would you do a tuberculin skin test?"                  I would no more

11   do a tuberculin skin test for a questionable QuantiFERON

12   than I would do a Coghnaunt skin test with a questionable

13   Aplisol.         I think that to do that is trying to beat a

14   technology beyond its capabilities.

15                     The disparity between Aplisol and Coghnaunt

16   tuberculin skin test reactivity is not due to measuring

17   very different things.           It's due to the inherent error

18   in the biological assessment of tuberculin skin test

19   reactivity.        You have to go to a completely different

20   system; for example:         history, physical exam, et cetera.

21    That's my point of view anyway.

22                     DR. CHARACHE:      Well, I would think it might

23   be helpful to see if we can understand better some of

24   these discrepancies and what it looks like when you use

25   30 in the most unlikely to have TB.              We haven't seen that

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1    data.        But, also, when we look at the higher groups, we

2    can still see things that we really can't explain too

3    easily.

4                        There was one comment that there were 55

5    patients tested who had discrepant TD skin test compared

6    to the QuantiFERON, and there were 39 that were retested.

7     Of those 39 that were retested, only 18 were repeat

8    positive with the QuantiFERON.                  So I think these are some

9    of the questions I have in terms of how we can improve

10   it.

11                       DR. ROTHEL:         Introduce yourself.

12                       DR. RADFORD:          My name's Tony Radford.                 I'm

13   the Chief Executive Officer of Cellestis, and I also have

14   a shareholding in the company.

15                       I think that I could perhaps best address

16   your question by putting up an overhead which looks at

17   the percentage positive in all of the studies that we've

18   done, all the risk groups from one, two, three and all

19   the Walter Reed studies, using the risk-adjusted cutoff

20   at 30 percent for low-risk or what you might call almost

21   no risk groups.             I think if you look at the percentage

22   figures          there,     you    will     see    that      the     percentage

23   differences are really quite small and won't lead to major

24   changes in epidemiological beliefs in the instance of

25   tuberculosis.         That slide's just going up behind you.

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1                          You'll see that it's the Walter Reed low-risk

2    group on the left, again, using risk-stratified cutoff

3    both for QFT and the tuberculin skin test.                       What you can

4    see is that the percentages very closely parallel each

5    other in each of the independent groups.

6                          We come up here to, of course, the top.                 This

7    is the active TB group.                You come down here to the at-risk

8    group, and if I go to the Walter Reed primary risk group,

9    what you'll see in that primary risk group, where there

10   is a higher risk of tuberculosis and it is, in fact, a

11   reasonable percentage, they are closely parallel.                                As

12   we go across into our lower-risk groups, we're applying

13   stratified cutoffs in both cases, and you will see there

14   is no significant change to the instance of tuberculosis.

15                         So I don't think you'll find there is a major

16   change in the epidemiological beliefs in the country in

17   the incidence of latent tuberculosis using this test.

18                         DR. CHARACHE:          Okay, I'm working from the

19   tables in which there are three risk groups rather than

20   six.       So I couldn't really relate to this.

21                         DR. ROTHEL:         The data I think that you want

22   to see is what I've presented in the talk.                       On the second

23   one of those specificity slides -- I think you have a

24   copy of the slides -- where we apply the 15-millimeter

25   cutoff           to   the    TST    and    the    30   percent    cutoff       for

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1    QuantiFERON.         I think they're the figures you're wanting

2    to see.          Am I correct?

3                        DR. CHARACHE:       I'm sure you have it.

4                        DR. ROTHEL:     Oh, we do have it, yes.          We can

5    put it up.

6                        CHAIRMAN WILSON:        Dr. Janosky.

7                        DR. JANOSKY:      Just a very quick followup to

8    the question that was asked:                Do you have the data to

9    show us the discordance based on age and gender?

10                       DR. ROTHEL:      Yes.

11                       DR. JANOSKY:      What's the directionality of

12   the discordance of what I'm actually looking --

13                       DR. ROTHEL:      Yes, I can talk to it; it is

14   probably easiest.           The table that was in your panel pack

15   actually shows the moderate directional analysis legacy

16   regression.

17                       Age   was     associated        with   a     positive

18   TST/negative QuantiFERON.                 Age greater than 60 was

19   associated with that type of discordance.                  Male sex was

20   associated with having a positive QuantiFERON/negative

21   TST.

22                       DR. JANOSKY:        I did see it in the panel

23   packet, but just to refresh my memory again, you're saying

24   males are more likely to be called positive when they're

25   not and older individuals are more likely?

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1                     DR. ROTHEL:     Males are more likely to have

2    a QuantiFERON positive/TST negative response than having

3    a concordant response with both tests, either doubly

4    positive or doubly negative.           So that was the reference

5    group for all of that discordance analysis for individuals

6    with concordance results.

7                     DR. JANOSKY:     Okay.      That's what I needed.

8     Thank you.

9                     CHAIRMAN WILSON:       Dr. Lewinsohn?

10                    DR.   LEWINSOHN:        I    guess        a     couple        of

11   questions.       The first was I think a test that doesn't

12   require coming back to the doctor obviously has some real

13   advantages over the current skin test.                     So I was just

14   looking over the data that's on page 40 that had to do

15   with exclusions from the trial.              I'm just trying to add

16   these up very quickly, but it looked as if about 70 were

17   excluded because of reasons sort of related to the

18   QuantiFERON      test;    that   is,    unable        to       draw     blood,

19   insufficient blood, blood clotted, or other QuantiFERON

20   errors, and about 130 were excluded because of TST errors.

21                    I guess my question was, and this is in the

22   context of a clinical trial where things are being done

23   very carefully:        What's been your experience with regard

24   to blood being drawn for the QuantiFERON and then

25   ultimately not actually having the test successfully

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1    done?

2                     DR. ROTHEL:     It's a fairly uncommon event,

3    and a lot of events listed there are quite explainable.

4     One, an incubator went down.           I think there were 40 or

5    something blood samples just lost in one event by an

6    incubator going down overnight.            Another one was at one

7    of the trial sites and the lady had been there to collect

8    the blood samples, slipped on the snow, on the ice, and

9    broke them all.        Yes, there's a few things like that.

10                    You do see occasional blood samples where

11   the people haven't shaken the heparin tube and you get

12   blood clots.      There's no point in running that sample.

13                    You do see occasions where a phlebotomist

14   has not collected sufficient blood to do it.                      Quite

15   commonly, people think, "Oh, I've got a mil in there.

16   We'll take the tube off now and do the next person."

17   That is an occasional thing.               It's just a matter of

18   training individuals to say we need at least 5 ml of blood

19   in the tube.

20                    DR.   LEWINSOHN:        And   then   some     of     the

21   requirements are fairly tight.            For example, incubating

22   the blood within the first 12 hours, is that an issue

23   for places that don't have a 24-hour lab?

24                    DR. ROTHEL:    I think it probably has got some

25   issues in some settings, yes.           Situations where there's

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1    a path lab associated with a hospital nearby, that's not

2    an issue at all.       It's quite a normal sort of practice.

3     If you're out in the middle of -- we call it "the Outback";

4    I don't know what you call it here -- if you're out in

5    the middle of there --

6                     DR. LEWINSOHN:       Oregon.

7                     (Laughter.)

8                     DR. ROTHEL:      Yes, Oregon, okay.       If you're

9    out there and you collect a blood sample in some remote

10   country town with no pathology lab, yes, it would probably

11   be an issue to get it to the local town by then.                     But

12   you've got to remember, too, the screening generally

13   happens at large institutions.              It's not something the

14   local GP generally does to you.

15                    DR. LEWINSOHN:       I have two more questions.

16                    CHAIRMAN WILSON:        Go ahead.

17                    DR. LEWINSOHN:       My other question had to do

18   with the issue of BCG.          I was just going over the paper

19   that was published where you gave the medical students

20   BCG.       While most people had a quantifiable rise, I guess

21   it was about 15 percent that actually would have been

22   interpreted as going from negative to positive in that

23   regard, and that was just one point in time.                        Your

24   argument is that perhaps QuantiFERON is better able to

25   distinguish BCG exposure.

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1                       So my question is, first of all, in those

2    medical students, have you had a chance to look down the

3    road; that is, did their QuantiFERONs come back down as

4    you might expect?          Kind of as a corollary to that, at

5    least we know from the skin test that most people, if

6    they've had at-birth BCG vaccination, will have a negative

7    skin test by the time they're 20 or so.                 So is there a

8    correlation with age and the likelihood of having a test

9    that's TST positive/QuantiFERON negative?

10                      DR. ROTHEL:     Yes, that group, I agree, there

11   were about 15 percent positive by QuantiFERON and I think

12   12      percent     or    something      positive       by      the       TST.

13   Interestingly, though, different people.                     But, no, we

14   haven't had a chance them up, the short answer.

15                      To give you a better answer to the question,

16   in the Streeton study, out of 478 in the low-risk group,

17   in the zero group, roughly 200-or-so, off the top of my

18   head,       came   from   Dr.    Jonathan     Streeton's         practice.

19   They're Australian-born individuals of various ages, and

20   BCG vaccination was routinely used in Australians about

21   13 in years of age or 16 in 1994.                   So anyone of the

22   appropriate age had been BCG-vaccinated.

23                      Of those 200 that Jonathan recruited into

24   that low-risk group, I think it was around about a third

25   were BCG-vaccinated.            There was absolutely no effect of

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1    BCG vaccination comparing them to the other individuals

2    that hadn't received BCG.         They were looking at a longer

3    timeframe rather than this five-month experimental period

4    we used.

5                     DR. RADFORD:      I might also ask Dr. Damien

6    Jolly, who is a consultant statistician for Cellestis,

7    as he has a comment to make on this subject, if that's

8    okay.

9                     DR. JOLLY:     My name is Damien Jolly.             I'm

10   employed by Deacon University in Melbourne, Australia.

11    I work as a consultant for Cellestis Proprietary Limited.

12    I have purchased shares in that company.

13                    I would like to address the question asked

14   by Professor Carache particularly with respect to the

15   table on page 77 of the provided pack, because I'd like

16   to direct your attention to page 2-196 in the appendix

17   quite a way through, appendix 2, page 196.            In this title

18   you'll find the complete breakdown of the WRAIR dataset

19   by cutoff at 10 percent of QuantiFERON in human response,

20   15 percent QuantiFERON response, 30 percent QuantiFERON

21   response, and also stratified by the various risk groups

22   within the WRAIR dataset.

23                    You'll notice that in these tables all the

24   numbers in the middle column add up to exactly the numbers

25   that are presented on page 77, which was the title which

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1    concerned you.      The column on the right provides all the

2    data for the cutoff at 30 percent, which provides the

3    actual concordance and discordance data at the level of

4    30 percent.

5                     I submit this, Mr. Chairman, simply for the

6    point of clarification.

7                     CHAIRMAN WILSON:       Thank you.

8                     Dr. Charache?

9                     DR. CHARACHE:     I think that's very helpful.

10    As I said, I'm looking for a way of having this available

11   without the false positives.             I'm wondering about the

12   possibility of using that same cutoff for all risk factor

13   groups.

14                    The reason for changing the millimeters is

15   based on positive predictive value.              If we looked at it

16   from the same perspective, I'm wondering if it would be

17   of value to correct in a similar manner all groups, because

18   you can see, even in the high group, you see a similar

19   degree of change.       So that's one among my question, is

20   whether this is really set in a way that would avoid false

21   positives.

22                    CHAIRMAN WILSON:       Okay.    Dr. Ng?

23                    DR. NG:     I think my question is for Dr.

24   Catanzaro.       One of the arguments in favor of this test

25   is the 30 percent no-show rate for the second reading

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1    of the TST.      I'm assuming you want -- let me restate this.

2     People who come back to get their TST read is often a

3    surrogate for those people who will continue to be

4    followed and be tracked, et cetera.               So my question to

5    you is, of that 30 percent who do not return, how effective

6    is the public health system in identifying these people

7    and following them and being able to track them down,

8    if they don't return for this appointment?

9                     DR. CATANZARO:       Well, it depends completely

10   on the clinical situation.            As I said, I work at UCSD

11   Med Center.      We basically have no ability to follow people

12   up and go out into the community.                On the other hand,

13   the Health Department is very much structured to do

14   exactly that.      I think, frankly, that's where this really

15   makes a difference because, if you skin test 100 people,

16   you can expect perhaps 10 or 15 percent, depending on

17   the setting, to be reactive.                To focus in on those

18   individuals needing followup is to reduce the workload

19   dramatically.       I think that that's where this kind of

20   test plays a very strong role.

21                    A similar situation is prisons, where there

22   are a large number of inmates that come through that system

23   and often leave the system fairly promptly, depending

24   on whether you're in a prison, jail, et cetera.                 Again,

25   it's a matter of following up a small number of individuals

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1    rather than following up everybody.

2                     I think you're completely right as returning

3    for a reading being a surrogate of taking the pills on

4    your own.        The CDC has been stressing to a very great

5    extent observed therapy under various situations -- in

6    prisons, in substance abuse centers, in mental health

7    situations.       In each of these situations, knowing that

8    the population you're dealing with is -- or focusing in

9    on the target population -- is to eliminate a large part

10   of the workload.       So that's how I see the applicability

11   of a one-time measurement being better than a two-time

12   measurement, even though I quite agree with you that

13   returning for a reading is a surrogate for whether you'll

14   return for treatment.

15                    DR. NG:     So then you have no information,

16   in your example, if you had 100 people skin tested, 30

17   don't return, how effective the system is at finding those

18   30 to get the second reading?

19                    DR. CATANZARO:        That's correct, I have no

20   information.        I submit it will be different in each

21   setting.

22                    CHAIRMAN WILSON:        Dr. Baron?

23                    DR. BARON:      I just have a quick question

24   about non-tuberculosis mycobacteria other than MAC.                    We

25   see a lot of kansasii and chelonae and that sort of thing

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1    in our setting.        Have you looked at the results in those

2    patients?

3                       DR. ROTHEL:     No, we haven't looked at that

4    yet.        I think it's very difficult to find those patients.

5     I'd be interested in speaking to you later to see if

6    we can do a study.          That's a very rare event, from my

7    knowledge.

8                       But the best information we have there is

9    from the bovine model, where we experimentally infected

10   animals with kansasii as well M. avium, if you remember,

11   and animals with kansasii came out with the avian profile

12   in the QuantiFERON, all above or equivalent in the

13   QuantiFERON test.

14                      CHAIRMAN WILSON:       Dr. Cockerill?

15                      DR. COCKERILL:      I think this is in the data,

16   but     I    was   trying   to   determine this.          This is an

17   interesting slide here.          When clinicians look at patients

18   with tuberculin skin tests, even a 5-millimeter skin test

19   can be considered positive for latent TB based on, I

20   believe, the CDC criteria.             It would be interesting to

21   see specificity comparing the QFT to the TST when it is

22   interpreted as a positive based on the CDC criteria,

23   whether it be 5 or 10 millimeters.                      Fifteen, as I

24   understand, is a positive, regardless of what the patient

25   presents at, the point being that in groups one or low-risk

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1    groups you will find a 15-millimeter induration.                        As we

2    focus on these various groups, I don't want to lose track

3    of what the comparison is to "a standard" that may not

4    be a gold standard, and by virtue of criteria that have

5    to be developed to interpret it, we have some sort of

6    gold standard.                How does this stack up compared to the

7    interpretation of 5 versus 10 versus 15?

8                            DR. ROTHEL:        All of the data that I've

9    presented for the TST was done by a risk-stratified

10   cutoff, which is the CDC guidelines cutoff.                  In the panel

11   pack you have data presented to you using a 10-millimeter

12   cutoff.                 Then     there's      also     something      called

13   risk-stratified cutoff.                That's precisely using the CDC

14   ATS-recommended cutoffs for the TST.

15                           DR. COCKERILL:     So the positive 5-millimeter

16   in the charts was a 5-millimeter that was interpreted

17   as a true latent state based on the CDC criteria or was

18   it just the measurement?

19                           DR. ROTHEL:    The CDC criteria suggests that

20   for people that are TB suspects you use 5 millimeters;

21   for people suspected of latent TB, having risk factors

22   for latent TB infection, you use 10 millimeters; for

23   people           with    no    identified     respecters,    you     use     15

24   millimeters.             Those are the cutoffs we have used for those

25   respective group.

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1                      DR. COCKERILL:           Okay.     So a 5-millimeter

2    patient, if they come and they're 5 millimeter induration,

3    if      they     don't     fulfill      criteria      for   a     positive

4    interpretation of that CDC criteria, that was not included

5    as a positive?

6                      DR. ROTHEL:        No.   So individuals at risk of

7    latent TB, if they had a 5-millimeter reaction, would

8    be deemed as negative.

9                      CHAIRMAN WILSON:          Dr. Beavis?

10                     DR. BEAVIS:         I had a question about your

11   slide 31.        It's also presented in the data packs that

12   we received.       It concerns the cutoff for the percent avian

13   difference.

14                     My     understanding        as   to     how   that       was

15   determined is that you've got people with known TB, known

16   MAC, and then drew a line trying to discriminate between

17   the two groups.          It was Dr. Wood, he said it beautifully.

18    He said that adjusting the cutoff depends on the goal.

19                     I was wondering what your thoughts were and

20   how you picked the cutoff for this.                 Because you're not

21   calling any of the people with known MAC positive for

22   TB, but you are leaving a couple of people off who are

23   TB-positive and calling them negative.                    I realize it's

24   overlapping groups, and no matter where you set the

25   cutoff, you're going to wrong in some of the patients.

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1     But if you could give me a little bit of your thought

2    process with that, please?

3                       DR. RADFORD: We haven't anything in here to

4    sort of address that in the active TB groups, but I would

5    say that the general thrust was to actually include all

6    positive TB cases rather than to diagnose MAC infection.

7     What we're trying to do is to exclude those that we can

8    have       a     very   strong     assurance       of      are,   in     fact,

9    MOTT-reactive rather than TB.

10                      Now what we've done, and I think it might

11   be in the panel pack as well, or is it?

12                      DR. ROTHEL:        No, I don't think it is.               Oh,

13   yes, it is, a graph.

14                      DR. RADFORD:        I have a graph here that looks

15   at the use of avian at different cutoff levels in patients

16   in       the      CDC     study       with      active       tuberculosis,

17   culture-confirmed.

18                      What we see, applying the minus 10 percent

19   avian in different cutoffs, is that there is in fact a

20   very large threshold.              We could, in fact, increase the

21   avian difference a great deal more before we start losing

22   sensitivity for TB.             So there is an argument to be made

23   we have not put a stringent enough threshold on, but in

24   the studies we've seen today we believe that it's better

25   to diagnose tuberculosis than to identify a MOTT reactor.

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1     So, again, that's another reason for discordance that

2    could occur in the test.

3                     DR. BEAVIS:        So are you saying that you would

4    consider changing that cutoff for minus 10 percent?

5                     DR. RADFORD:         This is the best cutoff we've

6    had to date, and the data we have supports it, and we

7    believe it does.          We have that original study that does

8    support that.          It's done in patients which actually have

9    an immune response in many cases; other patients with

10   MAC responses are immunocompromised.

11                    DR. BEAVIS:         I just want to be clear, make

12   sure that we're in agreement.                I guess it's always the

13   case      with   any    laboratory       test,    when    you   have       two

14   overlapping groups, that no matter where you put your

15   cutoff, you're going to misclassify some patients.                          In

16   this particular situation one has the option of calling

17   some TB patients negative or you can call some MAC patients

18   positive for TB.           The way that the cutoff was made, it

19   seems that the choice is made to make the error of calling

20   some of the TB patients negative rather than MAC patients

21   positive.

22                    DR. RADFORD:         If I can just add something,

23   yes, it does like that from that original study we did.

24    We set at a minus 10 percent, but that cutoff was then

25   being used in all subsequent studies we have done.                         The

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1    best example is probably when we've got a gold standard,

2    which is individuals with culture-confirmed TB disease.

3     We haven't missed any, from off the top of my head.

4    I have to check the figures.          I don't think we've missed

5    any individuals with a culture-confirmed TB disease due

6    to them having an avian difference less than minus 10

7    percent.

8                     DR. BEAVIS:     Of minus 10 percent?

9                     DR. ROTHEL:    Of less than minus 10 percent,

10   yes.

11                    DR. BEAVIS:     Okay.

12                    DR.   RADFORD:       Well,     to    be     absolutely

13   correct, if you'll see my graph there, we missed one.

14   If we had gone down to minus 40 percent --

15                    DR. BEAVIS:     Exactly.

16                    DR. RADFORD:     -- we would have had one more.

17                    DR. BEAVIS:     Okay.

18                    CHAIRMAN WILSON:        In light of our need to

19   stay on a tight schedule today, we only have time for

20   a couple of more questions.

21                    Dr. Nolte?

22                    DR. NOLTE:     I'd like to follow up on the

23   percent avium difference.          Basically, has the data been

24   analyzed if you didn't consider the percent avium?                              I

25   mean I'm trying to figure out what the effect is on the

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1    overall test in terms of having this additional component,

2    because there's little data presented to the panel that

3    documents its effectiveness in avium or MOTT-infected

4    individuals?           Do you know what I'm trying to get at?

5                          DR. ROTHEL:          Yes.        I know where you're

6    coming from.           We've got a slide to address that.

7                          DR. NOLTE:        I mean, does it contribute?

8                          DR. ROTHEL:        Yes, that contributes greatly

9    to specificity.

10                         DR. NOLTE:        I'm sorry?

11                         DR. ROTHEL:         That contributes greatly to

12   specificity.

13                         DR. NOLTE:        Greatly?       Yes.

14                         DR. RADFORD:        What I have here, I've got more

15   slides, looking at two different groups, three different

16   groups, and illustrating the effect on sensitivity and

17   specificity.

18                         What we can see here -- and we're looking

19   at the high-risk individuals in this top group, and we're

20   looking          at   it    with    a   range     of    various     percentage

21   differences cutoff, and "no ADCO" there refers to no avian

22   difference supplied at all.

23                         What you really have to look at, when you

24   look at those tables, is think about it in terms of those

25   two-by-two tables we described.                         The number of PPD

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1    positive, QuantiFERON positives in the CDC at-risk group

2    up there is reflected on the NOAD code 158.                    So that's

3    actually a rise from 145, I think, in the original figure

4    to 158.

5                      What we see, though, here is a TST-positive

6    QuantiFERON negative at 70 percent, where it should be,

7    but       the    QuantiFERON       positive/TST         negatives       rise

8    substantially from a figure -- actually, I think it was

9    80, my recollection, 72, sorry, up to 122.                      So we're

10   getting 50 more QuantiFERON positives if we don't apply

11   the avian difference level.

12                     I think that generally is reflected in most

13   of the data.            We lose sensitivity -- sorry, we lose

14   specificity.        We do, in fact, maintain concordance.                  In

15   fact, it's quite interesting to see that you actually

16   can get a better concordance with PPD to some degree by

17   actually doing this, but, of course, you do get these

18   QuantiFERON positives at a higher level.

19                     DR.     NOLTE:        Again,      with    the       avian

20   difference, the only patients that were documented avian

21   infections are the 10 or 15 or so children that were

22   described in the packet insert?

23                     DR. RADFORD:       That's correct.

24                     DR. NOLTE:       Obviously, this is not meant as

25   a diagnostic aid for MOTT infection?

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1                     DR. RADFORD:     No, this is not being intended

2    as a diagnostic guide for MAC.

3                     CHAIRMAN WILSON:       Okay, time for two more

4    questions.

5                     Dr. Lewinsohn?

6                     DR. LEWINSOHN:     I was very interested, there

7    was a table that's shown on page 48 that looks at a subgroup

8    of patients, I guess it was 39, who had discordant results

9    and where you were able to retest them.                I was actually

10   surprised at the numbers that changed their results on

11   retesting.       So, for example, if you were QFT-negative,

12   I think there were a total of nine that on retesting became

13   QFT-positive.      Also, if you were QFT-positive, I think

14   there were -- what is it here? -- there was a total 21 --

15                    DR. CHARACHE:     It's on the last three lines

16   on that page.

17                    DR. LEWINSOHN:      I think it was a total of

18   21 that changed.       So I'm just interested to know what

19   your thoughts about what accounts for those test changes.

20    Obviously, the TST changed in some cases as well.

21                    DR. ROTHEL:    To be honest about my thoughts,

22   I can't really glean anything from it.                It's a terribly

23   biased population of individuals.              They had discordant

24   results initially to start with.           To really do this study,

25   you need to do individuals that had concordant results,

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1    both positive and negative concordant results.

2                     There's only a very small number of the

3    individuals that were meant to be done who had this done.

4     The biggest factor is:            What is the effect of having

5    a prior TST on the QuantiFERON test?                  We've done that

6    in cattle, and we've shown that initially it depresses

7    responses to subsequent QuantiFERON tests and then boosts

8    them for a while, and then past 30 days they come back

9    down to normal.        We haven't done that in humans, but it's

10   just to me some data we have to present in here because

11   it was in the protocol, but it's somewhat irrelevant.

12                    DR.    RADFORD:      To    perhaps      answer       your

13   question as to whether or not it actually relates to the

14   stability of the test, we actually do have data presented

15   showing reproduction of the test in individual --

16                    DR. LEWINSOHN:       No, I was more interested

17   in the issue of interference between the TST and the

18   QuantiFERON and as to whether you would, as part of your

19   advice to clinicians, tell them to one or the other, or

20   if they were interested in doing both, to do one first

21   and then the other?

22                    DR. ROTHEL:     A good point.         I think you've

23   raised something I must admit we hadn't thought of, that

24   you should advise people if they perhaps are going to

25   do both tests.         I don't know why you'd want to do that,

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1    but if you were going to do both, yes, you'd want to do

2    QuantiFERON before placing the TST.

3                       CHAIRMAN WILSON:          A final question, Dr.

4    Reller?

5                       DR. RELLER:     I work in North Carolina, where

6    the prevalence is considerably higher than -- we're in

7    the upper quartile nationwide.              So it's more than 10 per

8    100,000.         Smear-positive patients, to give some feel for

9    the magnitude of MOTT infections, it's about four or five

10   to one; that is, if we have a smear-positive, it's far

11   more likely to be.               Some of those patients, it's

12   controversial what constitutes disease.

13                      So in that sort of population, how would you

14   expect this test to work?             Do you have any experiences,

15   is it even possible by looking at the other side of things,

16   the response to the avium antigen stimulation that one

17   might even be able to, owing to the response, separate

18   out those people who have real disease with MOTT versus

19   those who are simply colonized?

20                      So there's two parts.         One is, how would you

21   expect the test to perform in our area and what about

22   its use from a totally different perspective?

23                      DR. ROTHEL:       I would expect the test to

24   perform quite well in your area in discriminating between

25   the two infections.          As far as looking at disease, that's

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1    specifically what that study was done that we used to

2    establish the percentage avian difference cutoff, the

3    paper by Stapledon, et al., which is appended in your

4    panel packet, physicians working in Adelaid.                They wanted

5    to use the test to do exactly what you're talking about,

6    discriminate      between    disease     caused       by   TB    or     MOTT

7    bacterium avium complex.

8                     They found in that data they would use a

9    different cutoff to do that interpretation.                  That's not

10   what we're proposing the test for, of course, in this

11   situation, but it discriminated 100 percent, I think is

12   the conclusion they drew in that paper.

13                    Again, it's a limited study, and I think for

14   that application we need to do obviously vastly more work,

15   but I think it's got applications there.

16                    CHAIRMAN WILSON:        Okay, while the FDA is

17   getting their presentation materials together, let's take

18   a very brief break, about five minutes.

19                    (Whereupon, the foregoing matter went off

20   the record at 10:44 a.m. and went back on the record at

21   10:54 a.m.)

22                    CHAIRMAN    WILSON:         Okay,     I'd      like       to

23   reconvene the meeting at this time, please.

24                    At this point we'd like to move on to the

25   FDA's presentation.         Again, I'd like to ask the panel

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1    members          to    hold   any     questions       until     all      three

2    presentations are complete.                  I'd like to remind the

3    audience that only panel members can ask questions of

4    the speakers.

5                          FDA, the first presentation will be given

6    by Roxanne Shively, who is a Senior Scientific Reviewer

7    for the Bacteriology Devices Branch.

8                          MS. SHIVELY:      Good morning.         It's kind of

9    hard coming after such good discussions have already

10   opened up a lot of issues.

11                         For FDA, the QuantiFERON-TB application is

12   a multi-level endeavor.               Not only is there a bridging

13   of the continents with Australia here, but within FDA

14   we've had cross-center activity with CDER participation,

15   CBER, and of course CDRH on this review.

16                         We really appreciate the company's effort

17   in compiling the panel packages for you and their complete

18   presentation to you this morning.

19                         Because of the public health importance of

20   a test for used for diagnosing latent TB infection, FDA

21   review of this application is expedited.                   We also brought

22   this to the Microbiology Advisory Panel early in the

23   review cycle because we recognize the importance of

24   questions related to evaluating the performance of a new

25   assay when the only current approach, the tuberculin skin

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1    test, has considerable limitations.                      We believe your

2    input will help the company and FDA to most efficiently

3    develop a path for identifying the clinical merits of

4    this assay.

5                     Next     slide.       The    first      part    of     FDA's

6    presentation covers the intended use for the QuantiFERON

7    assay, a brief discussion of in vivo versus in vitro

8    testing, and then some elements of the QuantiFERON

9    analytical performance that we believe is important to

10   the discussion overall today.

11                    The QuantiFERON assay is submitted as an aid

12   in the detection of mycobacterium tuberculosis infection.

13    This is the same labeled intended use as tuberculin PPD

14   for in vivo use.              The proposed labeling does have

15   limitations, as already mentioned, and we would note that

16   the primary clinical studies did not include these groups,

17   either pregnant women, 17-year-olds, or HIV-positives,

18   other immunosuppressed.

19                    I would like to clarify one thing that came

20   up the end of the discussion, that this assay is not

21   submitted        to   differentiate        individuals          with      MOTT

22   infection.       The avium PPD portion of the assay is intended

23   to control for cross-reactivity, and it hasn't been

24   evaluated for differential capabilities.

25                    We are at the next slide.               Much of the data

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1    and information available to characterize the QuantiFERON

2    is relative to skin testing.          One of our concerns is how

3    to understand differences that would affect who is tested

4    and how we use the results from the new assay.

5                     The areas that I will initially present look

6    at similarities and differences between these two tests.

7     This slide blocks out in a very simple way the basic

8    elements of the skin test versus the QuantiFERON.                   The

9    company has already discussed differences here at the

10   pre-analytic level; that is, intradermal injection versus

11   collection of the venous whole blood, and performing the

12   test in the clinic versus performing the test in the

13   clinical laboratory.

14                    We would like to point out that one of the

15   cited advantaged that the company makes is that the

16   QuantiFERON assay has the benefit of being a lab-based

17   test that will add greater control and standardization.

18    We will want to look and make sure that that control

19   and standardization within the clinical laboratory is

20   possible, too.

21                    The direct common elements between the two

22   tests is the human PPD reagent.          That is the same reagent

23   as the tuberculin PPD that's used in the skin testing.

24    Although the two tests use different measures, they

25   essentially       are   measuring      an    individual's      immuno

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                                                                                    84
1    response.        The TST does have the progressive end-points

2    that have already been discussed.                    As the company has

3    presented, they are proposing to change the cutoff for

4    the QuantiFERON to a scaled differential cutoff based

5    on risk.

6                         I would like to point out that with this

7    cutoff modification that we have encourage the company

8    to look at options with the cutoff, and that the new

9    analyses and data supporting this were submitted within

10   the past two weeks, right at the time of your panel packs.

11    So we wanted you to have this available, but we will

12   be focusing on the original data that was submitted to

13   us, looking at the implications of the tools and how we

14   evaluate comparisons between the two assays and overall

15   performance parameters.

16                        Okay, next slide.          This slide illustrates

17   the initial immune response at the cellular level and

18   what is being measured by the skin test on top and the

19   QuantiFERON on the bottom.                 Both assays are detecting

20   components of cell-mediated immunity reacting to antigen

21   that is injected intradermally for the skin test and added

22   to the blood culture for QuantiFERON.                        The skin test

23   measures         a    delayed-type        hypersensitivity           reaction

24   resulting        from     the    interaction       of      multiple     cells,

25   including memory T-cells and the network of cytokines

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1    and other immune mediators.            The QuantiFERON measures

2    the presence of these memory T-cells, which are down in

3    the dish now, in a venous blood sample by the production

4    of gamma interferon.

5                     One other difference at the cellular level

6    that already came up in the discussion that could affect

7    responses in each of these assays is that, when the PPD

8    is injected intradermally, memory T-cells are recruited

9    to the site of infection; whereas, with whole venous blood

10   the circulating T-cells that are sensitized that are the

11   memory T-cells are already present in the venous draw

12   that is collected.       So there's no recruitment.

13                    You have already asked about the differences

14   in white cell levels and the effect of those levels on

15   QuantiFERON results.         We would certainly welcome your

16   comments on the need to look at that type of data to qualify

17   and standardize this assay, too.

18                    Next slide.     The next few slides highlight

19   some of the things we know about skin testing accumulated

20   from its history of use.           Our primary question to you

21   today is going to be, how can we best describe similar

22   attributes for the QuantiFERON and what statistical tools

23   are best to use?

24                    The delayed-type hypersensitivity reaction

25   of the skin test is detectable two to twelve weeks after

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                                                                                   86
1    infection.       From available research, we would expect

2    gamma interferon to parallel that.

3                     Sensitivity of skin testing approaches 100

4    percent in persons with normal immune responsiveness,

5    but up to 25 percent of infected or diseased individuals

6    we know may be falsely negative.                    Most of these may

7    primarily be due to HIV immunosuppression, but also

8    certainly the other host variables and problems cited

9    by Dr. Catanzaro.

10                    Next slide.         Specificity of the TST is

11   improved by increasing the reaction size that separates

12   a positive from a negative reading, and we expect, as

13   Dr.       Charache     has   already      pointed        out,       improved

14   sensitivity using those cut points.              We would expect that

15   approximately 95 percent specificity when there is common

16   cross-reactivity in the population with non-tuberculosis

17   mycobacteria.        We are including BCG and NTM together as

18   non-tuberculous         mycobacteria        in    this        category        as

19   potential cross-reactants.            When BGC vaccination or NTM

20   is not common, we would expect the specificity to be higher

21   and about 99 percent.

22                    Our    last    point:        The       TST    performance

23   overall, both sensitivity and specificity, is affected

24   by other population variables, too, such as age, the

25   prevalence of disease, and in addition to BCG vaccination

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1    and non-tuberculosis mycobacteria.

2                     Next slide.     We've already discussed using

3    the progressive cut points.          These are the joint CDC/ATS

4    criteria, using 15 millimeters for a low-risk population,

5    10 millimeters for those with increased or moderate risk,

6    and the smallest cutoff, 5 millimeters -- actually, it's

7    the most stringent -- in the high-risk groups.

8                     Next slide.     Risk assessments on which the

9    cut points are based are from both epidemiological and

10   clinically-defined groups.          I am not going to go through

11   all these, but we did want to have them available because

12   it can get confusing, too.          I do want to highlight that

13   the ones in red are those that have the highest risk and

14   would be read at the 5 millimeter cutoff.                You and refer

15   to Table 7 from the joint statement, too, for the complete

16   listing of these.

17                    Next slide.      Using gamma interferon as a

18   marker, a post cell-mediated immunity certainly has a

19   solid foundation of research evidence.                    Besides the

20   importance of gamma interferon in the cell-mediated

21   immune response to MTB infection, reports have shown that

22   production is decreased in patients with active TB,

23   especially those with severe disease.                 This suppression

24   may last more than a year.

25                    We do want to note a word of caution:                 that

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1    the gamma interferon measurements from published research

2    characterizing responses may not always be comparable,

3    depending upon the host models used, the methods, and

4    types of assay used.

5                     Next.    I think I am going to skip this slide

6    because I know we are anxious to get through this.

7                     I am going to go to the basic analytical

8    portion of the QuantiFERON as detecting gamma interferon.

9     Gamma interferon is estimated for each of the four

10   harvested plasma samples, and this is done from an EIA

11   standard curve using the kit standards which are provided

12   in the kit.        These are zero, low, medium, and high

13   standard.

14                    There are acceptance criteria for using these

15   standard results.        Again, I won't go through these, but

16   they are critical because they are the only controls

17   applied to the EIA portion of the QuantiFERON and there

18   is no independent control material in the kit outside

19   of the kit standards themselves.

20                    Next slide.      Okay, the QuantiFERON kit has

21   no external control materials, and also the labeling

22   doesn't recommend any external control materials that

23   could be tested.         Instead, the labeling recommends for

24   QC that the acceptance criteria for the standard curve

25   be used and also adherence to recommended procedures,

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1    and that following these procedures and using the curve

2    acceptance criteria will contribute to control of the

3    assay.

4                       The design of this assay does, however, have

5    an internal control, and that is the mitogen-cultured

6    sample that is supposed to control for functionality of

7    blood cells to produce gamma interferon.                 Another design

8    aspect of the assay is the         nil control, which essentially

9    would control for background of gamma interferon activity

10   in the patient sample.              This is value is acceptable

11   whether it is zero, less than zero, or greater than zero.

12                      Although we would expect this value to be

13   almost always zero, the nil result is subtracted out as

14   background regardless.           We do understand the importance

15   of both the mitogen and the nil for getting reliable

16   results with this assay, but we do question whether they

17   are sufficient for ensuring reproducibly reliable results

18   in clinical laboratories.            We have put that question to

19   you today.

20                      Next slide.     Oops, I'm sorry, that's it.

21                      The decision thresholds are cutoffs for the

22   QuantiFERON assay, and how those cutoffs are calculated

23   has      already    been   described      by    the     company.          The

24   discussion has already rapidly moved forward on modifying

25   these cutoffs and looking at variables that affect the

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1    cutoffs.

2                     So I am not going to linger here, but I do

3    want to point out that basic principles that are used

4    in these studies may affect the outcome of the study and

5    what cutoff chosen.         The major question is whether the

6    cutoff will be applicable to other populations other than

7    the one where the initial study was done.

8                     For the human response cutoff, the Australian

9    guidelines are slightly different than those used in the

10   U.S.       Only nil values greater than zero were used in the

11   calculations, and mitogen results less than 0.5 rather

12   than 1.5 were considered indeterminate.                We would ask

13   whether any of these factors could affect use of this

14   cutoff in other populations.

15                    The same for the percentage avium difference.

16    The study was originally done to show the difference

17   between a group of children who had been infected with

18   MOTT and a larger group of adults who had had TB disease.

19    Again, we would question whether this cutoff would apply

20   to general other cutoffs for controlling the level of

21   cross-reactivity in populations.

22                    One final cutoff that we consider to be

23   important is the mitogen minus nil because it's this value

24   that distinguishes whether an assay will be indeterminate

25   or will be valuable in the QuantiFERON test.

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1                     We would note that, regarding this mitogen,

2    in order to get a 15 percent human response, you would

3    need to have at least a 10 international unit reading

4    with the mitogen.

5                     Next slide.       The last area I want to cover

6    this morning is reproducibility.            There have been various

7    studies presented by the company to support inter- and

8    intra-assay reproducibility.            As pointed out already,

9    there are appreciably difficulties with designing these

10   studies because of the nature of the assay itself.

11                    We are going to look at the one study that

12   we    consider    to   be   very    good in that it looks at

13   inter-laboratory reproducibility.                We did not have

14   inter-laboratory reproducibility established during the

15   clinical studies.       So this is an area that concerns us,

16   to be able to ensure that the test can be done reproducibly

17   in different laboratories.

18                    The data is up here, and the table was done

19   using 50 duplicate blood specimens tested at two different

20   sites in Australia.          If you look at the table, the

21   majority of the samples tested were positive in the

22   QuantiFERON, gave an agreement of 98 percent, Kappa .89,

23   with an ICC of .94.         Even though the agreement is good

24   in this study, we would question whether we would see

25   the same type of data when you have more negative results.

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1                     Because of our concerns with controls and

2    not having inter-lab reproducibility across the range

3    of the assay, we also are concerned that results from

4    the      clinical   studies     may     possibly       be    affected         by

5    inter-laboratory variations.            We would certainly welcome

6    your suggestions in the discussion for bridging that

7    concern.

8                     Next slide.     There are additional supportive

9    data from published and unpublished literature with

10   comparisons of QuantiFERON and skin tests.                  These include

11   testing different or selected populations, and the

12   company has discussed some of these this morning.                        These

13   also include the Bovigam studies done using the assay

14   that's very similar to the QuantiFERON but does have

15   different reagents and a different methodology.

16                    Also, we would note regarding the studies

17   in animals that there is a different host, a different

18   pathogen, and different tests were used.                    We would again

19   welcome your comments on how to position these additional

20   studies into the wealth of information that we have from

21   the      clinical   studies,      and     even     further,          how      to

22   statistically evaluate those assays and derive some

23   meaningful statistics from that data.

24                    Next slide.          Dr. Leonard Sacks will be

25   covering the clinical studies in the next minute.                      Before

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                                                                              93
1    ending, I do want to point out that there are differences,

2    very small differences, between the published CDC data

3    and what is being presented here.               Also, of course, we

4    are going to be looking at some new data today using the

5    30 percent cutoff.        As I mentioned before, this has been

6    very recently submitted.            We would encourage you all to

7    consider how we can best look at this proposal and the

8    new analysis done, and how we should validate new cutoffs

9    to be used in the different calculations.

10                    So I'll turn it over to Dr. Sacks now.             Thank

11   you very much.

12                    DR. SACKS:      Good morning.         My name is Dr.

13   Sacks, Leonard Sacks, from the Division of Special

14   Pathogens, and I will be spending the next approximately

15   ten minutes reviewing the clinical use of QuantiFERON

16   as an assay for tuberculosis.            I will be restricting my

17   presentation      to   the    two    pivotal    studies     that      were

18   submitted by the applicant.

19                    Can I have the first slide, please?

20                    Just a bit of background, and I think a lot

21   of this has already been covered and most of the audience

22   is familiar with it.         But there are several ways in which

23   people respond to exposure to tuberculosis.                  These may

24   range from no detectable response through simple skin

25   test      conversion   and    self-limited       primary     complexes

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                                                                                  94
1    developing in the lung with or without positive skin

2    tests.           Then there are a couple of responses which may

3    result in overt or active TB, the primary progressive

4    TB, as a result of the initial exposure or reactivation

5    subsequently once exposure has already occurred.                        It is

6    really in the first three categories that latency becomes

7    an issue.          This is the area where QuantiFERON has proposed

8    its utility.

9                         Let's go on to the next slide.            These were

10   the intended uses of QuantiFERON as submitted in the

11   original application.                  It was to be an aid in the

12   detection           of     latent       mycobacterium        tuberculosis

13   infection.          There were a couple of other points that were

14   included.

15                        First of all, that a negative result does

16   not preclude active tuberculosis.                     Second of all, that

17   the       QuantiFERON          tests     may     be     inconclusive         in

18   immuno-compromised or immunosuppressed individuals and

19   those with no cellular or impaired cellular immune

20   response to tuberculin.                Finally, that the safety and

21   the effectiveness of this test was not established in

22   individuals under 17 years of age and in pregnant women.

23                        Let's go on to the next slide, which again

24   reiterates some of the points that were very adequately

25   made early on, but there is no gold standard for the

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                                                                                95
1    diagnosis of latent tuberculosis.               The tuberculin skin

2    test is one of the methods or one method that is used

3    to detect latency.        The tuberculin skin test allows the

4    institution of prophylaxis to prevent reactivation in

5    patients having a positive test, and that's how it is

6    conventionally used.

7                     The tuberculin skin test is fraught with

8    problems.        As we know, it is an archaic test.                 It has

9    problems with sensitivity, particularly in patients who

10   are immunosuppressed or such as HIV-positive patients

11   or patients on steroids, et cetera.             It has problems with

12   specificity related to infections with mycobacteria other

13   than      tuberculosis,    and    it    has    the      well-recognized

14   practical limitations of compliance.                   Patients have to

15   come back for a re-read after 48 to 72 hours.                    There is

16   some subjectivity in interpretation of the size of the

17   induration.       There is some discomfort in the application.

18                    The last point to be made here is that only

19   a small proportion of TST-positive patients will actually

20   develop TB, approximately a 10 percent lifetime risk.

21                    Let's go on to the next slide.              Now in the

22   absence of a gold standard, what methods can we use to

23   evaluate a new diagnostic test for latent tuberculosis?

24    What I have done is just put up a couple of suggestions.

25    There are obviously many other different ways in which

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                                                                                      96
1    this can be approached.

2                           First   of     all,    one    could     contemplate            a

3    prospective study to determine the ability of a positive

4    test to predict active tuberculosis.                         Another method

5    would be to compare with existing diagnostics for the

6    diagnosis of latent tuberculosis.                     The third suggestion

7    would be to correlate the performance of the diagnostic

8    test with the clinical risk for tuberculosis.                         It is the

9    latter           two   approaches      that    have     been    used     by     the

10   applicants.

11                          Let's go on to the next slide.             There, too,

12   pivotal studies, one performed in collaboration with

13   Walter Reed, one performed in collaboration with the CDC,

14   these were roughly the inclusion and exclusion criteria.

15    The Walter Reed studied included naval recruits.                                It

16   was a single-site study based in Illinois at a recruiting

17   center, although the actual enrollees were from all over

18   the country.            They were to be HIV-negative.

19                          The CDC study, to some extent this was a

20   clinic-based study, a multi-center study on clinic

21   subjects presenting for screening with tuberculin skin

22   tests.           It was a five-center U.S.-site study, as was

23   mentioned before, in Massachusetts, Maryland, two sites

24   in California and New Jersey.                       Patients over 18 years

25   of age, also HIV-negative, and non-immunosuppressed.

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                                                                                 97
1                      So there were a lot of similarities but some

2    differences between these studies.                      They do seem to

3    reflect the demography of patients who would use this

4    test.

5                      Next slide.      Just to give you some idea of

6    the numbers, initially, there were 1,627 enrolled in the

7    CDC study, 1,961 in the Walter Reed study, a total of

8    over 3,000 patients; quite a number of exclusions, 670

9    in all leaving, approximately 3,000 evaluable patients

10   when both studies were pooled.

11                     Let's move on to the next slide.            Just a word

12   about patients excluded from the analysis.                   We did note

13   that almost 20 percent, 19 percent, of all enrollees were

14   excluded.        There were 144 patients excluded at a single

15   site in the CDC study, and this was apparently on the

16   basis of unverifiable informed consent.                        The other

17   reasons for exclusion were also mentioned earlier.                       Some

18   of them were technical errors, incubator failure, the

19   TST was not read at the right time or not read at all.

20                     Let's move on to the next slide.              This just

21   gives you an outline of the demographics in both of these

22   studies.         In the CDC studies we see that this was a

23   slightly older population.            The mean age was 39 compared

24   to 20 in the Walter Reed study.             There were more females

25   in the CDC study, 49 percent, and only 17 percent in the

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                                                                              98
1    Walter Reed study.          There was a higher representation

2    of black persons in the CDC study, whereas 56.3 percent

3    of the patients in the Walter Reed study were white.

4                     Let's    move   on   to    the   next   slide.          In

5    practice, there were seven embedded subgroups within

6    these two big studies, each consisting of different risks

7    for development of tuberculosis.               What I have done in

8    this slide is I have ranked these subgroups for both

9    studies according to increasing risk for tuberculosis

10   as we go down the table.

11                    So in the first Walter Reed subgroup there

12   were       397   patients    with     no    identified      risk        for

13   tuberculosis, and a similar group of 98 patients in the

14   CDC study, again with no identified risk.                     It was a

15   low-risk group of 1,066 patients in the Walter Reed study

16   from the U.S. state with a TB incidence of greater than

17   10 per 100,000.      Then there were two subgroups here which

18   represent the population where TST is often used to decide

19   on prophylaxis.          Two thirty-two patients were in the

20   Walter Reed study who were TB contacts who came from

21   countries where TB was prevalent, and a similar group

22   over here, TB contacts, persons from countries where TB

23   was prevalent:      patients from shelters, intravenous drug

24   addicts, and others.

25                    Finally, there were two categories at the

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                                                                                        99
1    bottom where the risk of TB was appreciable.                             In group

2    three these were patients with pulmonary symptoms which

3    were compatible with those who were evaluation for

4    tuberculosis.               In the risk group four these were patients

5    who had had previously cultured-confirmed tuberculosis

6    and had completed therapy.

7                           Now     the     next     slide     demonstrates            the

8    comparable performance of the tuberculin skin test and

9    the QuantiFERON test.                     Let me just mention that for

10   simplicity and a couple of other practical reasons which

11   I will mention, I have used the 10-millimeter cutoff for

12   the tuberculin skin test across the board.                             I thought

13   that this was an equitable comparison because QuantiFERON

14   doesn't          use    a    ranked       cutoff,    so   I     have   used       the

15   10-millimeter for that reason.                      That is also the cutoff

16   that people would defer to in the risk categories.

17                          Here what we see is that in the low-risk

18   populations up here, these are populations with no risk

19   for     tuberculosis.                We   see   a    tuberculin        skin     test

20   positivity of somewhere between 1 and 4 percent, whereas

21   the QuantiFERON is appreciably higher, between 5 and 8

22   percent.

23                          When we look at the middle risk group, we

24   see that the QuantiFERON and the tuberculin skin test

25   positive rates are somewhat similar.                           In fact, in this

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1    particular group, CDC risk population two, 24 percent

2    and 23 percent.              When we move into the higher-risk

3    categories of either confirmed or suspected tuberculosis,

4    it is clear that tuberculin skin tests are much more

5    frequently positive than QuantiFERON tests, 84 percent

6    in the tuberculin skin test group, 70 percent in the

7    QuantiFERON.            In   patients      with    previous       confirmed

8    tuberculosis, 92 percent positive by TST, 64 percent

9    positive by QuantiFERON.

10                       Let's move on to the next slide, which just

11   shows the same information graphically.                   What I have done

12   here is I have the increasing risk for TB along the X

13   axis and the percentage positive by each of the two tests

14   on the Y axis.          I think it is quite clear that both of

15   these        tests     correlate      with     increasing        risk        for

16   tuberculosis, but there are some differences, and I am

17   going to concentrate on those now.

18                       Let's first take a look at this area of the

19   curve.           Let's go on to the next slide.             How about the

20   performance in high-risk populations?                     Well, we can see

21   that there is clearly differences in sensitivity for the

22   two tests in patients with confirmed tuberculosis.

23                       Now it has been mentioned earlier that there

24   are reports that gamma interferon is decreased in patients

25   with active tuberculosis disease.                   The effect of this

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                                                                           101
1    finding on the sensitivity of QuantiFERON in other risk

2    groups is really unclear.

3                     How about this section of the curve?              Let's

4    move to the next slide.          What we are addressing here is

5    the performance in low-risk populations.                   Now here,

6    although the apparent difference is small, these are the

7    patients who would qualify for TB prophylaxis over here.

8                     Now just bear in mind that, since the lifetime

9    risk of tuberculosis is only 10 percent, many healthy

10   individuals       may   receive      unnecessary       therapy       with

11   potentially toxic drugs.          So our aim would be to maximize

12   the specificity of an assay in this sort of population

13   group.

14                    If we look at population one, which is at

15   the end here, TST was positive in 1 percent of the

16   population, and QuantiFERON was positive in 5 percent

17   of the population.        So potentially a fivefold difference

18   in the number of individuals qualifying for treatment.

19                    What about the middle of the curve?               Let's

20   move on to the next slide.                The performance in the

21   population for intended use, these are patients with risk

22   factors for tuberculosis:           patients from countries with

23   a high incidence of tuberculosis, patients from shelters,

24   and drug users.

25                    I would like to draw your attention to

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                                                                                102
1    population group five.             I have mentioned these a little

2    earlier.          Here both tests look strikingly similar, and

3    the question we are left with is whether the 23 percent

4    that are positive by QuantiFERON in this group are the

5    same individuals as the 24 percent that are shown to be

6    positive by tuberculin skin tests.

7                        The next slide addresses this in some detail.

8     This may be a little confusing.              These are not completely

9    drawn to scale, but let me just orientate you.

10                       This is CDC risk group two, intermediate risk

11   for tuberculosis, 944 patients in total.                  Tuberculin skin

12   test cutoff has been set at 10 millimeters.                   What we see

13   here are those positive by QuantiFERON are in this circle;

14   those positive by tuberculin skin tests are in this

15   circle.          Those negative on both tests are out here.

16                       So we see that 68 percent of the population

17   are negative on both tests, but we can clearly see that

18   there is a discordance between the patients that are

19   detected positive by TST and those that are detected

20   positive by QFT.          What we can see that, if you did a QFT,

21   a third of the QFT-positive patients would not be

22   TST-positive.           Conversely, by TST, a third of the

23   QuantiFERON-positive patients would not be found by TST.

24    So there is a significant discordance even though the

25   absolute percentage of positive tests in both of those

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                                                                               103
1    groups appears the same.

2                     Let's just look at this sort of analysis for

3    a couple of the other risk groups, the next slide.                         Now

4    this is the low-risk group, 98 patients with no observable

5    risk or no identifiable risk for tuberculosis.                      What we

6    see here is TST is picking up less patients; 91 percent

7    or 92 percent approximately are negative by both tests.

8     TST, as I say, is picking up less patients; QuantiFERON

9    is picking up a lot more patients.                    In fact, almost

10   five-eighths      of    the    patients       who    are    positive        by

11   QuantiFERON are not found to be positive by TST.                         This

12   is in the low-risk group.

13                    Let's look at the flip side, next slide.

14   These are patients with confirmed tuberculosis.                          Here

15   we see that the tuberculin skin test positivity is much

16   higher than the QuantiFERON positivity.                 The overlap is

17   pretty good, but QuantiFERON is not picking up almost

18   a third of the patients that are picked up by the

19   tuberculin       skin    test,      a   very        small    number         of

20   QuantiFERON-positive patients that are not picked up by

21   the TST.

22                    Okay, I would like to just change gears a

23   little here.      Let's move on to the next slide.                This was

24   mentioned a little earlier.             I am just highlighting it

25   as an issue of interest.

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1                           These     were         the   discordant       results

2    reinterpreted, or at least retested by both QuantiFERON

3    and TST.         As has been pointed out earlier, this was not

4    a randomized sample.               This did not include patients who

5    had concordant results.                  So I guess, treated with that

6    degree of circumspection -- but what we see here is that

7    patients              changing     from        QuantiFERON-negative           to

8    QuantiFERON-positive, there were 22 patients who started

9    off QuantiFERON-negative with discordant results and 41

10   percent of them became positive on retesting.                       When you

11   do the same thing with the tuberculin skin test in 39

12   patients who had discordant results, you find that 26

13   percent          of    those     who    are    TST-negative    changed        to

14   TST-positive.            So a bigger change in the QuantiFERON.

15                          When we look at the reverse, the percentage

16   of patients who changed from QuantiFERON-positive to

17   QuantiFERON-negative, we see that 54 percent of the 39

18   patients became negative after an initial positive test,

19   whereas in the tuberculin skin test it was unusual for

20   patients to become negative on a second reading, only

21   18 percent or 4 out of 22.

22                          Just one other aspect, the next slide, which

23   was also touched upon.                   These were the results of a

24   subgroup of patients in the CDC study who were identified

25   as being BCG-positive.                 BCG, as we know, may itself affect

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                                                                                 105
1    the performance or at least affect the positive rates

2    of the tuberculin skin test.             It may also be a co-variable

3    for exposure or risk of exposure to tuberculosis.

4                      What    we     see   here       in    157     vaccinated

5    individuals was that QuantiFERON was positive in 43

6    percent; tuberculin skin test was positive in 58 percent.

7     In unvaccinated individuals, the positive rates were

8    the same for both tests.

9                      The next slide just discusses a couple of

10   the thoughts that I had about the qualities of an ideal

11   test for latent tuberculosis.             Theoretically, such a test

12   should always be positive in confirmed tuberculosis,

13   should always be negative in patients with no TB risk.

14    It should be negative in other mycobacteria infections.

15    Conversions from negative to positive should correlate

16   with TB exposure.          Finally, there should be confirmed

17   value of the test in its ability to predict the development

18   of tuberculosis.

19                     As you will notice, a couple of these points

20   have been addressed by this submission.                 Several of them

21   have not.        That may leave some room for discussion.

22                     The    next    slide     just    brings       me     to     my

23   conclusions, which were, first, that the sensitivity of

24   QuantiFERON differs from tuberculin skin tests when it

25   is evaluated in patients with confirmed tuberculosis.

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                                                                                  106
1    I do mention again, or remind you, that interferon

2    production          is    reported     to    be    inhibited     in     active

3    tuberculosis.            The effect of this on the sensitivity of

4    QuantiFERON in other populations is unclear.

5                         Next slide.      Positive rates for QuantiFERON

6    were higher than tuberculin skin tests in low-risk

7    populations.             The pivotal clinical studies did not

8    determine whether this was an indication of poor risk

9    specificity or increased sensitivity of QuantiFERON

10   tests.

11                        Finally, just to remind ourselves that the

12   populations identified as positive by QuantiFERON or

13   positive by tuberculin skin test often differed.

14                        Thank you.

15                        CHAIRMAN WILSON:         Thank you, Dr. Sacks.

16                        The next presentation will be by Mr. John

17   Dawson, who will present the statistical analyses of the

18   data.

19                        MR. DAWSON:       Good morning.        Thank you for

20   affording          me    the   opportunity        to   present    the     FDA's

21   statistical perspective on this application.

22                        I am going to cover two things in my 10 minutes

23   or so.           First, sensitivity/specificity-type evaluation

24   of performance of QFT relative to TST as a gold standard

25   and, secondly, some measures of agreement and some results

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1    using them which may be appropriate if TST is, as we I

2    guess generally agree, not a gold standard.

3                     Next, please.     The sponsor has in their draft

4    labeling estimates of sensitivity and specificity that

5    derive from the Streeton study, 1998 Streeton study.

6    They estimate sensitivity at 90 percent and specificity

7    at 98 percent.         I have a little bit of a worry about using

8    the Streeton numbers rather than the QFT current study,

9    the PMA study estimates in the labeling, because the

10   percent human response cutoff used in this study was

11   derived in the Streeton study and also used to estimate

12   sensitivity and specificity.           When the cutoff is arrived

13   at by ROC analysis, the problem is that performance may

14   be overly optimistic, simply a function of trying to

15   optimize or maximize something about the performance in

16   choosing the cutoff.

17                    This a little bit shows up and possibly

18   explains what happens here when I use the PMA data to

19   estimate sensitivity using the TB suspect category

20   patients,        and      among    those,       those     that         are

21   culture-positive, what I get is an 88 percent estimate

22   for sensitivity compared to the 98 percent in the Streeton

23   study.

24                    Specificity using the low-risk group in the

25   PMA data is 92 percent versus the 98 in the Streeton study.

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1     I don't know whether this is because of overoptimism,

2    but I am simply pointing out that it is probably not

3    appropriate to use the numbers from the Streeton study

4    in the labeling in place of numbers from the PMA study.

5                        Another problem that we have with these

6    estimates, the sensitivity and the specificity, is that

7    they are based on selected parts of the intended-use

8    population, rather small groups at the two extremes, the

9    low-risk group and the TB-suspect group.                 The problem

10   there is what we know as spectrum bias can be work at

11   here.            The largest group of patients were in the

12   intermediate-risk category.               We have no justification

13   for assuming that the estimates of sensitivity from those

14   extreme groups would apply in the intermediate-risk

15   group.

16                       If there is no gold standard, then we have

17   the option of evaluating agreement between QFT and TST.

18    Now I want to move to that topic and talk a little bit

19   about agreement.          Next, please.

20                       This is a depiction of the two-by-two table

21   which you have seen numerous ones this morning.                     I use

22   the term "agreement" to mean literally on a per-case

23   basis, whenever we have QFT-positive and TST-positive,

24   that's an agreement.           If one is negative and the other

25   is negative, that is also an agreement, and the overall

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1    agreement derived from a two-by-two table is basically

2    the numbers from the main diagonal of the table divided

3    by the table total.

4                        Next, please.       Now I want to give you a couple

5    of other definitions very quickly, one of which is

6    expected agreement.          The reason for that is that the Kappa

7    agreement statistic, which is the one that the company

8    has chosen as their primary agreement measure, involves

9    both the observed agreement on the main diagonal of the

10   table, expected agreement, and I have to apologize; I

11   have it written as "A plus B over N."                    It should be "A

12   plus D over N."

13                       What is done in getting an expected number

14   is that you set up basically the null hypothesis that

15   the two tests being compared are mutually-independent,

16   and then you use the marginal frequencies, the proportions

17   on the margins of the two-by-two table, to generate

18   numbers for the four cells of the table, which is what

19   you         would     expect       if      the     two      tests          are

20   conditional-independent.

21                       I always have the same problem with this

22   statistic in these kinds of method comparison studies

23   because the null hypothesis simply is not reasonable.

24   It makes it very easy to get a statistically-significant

25   result because inherently the methods being compared have

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1    some amount of built-in agreement.

2                     The Kappa correlation coefficient takes the

3    observed numbers of cases on the main diagonal, subtracts

4    out the expected number of cases on the main diagonal,

5    and then is scaled by one minus the expected frequency.

6                     Another   measure      is   agreement    with       the

7    positive skin test; that is, taking those that are given

8    as TST-positive, what percentage of those are also

9    QFT-positive.      Agreement with the TST-negative, you take

10   those that are TST-negative and divide that into the

11   number which are also QFT-positive.

12                    We have an agreement index, both a positive

13   and negative variation.        What this does that is different

14   than those above is you take the total number of cases

15   that are positive by TST, add that to the total number

16   that are QFT-positive, and call that an overall number

17   of positive results.        Then you take the number that are

18   positive by both QFT and TST, multiply that two, and that

19   ratio then is what we call agreement index positive.

20   In agreement index negative, you get the total number

21   that are negative by either and divide that into the number

22   that are negative by both.

23                    Next, please.      I am sorry this is such a

24   massive table, but I think I can get you through it pretty

25   quickly.

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1                      What this does is to compare the agreement

2    between QFT and TST on the various indices just described.

3     Just to orient you on this table, this first part deals

4    with      the    low-risk   group,     using    the     15   millimeters

5    induration for the skin test.               This little block over

6    here is the array of the 98 cases in the low-risk category.

7     The plus indicates the test positive; the minus is test

8    negative.        The columns are for QFT and the rows are for

9    TST.

10                     So we have, for example, 89 cases that are

11   negative by both tests.            We have just one case in the

12   low-risk category that's positive by both.

13                     Now I have to deal somehow here with the

14   problem that we have with basically any measure of

15   agreement, which is the dependency on prevalence.                         That

16   is, prevalence is a confounding factor in any of these

17   measures of agreement.

18                     How do we know that prevalence is a problem?

19    We know that because you can take the two-by-two table

20   and write out a probability model of that table in terms

21   of     sensitivity/specificity          and    the      probability          of

22   agreement between the two tests being compared and

23   prevalence.        So you put all those parameters together

24   in a two-by-two table and it gives you what we can an

25   expected number of the four cells in the two-by-two table

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1    that you can compare with the observed.

2                       Once you have done that, then you are free

3    to     fix       the   parameters      sensitivity/specificity               in

4    agreement and vary the prevalence.                  Each time you vary

5    the prevalence, get your expected table and calculate

6    your agreement statistics from it and see if they change,

7    you haven't changed the performance.                 What you have done

8    is changed the prevalence.              Unfortunately, all of these

9    measures undergo a change when you vary the prevalence.

10                      Let me just point out the problem that we

11   have with Kappa.           It is well-known, established in the

12   literature, and it is easy to show that Kappa, where

13   performance is held fixed, will be very low at the extremes

14   of prevalence.             Very low prevalence and very high

15   prevalence, it will be a low value.                       You see that 17

16   percent for the low-risk group.                That's exactly what we

17   would expect.          Then when you go from the low-risk category

18   up to the intermediate-risk and the suspect category,

19   you see that it goes up considerably.

20                      So when you see a Kappa that looks good, you

21   need to ask, well, are we looking at a high prevalence

22   population here?          If it is, then, well, maybe that's just

23   what you should expect because of the relationship with

24   prevalence.

25                      The same thing applies -- let me just quickly

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1    say something as a footnote here about the agreement.

2    Where you get Kappa with a large agreement, or the expected

3    number very large, producing a small value Kappa, is where

4    the numbers are concentrated on that main diagonal in

5    just one cell.         So that you see for the low-risk, where

6    you have 90 cases, 89 of them are down there in that lower

7    righthand corner.          That is the kind of thing that gives

8    you a large expected number and a small Kappa.

9                     So    when    you    get   to   the     next   level      of

10   prevalence, the intermediate risk, you see there's a much

11   more even distribution of cases between those two cells,

12   and that that sort of lightens you up a little bit on

13   the expected number.           Then when you get to the high-risk

14   group, it begins to fall off again because you've got

15   numbers that are concentrated up in that upper lefthand

16   corner.

17                    All of the agreement indices show a pattern

18   with prevalence.         What I am going to suggest is the one

19   that we might consider as my basic analysis of agreement

20   between QFT and TST is the overall agreement, simply

21   because it shows the least variation with prevalence.

22                    Next slide, please.           What I have done here

23   is to calculate the overall agreement for the three risk

24   groups and calculated the confidence intervals.                     I want

25   to call your attention to the lower confidence limit,

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1    because that's what we like to say is what we know for

2    sure, that the agreement is going to be possibly that

3    low, but it may also be higher.

4                            So for the low and intermediate group we've

5    got 80 percent or more agreement in terms of the lower

6    confidence limit.                 So I would say that basically is

7    telling me what the chances are of agreement between QFT

8    and TST for the suspected group.                     It falls off and the

9    agreement is down around two-thirds.                      If you are a user

10   of the McNemar test, I would also say that we have

11   significant McNemars in the suspected group.                             It tends

12   not to support agreement at that level, but it is okay

13   at the low and intermediate levels.

14                           Thanks for your attention.

15                           CHAIRMAN WILSON:        Thank you.

16                           At this time I would like to invite the panel

17   members to ask questions of the FDA's speakers.                                  Dr.

18   Charache?

19                           DR. CHARACHE:       I wonder if I could ask a

20   question           of    Mr.    Dawson.        Looking        at   the    percent

21   agreement, if we go back to your next-to-last slide for

22   a moment, I think maybe it is the one before it.

23                           MR. DAWSON:      No. 7?

24                           DR. CHARACHE:      No, it's the complicated one,

25   No. 6.           If we look at, instead of the overall agreement,

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1    which is the first three columns, if we look at the

2    agreement, just the agreement with the TST-positive and

3    negative, there the agreement is very good for the

4    negatives, but only 12 percent agreement among the

5    positives.

6                      MR. DAWSON:        In the low risk, yes.

7                      DR. CHARACHE:        In the low risk.         Now looking

8    at the WRAIR, it is also 12 percent for the low-risk group,

9    and that's the group that we're targeting.                             So I'm

10   wondering        if,    rather     than    looking        at   the    overall

11   agreement, which certainly in low-risk patients and

12   moderate-risk patients who are the ones where we are

13   really looking for latency in, the important question

14   is agreement of the positives, not the negatives.                         There

15   will always be more negatives.                 If we use the overall

16   agreement, we will always see very good agreement, but

17   the group we are concerned about are those who are

18   candidates for therapy.

19                     So I wondered if we could look at that number

20   for the populations for which the test is proposed;

21   namely, those for which there is a test of latency, and

22   just      look   at    the    agreement      of   the     positives,          the

23   candidates for therapy, which is the purpose of the test.

24    Because it seems to me that for most tests we either

25   want to look at the negative agreement or the positive

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1    agreement, and for this test we want to look at the

2    positive agreement, which in the candidate populations

3    for therapy are going to be in the low-risk category,

4    where agreement is extremely poor.

5                          Then we have to decide what to do with it.

6     Maybe it is to increase the agreement by modifying the

7    cutoffs.          But I wondered what the comments would be on

8    that thought.

9                          MR. DAWSON:     I think it is appropriate to

10   look at agreement with the positive TST results as long

11   as you keep the prevalence groupings broken out, because

12   it is drastically different.

13                         DR.   CHARACHE:         Yes,   I     would   make       the

14   prevalence grouping the candidate population for which

15   the test is targeted.

16                         MR. DAWSON:     Are you saying that there is

17   one part or another of this table right here that we are

18   looking          at    that   would      be    appropriate         for      that

19   interpretation?

20                         DR. CHARACHE:        Well, the low-risk group

21   would.           That's not a candidate for skin testing now,

22   according to CDC, because of false positives.                         But the

23   false positives under that category would be fair greater

24   with the QFT test.

25                         So I would want to look for the concordance

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1    with that population as opposed to negatives which will

2    always overwhelm your ability to know about the group

3    you want to treat when you're looking at the targeted

4    population.

5                      CHAIRMAN WILSON:           Dr. Cockerill?

6                      DR. COCKERILL:         Another question regarding

7    statistics:       Of course, the negative 99 percent, as you

8    mentioned, is not that remarkable considering it is a

9    very low prevalence group.               So you are going to have a

10   very high percent there because the prevalence is so low.

11                     Do    you    have    any    idea    --   we   saw      some

12   two-by-two's I think earlier -- if the cutoff is 30 percent

13   versus 15 percent, how that would affect that positive

14   12 percent result, or can you make any comments about

15   that?

16                     MR. DAWSON:       I don't have any intuition about

17   that.        We did see that when they raised the cutoff for

18   percent human response from 15 to 30, that the specificity

19   went from 90 up to 98.             So it is possible here and now,

20   after the fact, to go through and look at the different

21   cutoffs, which the company has been doing.                 We encourage

22   them to do that because you want to learn from the PMA

23   studies as well as to get an approval.

24                     We do have analytical means after the fact,

25   a type of cross-validation involving what's known as the

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1    bootstrap to validate a different cutoff after the fact,

2    using the clinical trial data.               But I'm sorry, I don't

3    have just off the top of my head any idea what that would

4    do for agreement.

5                      CHAIRMAN WILSON:        Dr. Janosky?

6                      DR. JANOSKY:      The question is either for Mr.

7    Dawson or Dr. Sacks.            I want to go back a few levels,

8    sort of thinking about the data and analyzing the data

9    for a second.       The sponsor had told us this morning that

10   the values of test performance for the TST are quite low.

11    If we use that as an assumption and we work from that,

12   when we see discordance with these two tests, do we have

13   any hint as to what might be going on?

14                     I ask you, when you answer that, to please

15   think about the fact that the odds ratio for the Asian

16   population that the sponsor reports is about a 5, and

17   the     odds     ratios   for   some    of   these      other    personal

18   characteristic        variables        are    quite      high     in      the

19   discordance.

20                     MR. DAWSON:      I don't have any analysis to

21   offer on the discordance.            Sorry.

22                     DR. JANOSKY:       Okay.     I am still trying to

23   tease apart as to, if we're trying to evaluate this test

24   based on an imperfect test, who are we penalizing when

25   we come up with disagreements?               I mean, just think of

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1    some ways to sort of try to answer and think through the

2    question, but since you two are very close to the data,

3    I was wondering if either one of you had worked through

4    some of those hypotheses.

5                     MR. DAWSON:       If Leonard doesn't have an

6    answer, it may be that the company does because the company

7    always knows the data better than any of us at FDA.

8                     (Laughter.)

9                     DR. JANOSKY:     Well, I would feel comfortable

10   also asking the question for the sponsor.

11                    DR. SACKS:     This is nothing really new, but

12   I think the other way in which a clinician would look

13   at the data is in terms of the TB risk.               Obviously, in

14   a population where the risk is negligible one would like

15   to see the lowest positive rate; in a population where

16   the TB risk is highest, one would like to see the highest

17   possible rate, bearing in mind the caveats for the

18   different types of tastes.

19                    DR. JANOSKY:      Yes.    When I took a look at

20   one of the tables that you presented today, which I thought

21   was very illuminating, by the way, the one where you were

22   looking at the different populations and the expected

23   prevalence rates in both of those tests, if I think about

24   it from a population perspective, my conclusions of those

25   tests might be that I'm very comfortable with it.                      If

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1    I think about it on an individual basis, that is what

2    I am trying to grapple with because that's really where

3    we are.

4                       DR. SACKS:     Yes, I think, as we get down to

5    the level of the individual, not only are the overall

6    prevalences of positive tests in each population group

7    important, but the concordance within those, and that's

8    what I tried to highlight with the Venn diagrams.

9                       Personally, I am not sure how in those groups

10   one does interpret discordant results, a positive QFT

11   with a negative TST, or a positive TST with a negative

12   QFT.       You know, all I can say is that with a TST, with

13   all its pitfalls, at least it has some clinical validation

14   over the many years of use.              We know the percentage of

15   patients who are going to get TB, if we found a positive

16   TST.       We know that TST is likely to convert if patients

17   have been exposed to TB.             So we have some sense of how

18   the TST behaves clinically, but I'm not quite sure how

19   to evaluate the QuantiFERON.

20                      DR. JANOSKY:      So, in that respect, you are

21   more comfortable sort of putting the onus on the new test

22   as opposed to the TST, just because of the performance

23   and     the      current   approval?        Is   that    what    you     are

24   concluding?

25                      DR. SACKS:      Well, in the absence of data,

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1    I think what we would have to do, the way I would phrase

2    it is we would need to see data to validate the discordant

3    results by QFT.

4                         DR. JANOSKY:       Okay.     Then that goes to the

5    question          that   I    asked.       Is   there       any   information

6    available besides seeing some of the discordant personal

7    characteristics              data   that     were     presented          in      the

8    application?

9                         DR. SACKS:        I will defer to the company

10   there.           I don't have any additional data.

11                        CHAIRMAN WILSON:           Would anyone from the

12   sponsor like to comment on that?

13                        DR. RADFORD:        First, I will deal with the

14   issue       in     the   low-risk      group,    which       we're      actually

15   stressing here because it is the one with the 12 percent.

16                        The thing that we would actually like to make

17   absolutely clear here is that this is an extremely

18   low-risk group.              This is a group that has been deleted

19   on every risk factor that we can find.                      I would note that

20   the FDA noted that there, in fact, in the initial

21   classification we actually had to go back and delete out

22   people who were set perhaps initially.                      No acquired risk.

23    There is no risk.

24                        So they are at absolutely no risk and put

25   there because there is no reason to believe that any of

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1    them have tuberculosis whatsoever.                    So the point we make

2    there is that we are not really looking at that data for

3    concordance.          We're looking at what you might call the

4    random or the background variation of either test.                       Given

5    that point, that is why we stress the 30 percent is a

6    more effective cutoff in a very low-risk group because

7    you don't want to show up in low-risk groups a large number

8    of individuals.

9                        I can answer the two-by-two table at the 30

10   percent          margin     by    saying,      in   fact,    there     is     no

11   concordance.          We actually have no double positives and

12   we have two individually positive for the TST and to

13   QuantiFERON at the 37 group, and the rest of them are

14   the negatives.

15                       But I think that is the point that we would

16   like to stress:             that if you actually start focusing in

17   on the low-risk groups, the WRAIR one group, the CDC one

18   group, you are looking at a group that is stressed to

19   have no contacts, no possible exposure to anyone with

20   TB, nothing.         In fact, you will notice in the WRAIR group

21   we even took out people from an incidence of greater than

22   10 in 100,000 states of the United States.                     Now that is

23   a very severe cutback.                     So we don't expect great

24   concordance in that.               Of course, it is a low incidence

25   group, and of course the cutoff will be low, as discussed.

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1                       So I don't think we should actually focus

2    in on concordance in low-risk groups because basically

3    none of these people probably have tuberculosis.                         That

4    is why we say we should raise it up to 30 percent, in

5    our case to get that specificity.

6                       CHAIRMAN WILSON:        Dr. Charache?

7                       DR. CHARACHE:         The concordance is also

8    extremely low.         It is not 12 percent.             I didn't do the

9    calculation, but it is maybe 15 percent in the secondary

10   risk group at WRAIR.          Those two groups, one and two, were

11   added for analysis as being those that were candidates

12   for the test.

13                      DR. RADFORD:      Perhaps I'll might this point

14   clearly:         In the ATS and the CDC guidelines, it doesn't

15   say:       Test people at no risk for tuberculosis.               It says:

16    Don't test people with TST with no risk for tuberculosis,

17   but if you must, use the 15-ml cutoff.                   Low-risk people

18   aren't generally recommended to be tested.                    The people

19   who are recommended to be tested are those at some risk

20   of latent tuberculosis detection.

21                      The WRAIR two group, again, is in fact a

22   fairly limited risk there because they're the group that's

23   actually         incorporated       --    the     only     risk      factor

24   incorporated is they came from a U.S. state with greater

25   than 10 cases of TB per 100,000.

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1                        Jim, would you like to speak to that?

2                        DR. ROTHEL:      Yes, if I could just -- we are

3    not proposing to use the 15 percent cutoff for low-risk

4    people.          We are proposing to use the 30 percent.                So in

5    both of the low-risk groups from the WRAIR study,

6    specificity is not yet equivalent to the TST.

7                        But I want to come back to your discordance

8    question because I don't know if we totally addressed

9    what you were asking.

10                       DR. JANOSKY:      You didn't, so thank you.

11                       DR. ROTHEL:     I think it is terribly difficult

12   to try and resolve what the real result is in human

13   studies.          They're going to be very long-term studies.

14   They're going to take us a long time to do, confounded

15   by the fact that if you identify an individual as being

16   positive in a test, you may have to prophylaxis them.

17   So, therefore, the possibility of their coming down with

18   disease is vastly reduced.

19                       So it is basically an ethically difficult

20   study to do and a very long-term study.                   I think the best

21   evidence comes from the bovine data, where we can actually

22   kill the animals and we have a gold standard, or that

23   is about the only conclusion we can draw within getting

24   into terribly complicated, long-term studies that we

25   probably wouldn't be able to ethically do.

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1                       CHAIRMAN WILSON:       We have time for one more

2    question.         Mr. Reynolds?

3                       MR. REYNOLDS:         On the retesting of the

4    discordant results, does anyone know how close the initial

5    result was to the cutoff?             Anyone from the manufacturer

6    have any idea whether those discordant results have

7    changed on retest, how close they were to the cutoff?

8                       DR. JOLLY:     If I might be allowed to address

9    that question, Mr. Chairman?

10                      CHAIRMAN WILSON:         Yes.

11                      DR. JOLLY:      I can't give you quantitative

12   answers.         I can tell you that almost all of the changes

13   were very close to the cutoff.                     I think this is a

14   characteristic which is inherent in any test where we

15   are trying to find a magic number.                 I think the strength

16   of any quantitative test -- and this includes the TST

17   as well as the QFT -- is that there is an underlying numeric

18   quantity which allows us to alter the cutoff appropriate

19   to this.

20                      Thank you.

21                      DR. NOLTE:     Can I get a clarification on the

22   retesting?         For the QFT, that was a second sample drawn

23   at another point in time?             Or?     Clearly, the skin test

24   was.

25                      DR. ROTHEL:     Yes, I think Jerry Mazurek who

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1    is here from the CDC might be able to address that

2    accurately, but from my memory anyone with a discordant

3    result in the CDC study was meant to have another blood

4    drawn within two months.              Yes, Jerry?         Yes.     Thank you,

5    Jerry.           Retested, a very small percentage of those

6    individuals that had discordant results were done.                            Some

7    were retested as soon as a week after, and the others

8    were tested up to a month after the initial test.

9                       CHAIRMAN WILSON:           Thank you.

10                      At this point I would like to move to the

11   open public hearing.

12                      Two individuals have notified the FDA that

13   they would make a public comment.                 The first is Dr. James

14   McAuley from Cook County Jail, Illinois, who is going

15   to discuss difficulties with tuberculosis testing.

16                      DR. McAULEY:         Thank you.         My name is Jim

17   McAuley.         I'm the Medical Director at Cermak, which is

18   Cook County Jail, one of the larger jails in the country.

19    I have done TB control for about 10 years.                       I will make

20   it very brief.          I will just give you a quick overview

21   of how we use it.

22                      I   do    a    lot    of      actually    teaching            on

23   tuberculosis.          I will say that when I teach, I always

24   say that if you're going to use 15 millimeters, you

25   shouldn't have done the test.                    I mean, that's really

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1    functionally how I think of it.                 I have always worked

2    in high-risk groups.           So, for me, when I talk, think of

3    my population as being right in the middle.

4                       I would also say that clinically I am very

5    much a clinician in this regard:               I don't use it at the

6    other end either.           If they clinically have tuberculosis,

7    I don't use the skin test.               I use my clinical and my

8    laboratory.         If they have a smear-positive, I see what

9    that organism is.

10                      Prisons     and     jails      are     an       important

11   environment because there are 2 million people behind

12   bars in the United States with 600,000 in jails.                          Jails

13   are pre-trial detection centers.                  So you're awaiting

14   trial, or if you have been incarcerated for less than

15   a year.          Prisons are where you go for a longer period

16   of time.

17                      This is a high-risk group.            This is a group

18   that is a targeted testing group by the CDC's LTBI

19   guidelines.           Six    million    people     pass    through            our

20   correctional system each year, so a large segment of our

21   population.         It is mostly individuals who are high risk

22   for tuberculosis.

23                      It has been growing, so I think it is a

24   population base that needs to be addressed from a public

25   health point of view.            This just gives you a sense.

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1                       Now, again, I work in a jail setting, which

2    is a passthrough population.            In our setting the majority

3    are non-white and usually of lower socioeconomic status.

4                       Again, I am going to go quickly because I

5    just want to give you a flavor of what environment we

6    practice in and then how we use the TB test.                   We have

7    a lot of public health issues we address.                 The one we

8    are obviously focusing on is tuberculosis, but there is

9    a lot of HIV and AIDS in the correctional system.                       In

10   our jail setting 2.5 percent are HIV-infected, but in

11   New York it has been as high as 15 to 20 percent in

12   serosurveys in their jail system.               We also have a great

13   deal of hepatitis C.

14                      It is a congregate setting.          So there are

15   studies that I will show you real briefly in a second

16   that show that jails amplify tuberculosis transmission

17   in the community.          In fact, I will mention it now, but

18   in Tennessee 42 percent of their active tuberculosis had

19   passed through the jail system in the preceding year.

20   So they speculate that their jail was actually the

21   transmission foci.         In New York active tuberculosis, one

22   of the independent risk factors for developing active

23   TB    in     New   York   City   is having spent time in the

24   correctional setting.            Again, the case rates for active

25   disease are much higher.

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1                       So within that setting we have a fair bit

2    of active disease.          Now we want to target, as our cases

3    go down in the U.S., we are really focusing on what to

4    do with LTBI, or latent TB infection.                So that is really

5    the focus population.

6                       Again, I don't think either of these tests,

7    to my clinical judgment, are that important for active

8    disease.         We use chest x-rays.       We use symptoms.        We use

9    all of that to determine active tuberculosis, but what

10   we ask ourselves is:            Can we identify people who pass

11   through a correctional setting who are at high risk for

12   tuberculosis and can we get them treatment for their LTBI,

13   so that they do not develop tuberculosis down the road?

14    That has been our big focus at our site.

15                      Some of the references you have of the

16   publications that discuss tuberculosis in prisons and

17   jails, and, again, this is the Tennessee study, which

18   basically said that it was very important.

19                      I want to get to the -- maybe I will pass

20   through the immigrants, because I am looking at the time

21   and I know that there are people needing to go on.                 Again,

22   I want to get to just what we are focusing on here,

23   screening of this high-risk population.

24                      We do also screen employees.          So there are

25   two ways in which we look for tuberculosis in our setting.

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1     The CDC says that we should have basically an appropriate

2    policy.          I also think it is very important to keep in

3    mind that a jail in Chicago is not the same as a jail

4    in Montana as far as TB goes.                So in a jail in Montana

5    you might not do either test.              Always keep that in mind.

6                        So all TB is local, and I think it is

7    interesting to hear this discussion of 10 cases per

8    100,000 being the high risk.               If you are from Illinois,

9    where we are one of the high rate states, comparable to

10   most of your southeastern states, if you are outside the

11   metropolitan Chicago, your case rates of TB are about

12   2 per 100,000.          So you are actually a low risk.                 So if

13   you are a military recruit from rural Illinois, you're

14   obviously a low-risk person, very low risk, but you would

15   have been lumped into high risk.                          Conversely, the

16   alternate would happen if you were from an urban center

17   that was diluted by a rural population -- basically, the

18   imperfections of all this epidemiology.

19                       So at our site we screen 100,000 detainees

20   a year.          That's our passthrough population.           On any given

21   day, 10,500 detainees live on a 100-acre campus.                        So we

22   have both geography, a large compound to deal with, and

23   volume, 250 to 300 individuals passing through on a given

24   day.

25                       When you pass through our system, we screen

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1    you medically and we look for mental illness, and we do

2    a mini-chest x-ray because active disease is the thing

3    we are worried about from a transmission point of view.

4     We do place a skin test.           Frankly, I wonder if I want

5    to place a skin test.         I think it is an important public

6    health service, but it is not very important for my

7    institution, if you think about it, because I really need

8    to just look for active disease.              I will show you some

9    data in a minute about why I wonder about whether we should

10   place a skin test.

11                    But having said that, many, if not most,

12   states' regulations require correctional facilities to

13   place skin tests because it has been entrenched as one

14   of the things you ought to do to look for tuberculosis

15   in a jail setting.         So whether or not I believe it is

16   scientifically valid or valid for the individual patient,

17   I am required to place it.

18                    So we place 250 to 300 tests over a few hours

19   every day, and we try to read them at 48 to 72 hours.

20   We successfully read between 25 and 30 percent of those

21   skin tests.       So 75 percent of the skin tests we place

22   are not read.

23                    We do a mini-chest x-ray, which is read within

24   12 to 16 hours.       We read all of those, obviously.              This

25   is how you do it:      You take the 100 millimeters, you blow

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1    it up; you look for tuberculosis.

2                     We     have     found     over     the     years       that,

3    fortunately, our TB case rates are going down.                       We find

4    most of our cases by chest x-ray, but we do have some

5    people who come in with a normal chest x-ray but give

6    us symptoms that suggest tuberculosis.

7                     As you would expect, our tuberculosis case

8    rates mirror the city a little bit.                 We believe we have

9    actually significantly contributed to the city's control

10   of tuberculosis because, as an example, 60 percent of

11   people who are homeless in Chicago pass through the jail

12   each year.       So we actually probably control a lot of the

13   homeless tuberculosis inadvertently.                     So we contribute

14   significantly.

15                    Now to the case in point, where I think that

16   skin tests or any blood test is important.                       Actually,

17   I should take a second -- I didn't explain.                    I have had

18   nothing to do with the company except they heard my

19   presentation at a TB meeting earlier this year and asked

20   if I would come.         So they have paid my way here and for

21   my time today.

22                    So I say that because, obviously, I have been

23   paid by them and they have paid my transportation, but

24   my personal view is I would like to have a good test.

25   I actually don't really care who gives me the good test,

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1    but I would like to have a good test.

2                      We started looking at LTBI because we have

3    this problem that we are placing 100,000 skin tests,

4    25,000 are being read.           Then we started them Isoniazid,

5    and only 11 percent completed because they pass through

6    our jail so quickly.           So we felt it was somewhat of a

7    futile activity.

8                      So we began using the two-month rifampin

9    pyrimidazide, and we got our completion rates up to 67

10   percent.         So now I think we are actually doing a good

11   service for the community and for the individual patient,

12   because not only can we identify them with infections,

13   some of them, but we can get them on therapy and actually

14   complete therapy.        So now we are a little bit more excited

15   about our latent TB program.

16                     But what are our big challenges left?            Well,

17   our biggest challenges is this graph, which is probably

18   better in your handout than on the screen.              The next one

19   will show it as well.

20                     That is, when you come to jail, the good news

21   is you get out right away.           The bad news is I don't have

22   time to intervene in your health care very well.                     What

23   this translates into practically speaking is that, as

24   seen on the very last slide, fully 22 percent of people

25   are gone in 48 hours.           So 22 percent of the skin tests

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1    I have no chance of reading, and then the rest trickle

2    out over time, but then I have the logistics of staffing

3    going to find these people over a 100-acre compound who

4    have been moved around for security reasons, not for

5    medical reasons.      That is the other reason why we can't

6    read the skin tests.

7                     So from my point of view, when a person

8    enters, if I draw their blood, which I do already looking

9    for syphilis, because we play a big role in the city's

10   syphilis elimination program, I could at least identify

11   those who are positive.            Now can I engage them and

12   complete them in treatment?          I think I can complete more

13   of them than I used to because I am completing about

14   two-thirds now.       How many more I don't know, but from

15   my point of view it would be significantly improved if

16   I could actually identify quickly, without having to bring

17   that person back.

18                    I think it gets to the point about, if

19   somebody doesn't come back for the reading, doesn't that

20   mean that they are not likely to finish their therapy,

21   which is what I think is inherent in the question.                         I

22   think in our population what it means is we are just not

23   able to get to them to read it.            Now, again, we may not

24   complete all of them because of them will go again.

25                    So from my point of view, in a correctional

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1    setting a test that at least performs comparable to the

2    current in that intermediate group, which I think is the

3    right group to apply any test, would be of some value

4    to us.

5                      Thank you.

6                      CHAIRMAN WILSON:        Thank you, Dr. McAuley.

7                      The second public comment will be given by

8    Mr. Reynolds.        I would like to note that Mr. Reynolds

9    is prepared and is giving his statement from the State

10   Department of Health Laboratory in Pennsylvania.

11                     MR. REYNOLDS:       This statement is actually

12   from Mr. William Barry, who is the Director of the TB

13   Control Program for the Commonwealth of Pennsylvania.

14   I will make it very brief.

15                     Thanks for the opportunity to comment on the

16   QuantiFERON TB test.           Our hope is that the test will be

17   very useful in the diagnosis of latent tuberculosis

18   infections and would be more accurate than the reported

19   25 percent false negative rate in some PPD studies.

20                     Our problems with the PPD include ensuring

21   trained staff, placing and reading the test with accuracy

22   and consistency, patients returning within 48 to 72 hours

23   after the test is administered for reading, and difficulty

24   in separating the true latent tuberculosis infection from

25   positive         PPD's   due     to    BCG     or       non-tuberculosis

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1    mycobacterial infections.

2                      Hopefully, these problems could be resolved

3    with an ELISA test.         On a practical level, would the test

4    be     able      to   be   performed      by    laboratories        across

5    Pennsylvania or just the Bureau of Laboratories?                        This

6    would be important to us in the rapidity of specimen

7    submission and obtaining results.

8                      My understanding is that JAMA will have a

9    report on the QFT test this week.               We're looking forward

10   to reviewing it.

11                     I hope this is of some help to you.               Again,

12   thanks for the opportunity to comment.                   Any questions,

13   please give me a call.            Thank you.

14                     CHAIRMAN WILSON:         Thank you.

15                     Does any other member of the audience want

16   to make a statement?

17                     (No response.)

18                     If not, the open public hearing session is

19   now closed.

20                     We would like to take our lunch break now.

21    We will reconvene promptly at one o'clock.

22                     Thank you.

23                     (Whereupon, at 12:16 p.m., the proceedings

24   recessed for lunch, to reconvene at 1:00 p.m. the same

25   day.)

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1                     A-F-T-E-R-N-O-O-N          S-E-S-S-I-O-N

2                                                                    1:07 p.m.

3                      CHAIRMAN WILSON:           All right, I would like

4    to reconvene the meeting at this time.

5                      This is the open committee discussion portion

6    of the meeting.           This portion of the meeting is open to

7    public observers.              However, public observers may not

8    participate except at the specific request of the Chair.

9                      We have two primary reviewers for this PMA

10   submission, neither of whom would like to make individual

11   comments.        Therefore, I would like the FDA to put up the

12   first question for the panel.

13                     Okay, the first question states:                  "Did the

14   data      from    the    two    U.S.    studies     provide     sufficient

15   information on the performance of the QuantiFERON-TB

16   assay, and are there other types of data or other types

17   of analysis that can supplement those studies?"

18                     So I would like the members of the panel to

19   make any comments regarding those two questions.                             Dr.

20   Charache?

21                     DR. CHARACHE:         The CDC paper emphasized that

22   one of the significant variables that were found on

23   multivariate analysis was the differences between the

24   five sites that did the studies.                           Apparently, the

25   patients were the same, but there were differences.                                I

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1    wonder about looking at the two-by-two comparative data

2    from each site and then see if we can understand the

3    differences between sites.

4                     Similarly, I would wonder about looking at

5    some of the differences, see if we can understand better

6    the differences between gender and age.                I am thinking

7    here whether this is the kind of test that would use

8    different breakpoints by gender or by age rather than

9    a single one for all comers.

10                    I think it would be very helpful to look at

11   the data for all of the groups, not in terms of the overall

12   agreement, but in terms of the population at risk and

13   the purpose of doing the test in a given population to

14   determine which variables should be addressed.

15                    CHAIRMAN WILSON:       Does the sponsor have the

16   data divided in those ways, in a way that you could present

17   it now?

18                    DR. JOLLY:     Mr. Chairman and Dr. Charache,

19   if I can direct your attention to page 2-189, volume 2,

20   page 189, in this report we compare one measure of

21   agreement between sites in the CDC dataset and also

22   between risk strata in the same dataset.

23                    Now I will mention here that the fact is these

24   tables are Kappa statistics which, as the FDA statistician

25   pointed out, is a measure which is, if anything, biased

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1    toward low agreement status, because in the low population

2    groups we chose this measure specifically because it did

3    not give any implication of high value.                     The Kappa

4    statistic is bias toward low values and low prevalence

5    populations.        This is why we chose this statistic.

6                      Now if you look at the first table on page

7    189 of volume 2, you will see that we have got measures

8    of Kappa broken down by each of the five different sites.

9     All the values there are uniform.             There's no particular

10   variation        between   the    sites     and   the   agreement        or

11   disagreement status, whereas, as has been pointed out

12   by the FDA statistician, there are differences, as one

13   would expect, between the different risk groups because

14   Kappa does depend upon the prevalence in the data.

15                     I will also point out that on the page after

16   that there are the same figures broken down by site within

17   this group.        So we get comprehensive breakdown there,

18   Mr. Chairman, of the measures of agreement by site.

19                     DR. CHARACHE:         Yes, I think what I was

20   referring to, again, was not the overall agreement.                           I

21   think Dr. Sacks pointed out that we have to know the

22   relationships between what the overlapping agreement is

23   and how they differ.          I was thinking in terms of table

24   5, the factors associated with negative tuberculin tests

25   and the positive interferon gamma from the CDC paper in

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1    which it did vary by location.

2                       DR. JOLLY:     This is the JAMA paper?

3                       CHAIRMAN WILSON:        Yes.

4                       DR. JOLLY:      Yes.    Jim, do you have a copy

5    of that?

6                       DR. ROTHEL:      Thanks.       I just got this, and

7    I copied this, and it looks quite nice.

8                       The only comment I would like to make is that,

9    as far as my reading of the paper and my understanding

10   of the data -- and I wish Jerry Mazurek was here, who

11   actually did the study -- but the discordance associated

12   with different sites is associated with the TST.                           It

13   wasn't associated with QuantiFERON.                  It was associated

14   with people -- did give preference, which are just two

15   of the thoughts from memory.

16                      DR. CHARACHE:      I was just saying I think this

17   probably would be helpful to look at, and I think might

18   be helpful to look at with the two-by-two tables and see

19   how the sites compared with each other.

20                      DR. ROTHEL:      For the individual sites.

21                      DR. CHARACHE:       Yes.

22                      DR. ROTHEL:      I understand.        That is a good

23   comment.         I don't believe it is in your panel pack.                The

24   only trouble is that in some sorts there are as few as

25   15 or so people in group one, for example.               The two-by-two

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1    table is very meaningless with the low numbers, but, yes,

2    we can provide that if you need it at a later date.

3                     CHAIRMAN WILSON:       Dr. Baron?

4                     DR. BARON:    The only other information that

5    I think would be helpful, which you don't have, and I

6    fully appreciate the difficulty of gathering those data,

7    are the results of your assay and skin tests in patients

8    who are infected with pulmonary disease of mycobacterium

9    other than tuberculosis.

10                    CHAIRMAN WILSON:       Dr. Charache?

11                    DR. CHARACHE:      That reminds me of another

12   question, which has to do with the validity of the M.

13   avium as an overall control for all mycobacteria other

14   than tuberculosis.        I think particularly in the cattle

15   studies I would wonder about the mycobacteria that are

16   found in the ruminant sacks of the cows.

17                    I am wondering, if you had somebody with

18   kansasii and you tested with the assay, whether the M.

19   avium would be an adequate control or not.              Or, if you

20   just did the study that you did that showed that M. avium

21   control was a very good one, where you looked at the

22   ability of the M. avium to modify the results of the PPD,

23   if some of these false positives you could do the same

24   thing, but instead of using M. avium, use a different

25   mycobacteria.       I'm just interested in knowing whether

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1    we could extend the control if, instead of just M. avium

2    as a control, there were other mycobacteria that are

3    common causes of human disease included as part of the

4    control.         I think the control idea is terrific, however.

5                       CHAIRMAN WILSON:        Yes, go ahead.

6                       DR. WOOD:     Maybe I can just comment from the

7    veterinarian point before it over to other people to

8    comment on the human.          M. avium is actually used worldwide

9    as the distinguisher for comparative testing, probably

10   mostly initially because it was a fast-growing organism

11   and you could make the PPD.                But, in practice, it is

12   actually an extremely good antigen to us, as demonstrated

13   by its extensive use.

14                      Obviously, we made a decision in converting

15   to new tests just to stick with the same antigens.                       The

16   only other antigen that we have extensively looked at

17   in the cattle is Joni's disease and using impaired

18   tuberculosis antigens.           It answers, I think, the question

19   raised earlier:           In the long run would this sort of

20   technology work with MOTT infections?                    It is working

21   quite well in that circumstance.

22                      So I think you could possibly use other PPD's,

23   but I think in general practice is showing us that M.

24   avium is a pretty good indicator, although not absolute,

25   like anything in these assay systems.

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1                     DR. CATANZARO:      I wanted to remind us of the

2    work that was done by the Navy when they look at the various

3    tuberculins from rapid growers, from yellow bacillus,

4    kansasii, PPDB, and from the radish, the scraphilacio.

5     That work was done in skin testing.             From that came the

6    concept that PPDB from the battey bacillus or avium was

7    used as a representative of other mycobacteria.                     That

8    has been pretty well established in skin testing.

9                     Obviously, it hasn't been looked at by

10   QuantiFERON.       But I think that rather than looking at

11   it as a reflection of avium infection, we should look

12   at the response to avium as representative of other

13   mycobacteria.

14                    DR. CHARACHE:      Thank you.

15                    CHAIRMAN WILSON:       Dr. Nolte?

16                    DR. NOLTE:    I know the intended use of this

17   assay is not, the way you have stated it, is not to include

18   HIV-infected patients, but, clearly, the test is going

19   to be used in those populations, either knowingly or

20   unknowingly.

21                    I am wondering, there was data presented,

22   published data presented in the packet that, at least

23   to me, indicated that the test performance, at least

24   agreement with the tuberculin skin test was really not

25   that much different with HIV-infected individuals as it

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1    was with uninfected individuals.                 Is there any way that

2    more data like that could be included in terms of the

3    submission?

4                        DR. ROTHEL:      Yes, I agree, we have a fair

5    bit of data on HIV-infected people in here.                    There is

6    a paper by Converse, et al., Quatamera, et al., and the

7    Mason study that the abstract's reported in your panel

8    pack.

9                        The truth of the matter is we don't believe

10   we have sufficient data to go to the FDA to get approval

11   for it.          It is something that we may do as a post-market

12   study to extend their claims in HIV-infected individuals,

13   but it is not a simple study to do and quite an expensive

14   study to do.

15                       DR. NOLTE:     I understand.

16                       DR. ROTHEL:      Yes.

17                       DR. NOLTE:       The other thing that is of

18   concern to me is the intended use.                  The package insert

19   that you folks included was a little confusing to me.

20   In one place it said, essentially, to be used as an aid

21   in detection of infections with MTB, and in another place

22   in the package insert it said it is an aid in detecting

23   latent TB infections.            I am not sure -- I mean there is

24   not a lot of data that you presented in terms of the

25   performance of this test in active disease.

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1                     So I guess, where are we going with the

2    intended use here?

3                     DR. ROTHEL:     The intended use is not meant

4    to have the "latent" in there.           That was a typographical

5    error.

6                     We see no reason why not to include it for

7    TB in general.       When you are screening individuals for

8    latent TB infection, you are invariably going to pop up

9    very random, a very seldom event of someone with active

10   TB.      We have sufficient data, we believe, to prove that

11   or to demonstrate that individuals with active TB disease

12   are detected by the test in the vast majority.

13                    DR. NOLTE:      Again, in the data that is

14   included as part of this submission, how many infected

15   patients are --

16                    DR. ROTHEL:    There were 54 in there, and the

17   other data we provided in support was 129 from that

18   Australian study.

19                    DR. NOLTE:    So we're talking about a total

20   of 200 or so?

21                    DR. ROTHEL:     Nearly 200 or so, yes.

22                    DR. NOLTE:    Actively-infected individuals?

23                    DR. ROTHEL:    Yes, and both studies have come

24   out with a sensitivity of 81 percent.             It's not perfect,

25   but --

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1                     DR. NOLTE:    Sure.

2                     DR. ROTHEL:       -- it does definitely have

3    utility for detecting active TB disease.

4                     DR. NOLTE:    Okay, thank you.

5                     CHAIRMAN WILSON:       Dr. Carroll?

6                     DR. CARROLL:     Yes, along those same lines,

7    could the sponsor then clarify in terms of the labeling

8    whether you will then seek approval for both cutoffs,

9    the 30 percent cutoff for the low-risk individual and

10   the 15 percent cutoff for the intermediate?            Is that what

11   we're talking about here?

12                    DR. ROTHEL:    Yes, that's exactly what we're

13   asserting, yes.

14                    CHAIRMAN WILSON:       Dr. Durack?

15                    DR. DURACK:      With regard to the question

16   about supplementary data, I'm sure that it's clear from

17   the discussion that the pediatric group is particularly

18   important, and I know you will be working on that.                          I

19   would personally put that as the first priority as far

20   as supplementary data, and I would make the additional

21   point that this could be a group where it may be important

22   to separate the older children from the younger children,

23   possibly even infants, younger children, and teenagers.

24    So I think it might be better not to just lump everything

25   as zero to 18 for that study.

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1                        CHAIRMAN WILSON:          Okay.    Dr. Beavis?

2                        DR. BEAVIS:       My hope, too, is as additional

3    data is being collected that reproducibility be looked

4    at, not repeating a specimen, you know, different time

5    from the same patient, but splitting the specimens and

6    testing them in different laboratories.

7                        CHAIRMAN WILSON:         Any other comments on the

8    first question?

9                        (No response.)

10                       Okay, if we could have the second question

11   then?

12                       The second question states:                "Testing of

13   control material is not available to compare results

14   between          sites    in   the    clinical      studies.         Are      the

15   manufacturer's procedural and specimen controls adequate

16   to ensure reliability and reproducibility of QFT testing

17   between laboratories?"

18                       Any comments or questions from the panel?

19   Dr. Nolte?

20                       DR. NOLTE:       If I remember correctly, the only

21   data that we saw was the data that Ms. Shively presented

22   that was new, I mean that wasn't part of the packet in

23   terms of the two laboratories' split sample analysis.

24   Am I correct?

25                       MS. SHIVELY:        That was in your packet.

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1                     DR. NOLTE:    That was in the packet?            That's

2    the only data available in terms of interlaboratory

3    reproducibility?

4                     DR. ROTHEL:     The full study, yes.

5                     DR. NOLTE:    Okay.     Like I suggested, that's

6    probably not enough.

7                     CHAIRMAN WILSON:       Dr. Charache.

8                     DR.   CHARACHE:       I think the studies of

9    interlaboratory reproducibility would go a long way in

10   knowing about the ruggedness of the test, and I think

11   there are some questions about the ruggedness of the test,

12   if in fact there are differences between the labs.                            I

13   think this would be very helpful to us to establish that,

14   and then you could determine the extent to which you needed

15   outside controls.

16                    I'm obviously concerned about the false

17   positives because of the therapeutic implications in the

18   low-risk populations.

19                    DR.   LEWINSOHN:       What     would    an    outside

20   control be?

21                    DR. CHARACHE:     I'm not sure what the outside

22   control would be.       That is why I am hoping we won't need

23   them.

24                    DR. LEWINSOHN:      I'm sort of struggling with

25   that, I guess, because it seems like your standard curve

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1    sort of is the control in a way, I mean unless you're

2    going to ship serum from -- or not -- well, I guess it

3    is serum -- from these assays or it's actually I guess

4    plasma, from other assays as a control.

5                     DR. CHARACHE:          Yes, I suppose a surrogate,

6    at least interferon that you should get within a given

7    range in your system if the conditions are right.                        It's

8    not perfect.           It doesn't start with a leukocyte, but

9    you're in better shape.

10                    CHAIRMAN WILSON:           If there's a suggestion,

11   a    recommendation        to    the   sponsor      that   they    provide

12   additional data on this, the question would be:                   How much

13   data would suffice?

14                    DR. NOLTE:          Well, I mean, basically, I'm

15   trying to remember the data that we have in front of us,

16   but it's two sites and 50 specimens, right? -- almost

17   all of which were positive.               I think one of the points

18   that      came   out     in   terms    of    this    was   the    sort      of

19   reproducibility of negative as well.                  So certainly that

20   would be a component.            In terms of the numbers, I would

21   sort of leave that up to the statisticians to give me

22   the best sort of estimate of what that should involve.

23    Clearly, I don't feel comfortable that I know what the

24   reproducibility of this test is on the basis of two sites

25   and 50 samples, most of which are positive.

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1                        CHAIRMAN WILSON:        Dr. Charache?

2                        DR. CHARACHE:      They should also include some

3    in which the MAI was a factor or that had a high nil,

4    to see how it came out when it was done in different places.

5     So I think it should be just a nice gradient of tests,

6    but I would also prefer the statisticians selected it.

7                        CHAIRMAN WILSON:        Okay.     Would you like to

8    comment?

9                        DR. CATANZARO:       I would like to remind the

10   panel that while there was only that one formal study

11   comparing two laboratories, that the CDC trial was

12   conducted in five separate laboratories in five different

13   cities.          The results of the five sites are very uniform.

14    So even though we didn't ship the patients around from

15   one place to another to get them drawn in different labs,

16   I think we can look to that data and see that there are

17   significant, there are large numbers.                     If there was a

18   significant variation from one lab to another, I think

19   it would have shown up.

20                       DR. NOLTE:       You're talking about overall

21   performance?

22                       DR. CATANZARO:        I'm talking about overall

23   performance in five different laboratories as a surrogate

24   for how it might work in five different laboratories.

25   I mean it's a demonstration, I should say.

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1                     The other comment I wanted to make about

2    reproducibility is that, while perhaps the exact study

3    that was suggested wasn't done, that the hard data on

4    the same individuals being tested over and over again

5    a half a dozen times with no variation over a period of

6    time -- it's not the same thing, but reproducibility is

7    clearly very stable in that way.

8                     CHAIRMAN WILSON:          Any further comments?

9    Questions?

10                    DR. NOLTE:     One relatively -- I don't know

11   whether it is a small point or not.              It is a point that

12   bothers me, but it has to do more with -- I am looking

13   for the slide.

14                    DR.   BARON:      Could     you      speak   into       the

15   microphone, please?

16                    DR. NOLTE:     I'll try as soon as I find the

17   material.

18                    DR. BARON:     Okay.

19                    DR.   NOLTE:        Basically,         the     decision

20   thresholds or the values that are used to determine

21   whether you have a valid test, there is this 1.5

22   international unit per milliliter for the mitogen versus

23   nil that's the minimum to have an acceptable test?                        Am

24   I stating that correctly?

25                    Then we talked about being able to measure

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1    a 15 percent human response with the limited detection

2    of the assay being 1.5 international units.                    I think I

3    posed this to the sponsor in a written form, and I didn't

4    understand your answer, so that's why I'm asking again.

5     It came up on Ms. Shively's slide as well:              that if that's

6    the case, then don't you have to have a 10 international

7    unit per ml minimum mitogen versus nil response to be

8    able to reliably measure a 15 percent --

9                     DR. ROTHEL:       Yes -- no, because you can have

10   a 1.5 international units per ml for the mitogen and you

11   can have a 1.5 IU per ml for the human PPD, and get a

12   100 percent response and still be positive.               So it doesn't

13   mean that you need to have 10 units in your mitogen sample

14   to get a positive answer, if that is what you are

15   inferring.

16                    The mitogen is --

17                    DR. NOLTE:       That's what I'm worried about,

18   is     having    an   acceptable       test    where     you   have       1.5

19   international units per ml and then 15 percent of that

20   being below your detectable limit, so missing a 15 percent

21   response at the low end of your --

22                    DR. ROTHEL:       Sure, and that may be the case,

23   but the cutoff that's been used for all the clinical

24   trials, and were established very early on, used that

25   criteria, and that's what the data we have presented has

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1    been done using that criteria.              Sure, it means that if

2    your mitogen response is less than 10 IU per ml, you need

3    a response greater than 15 percent to be positive in the

4    test, but that same formula has been used for all clinical

5    trials.

6                     DR. NOLTE:     How often do you find values that

7    are that cutoff for the 1.5 international units per ml

8    for the mitogen versus nil?

9                     DR. ROTHEL:     It would be less than 5 percent

10   of the time, off the top of my head.               We could actually

11   give you that figure accurately.

12                    DR. NOLTE:     Your colleague over there is --

13                    DR. ROTHEL:      Do you know the figure, Tony?

14                    DR. RADFORD:       The answer is it's actually

15   a small number.

16                    DR. ROTHEL:     Talk into the microphone, Tony.

17                    DR. RADFORD:       The answer is it's actually

18   a small number.        I can tell you the CDC one group has

19   no risk, none.       In the other risk groups, we can dig it

20   out, but I think in fact we're talking about two or three.

21    It's a very uncommon event.

22                    DR. NOLTE:      Thank you.       I had the feeling

23   it was probably a small point, but I just wanted to

24   clarify.

25                    The other thing that I find a problem in terms

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1    of the interpretation of your test is the fact that for

2    an avium difference to be significant, it has to be less

3    than minus 10 percent.             I actually gave that criteria

4    to some of my colleagues in laboratory medicine and then

5    told them that, "Well, the difference is minus 100

6    percent.         Is that less than minus 10 percent?"

7                       DR. ROTHEL:      Yes.

8                       DR. NOLTE:      And all of them got it wrong.

9    Now I realize that the absolute -- I mean it's a difference

10   of -- it's an algebraic problem, but I think if you've

11   got     people     interpreting      this,     a   minus   100    percent

12   difference is a significant difference.                  At the face of

13   it that is a larger number, not a smaller number, to many

14   people, including myself, and I realize that's wrong

15   mathematically, but conceptually I think you might be

16   better served by having a different set of criteria for

17   that part of the test.

18                      DR. ROTHEL:     That's a very easy mathematical

19   calculation.         We can change it to a positive value if

20   we want to.         The truth of the thing is that we will be

21   preparing software to provide to people who will be using

22   this kit and having to get it approved through the FDA,

23   obviously.

24                      DR. NOLTE:      Yes, just don't convert it to

25   logs, okay?

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1                     (Laughter.)

2                     DR. ROTHEL:      Yes.    Done.

3                     CHAIRMAN WILSON:        Dr. Charache?

4                     DR. CHARACHE:      Yes, I'm just returning again

5    to the question of reproducibility of the test.                     Again,

6    from the CDC paper, there's only a single variable that

7    was associated with having a negative skin test and a

8    positive interferon assay, and that single variable was

9    if you were enrolled in site C.           On the other hand, there

10   were three reasons for having a positive skin and a

11   negative interferon.          One was BCG vaccine; one was an

12   avium complex assay, and the third was enrollment in site

13   E.      So I do think we really need to know about the

14   relationships between these different labs in terms of

15   reproducibility of testing.

16                    It's not just enough when you add the negative

17   and the positive agreements together.                  We really should

18   know more about it.

19                    CHAIRMAN WILSON:        Thank you.

20                    Yes, Dr. Lewinsohn?

21                    DR. LEWINSOHN:       Thank you.

22                    I had a question that sort of related back

23   to what Dr. Catanzaro had said earlier in the sense of

24   this being, in a sense the clinical function being an

25   integrative one.       It is true that we tend to look at the

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1    intensity of the TST test as being a surrogate for true

2    TB     infection,    certainly      if    it's     greater     than      15

3    millimeters or not, especially as we have been debating

4    whether to change the cutoff for those people who we would

5    consider to be low risk.

6                     What I'm wondering is, is there a way to

7    report out the test that would give some more information

8    to clinicians?        So, for example, you might say it's

9    positive, but like weak, strong, low, so that a strong

10   test might give you greater confidence in the low-risk

11   population that it's a true positive.

12                    DR. CATANZARO:      I think that's an absolutely

13   key factor, and, yes, the intention is to report that

14   it's positive and how positive it is.                  Clinicians are

15   always going to be faced with the problem of having to

16   integrate T-cell reactivity with the rest of the analysis.

17                    We have been talking about those cutoffs of

18   5, 10, and 15 as if they're written in stone.                  In fact,

19   those 5, 10, and 15 have changed over my career in medicine

20   a great deal from time to time, and today they're different

21   from place to place.        Those are the criteria that we have

22   been using that CDC has been recommending.

23                    I live in the State of California, which has

24   a lot of the TB problem.           The State of California says

25   we don't accept those criteria of CDC; we have our own

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1    criteria for what we're going to interpret as a positive

2    or negative skin test.              I don't want to enunciate what

3    those are.         I simply want to say that clinicians and

4    public health officials will change those cutoffs.

5                       So this panel is not going to put those

6    cutoffs in stone now and forever, probably for a week

7    or two.

8                       DR. LEWINSOHN:         So the data that you would

9    get back would be like --

10                      DR. CATANZARO:         Quantitative.

11                      DR. LEWINSOHN:             -- the percentage human

12   response or something like that?

13                      DR. CATANZARO:         Yes.

14                      CHAIRMAN WILSON:           Dr. Cockerill?

15                      DR. COCKERILL:         This kind of goes back to

16   a question I probably wasn't clear about earlier this

17   morning.          Is     there    any    data    that     correlates        the

18   positivity of the interferon gamma assay with the raw

19   measurement of the induration, the classification of the

20   scientist to the risk group and the interpretation?

21   Because that, to me, is probably a better way of looking

22   at this.         We're mixing apples and oranges here because,

23   as we just heard from Dr. Catanzaro, over his career,

24   and      over     mine    too     --    I'm    getting    older     --      the

25   interpretation of the PPD has changed.                    That's based on

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1    years and years of experience.

2                     So we're comparing two different assays here,

3    but the result for one of the assays is an interpretation

4    based on classification of risk group.                 Am I on the right

5    track here?

6                     So is there any data that just basically looks

7    at induration?       There was some in the handout, I think,

8    some       correlative   data     looking     at       that     agreement,

9    induration compared with the positivity of the gamma

10   interferon assay.

11                    DR. ROTHEL:     I think that our best indication

12   of that would be on the regression comparing induration

13   versus percentage of human response.                   That's been done

14   in the vast majority of papers that have been published,

15   and just about all of them have found that there is

16   significant association with that regression.                       A couple

17   of them have found no great association, but in the vast

18   majority, yes, there is.          The higher the induration, the

19   higher the same human response you will get.

20                    CHAIRMAN WILSON:        Okay, any other comments

21   on the second question?

22                    (No response.)

23                    If not, could we have the third question?

24                    The question states:         "In which populations

25   of       individuals     could      a    positive         or        negative

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1    QuantiFERON-TB assay provide clinical utility alone or

2    in      conjunction    with     TST?        Are       there    labeling

3    restrictions?      If any, if it would add to clinical utility

4    for any population groups?"

5                     Dr. Baron?

6                     DR. BARON:      Well, Dr. Nolte has already

7    talked about the fact that HIV-infected patients would

8    be another indication for labeling.                So we think once

9    that group gets properly assessed, they should be included

10   in here and children as well.

11                    CHAIRMAN     WILSON:         Other      comments        or

12   questions?

13                    DR. NOLTE:    I think we have touched on this,

14   but I mean the relationship between CD-4 positive cell

15   counts in this assay is known?          We haven't seen the data,

16   but I get the impression that that data is available?

17   Is that one way to deal with this problem of using the

18   assay in populations that you have some concerns about

19   in terms of being immunocompromised?              I mean the specific

20   immunocompromised that we're worried about is depressed

21   CD-4 positive cell counts?

22                    DR. ROTHEL:    I suppose my answer is the same

23   as the answer I gave before.           We do have a considerable

24   amount of data showing that it works generally in cases

25   of low CD-4 counts and HIV and other compromised people,

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1    but     we       don't   have    sufficient       data      to   support        its

2    registration and approval by the FDA.                       So we have to go

3    and get more data.            Probably what we will do is a smaller

4    study.           We have a lot of data already, but we need to

5    do a working study in the U.S. to extend that claim in

6    the HIV-positive and immunocompromised people.

7                        I should add that --

8                        DR. NOLTE:       Is it a realistic way to think

9    about getting around this exclusion of immunocompromised

10   patients is to hang it sort of on the CD-4?

11                       DR. ROTHEL:        Yes, I think that's quite an

12   appropriate way to do it.                If a person's HIV-infected,

13   it doesn't mean they're immunocompromised.

14                       DR. NOLTE:       Right.

15                       DR. ROTHEL:       You should be looking at their

16   CD-4 count and relating performance to CD-4 count or some

17   other measure of immuno-activity.

18                       DR. LEWINSOHN:         Can I ask another question?

19                       CHAIRMAN WILSON:          Dr. Lewinsohn.

20                       DR. LEWINSOHN:          So I guess this gets back

21   to that, I know admittedly, small number of patients who

22   got TST's and QuantiFERON tests, which seemed to show

23   more variability than you guys had seen when you just

24   did the repeated testing on an individual over time, which

25   in my mind raises this issue of whether the TST and

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1    QuantiFERON tests could interfere with one another or,

2    specifically, whether the skin test interferes with the

3    QuantiFERON test.

4                          So would you propose that that's a part of

5    the labeling, at least to make that suggestion, I mean

6    to suggest to do the QuantiFERON first then?

7                          DR. ROTHEL:       Yes, I agree.           I think I

8    acknowledged that to you this morning, that we probably

9    should have made the labeling to say that you shouldn't

10   skin test within "X" number of days, probably 30 days,

11   the same as just for a skin test.

12                         CHAIRMAN WILSON:       Dr. Reller?

13                         DR. RELLER:     Although it's plausible that

14   patients with intact, or reasonably intact, CD-4 counts

15   either before or after therapy would respond like most

16   other individuals, I would think until the data are in

17   hand that one couldn't count on that.

18                         Secondly, do you have any experience with

19   transplant populations?                At least in this country a

20   growing number of patients, and a rich source of clinical

21   tuberculosis, sometimes recognized late, at least are

22   recognized in our center.             So that, theoretically, either

23   before transplantation or at some point you would want

24   to know that.           Do we know what the effect of the whole

25   range            of   immunosuppressive         agents     to     preserve

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1    transplanted organs, what that does to this test?

2                      DR.   ROTHEL:       No.      That's     a   very      good

3    question, and we haven't done it.                   That's why we've

4    contraindicated or limited the applications for those

5    individuals.

6                      CHAIRMAN WILSON:        Dr. Charache?

7                      DR. CHARACHE:      To address this specifically,

8    which is, in which populations of individuals could a

9    positive or negative assay through clinical utility alone

10   or in combination -- it seems to me that if you have a

11   negative test for either and they have good, relatively

12   good concordance in people with active tuberculosis, it

13   would be a suggestion that you ought to look for other

14   causes of the patient's pulmonary disease and not assume

15   that it's only tuberculosis.

16                     I think there the caveat is that neither is

17   perfect.         So you can't rule out TB.              But it would be

18   highly suggestive, based on the data that we have, that

19   there is tuberculosis there.

20                     In terms of looking for latent TB, I think

21   right now we would probably want to see what happens with

22   the change in the end-points moving up on the curve, to

23   get rid of a lot of the false positives, because,

24   hopefully, it would be useful there.                But I think right

25   now it could be problematic in causing overtreatment of

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1    a very large population.

2                         CHAIRMAN WILSON:        Thank you.

3                         Yes, Dr. Cockerill?

4                         DR. COCKERILL:      Barth brings up a good point

5    about the transplant patients where we're febrile and

6    we're trying to figure out how the investigation is going

7    to go.           If you have a negative tuberculin skin test, the

8    patients may be anergic.               So we will check anergy.

9                         Is there any data with the mitogen control

10   with this assay as to mitogen-negative patients?                           Are

11   they anergic?           Were any additional studies done?

12                        The reason I am bringing that up is that,

13   if we have a mitogen-negative result, would it be possible

14   to suggest that the patient have a full complement of

15   anergy skin testing?             Is there any data related to that?

16                        DR. CATANZARO:        I think before I let Jim

17   answer the question about the mitogen, I want to remind

18   you that CDC specifically recommends against anergy

19   testing to assist in the interpretation of tuberculin

20   skin tests.           There's no correlation between those two

21   things, and they recently submitted an MMWR advising

22   people not to do that.

23                        So I don't know if you want to comment about

24   that.

25                        DR. COCKERILL:      Thanks.      I didn't know that.

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1                         DR. ROTHEL:      I can give you a little bit of

2    data on that study done in Kenya.                  We did, from memory,

3    I think 100 individuals, I think, and about 16 percent

4    were HIV-positive and various CD-4 counts ranging down

5    to 6.            We looked at the main mitogen response of the

6    individuals who were HIV-positive compared to those that

7    weren't and also stratified it by CD-4.                        Yes, there

8    definitely is a dropoff in mitogen as a main response

9    for all those individuals with low CD-4 counts and with

10   HIV infection.

11                        But the trouble is there is variability.

12   So a person can have a CD-4 count of 200 and have a decent

13   mitogen response, whereas a person with a CD-4 count of

14   1,500 can have a lower response than that.                     So I don't

15   think it's a definitive measure.                 Definitely if a person

16   hasn't got a mitogen response, yes, you go looking.

17                        CHAIRMAN     WILSON:          Other    comments         or

18   questions?           Dr. Charache?

19                        DR. CHARACHE:      I'm just wondering, I was just

20   thinking about the mitogen as being a very nice side

21   offshoot of this test, knowing about it.                   Is the mitogen

22   stimulation quantification that's used here adequate to

23   predict anything about the ability of a given patient

24   to respond?           Because you've got the data anyway.                   Can

25   you use it?           Or do we know if you can use it to predict

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1    responsiveness to mitogenic stimulation?                       And is that

2    data       known      for    those       that    were     PPD-positive        and

3    interferon-test-negative?

4                          DR. ROTHEL:        I think Tony can address that

5    question specifically.                  I will just state that there is

6    something         else      we    see    as     an   application     for      the

7    QuantiFERON technology, is a totally different test apart

8    from TB, which we're here to talk about today, which is

9    a measure of immune-competence, but we would use antigens

10   other than mitogen.

11                         But   Tony        can     address     your     question

12   specifically.

13                         DR. RADFORD:         Of course, as the ratio is

14   what's used, it's not dependent upon the actual absolute

15   mitogen response.            We have, in fact, analyzed the mitogen

16   response and the TST positivity.

17                         One of the interesting facts is that you're

18   twice as likely to be skin test positive if your mitogen

19   response         is    above      50    international       units    per      ml.

20   However, we still don't believe we actually have enough

21   data on the HIV population to address that.

22                         CHAIRMAN WILSON:          Any additional comments?

23                         (No response.)

24                         Okay, let's move to the fourth question.

25                         The        question        states,       "When          the

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1    QuantiFERON-TB assay is positive or negative and not used

2    in conjunction with TST, can available types of data from

3    the two clinical studies be used to interpret the

4    probability of TB infection for individuals with low,

5    moderate, or high risk?"

6                         Dr. Baron?

7                         DR. BARON:       Can I clarify that question?

8    Do you mean all by itself without any other clinical data?

9                         CHAIRMAN WILSON:          Steve, do you want to

10   clarify the question?

11                        MR. GUTMAN:     Sure.      The question, the heart

12   of the question, is:              If this product is approved, how

13   to label it, what kind of message to give to people who

14   use it.           So, yes, we are looking for advice on how to

15   characterize performance on the labels, and we need to

16   know what advice to give people who might actually buy

17   the test and use it.

18                        DR. BARON:     What does the skin test labeling

19   say?       I mean, I can't believe it would say:            Here's your

20   answer, all by itself.             I am sure there must be all kinds

21   of caveats with it that say, "in conjunction with a

22   history" and "physical findings," and all those other

23   things.

24                        DR. ROTHEL:      If I can briefly say, yes, it

25   does.            Their labeling claims are nearly identical to

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1    ours, and the diagnostic -- the detection of infection

2    with MTB, but then they have a whole lot of caveats in

3    interpreting      in   conjunction      with     all   the    clinical

4    findings, history, et cetera.

5                     MR. GUTMAN:     I think we have somebody from

6    CBER here who might be able to elucidate labeling because

7    that's obviously from a different shop, but we'd be happy

8    to share that.

9                     CHAIRMAN WILSON:         Could you come to the

10   microphone, please, and identify yourself, please?

11                    MR. MORRIS:     Yes, I'm Sheldon Morris.              I'm

12   the Chief of the Mycobacteria Lab at CBER.                Frankly, I

13   don't have these labels memorized, but it basically says,

14   as an aid in the diagnosis of MTB infections, and then

15   it gives some caveats.

16                    MR. GUTMAN:    So I guess the question on the

17   table is what you would like to see in this product.

18   Do you want to see less?          Do you want to see more?

19                    DR. BARON:    Yes, it looks good as they had

20   proposed it in their written proposal with those caveats.

21                    CHAIRMAN WILSON:       Any additional comments?

22    Dr. Nolte?

23                    DR. NOLTE:    I guess you're asking about the

24   statistics, I mean how to describe the performance?

25                    MR. GUTMAN:    Well, I'm asking -- one way to

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1    do that is not to describe it.               It's to provide just the

2    most general contour of association.                      Another is to

3    eloquently       and     extensively       describe       it.         We     have

4    experience in the Division with both.

5                     DR. NOLTE:        I mean, clearly, they have data

6    that addresses the performance characteristics of the

7    test relative to TST and the three groups that you outlined

8    there.

9                     MR. GUTMAN:        And would you like to perhaps --

10                    DR. NOLTE:        I think it would be reasonable

11   to include that in the package insert.

12                    CHAIRMAN WILSON:           Dr. Ng?

13                    DR. NG:       I think the most illuminating way

14   of looking at this data was Dr. Sack's presentation of

15   Venn diagrams, because I think the user really wants to

16   know what the non-concordance rate is, if you're just

17   using a QuantiFERON assay and you don't have a TST to

18   compare it with.

19                    CHAIRMAN WILSON:           Dr. Cockerill?

20                    DR. COCKERILL:          But I presume that would be

21   modified based on the 30 percent, which we haven't seen

22   that data.

23                    CHAIRMAN WILSON:           Dr. Charache?

24                    DR. CHARACHE:         I think it should go further

25   than the current physicians' instruction section, which

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1    has a paragraph on page 139, "The possibility should not

2    be excluded that a positive QuantiFERON-TB test is due

3    to a prior BCG vaccination."               It should also say that

4    false positives exist or something, that it's not only

5    BCG.

6                       CHAIRMAN WILSON:        Dr. Carroll?

7                       DR. CARROLL:      I would just like to reiterate

8    what Dr. Cockerill said.             I would like to see the Venn

9    diagrams with the 30 percent cutoff, particularly in that

10   low-risk group.         I think that would be very helpful in

11   terms of our comfort level with that low-risk group and

12   the false positivity rate.

13                      CHAIRMAN WILSON:        Okay.    Dr. Lewinsohn?

14                      DR. LEWINSOHN:        I was trying to think, I

15   mean, the sort of setting, I guess, that it seems like

16   we would most want to have this test would be in the setting

17   of something like a contact investigation where we're

18   really trying to tease out who's been recently infected

19   or not.          Obviously, we can't really tell who's truly

20   infected, you know, where there is a discordance between

21   those two data.

22                      So are there settings where it should be

23   recommended that you would do both tests, the hope being

24   that either would be sufficient or would you propose that

25   we would just do one or the other in that kind of a setting?

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1     It's a question to you, sure.

2                     DR. ROTHEL:     I think the talk we heard from

3    Jim McAuley would say that it was perhaps a waste of time.

4     In a real setting why would you use a skin test and miss

5    half of your results?

6                     DR. LEWINSOHN:        Well, but he's looking at

7    a different -- I mean he's screening for active disease

8    where there is high risk of spread.                      In a contact

9    investigation       you're     going    to    use      your     skin       test

10   information to figure out kind of how far to go, because

11   each person who you find who's positive may have been

12   a contact.       So that turns out to be very practical there.

13                    I'm just curious to know, would you do both,

14   the idea being that either one would be sufficient to

15   make you think they're a converter or --

16                    DR. ROTHEL:     My personal view would be, no,

17   I wouldn't, but I'll let Tony respond too.

18                    DR.   CATANZARO:         I   think      it       would       be

19   tremendously burdensome to suggest to do both, and it

20   would be analogous to say, well, why not do all three?

21    Why not require Connaught, Tubersol, and QuantiFERON?

22    I think that would be a very burdensome thing to do.

23                    I think that very nice data has been presented

24   here to show that the QuantiFERON is at least as good

25   as the tuberculin skin test, and the physicians, the

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1    public health people can make a decision based on their

2    circumstances which one to do.           Then regardless of which

3    one they do, it's an aid to the diagnosis; it has to be

4    put in the clinical context.           Lots of other information

5    has to be collected before you go ahead and prescribe

6    treatment.

7                     So I think there's lots of safety leaving

8    it as it is, as an aid, and I would be horrified if this

9    panel recommended to do two or three tests every time

10   we wanted to ask the question:             Does the patient have

11   latent tuberculosis infection?

12                    CHAIRMAN WILSON:       Dr. Cockerill?

13                    DR. COCKERILL:      If it's a false positivity

14   specificity      issue   in   your    low-risk        group   and     your

15   incidence of a positive result for the QuantiFERON is

16   very low, then confirming that with a second test may

17   be reasonable.       I'm not suggesting that, but based on

18   the data for the 15 percent cutoff, we see 7 versus 1,

19   I think, positive.       There's a 12 percent agreement.                But

20   the total number for that low-risk group is very, very

21   low, I think, in what I'm seeing.

22                    So one could consider a two-tiered approach,

23   not suggesting that, especially if the 30 percent doesn't

24   decrease that "false positivity."

25                    CHAIRMAN WILSON:       Dr. Reller?

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1                     DR. RELLER:      I can see two tests when one

2    is very sensitive but lacks specificity, and there are

3    ample models for this.           But in this case I've seen no

4    data that suggests that they're really complementary,

5    and it would be to me defeating the whole purpose to have

6    two tests.

7                     Each has its limitations, but unless there

8    were convincing data that you did one test and then the

9    other one added something to what you already had, and

10   vice versa, I think that would be the wrong way to go,

11   particularly one of the rationales for considering this

12   approach is all of the pitfalls with skin testing in the

13   first place in terms of followup, and quite apart from

14   interpreting, all of the things that have already been

15   discussed.       So I think, from what I have heard, the skin

16   test and this test are not of the genre that would be

17   logically done in sequence.

18                    CHAIRMAN WILSON:        Dr. Charache?

19                    DR. CHARACHE:       I'd like to agree with both

20   Dr. Reller and Dr. Cockerill.

21                    (Laughter.)

22                    I'm going to suggest that in the high-risk

23   group they're close enough.           So perhaps in the high-risk

24   group, since the sensitivity is better with the skin test,

25   if I got a negative with the interferon assay, it might

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1    be worth doing the skin test, but not on general

2    populations, and that's going to be a small number of

3    people.

4                     I would say the reverse is true with the

5    lower-risk groups one and two of CDC and groups one, two,

6    and three of the WRAIR study.            For those, if you got a

7    positive QuantiFERON test, it would be worth confirming

8    that it was really positive with a skin test, because

9    the skin test is going overcall positives in the low-risk

10   group, and it's, therefore, a safety valve to get rid

11   of the false positives.        Otherwise, we are going to have,

12   with this only 12 percent agreement in the low-risk group,

13   if you're doing case studies, surveillance kinds of

14   things, I think it would be helpful to take that small

15   population which give you a positive QuantiFERON and

16   follow it with a skin test.

17                    CHAIRMAN WILSON:       Dr. Reller?

18                    DR. RELLER:    This is probably the only time

19   I've ever differed with Dr. Charache.                 To me, there are

20   three groups of patients:            the one that we're really

21   worried about, and especially in a patient population

22   that I realize the test is not at this point, would not,

23   if     approved,   be   approved     for    use       in   HIV-positive

24   transplant patients.        But if I'm really worried and the

25   test is negative, I'm going to pursue other things:

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1    bronchoscopy, whatever it is going to take clinically

2    to get the diagnosis excluded comfortably; that is, active

3    disease excluded.

4                     If it's a very low-risk population, I think

5    we're wasting time and effort on patients who shouldn't

6    be tested in the first place.            And in the middle group

7    the test is as good or better than skin testing or it

8    shouldn't be approved for use, and if it is, you realize

9    that neither of them is going to be perfect, and you do

10   it.      If things change in the patient, you escalate the

11   diagnostic process.        But you've got an opportunity, in

12   passing through some of the testing operations that we

13   saw portrayed here, and you do it and act appropriately

14   on the results and get on with things.

15                    CHAIRMAN WILSON:       Dr. Charache?

16                    DR. CHARACHE:     I'm sure this is the only time

17   I've disagreed with Dr. Reller.

18                    (Laughter.)

19                    Whenever we both have our hands up and he's

20   called first, I don't have to speak.

21                    (Laughter.)

22                    But I think in this case I'm very concerned

23   about the five- to tenfold increase in use of prophylaxis

24   for the latent TB possibility.             Now I don't know what

25   that percentage will be when we look at different

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1    breakpoints.          That may solve the problem.

2                        But where we have such a low agreement, unless

3    the agreement is 80 percent or more, I think it would

4    be worth, rather than using prophylaxis, to do a skin

5    test, and certainly a lot less cumbersome to the patient

6    than the time they would need to be on therapy.

7                        CHAIRMAN WILSON:           Dr. Cockerill?

8                        DR. COCKERILL:           Well, I agree with both.

9    I'm trying to maintain my friendship with both.

10                       (Laughter.)

11                       But I would agree that, first of all, most

12   of us would not be doing risk one testing except for

13   contacts.          So if we it in that context, that this is a

14   contact that we're screening, putting aside the Army and

15   whoever else is screening probably inappropriately for

16   the risk one, you will have six more with a cutoff of

17   15 versus 1 in this group, and I don't know what that

18   percentage          is,     that     will    then,     based   on     current

19   recommendations -- and I'm not up-to-date on all the CDC

20   recommendations -- you would treat with either six months

21   of Isoniazid or two months of the combined.

22                       That, to me, if we would stay at a 15 percent,

23   one would then consider another test to substantiate that

24   result.          I don't know what that total incidence is, but

25   it probably is pretty low. Even though we have that

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1    discordance and the agreement is only 12, there were very

2    few that actually tested positive, either one, in that

3    risk group one.

4                     Now the 30 percent cutoff, when we see that

5    data, maybe we'll get down to 3 versus 1, and then I agree

6    with what you're saying.

7                     CHAIRMAN WILSON:        Dr. Sanders?

8                     DR. SANDERS:        Two comments -- actually, two

9    questions.         Although      I   agree   with      Dr.     Charache's

10   recommendations for potentially handling the risk groups,

11   are we saying that this is a recommendation we're actually

12   making and asking that to be printed in the package insert,

13   if ultimately approved, or are we making this as a

14   recommendation that could be considered by physicians

15   treating the patient who actually has that patient in

16   front of them to consider?             So that's one question.

17                    And then the other has to do with, we continue

18   to speak about the 15 percent and the 30 percent cutoff,

19   which we have not seen the 30 percent data.                    So I guess

20   the      other   question    is:       Are   we    going      to     make         a

21   recommendation today, having not seen that data?

22                    CHAIRMAN WILSON:        Do you want to comment,

23   Dr. Charache?

24                    DR. CHARACHE:        Yes.   I think before we make

25   any      recommendation     of     follow-up      testing,       the      most

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1    important points to be made are those that you and Dr.

2    Reller have made, which is the individual physician will

3    be assessing the patient.          But I think guidance should

4    be given.

5                     Now in terms of making a recommendation of

6    switching the cutoff to this 30 percent rather than 15,

7    I would recommend that the recommendation be made that

8    the cutoff be reviewed for each category of patient and

9    be adjusted to optimize the purpose for which the test

10   is to be performed.        So if the purpose of the low-risk

11   group is to determine who would benefit from antibiotic

12   therapy, then the breakpoint should be set to optimize

13   getting that information.           But I don't think we're in

14   a position to recommend what the numbers should be.

15                    CHAIRMAN WILSON:       Would you like to make a

16   comment?

17                    DR. JOLLY:    Thank you, Mr. Chairman.

18                    I would draw the panel's attention to the

19   document which starts on page 192 of volume 2.                In that

20   particular analysis we do present all of the data for

21   15 percent cutoff and for 30 percent cutoff.                 I refer

22   in particular to page 196, where there's a table which

23   shows precisely the Venn diagrams of the FDA, not Venn

24   diagrams but these tables, at the 15 percent cutoff and

25   at the 30 percent cutoff.

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1                     I would like to draw the panel's attention

2    to the fact that the specificity in each of those three

3    risk groups changes to 98 percent, 98 percent, and 94

4    percent, respectively, when we move the cutoff from 15

5    to 30 percent.       This is precisely the reason that we

6    recommended the change to 30 percent, because we believe

7    it matches these data precisely.

8                     In terms of maximizing, why was that 30

9    percent chosen?      I draw the committee's attention to the

10   rest of that document which says that the 30 percent cutoff

11   is appropriate for -- was chosen as being the appropriate

12   cutoff point based on the CDC data.

13                    So I would submit, Mr. Chairman, that those

14   are right there and we would draw the panel's attention

15   to those data.

16                    CHAIRMAN WILSON:       Thank you.

17                    Dr. Charache?

18                    DR. CHARACHE:       Just in reading that, the

19   table is set up and I want to be sure that I'm reading

20   it correctly.      What this is saying is that, of those that

21   are skin-test-positive -- there are four that were

22   skin-test-positive -- there were 41 that were positive

23   by the QuantiFERON?

24                    DR. JOLLY:    That's correct, but that's with

25   a cutoff of 10 percent.

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1                     DR. CHARACHE:       Then as we go across, the

2    differences are a threefold change?

3                     DR. ROTHEL:     If you go --

4                     DR. CHARACHE:       Of discrepant results.

5                     DR. JOLLY:     -- to 30 percent, then it's six

6    are in the discordant group --

7                     DR. CHARACHE:       Right.

8                     DR. JOLLY:     -- as opposed to two.

9                     DR. CHARACHE:       This is the Army recruits or

10   the Navy recruits?

11                    DR. JOLLY:     This is correct.

12                    DR. CHARACHE:       So we would also like to see

13   this in the other broader population, but this is exactly

14   the kind of data that I'm sure the FDA and the sponsor

15   will be looking at in terms of selecting the right cutoff.

16                    This   is    just   the     low   group,   and      then

17   intermediate group we would be concerned about as well,

18   where there's quite a few discrepants as well.

19                    DR. JOLLY:     Thank you.

20                    MR. GUTMAN:     Our statistician would like to

21   make a comment.

22                    CHAIRMAN WILSON:       Okay.

23                    MR. DAWSON:     I have to take exception to the

24   company's analysis arriving at the 30 percent cutoff for

25   human response.         It's based on ROC analysis, and, of

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1    course, that's a wonderful tool for deciding on a cutoff

2    because you get to look at the whole spectrum of possible

3    cutoffs and pick the one that gives you a desirable balance

4    between sensitivity and specificity.

5                     But the problem with what the company has

6    done is to base their ROC entirely on a comparison with

7    TST as a gold standard.              All I can say is we can't

8    interpret the result because we all in this room know

9    or believe, or have certainly heard today, that TST is

10   not a gold standard.          So I basically would ask you to

11   disregard anything related to those ROC figures in your

12   panel pack.

13                    As I mentioned this morning, we do have

14   analytical means available to us for evaluating an

15   after-the-fact       change     in     the    cutoff.          It's          a

16   cross-validation method involving a technique known as

17   the bootstrap.      So if the company, for whatever reason,

18   wants to change the cutoff, in this case from 15 to 30

19   percent, we can recommend an appropriate technique, but

20   that technique would be what I would expect would have

21   to be done for justification.

22                    CHAIRMAN WILSON:       Thank you.

23                    Any other questions or comments?

24                    (No response.)

25                    Question No. 5, please.

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1                     Question No. 5 states:         "Could conjunctive

2    or adjunctive use of QFT with TST testing provide

3    additional benefit in any of the above risk groups?"

4    I think we've discussed this to some extent, but are there

5    any additional comments or questions?

6                     Dr. Lewinsohn?

7                     DR. LEWINSOHN:      I guess if we're still kind

8    of talking about labeling, I mean it seems like having

9    the data certainly is, from both of the American studies

10   along with the Venn diagrams, would be very helpful for

11   the clinician.       It seems to me, though, that we don't

12   ultimately really know many of the answers that we would

13   like to know in terms of who's likely to go on to develop

14   active disease after they have either one of these tests

15   turn up positive.      I suspect those answers will come out

16   with more study and more clinical evaluation.                 So that

17   it might be smart just to have data, but a paucity perhaps

18   of specific clinical recommendations in the package

19   insert.

20                    CHAIRMAN WILSON:       Dr. Carroll?

21                    DR. CARROLL:       Yes, I just wanted to say

22   something similar.       As a clinician, I do not think that

23   the labeling should include a recommendation for TST

24   testing in conjunction with this assay.               I think that

25   should be left up to the individual physician's decision

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1    and the risk stratification of the patient and other data

2    that will be used to decide whether a patient has active

3    disease or is at low risk for disease.

4                      So I would disagree with actually including

5    that in the labeling.            I would say, though, that all

6    information should be provided to the clinician or the

7    labeling regarding discordance for each of the risk

8    groups.

9                      CHAIRMAN WILSON:          Mr. Reynolds?

10                     MR. REYNOLDS:       I again have a question on

11   the current labeling for the PPD.                 What does that say

12   about testing in low-risk groups?              Anyone have any idea?

13                     CHAIRMAN WILSON:       Does anyone from FDA want

14   to comment on that?

15                     DR. CATANZARO:       I don't know the labeling,

16   but I know CDC's recommendations quite well.                           They

17   recommend specifically against that.                    CDC recommends

18   targeted testing, as does the IOM, targeting based on

19   epidemiologic factors.            As someone pointed out, that

20   doesn't forbid anybody from using them in a low risk,

21   and     that     causes   problems     in    interpretation       that         a

22   clinician has to spend a lot of time on, but CDC recommends

23   targeted testing.

24                     MR. GUTMAN:       I do have, compliments of a

25   panel member, the package insert, and the CBER person

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1    will       quality   control     me,    but   it    looks     relatively

2    nondirective.

3                      CHAIRMAN WILSON:        Thank you.

4                      DR. COCKERILL:       It does recommend additional

5    testing, culture, chest x-ray based on clinical findings.

6                      CHAIRMAN WILSON:        Dr. Charache?

7                      DR. CHARACHE:        I think it would be helpful

8    to provide guidance which is accurate with any changes

9    that are being made in breakpoints, because I don't know

10   that the average physician would understand how to use

11   the data.        We're struggling with how to interpret it here,

12   and when you emphasize the agreement on the positives

13   and when you emphasize the agreement on the negatives.

14    I think that that's a lot to ask of someone who's, whether

15   he's doing the case study or taking care of a family member

16   of someone who's had TB, or whatever it is.                   So I think

17   some guidance would be helpful.

18                     But I think, as Dr. Sanders pointed out, this

19   should also be emphasized in terms of the overall

20   responsibility of the physician in deciding what's best

21   for that patient.

22                     CHAIRMAN WILSON:        Any other comments?              Dr.

23   Cockerill?

24                     DR. COCKERILL:       Yes, I would agree with that

25   because, as a clinician as well, we do have guidelines

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1    for interpreting the tuberculin skin test which aren't

2    part of the package insert.              We don't have guidelines

3    for interpreting this test outside of the package insert.

4     So anything that we can provide, especially if we have

5    two different cutoffs, that information has to be in there

6    as far as, what is a low risk, moderate, high risk, for

7    the clinician to make some sense out of it.

8                      CHAIRMAN WILSON:       Okay, again, in an effort

9    to help everyone get to the airport on time today, I'm

10   going to rearrange the agenda somewhat.                 I would like

11   at this point to go to the open public hearing.                  If any

12   members of the audience would like to make a comment,

13   please come forward at this time.

14                     (No response.)

15                     There being none, the open public hearing

16   is closed.

17                     I spoke briefly with industry over the lunch

18   hour.        They were hoping to have a little bit of time to

19   prepare the industry response.              So what I would like to

20   do now is take a break from now until 2:30 to allow them

21   at least 15 minutes to work on that, if you would like

22   to take that time.

23                     DR. ROTHEL:      I think we would just like to

24   thank the panel for their considerations today, and we're

25   quite happy.        Thank you.

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1                     CHAIRMAN WILSON:       Okay.     Does FDA need time

2    to do anything to prepare their response?

3                     MR. GUTMAN:      No, we have no response.

4                     CHAIRMAN WILSON:          You have no response?

5    Okay.

6                     At this time let's move forward, then, with

7    the final recommendations and vote.                At this time it's

8    the      responsibility     of    the   panel    to    provide      final

9    recommendations to the FDA and to vote on the product

10   that is before us today.          I would like to remind everyone

11   that only voting and temporary voting members can vote.

12                    Before we get there, I just want to make sure

13   that if there are any last issues that the panel members

14   have that they would like to clarify prior to the final

15   recommendations and vote, we could do that now.

16                    Dr. Nolte?

17                    DR. NOLTE:      Yes, we were talking about having

18   guidelines or recommendations for how to interpret tests

19   that were outside of the package insert.               Clearly, there

20   are guidelines for interpreting tuberculin skin testing

21   that has come from the CDC and other places.

22                    I wonder, since the CDC was so intimately

23   involved with the clinical trial of this particular test,

24   whether there are going to be guidelines forthcoming soon

25   from them in terms of how to interpret such a test, should

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1    it be approved.

2                     DR. MAZUREK:     Jerry Mazurek, CDC.

3                     Yes, we're working on it.

4                     DR. NOLTE:    Okay.

5                     CHAIRMAN WILSON:       Does anyone on the panel

6    feel like they need any time to look at any more of the

7    data, particularly the article that was passed out today?

8                     Dr. Ng?

9                     DR. NG:      Dr. Mazurek, I would be very

10   interested in seeing the interlaboratory reproducibility

11   before the CDC comes out with its guidelines.                In other

12   words, I want to know how reproducible a 15 or a 30 percent

13   cutoff is from lab to lab.

14                    DR. MAZUREK:       For additional studies and

15   studies that are coming up for the QuantiFERON, we will

16   try to take that into account and include reproducibility

17   and interlaboratory variations in assessing the test.

18                    CHAIRMAN WILSON:       Okay.    Ms. Poole?

19                    MS. POOLE:    Good afternoon.        I'll now read

20   the panel recommendations, all voted options.

21                    "The   medical    devices      amendments     to     the

22   Federal Food, Drug and Cosmetic Act (the Act) as amended

23   by the Safe Medical Devices Act of 1990 allows the Food

24   and Drug Administration to obtain a recommendation from

25   an expert advisory panel on designated medical devices

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1    pre-market approval applications that are filed with the

2    agency.

3                      "The PMA must stand on its own merits, and

4    your recommendations must be supported by safety and

5    effectiveness data in the application or by applicable

6    publicly-available information.                Safety is defined in

7    the Act as a reasonable assurance, based on valid

8    scientific evidence, that the probable benefits to health

9    under conditions of intended use outweigh any probable

10   risk.        Effectiveness is defined as a reasonable assurance

11   that in a significant portion of the population the use

12   of the device for its intended uses and conditions of

13   use, when labeled, will provide clinically-significant

14   results.

15                     "Your recommendation options for the vote

16   are as follows:          approval, if there are no attached

17   conditions; approvable with conditions.                 The panel may

18   recommend that the PMA be found approvable subject to

19   specified        conditions     such    as    physician    or    patient

20   education, labeling changes, or a further analysis of

21   existing data.        Prior to voting, all of these conditions

22   should be discussed by the panel.

23                     "A vote of not approvable, the panel may

24   recommend that the PMA is not approvable if the data do

25   not provide a reasonable assurance that the device is

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1    safe or if a reasonable assurance has not been given that

2    the device is effective under the conditions of use

3    prescribed, recommended, or suggested in the proposed

4    labeling.

5                      "Following the vote, the Chair will ask each

6    panel member to present a brief statement outlining the

7    reasons for their vote."

8               Our voting members are Kathleen Beavis, Valerie

9    Ng, Natalie Sanders, and appointed as temporary voting

10   members -- and we have another citation to read:

11              "Pursuant to the authority granted under the

12   Medical Devices Advisory Committee charter dated October

13   27th, 1990, and as amende August 18th, 1999, I appoint

14   the      following    persons      as    voting     members    of      the

15   Subcommittee of the Microbiology Advisors Panel for the

16   duration of this panel meeting on October 12th, 2001:

17   Ellen J. Baron, Frederick Nolte, and Barth Reller.

18                     "For the record, these people are special

19   government employees and are either a consultant to this

20   panel or a voting member of another panel under the Medical

21   Devices Advisory Committee.               They have undergone the

22   customary        conflict-of-interest         review.     They       have

23   reviewed the material to be considered at this meeting."

24                     And it is signed "David W. Feigal, M.D., MPH,

25   Director for the Center for Devices and Radiological

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1    Health," on October 10th of this year.

2                     CHAIRMAN WILSON:        Thank you.

3                     Are there any questions from members of the

4    panel?

5                     (No response.)

6                     All right, then at this point I will entertain

7    motions regarding this PMA submission.                 Dr. Baron?

8                     DR.   BARON:       I   move    that     we   vote       for

9    approvable with conditions, and I hope the panel will

10   help me with the conditions here.

11                    DR. SANDERS:      I'll second that.

12                    CHAIRMAN WILSON:        Okay, we need to specify

13   the conditions then.

14                    DR. BARON:     Karen has handed me a few.

15                    Attached conditions should be statistical

16   analysis, as suggested by Dr. Dawson and originally by

17   Dr. Charache, about stratification of risk groups and

18   appropriate      cutoffs;     interlaboratory          reproducibility

19   studies previewed and then followed by CDC guidelines

20   for use external to the package insert, independent of

21   the package insert.

22                    CHAIRMAN    WILSON:        Dr.    Gutman,      I    don't

23   believe we can specify --

24                    MR. GUTMAN:       You can recommend that, but

25   don't make that a condition of approval.

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1                      DR. BARON:     Okay, and one more before I stop:

2     physician        recommendations       for    utilization     of      the

3    results.

4                      DR. SANDERS:        Actually, I would like to

5    modify that last one and ask for a physician education

6    program to educate physicians, treating physicians, about

7    the test.        I know that there's probably a program in place

8    for the laboratory physicians in order to be able to

9    ultimately report and interpret the results, but an

10   additional physician or practicing physician education

11   program.

12                     DR.   NOLTE:        In    addition    to   any       CDC

13   recommendations that might be forthcoming?

14                     DR. SANDERS:       Well, we can't mandate that

15   part, but we can ask the company to provide physician

16   education.

17                     DR. NOLTE:     No, I'm asking you in terms, if

18   there were CDC guidelines forthcoming, would you have

19   the same recommendation?

20                     DR. SANDERS:      If there were CDC guidelines

21   forthcoming, I would accept those.

22                     CHAIRMAN WILSON:         Okay, we have a motion of

23   approvable with conditions, those conditions being that

24   there be further statistical analysis with stratification

25   of the risk groups by the varying cutoffs; that there

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1    be     further      data     provided     on   the       reproducibility,

2    particularly regarding interlaboratory variability in

3    test results, and the third one being recommendations

4    for physician interpretation and education regarding the

5    use of the product.

6                       Dr. Ng?

7                       DR. NG:    I would ask that there be expansion

8    in your package insert for people like me, so when I use

9    it, I have the different risk groups and the concordance

10   and non-concordance of the two tests, so I can explain

11   to my users.

12                      CHAIRMAN WILSON:        Dr. Baron?

13                      DR. BARON:      Dr. Charache is suggesting that

14   we also add that data be presented in the package insert

15   on the agreement of positives.

16                      DR. CHARACHE:      I shouldn't be speaking.              May

17   I speak?         No, I shouldn't speak?

18                      CHAIRMAN WILSON:        No, you can't speak.

19                      DR. BARON:      Okay, she's suggesting that we

20   add agreement not just on the positives and negatives,

21   but data presented separately.

22                      DR. SANDERS:       Mr. Chairman, is it not our

23   usual        practice,     after     we     have     made     our       final

24   recommendation and vote, that we then go through the

25   package insert in greater detail?                    Is that our usual

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1    practice or do we do it now?

2                     CHAIRMAN WILSON:       We do it now.

3                     DR. SANDERS:     Well, if we do it now, I think

4    also we had discussed earlier that we would be careful

5    about the timing, if skin testing had been performed,

6    that there should be perhaps a warning or a limitation

7    indicated in the package insert of a timeframe with which

8    not to perform the QFT.          So that should also be added

9    in the package insert.

10                    CHAIRMAN WILSON:          Dr. Baron, could you

11   further clarify what additional data that you were

12   suggesting be included?

13                    DR. BARON:     Well, it's not my suggestion.

14                    (Laughter.)

15                    CHAIRMAN WILSON:         Yes, but you made the

16   motion.

17                    DR. BARON:     I made the motion, but I don't

18   quite understand it.

19                    (Laughter.)

20                    CHAIRMAN WILSON:      We need to know before we

21   can make a recommendation to the manufacturer --

22                    DR. BARON:    Can some other committee member

23   agree with it or not, and then --

24                    CHAIRMAN WILSON:       Dr. Ng?

25                    DR. NG:   If I can interpret what I think Dr.

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1    Charache was asking, it's the two-by-two tables, because

2    the agreement is looking at that diagonal axis of what

3    in boxes A and D in the two-by-two table.                     What I was

4    asking for was slightly different, which was the overlap

5    and the missed populations between the two tests.                          But

6    if we include all that information, it would really help

7    with the interpretation of the test result.

8                     DR. RELLER:     So what Dr. Ng is talking about

9    is basically the two-by-two tables plus the Venn diagrams?

10                    CHAIRMAN WILSON:      Correct.       Okay, so we have

11   a motion, then, for approval with conditions, and so far

12   there are, depending on how you slice it, five or six

13   conditions.

14                    Dr. Reller?

15                    DR. RELLER:       I'm assuming that in those

16   conditions       are   the     explicit      description           of      the

17   populations      for   which    data   are    not     yet     available:

18   transplant, et cetera.          I think this is very important

19   because with a new test that is more -- the scientific

20   basis of it is more delineated.           You're recalling memory

21   from lymphocytes with a purified protein derivative of

22   what you are seeking to elicit the memory of, that there

23   is maybe an assumption that it's a better test.

24                    With the CDC guidelines and more experience,

25   it may turn out to be that way, but I can envision a

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1    situation where in the very patients for which there are

2    no current data would be the very patients that Dr. Ng

3    and others, including ourselves, would be pounded upon

4    to do the test.          I think that it should be very explicit,

5    and then to come in subsequently, as the data unfolds

6    and the guidelines are clarified, but to have that

7    unequivocally spelled out in the package insert, so that

8    there would be a sequenced introduction that was consonant

9    with the database available.

10                       CHAIRMAN WILSON:         Thank you.       Is there any

11   further discussion of the conditions?                      Dr. Sanders?

12                       DR. SANDERS:        Well, I just want to make a

13   comment          that   that    actually,      those       limitations        are

14   actually spelled out as the company has given it to us,

15   and I would be very surprised if they were not already

16   planning to look at this in those populations.

17                       CHAIRMAN WILSON:          We have a motion and we

18   had a second on the original motion.                       At this point I

19   would need a motion on the amended conditions.                              Does

20   everyone have firmly set what all the conditions are or

21   would you like me to go over those again?

22                       First      is   further     statistical        analysis,

23   particularly regarding stratification of the data by the

24   different risk groups and the varying cutoff points.

25                       Second is the issue of reproducibility,

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1    particularly regarding interlaboratory variability.

2                     The    third     is     information         regarding

3    interpretation of the tests, both by laboratory physician

4    or scientists as well as the practicing clinician.

5                     The next is inclusion of further data, both

6    the Venn diagrams as well as the two-by-two tables.

7                     And the final one is that there be a comment

8    regarding the possible effect of tuberculin skin testing

9    on the QFT test and the need for possibly separating those

10   two.

11                    DR.    BARON:          Can      I     clarify          the

12   interlaboratory        reproducibility        studies,     that       they

13   should include a lot of negatives.                    It's the false

14   positives we're concerned about here.

15                    DR. NOLTE:      I think it needs to include a

16   whole range, the range of expected values and sort of

17   representative of what you might see in a population that

18   you were screening.         I know this is different; we're

19   talking about different populations here, but something

20   more representative of what you might actually wind up

21   testing.

22                    CHAIRMAN WILSON:       Okay, thank you.

23                    DR. NOLTE:     I need a clarification on this

24   physician education aspect of this and how this becomes

25   a condition to approval.         I mean, what are we suggesting

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1    when we say this, that the manufacturer contact each and

2    every practicing physician and tell them how to interpret

3    this or what?              I mean, to do education programs?                    What

4    are we buying into here by physician education?

5                            MR. REYNOLDS:      I was thinking something more

6    along the line of a little booklet or leaflet or something

7    that could be given out to physicians, explaining in more

8    detail           how    this   test     works    and    how   it     should        be

9    interpreted.              I don't know what the other folks on the

10   committee were thinking of.

11                           DR. SANDERS:      Since I made that suggestion,

12   actually, that's what I envision.                      But I envision it in

13   two ways:              one, that as this test becomes purchased by

14   entities, there would be an education process for the

15   laboratory and the supervising physician or lab director

16   at that institution.

17                           I would also envision, subsequently, some

18   type of program for instructing the using clinicians,

19   with materials provided by Cellestis.                     Now I'm not saying

20   that Cellestis has to actually come out and do that

21   education              program,   but    with     materials    provided            by

22   Cellestis.               That could actually be done by the lab

23   director or the lab director's staff, because once that

24   test has been purchased by the entity, they're going to

25   want people to use it.

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1                     So that is how I had envisioned.         Does that

2    help you, Dr. Nolte?

3                     DR. NOLTE:     Yes, I guess it does, but I'm

4    just trying to think if there really are going to be

5    guidelines, of course, coming from CDC, it's hard to see

6    how the information from the sponsor is going to have --

7                     DR. SANDERS:       I made that recommendation

8    because I do feel that clinicians will need to be educated

9    on how to use this test.

10                    DR. NOLTE:     Yes.

11                    DR. SANDERS:       And we could not, for the

12   record, state that we would encourage CDC, another

13   government agency, to do this.           So we would have to then

14   make it a recommendation for the sponsor.

15                    DR. NOLTE:     We've also asked them to include

16   a lot of that type of information in the package insert.

17    So I'm trying to figure out what this pamphlet from the

18   sponsor is going to say that's not in the package insert.

19                    DR. SANDERS:     Well, as a treating physician,

20   I actually never see the package insert for a lab test

21   that I order.

22                    DR. NOLTE:       No, I understand that.                   I

23   understand that, but whose responsibility is it to

24   educate, the sponsor or the offering laboratory?

25                    CHAIRMAN WILSON:       Dr. Gutman?

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1                       MR. GUTMAN:     Yes, we're prepared to work with

2    the company and also to consult with CDC and try and create

3    some path for it.         I think you are trying to micromanage.

4     You've made a recommendation.                We'll try and take it

5    to heart.

6                       DR. NOLTE:     Okay.

7                       CHAIRMAN WILSON:           We have a motion for

8    approvable with conditions.                I need a second on the

9    conditions as clarified.

10                      DR. NG:    Second.

11                      CHAIRMAN WILSON:         We have a motion and a

12   second.          Is there any further discussion at this time

13   regarding either the main motion or the conditions?

14                      (No response.)

15                      Okay, there being none, then I would like

16   to take the vote.          All the voting panel members who are

17   in favor raise their hand.

18                      (Show of hands.)

19                      Do it by voice as well?       Shall we do it again?

20                      Dr. Reller?

21                      DR. RELLER:      Reller, yes.

22                      CHAIRMAN WILSON:        Dr. Nolte?

23                      DR. NOLTE:     Nolte, yes.

24                      CHAIRMAN WILSON:        Dr. Beavis?

25                      DR. BEAVIS:      Beavis, yes.

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1                     DR. NG:   Ng, yes.

2                     DR. SANDERS:     Sanders, yes.

3                     DR. BARON:    Oh, Baron, yes.

4                     CHAIRMAN WILSON:        The vote is unanimous.

5    Thank you.

6                     Okay, at this point then we would like to

7    move to have each of the voting members state the reason

8    for their vote, beginning with Dr. Reller.

9                     DR. RELLER:     I believe the data presented

10   justified the recommendation and the vote that we have

11   just taken.

12                    CHAIRMAN WILSON:       Dr. Nolte?

13                    DR. NOLTE:    Yes, obviously, I think this test

14   represents an advance in terms of its intended use, and

15   the issues that I have in terms of the data were

16   essentially around the statistics to validate the 30

17   percent cutoff and the interlaboratory reproducibility,

18   and both of those have been addressed in the conditions

19   we attached.

20                    CHAIRMAN WILSON:       Dr. Beavis?

21                    DR. BEAVIS:    I want to thank and commend the

22   sponsors for tackling, I think, a very difficult area

23   and a severe public health issue in this country,

24   especially being from Cook County.

25                    Again, I think the data are very strong and

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1    that the additional data will only further support the

2    use of this test.

3                     CHAIRMAN WILSON:       Dr. Ng?

4                     DR. NG:    I voted yes because anything has

5    to be better than the skin test.

6                     (Laughter.)

7                     CHAIRMAN WILSON:       Dr. Sanders?

8                     DR. SANDERS:    I would agree with the opinions

9    that have already been expressed from my colleagues.

10   Thank you.

11                    CHAIRMAN WILSON:       And Dr. Baron?

12                    DR. BARON:     I want this test.      Also, I like

13   the idea of having it be a laboratory test that I can

14   charge somebody for.

15                    (Laughter.)

16                    CHAIRMAN WILSON:       All right, thank you.

17                    That concludes the business for today.                     I

18   would, in particular, like to thank the sponsor.               I think

19   this was a very well-done submission, both in terms of

20   the written material as well a their presentations today.

21    I would really like to applaud the efforts that they

22   have made.

23                    I would like to thank all the panel members,

24   particularly our guest, Dr. Lewinsohn, who had to leave

25   a few minutes ago, could not stay, had to make a flight;

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1    all the members of the FDA for all the work they've done

2    on this.         This has been a very good meeting.

3                       I would like to particularly thank everyone

4    who made the efforts to get here in these trying times.

5     Travel is not easy right now.                I know what it's like,

6    and we do appreciate everybody who's willing to fly at

7    a time like this.

8                       Thank you, and the meeting is adjourned.

9                       (Whereupon, at 2:36 p.m., the meeting was

10   adjourned.)

11

12

13




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