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1954 Salk polio vaccine trials

► Biggest public health

experiment ever

► Polio epidemics hit

U.S. in 20th century

► Struck hardest at

children

► Responsible for 6% of

deaths among 5- to 9-

year-olds

Number of polio cases in the U.S.

1930 to 1955

60000





50000





40000





30000





20000





10000



0

1930 1934 1938 1942 1946 1950 1954

1932 1936 1940 1944 1948 1952





YEAR

Salk vaccine trial: Background

► Polio is rare but the virus itself is common

► Most adults experienced polio infection without

being aware of it.

► Children from higher-income families were more

vulnerable to polio!

► Children in less hygienic surroundings contract

mild polio early in childhood while still protected

from their mother’s antibodies. They develop

immunity early.

► Children from more hygienic surroundings don’t

develop such antibodies.

Salk trial: The need for testing

► By 1954, Salk’s research with a vaccine looked

promising

► Government agencies were ready to try the

vaccine in the general population but some

scientists feared the vaccine was unsafe or

ineffective.

► There was enormous fear and desperation

throughout the country.

► Why not just distribute the vaccine to some and

see if it lowered the polio rate?

 A yearly drop might mean the drug was

effective, or that that year was not an

epidemic year

► Vaccine could not be distributed without testing

Salk vaccine trial:

The need for controls

► An experiment requires controls.

► To test if the vaccine was effective the only variable that

should be considered is the vaccine itself

► This means that some children would get the vaccine and

some would not.

► This raises enormous ethical questions:

 Is it ethical to not give children the vaccine?

 Imagine yourself as a parent in these desperate times.

Would you participate in such an experiment.

 Ultimately, does the benefit to society outweigh the risk

to those children who would not get the vaccine?

Salk vaccine:

The need for massive trials

► Polio rate of occurrence is about 50 per100,000

► Suppose the vaccine was 50% effective and

10,000 subjects were recruited for each of the

control and treatment groups

 You would expect 5 polio cases in control group and

2-3 in treatment group

 Such a difference could be attributed to random

variation

were needed on a massive scale

► Clinical trials

► The ultimate experiment involved over 1.6

million children, with over 600,000 children

inoculated

Controversy over the

design of the experiment

► In order to isolate the vaccine as the only variable to be

considered, the treatment and control groups need to

be as similar as possible

► But how should subjects be recruited?

► Fact: volunteers tend to be better educated and more

well-to-do than those who don’t participate

► In the context of the polio disease, relying on volunteers

could potentially bias the results

 Subjects would tend to have higher rates of polio

 Subjects are not representative of the population

 Results would be biased against the vaccine

► After much debate, the trials proceeded with two different

protocols.

“Observed Control” approach



► Administer the experiment to 1st, 2nd, and 3rd graders

► Offer the vaccination to 2nd graders

 This group would rely on volunteers (parental consent)

► Use 1st and 3rd graders as control group

 These children would be observed for incidences of polio

► Supporters of this approach argued that there would not

be much variability between grades so treatment and

control groups would be similar

► And the control group would be “observed controls”

► But there were objections . . .

NFIP Observed Control study

► Volunteers would result in more children from higher

income families in treatment group

 Treatment group is thus more vulnerable to disease than

control group

 Would expect more incidences of polio in the treatment

group than in the control group

 Biases the experiment against the vaccine

► How would incidents of the disease be diagnosed?

 Many forms of polio are hard to diagnose

 In making the diagnosis physicians would naturally ask

whether a child was vaccinated or not

 Diagnosis for borderline cases could be affected by

knowledge of what grade the child was in and whether the

child was vaccinated or not

Randomized control approach

► This experiment relied on volunteer subjects overall.

► But subjects were randomly assigned to treatment and

control groups

► Control group was given a placebo

► Placebo material was prepared to look

exactly like the vaccine so subjects didn’t

know what treatment they were getting

► Placebo-control group guards against the

“placebo effect”

► Many objected to the design on ethical

grounds.

► Jonas Salk himself called it “A `beautiful’ experiment over

which the epidemiologist could become quite ecstatic but

which would make the humanitarian shudder.”

Randomized control approach



► Subjects were “blind”: they did not know to which

group they were assigned

► Also, those doing the evaluation

didn’t know which treatment

any subject received

► Each vial was identified by a code

number so no one involved in the

vaccination or the diagnostic

evaluation could know who got

the vaccine.

► Experiment was double-blind:

neither subjects nor those doing

the evaluation knew which

treatment any subject received

Results of vaccine trials

The randomized, controlled experiment



Size Rate (per 100,000)

Treatment 200,000 28



Control 200,000 71



No consent 350,000 46



The Observed Control study



Size Rate (per 100,000)

Grade 2 (vaccine) 225,000 25

Grade 1, 3 (control) 725,000 54

Grade 2 (no consent) 125,000 44



Source: Thomas Francis, J r., “An evaluation of the 1954

Poliomyelitis vaccine trials---summary report,” American Journal

of Public Health vol 45 (1955) pp. 1-63.

Comparing the two studies

► Results show that the observed control study was biased

against vaccine

 Treatment group got the vaccine but was more prone to higher

polio rates

 Control group didn’t get the vaccine but was more prone to lower

polio rates

► It’s impossible to determine what’s the effect of the

vaccine and what’s the effect of socio-economic status

► This is called confounding—the inability to distinguish the

separate impacts of two or more variables on a single

outcome.

► In a randomized controlled experiment, by making the

treatment and control groups as similar as possible (by

randomization), we are able to isolate the variable of

interest and eliminate confounding

Comparing the two studies:

are the results “significant”?

► In the “observed control” approach, chance

enters the study in an unplanned and

haphazard way based on what families will

volunteer

► By contrast, for the randomized controlled

experiment chance enters the study in a

planned and simple way

 Each child has 50-50 chance to be in the

treatment or control group

► Thisallows for the use of probability to

analyze the results

Are the results significant?

► Twocompeting positions—which side would you

be on?

 Pro: “The vaccine is effective. There were less cases

of polio in the treatment group than in the control

group. We should undertake a massive vaccination

program throughout the general population.”

 Con: “We are not convinced. The two groups were

randomly divided. There may have been fewer polio-

prone people in the treatment group. It was all done

by chance. We can’t be sure and we’re not willing to

commit millions of dollars of taxpayer’s money on a

vaccination program that might not be effective.”

Are the results significant?

► Assume the cons are right and that the

vaccine is worthless. What are the

chances of seeing such a large

difference in the two groups?

► Imagine a “polio” coin where the

chance of heads is equal to the

chance that a person gets polio.

Flip the coin in Room A for 200,000 times. Then flip it

in Room B for 200,000 times. What’s the chance that

we would get such a large difference as 28 heads in A

and 71 heads in B?

► They are over a billion to one against!

► In the face of such odds, we say that the outcome is

statistically significant. The effect is so large that it

would rarely occur by chance.

Salk vaccine trials aftermath

► The results, announced in 1955, showed good statistical

evidence that Jonas Salk's vaccine was 80-90% effective in

preventing paralytic poliomyelitis.

► Postscript: Polio was virtually eliminated from the

Americas in 1994, but still circulates in Asia and Africa,

paralyzing the world’s most vulnerable children.

► The Global Polio Eradication Initiative was begun in 1988.

That year, an estimated 350,000 children were paralyzed

with polio worldwide.

► In 2004, polio cases had fallen to just over 1,200 cases

globally.

The language of experimental design



 In an experiment, we have at least one explanatory

variable, called a factor, to manipulate and at least

one response variable to measure

 The specific values that the experimenter chooses

for a factor are called the levels of the factor.

 A treatment is a combination of specific levels from

all the factors that an experimental unit receives.

 The ability to manipulate factors, apply treatments,

and compare the responses is what differentiates an

experiment from an observational study

Observational studies



 Nurses Health Study often in the news

– Over 100,000 registered nurses aged 30 to 55 have been

followed for more than 30 years

– Detailed questionnaires sent out every two years on a wide

variety of health and nutrition issues

– 90% response rate

– “One of the most significant studies ever conducted on the

health of women.” -- Donna Shalala, Former Secretary of

the U.S. Department of Health and Human Services

 This is a prospective study. Subjects were identified

in advance and data collected as events unfolded.

 Many observational studies are retrospective.

Subjects are selected and their previous conditions

or behaviors are determined.

Confounding



 Observational studies can suffer from

confounding and lurking variables

 You’ll read about this over the weekend in

“Hormone Studies: What Went Wrong?”

 The ability to control and manipulate

variables and compare groups allows for

eliminating confounding and the effect of

lurking variables

Double-blind, placebo-controlled

randomized comparative experiment:

The “gold standard” of statistics

 Massive clinical trials industry

 Complex ethical questions for experiments involving human

subjects

– Informed Consent, Institutional Review Board, Confidentiality

 Placebo effect is a fascinating area of research

– In conditions such as pain, the percent of patients responding to

placebos has been shown to be 20% to 50%.

– Reflects the amount that the body can be coaxed/empowered to

heal itself, in the absence of other active agents.

 Today, few clinical trials compare against placebo. Most new

drugs are improvements over existing therapies. If an existing

medicine exists it would be unethical to deny it to subjects

Other experimental design issues:

Blocking



 When groups of experimental units are similar, it’s

often a good idea to gather them together into

blocks.

 Blocking isolates the variability due to the differences

between the blocks so that we can see the

differences due to the treatments more clearly.

 When randomization occurs only within the blocks,

we call the design a randomized block design

 By contrast, a completely randomized design, all

subjects have an equal chance of receiving any

treatment.

Diagram of a blocked experiment

Hypertension pharmacogenetics study



• Hypertension is most prevalent risk factor for diseases

of the heart, brain and kidneys, affecting 43 million in

U.S.

• Complex disease affected by physical, physiological

and environmental factors

• State-of-the-art for treatment is trial-and-error

• Less than 40% of treated patients achieve blood

pressure control (systolic blood pressure < 140)

• Ultimate goal of this study is to identify unknown

genes that influence drug response with the potential of

tailoring antihypertensive therapy for individuals

GERA Clinical Trial

• Black and white patients react differently to blood pressure

medicine

• Blocked experimental design

• Mayo Clinic – Rochester, MN

– 300 white subjects with hypertension (150 women and 150 men, ages

30 to 60)

• Emory University – Atlanta, GA

– 300 Black subjects with hypertension (150 women and 150 men, ages

30 to 60)

• Subjects had previous medications discontinued for 4 weeks;

blood pressure rose and stabilized in hypertensive range

• Hydrochlorothiazide administered for 4 weeks

• Blood pressure measured at the beginning of therapy and after

4 weeks

• In each group, identify 100 “best” responders and 100 “worst”

responders by change in blood pressure

BP decrease BP increase









Yr N Race Drug Race N

1 100 B Hydrochlorothiazide B 100

2 100 W W 100

GERA clinical trial

• DNA collected for each patient

• Data consists of 100,000 genetic markers called Single-

Nucleotide Polymorphisms (SNPs)

• Goal: to find an association between blood pressure response

and genetic makeup

• Ultimate goal: to find those genes that affect blood pressure

response

• What makes this complicated is that we have only 400

observations (the patients) and over 100,000 variables (the

genetic markers)

• Classically in statistics we had a “few” variables and “many”

observations. As datasets become larger and more complex,

this classic paradigm is shifting and the challenges are

enormous!


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