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lichtenberg

VIEWS: 7 PAGES: 48

									   The impact of new drug
    launches on longevity:
evidence from longitudinal, disease-level
   data from 52 countries, 1982-2001

             Frank R. Lichtenberg
               Columbia University and
         National Bureau of Economic Research
    United Nations
Human Development Index
(unweighted) average of three indexes:
• an index of per capita GDP
• a life expectancy index
• an education index



                                         2
U.S. economic growth,                 20th   C.

                            Nordhaus: ―to a first
                            approximation, the
                            economic value of
 Longevity    GDP growth,
                            increases in longevity over
growth, 50%      50%        the twentieth century is
                            about as large as the value
                            of measured growth in
                            non-health goods and
                            services‖

                                                   3
 Life expectancy at birth, world,
           1950-2000
70
                                                             63.9   65.0
65                                                    63.0
                                               61.4
                                        59.8
60                               58.0
                          56.1
55                 52.4
            49.6
50
     46.5
45

40
     1950- 1955- 1960- 1965- 1970- 1975- 1980- 1985- 1990- 1995-
     1955 1960 1965 1970 1975 1980 1985 1990 1995 2000

                                                                           4
     Life expectancy at birth, by region
80
75
70
65
60
55
50                                          More developed regions
45
40                                          Less developed regions
35
     1950- 1955- 1960- 1965- 1970- 1975- 1980- 1985- 1990- 1995-
     1955 1960 1965 1970 1975 1980 1985 1990 1995 2000


      Unlike GDP, longevity is converging
                                                                     5
Sources of longevity increase?

 • improved quality of, and access to,
 medical care
 • other factors
          Conventional wisdom
• ―the empirical evidence indicates [that] the overall
  contribution of medical care to health is rather
  modest at the margin …education, lifestyle, the
  environment, and income [are] the major
  contributing factors‖ (Santerre and Neun (2000, p.
  69)).
• ―increase in life expectancy [has] been much more
  influenced by economic development than
  improvements in medical care …the most
  important medical advances are being brought
  about by improvements in information technology,
  not pills and scalpels‖ (Getzen (1997, p. 330)).
                                                         7
            Conventional wisdom
• ―Research on the relationship between health status and
  medical care frequently has found that the marginal
  contribution of medical care to health status is rather
  small …any significant improvements in health status are
  more likely to originate from factors other than medical
  care…Factors that determine the level of health include
  income and education, environmental and life-style factors,
  and genetics‖ (Henderson (1999, p.142)).
• ―The historical declines in population mortality rates were
  not due to medical interventions because effective medical
  interventions became available to populations largely after
  the mortality had declined. Instead, public health,
  improved environment, and improved nutrition probably
  played substantial roles‖ (Folland, Goodman, and Stano
  (2001, p. 118)).                                            8
      Paul Romer’s Model of
   Endogenous Technical Progress
Y = (A L) 1- K 
   Y = output
   A = the ―stock of ideas‖
   L = labor used to produce output
   K = capital
   0<<1
The cumulative number of drugs launched
  (N_DRUG) is analogous to the stock of ideas.

                                                 9
  Health production function
 AGE_DEATHijt = b ln(N_DRUGij,t-k)
                       + g Xijt + eijt

AGE_DEATHijt = a statistic based on the age
  distribution of deaths from disease i in country j in
  year t
N_DRUGij,t-k = the number of drugs launched to treat
  disease i in country j by year t-k
Xijt = a vector of other factors (e.g. education, income,
  nutrition, the environment, and ―lifestyle‖) affecting
  the age distribution of deaths from disease i in country
  j in year t
                                                         10
              Specification
• diminishing returns to additions to the
  stock of drugs
• specify a k-year lag in the relationship to
  allow for gradual diffusion of new drugs to
  consumers; we will estimate the model
  using different assumed values of k (k = 0,
  1, 2,…).

                                                11
  Controlling for ―other factors‖
Hypothesize that many of the ―other factors‖
  affecting the age distribution of deaths from
  disease i in country j in year t (e.g. per capita
  income, public health expenditure, and
  environmental quality) are:
• invariant across diseases within a country and year
• invariant across countries within a disease and
  year, or
• invariant across years within a country and disease

                                                    12
   Controlling for ―other factors‖
decompose Xijt as follows:

Xijt = ’it + d’jt + ’ij + ’ijt   (2)

where
’it = a fixed effect for disease i in year t
d’jt = a fixed effect for country j in year t
’ij = a fixed effect for disease i in country j
                                                   13
                 Reduced form
AGE_DEATHijt = b ln(N_DRUGij,t-k)
                      + it + djt + ij + uijt

Zero-lag equation (k = 0), is estimated using 4678
  observations, included 496 country*year effects, 189
  disease*year effects, and 502 country*disease effects. The
  equations are estimated via weighted least squares, using
  the number of deaths in that disease-country-year cell as
  the weight.




                                                          14
    IMS Health Drug Launches
            database
• Has tracked new product introductions worldwide
  since 1982
• In August 2001 the database contained over
  165,000 records of individual product
  introductions between 1982 and 2001
• Allows measurement, for each country and
  therapeutic area, of the total number of ingredients
  launched, and the number of new chemical entities
  launched
                                                    15
Example: tenecteplase
Launch date   Country
6/00          USA
3/01          Finland
5/01          UK
9/01          Norway
10/01         Canada
10/01         South Africa
11/01         Ireland
                             16
      Drug launch probability profiles:
              U.S. vs. Canada
60%
                                                           54%    55%
50%                                       50%       52%
                                46%
40%                  39%                            40%    40%    41%
                                          37%
30%                             31%
                                           CANADA
20%                  20%
                                           USA
10%

0%          0%
        0        2          4         6         8         10     12
                       Years since initial world launch
                                                                      17
    Censoring of drug launches
• IMS Health Drug Launches database has
  tracked new product introductions
  worldwide since 1982
• NCE launches are guaranteed to be initial
  launches, but non-NCE launches may be
  either initial launches or re-launches; we
  suspect they are predominantly the latter.

                                               18
    Censoring of drug launches
AGE_DEATHijt = bNCE ln(CUM_NCEij,t-k)
   + bNON ln(CUM_non-NCEij,t-k)
    + it + djt + ij + uijt

CUM_NCE = the cumulative number of NCEs
  launched
CUM_non-NCE = the cumulative number of non-
  NCEs launched
Hypothesize that bNCE > bNON
bNON could be negative?
                                              19
      WHO Mortality database
• Provides data on the age distribution of
  deaths, by disease, country, and year
• Use aggregate life tables to translate our
  estimates of the impact of new drug
  launches on survival probabilities into
  estimates of the impact of new drug
  launches on life expectancy

                                               20
Relationship between life expectancy and probability
       of survival to age 65, U.S., 1900-2000

80
75
70
65
60                           Life expect. at birth
55                           Life expect. at age 30
50
45
40
35
  40%       50%       60%         70%                 80%

                                                            21
    Linkage of drug launches to
             diseases
• Drug launches documented in the IMS Health
  Drug Launches database are classified by
  therapeutic category
• Deaths documented in the WHO Mortality
  Database are classified by cause (disease), using
  the International Classification of Diseases
• The high-level IMS drug classification
  corresponds quite closely to the high-level ICD
  disease classification, e.g. cardiovascular system
  drugs obviously correspond to (are used to treat)
  diseases of the circulatory system                   22
                    11 broad disease categories

IMS drug class(es)          ICD10 codes ICD10 disease class(es)
A Alimentary Tract And      K00-K92,    Diseases of the digestive system; endocrine,
Metabolism                  E00-E88     nutritional and metabolic diseases
                            D50-D89      Diseases of the blood and blood-forming
B Blood and Blood Forming                organs and certain disorders involving the
Organs                                   immune mechanism
C Cardiovascular System    I00-I99       Diseases of the circulatory system
D Dermatologicals          L00-L98       Diseases of the skin and subcutaneous tissue
G Genitourinary System and N00-N98       Diseases of the genitourinary system
Sex Hormones
J General Anti-Infectives, A00-B99       Certain infectious and parasitic diseases
Systemic; P Parasitology
L Cytostatics              C00-D48       Neoplasms
                           M00-M99       Diseases of the musculoskeletal system and
M Musculoskeletal System                 connective tissue
N Central Nervous System   F01-F99,      Mental and behavioural disorders, diseases of
(CNS)                      G00-G98       the nervous system
R Respiratory System       J00-J98       Diseases of the respiratory system
                           H00-H5,       Diseases of the eye and adnexa; diseases of
S Sensory Organs           H60-H93       the ear and mastoid process

                                                                                     23
 Countries with most and fewest
         drug launches
450   422 422 414
400                 373 373                             ITALY
350                                                     JAPAN
300                                                     USA
                                                        ARGENTINA
250
                                                        UK
200                           174 171
                                        153 142         PAKISTAN
150                                               122
                                                        SINGAPORE
100                                                     SAUDI ARABIA
 50                                                     EGYPT
  0                                                     MALAYSIA
             Number of NCEs launched

                                                                   24
                   Findings
• Launches of New Chemical Entities (NCEs) have
  a strong positive impact on the probability of
  survival
• It takes at least three years for new NCE launches
  to have their maximum impact on survival rates
• This is probably due to the gradual diffusion of
  drugs to consumers following launch; data on
  pharmaceutical expenditure are consistent with
  this interpretation
• Launches of (older) drugs that are not NCEs—
  many of which may already have been on the
  market—do not increase longevity
                                                   25
   Estimates of bNCE for different lags between
     stock of NCEs launched and longevity

0.008                                                    0.0071
0.007                                0.0066    0.0065             0.0067
0.006                     0.0055
0.005
                 0.0038
0.004
0.003   0.0025
0.002
0.001
    0
          0        1        2           3            4     5        6
                                Lag length (years)                   26
        Estimates of bNCE and bexpend
           at different lag values
0.05                                                  0.008


                                                      0.007
0.04


                                                      0.006
0.03

                                                      0.005
0.02
                          log(expend) coeff
                          pct_gt65 coeff              0.004
0.01
                                                      0.003

   0
        0   1    2    3          4            5   6   0.002


-0.01
                                                      0.001


-0.02                                                 0



                                                          27
      Contribution of NCE launches to
             longevity increase
• NCE launches appear to account for a significant
  fraction of the long-run increase in longevity in
  the sample as a whole
• Between 1986 and 2000, average life expectancy
  of the entire population of sample countries
  increased by almost two (1.96) years.
• The estimates imply that NCE launches accounted
  for 0.79 years (40%) of the 1986-2000 increase in
  longevity.
• The average annual increase in life expectancy of
  the entire population resulting from NCE launches
  is .056 years, or 2.93 weeks.                     28
      Contribution of NCE launches to increase in average
         life expectancy of the population since 1986
2.5
             increase in longevity due to NCE launches                                    2.0
2.0          total increase in longevity                                           1.8
                                                                             1.7
                                                                      1.5
1.5                                                             1.4
                                                         1.2
                                                   1.1
                                            0.9
1.0
                                   0.7 0.8                0.7 0.7 0.7 0.8
                              0.6             0.6 0.6 0.6
                          0.4     0.4 0.5 0.5
0.5
                    0.2
             0.1
0.0
      1986         1988     1990     1992         1994         1996         1998     29
                                                                                         2000
Cost per life-year gained from the
         launch of NCEs
•    In 1997, average per capita pharmaceutical expenditure in
    OECD countries was about $250
•    The average annual increase in life expectancy of the
    entire population resulting from NCE launches is .056
    years
•    Hence pharmaceutical expenditure per person per year
    divided by the increase in life-years per person per year
    attributable to NCE launches is about $4500
•    This is far lower than most estimates of the value of a life-
    year
•    Moreover, since the numerator includes expenditure on
    old drugs as well as on recently-launched NCEs, it
    probably grossly overstates the cost per life-year gained
    from the launch of NCEs                                      30
Micro evidence from
a Medicaid program
   Vintage of drugs
  used Jan-June 2000
   • % approved after 1970
   • % approved after 1980
   • % approved after 1990               Probability
                                         of death by
                                         end of 2002
Other characteristics
• age
• sex
• region
• utilization Jan-June 2000
      • no. of MD visits
                                     540,000 people
      • no. of Rx’s
                                     12.2 million claims
      • no. of hospital admissions
• nature of person’s illnesses


                                                           32
                    Data
• All medical and pharmacy claims of
  Medicaid beneficiaries during the period
  January 1-June 30, 2000
  – Almost 800,000 people; 540,000 had pharmacy
    claims
  – About 12.2 million claims
• List of all residents who died during the
  period 2000-2002.
                                              33
                               Mortality rate declines as
                                drug vintage increases
                        5.0%
                                 4.4%
                        4.5%
3-year mortality rate




                        4.0%               3.6%
                        3.5%                             3.0%
                        3.0%                                    2.5%
                        2.5%
                        2.0%
                        1.5%
                        1.0%
                        0.5%
                        0.0%
                                pre 1970   1970s        1980s   1990s
                                              Drug vintage


                                                                        34
             Actual vs. hypothetical
                 mortality rates
5.0%           4.4%
4.5%
4.0%                           3.7%
                                               3.5%
3.5%
3.0%
2.5%
2.0%
1.5%
1.0%
0.5%
0.0%
       If all drugs pre-1970   Actual     If same vintage
                                        distribution as U.S.
                                         Medicaid in 2000

                                                               35
        Analysis by disease group
25.0%

                                     pre 1970                     20.1%
20.0%
                                     1970s                            16.7%
                                     1980s
15.0%                                                                     13.1%
                                                                               14.0%
                                     1990s
        10.9%

10.0%
                7.8%                  7.6%
                       7.0%
                              5.6%           6.0%
                                                    5.1%
5.0%                                                       4.0%



0.0%
        Circulatory system           Endocrine/metabolic              Neoplasms


                                                                                       36
 The Economics of Invention
Incentives: Patents, Prizes, and
     Research Contracts
        Brian D. Wright
  American Economic Review 73,
       1983, pp. 691-707.
  How should the government
 support biomedical research?
Alternative mechanisms:
• Government labs
• Research grants and contracts
• Regulation (e.g. Orphan Drug Act)
• Antitrust law (Joint ventures)
• Patent law
• Prizes & purchase commitments


                                      38
      Simple model of research
• Large number of firms, each of which can
  undertake one research project
• Each research firm can conduct one research study
  at a cost of c = $1
• The more firms actively searching for a particular
  invention, the higher the probability that at least
  one of them will discover it. The probability of
  success is an increasing function of n

                                                    39
                 Optimal number of firms


$30.00

$25.00

$20.00

$15.00

$10.00                                   Expected social benefit
 $5.00                                   Social cost
 $0.00
         1   6           11              16            21
                          No. of firms
                                                                   40
                    Optimal number of firms

$5.00
$4.50
$4.00                        Expected marginal social benefit
$3.50
$3.00                        Marginal social cost
$2.50
$2.00
$1.50
$1.00
$0.50
$0.00
        1

            3

                5

                     7

                         9

                               11

                                     13

                                           15

                                                    17

                                                         19

                                                              21

                                                                   23

                                                                        25
                                                                        41
         Research contracts
 If government can determine the optimal
number of contracts (n), and firms engage in
energetic research even though payments are
independent of success, govt. should offer
research contracts to the n lowest bidders;
competition drives price down to cost


                                               42
          Government prizes
• Even if there is no patent protection, a large
  enough prize can induce research
• If the government sets the prize properly,
  the optimal number of firms race to win it
• A higher prize stimulates excessive research
• A prize equal to the social value of the
  innovation may be too high—it induces
  excessive innovation
                                               43
   Government uncertainty
When the government has full information,
 patents and joint ventures are less
 desirable than prizes or research
 contracts because they distort pricing
However, if inventors have more
 information before they start inventing
 than do government officials, patents
 and joint ventures may be superior
                                        44
                     Patents
• Because patents lead to distortions due to
  monopoly pricing, they are less efficient than
  optimal prizes or research contracts if the
  government has sufficient information to induce
  the optimal amount of research
• Permanent patent may lead to excessive research
• By having patents last shorter periods of time, the
  government can reduce the incentive for excessive
  research

                                                    45
                     Patents
• Tradeoff: the longer the patent, the greater the
  inducement of research (and the probability of
  success), but the larger the cost due to more
  research projects and the monopoly loss
• Government should choose patent length to
  maximize expected net social benefit
• Because of the distortions associated with patents,
  society may want fewer projects than it would
  with prizes or research contracts

                                                    46
Public policy towards innovation
• In reality, the government cannot directly control
  the number of projects
• But the government can influence the number of
  projects by establishing a system of intellectual
  property rights (e.g. patents), which affect firms’
  incentives to invest in R&D
• Designing an optimal patent system is a
  challenging task, however. A patent system could
  lead to either too little or too much R&D
  investment.
                                                    47
      Patents: benefits and risks
• In the absence of patents, there may be inadequate
  investment in R&D, since firms attempt to ―free
  ride‖ on other firms’ investments
• Patents can solve the problem of under-
  investment.
• However, since patents create a ―winner-take-all‖
  competition, patents can cause over-investment.
• Other aspects of patents
   – Prices
   – Disclosure of invention
   – Sequential innovation
                                                   48

								
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