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International Journal of Health Economics and Management
Published in: International Journal of Health Economics and Management 3/2015

Open Access 01-09-2015 | Research Article

The impact of pharmaceutical innovation on premature cancer mortality in Canada, 2000–2011

Author: Frank R. Lichtenberg

Published in: International Journal of Health Economics and Management | Issue 3/2015

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Abstract

The premature cancer mortality rate has been declining in Canada, but there has been considerable variation in the rate of decline across cancer sites. I analyze the effect that pharmaceutical innovation had on premature cancer mortality in Canada during the period 2000–2011, by investigating whether the cancer sites that experienced more pharmaceutical innovation had larger declines in the premature mortality rate, controlling for changes in the incidence rate. Premature mortality before age 75 is significantly inversely related to the cumulative number of drugs registered at least 10 years earlier. Since mean utilization of drugs that have been marketed for less than 10 years is only one-sixth as great as mean utilization of drugs that have been marketed for at least a decade, it is not surprising that premature mortality is strongly inversely related only to the cumulative number of drugs that had been registered at least ten years earlier. Premature mortality before age 65 and 55 is also strongly inversely related to the cumulative number of drugs that had been registered at least ten years earlier. None of the estimates of the effect of incidence on mortality are statistically significant. Controlling for the cumulative number of drugs, the cumulative number of chemical subgroups does not have a statistically significant effect on premature mortality. This suggests that drugs (chemical substances) within the same class (chemical subgroup) are not therapeutically equivalent. During the period 2000–2011, the premature (before age 75) cancer mortality rate declined by about 9 %. The estimates imply that, in the absence of pharmaceutical innovation during the period 1985–1996, the premature cancer mortality rate would have increased about 12 % during the period 2000–2011. A substantial decline in the “competing risk” of death from cardiovascular disease could account for this. The estimates imply that pharmaceutical innovation during the period 1985–1996 reduced the number of years of potential life lost to cancer before age 75 in 2011 by 105,366. The cost per life-year before age 75 gained from previous pharmaceutical innovation is estimated to have been 2730 USD. Most of the previously-registered drugs were off-patent by 2011, but evidence suggests that, even if these drugs had been sold at branded rather than generic prices, the cost per life-year gained would have been below 11,000 USD, a figure well below even the lowest estimates of the value of a life-year gained. The largest reductions in premature mortality occur at least a decade after drugs are registered, when their utilization increases significantly. This suggests that, if Canada is to obtain substantial additional reductions in premature cancer mortality in the future (a decade or more from now) at a modest cost, pharmaceutical innovation (registration of new drugs) is needed today.
Appendix
Available only for authorised users
Footnotes
1
Lichtenberg (2014b) analyzed the impact of pharmaceutical innovation and other types of medical innovation on cancer mortality in the U.S. during the period 2000–2009. But as the Squires (2011) demonstrated, the U.S. health care system differs dramatically from the health care systems of other OECD countries, including Canada. For example, in 2008 per capita spending on health was 85 % higher in the U.S. than it was in Canada. Also, the outcome measure and the measure of pharmaceutical innovation used in the present study will differ from those used in Lichtenberg (2014b).
 
2
I use the sample period 2000–2011 to avoid potential discontinuities in the mortality data, because Canada used the ICD9 cause-of-death classification during 1979–1999, and the ICD10 cause-of-death classification during 2000–2011.
 
3
The 15 cancer sites are the 15 malignant neoplasm ICD-10 blocks defined by the World Health Organization.
 
4
Jalan and Ravallion (2001) argued that “aggregation to village level may well reduce measurement error or household-specific selection bias” (p. 10).
 
5
Survival time for cancer patients is usually measured from the day the cancer is diagnosed until the day they die. Patients are often diagnosed after they have signs and symptoms of cancer. If a screening test leads to a diagnosis before a patient has any symptoms, the patient’s survival time is increased because the date of diagnosis is earlier. This increase in survival time makes it seem as though screened patients are living longer when that may not be happening. This is called lead-time bias. It could be that the only reason the survival time appears to be longer is that the date of diagnosis is earlier for the screened patients. But the screened patients may die at the same time they would have without the screening test. See National Cancer Institute (2015a).
 
6
The most recent available incidence data are for the year 2010.
 
7
According to the Merriam Webster dictionary, one definition of vintage is “a period of origin or manufacture (e.g. a piano of 1845 vintage)”. http://​www.​merriam-webster.​com/​dictionary/​vintage. Robert Solow (1960) introduced the concept of vintage into economic analysis. Solow’s basic idea was that technical progress is “built into” machines and other goods and that this must be taken into account when making empirical measurements of their roles in production. This was one of the contributions to the theory of economic growth that the Royal Swedish Academy of Sciences cited when it awarded Solow the 1987 Alfred Nobel Memorial Prize in Economic Sciences (Nobelprize.org 2015).
 
8
For example, dactinomycin is used to treat C45–C49 connective and soft tissue neoplasms, C51–C58 female genital organ neoplasms, C60–C63 male genital organ neoplasms, and C64–C68 urinary organ neoplasms.
 
9
Outpatient prescription drug claims usually don’t show the indication of the drug prescribed. Claims for drugs administered by doctors and nurses (e.g. chemotherapy) often show the indication of the drug. In the US, 70 % of spending on anticancer drugs is for drugs covered under the medical benefit and infused or injected. However, t data on claims for drugs administered by doctors and nurses are not available for Canada.
 
10
A separate model is estimated for each value of k, rather than including multiple values (CUM_NCE\(_{\mathrm{i,t-1}}\), CUM_NCE\(_{\mathrm{i,t-2}}\), CUM_NCE\(_{\mathrm{i,t-3}}\),...) in a single model because CUM_NCE is highly serially correlated (by construction), which would result in extremely high multicollinearity if multiple values were included.)
 
11
The number of standard ‘dose’ units sold is determined by taking the number of counting units sold divided by the standard unit factor which is the smallest common dose of a product form as defined by IMS HEALTH. For example, for oral solid forms the standard unit factor is one tablet or capsule whereas for syrup forms the standard unit factor is one teaspoon (5 ml) and injectable forms it is one ampoule or vial. Other measures of quantity, such as the number of patients using the drug, prescriptions for the drug, or defined daily doses of the drug, are not available.
 
12
Since the dependent variable of Eq. (2) is logarithmic, observations for which SU\(_{\mathrm{my}}\) = 0 had to be excluded.
 
13
The measure of pharmaceutical innovation, CUM_NCE\(_{\mathrm{s,t-k}}\) = \(\Sigma _{\mathrm{d}}\) IND\(_{\mathrm{ds}}\) REGISTERED\(_{\mathrm{d,t-k}}\), is based on whether drug d had an indication for cancer at site s at the end of 2011. One would prefer to base the measure on whether drug d had an indication for cancer at site s at the end of year t - k. Data in the U.S. FDA’s Drugs@FDA data files indicate that about one in four new molecular entities has supplemental indications, i.e. indications approved after the drug was initially launched.
 
14
Source: Drugs@FDA Data Files.
 
15
For example, the five levels associated with the chemical subgroup “nitrogen mustard analogues” are:
L
ANTINEOPLASTIC AND IMMUNOMODULATING AGENTS
L01
ANTINEOPLASTIC AGENTS
L01A
ALKYLATING AGENTS
L01AA
Nitrogen mustard analogues
L01AA01
cyclophosphamide
L01AA02
chlorambucil
L01AA03
melphalan
L01AA05
chlormethine
L01AA06
ifosfamide
L01AA07
trofosfamide
L01AA08
prednimustine
L01AA09
bendamustine
 
16
Many drug databases contain information about drug indications, but this information is usually in text form only.
 
17
Mortality data are reported in 5-year age groups in the WHO Mortality Database. I assume that deaths in a 5-year age group occur at the midpoint of the age group. For example, I assume that deaths at age 35–39 years occurred at age 37.5. The Association of Public Health Epidemiologists in Ontario (2015) uses this method.
 
18
Complete estimates of model 4 are presented in Appendix Table 4.
 
19
According to one medical dictionary, drugs that have “essentially the same effect in the treatment of a disease or condition” are therapeutically equivalent. Drugs that are therapeutically equivalent may or may not be chemically equivalent, bioequivalent, or generically equivalent. http://​medical-dictionary.​thefreedictionar​y.​com/​therapeutic+equi​valent.
 
20
In Appendix Table 4, the point estimate of \({\updelta }_{2000}\) is \(-\)0.1157 (p value = 0.0003). If CUM_NCE\(_{\mathrm{s,t-15}}\) is excluded from the equation, the point estimate of \({\updelta }_{2000}\) is 0.0873 (p value = 0.0008).
 
21
An important possible reason why the premature cancer mortality rate would have increased in the absence of previous pharmaceutical innovation is a substantial decline in the “competing risk” of death from cardiovascular disease. See Honoré and Lleras-Muney (2006).
 
22
2010 is the most recent year for which these data are available.
 
23
Since some of these drugs are used to treat diseases other than cancer, this is probably an overestimate.
 
24
Law (2013) also argues that recent changes have moved these price ceilings lower in almost every province, to a nationwide low of 25 % in Ontario.
 
25
Twenty-eight of the reviewed articles used U.S. data; the remaining articles used data from the U.K. (4), Canada (3), France (1), and Denmark (1). National origin did not significantly affect the values.
 
26
Lichtenberg (2009) demonstrated that, although the health of cancer patients is less than perfect, the number of QALYs gained from pharmaceutical innovation could be either greater than or less than the number of life-years gained.
 
27
The U.S. Consumer Price Index increased by 40 % between 1997 and 2011.
 
Literature
Honoré, B. E., & Lleras-Muney, A. (2006). Bounds in competing risks models and the war on cancer. Econometrica, 74(6), 1675–1698.CrossRef
Lichtenberg, F. R. (2009). The effect of new cancer drug approvals on the life expectancy of American cancer patients, 1978–2004. Economics of Innovation and New Technology, 18(5), 407–428.
Lichtenberg, F. R. (2014a). The impact of pharmaceutical innovation on longevity and medical expenditure in France, 2000–2009. Economics and Human Biology, 13, 107–127.PubMedCrossRef
Lichtenberg, F. R. (2014b). Has medical innovation reduced cancer mortality? CESifo Economic Studies, 60(1), 135–177.CrossRef
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Metadata
Title
The impact of pharmaceutical innovation on premature cancer mortality in Canada, 2000–2011
Author
Frank R. Lichtenberg
Publication date
01-09-2015
Publisher
Springer US
Published in
International Journal of Health Economics and Management / Issue 3/2015
Print ISSN: 2199-9023
Electronic ISSN: 2199-9031
DOI
https://doi.org/10.1007/s10754-015-9172-2