Are Increasing 5-Year Survival Rates Evidence of Success Against Cancer? A reexamination using data from the U.S. and Australia
AbstractPrevious investigators argued that increasing 5-year survival for cancer patients should not be taken as evidence of improved prevention, screening, or therapy, because they found little correlation between the change in 5-year survival for a specific tumor and the change in tumor-related mortality. However, they did not control for the change in incidence, which influences mortality and is correlated with 5-year survival. We reexamine the question of whether increasing 5-year survival rates constitute evidence of success against cancer, using data from both the U.S. and Australia. When incidence growth is controlled for, there is a highly significant correlation, in both countries, between the change in 5-year survival for a specific tumor and the change in tumor-related mortality. The increase in the relative survival rate is estimated to have reduced the unconditional mortality rate by about 15% in the U.S. between 1976 and 2002, and by about 15% in Australia between 1984 and 2001. While the change in the 5-year survival rate is not a perfect measure of progress against cancer, in part because it is potentially subject to lead-time bias, it does contain useful information; its critics may have been unduly harsh. Part of the long-run increase in 5-year cancer survival rates is due to improved prevention, screening, or therapy.
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Bibliographic InfoPaper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 16051.
Date of creation: Jun 2010
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Publication status: published as Frank R. Lichtenberg, 2010. "Are Increasing 5-Year Survival Rates Evidence of Success Against Cancer? A Reexamination Using Data from the U.S. and Australia," Forum for Health Economics & Policy, Berkeley Electronic Press, vol. 13(2).
Note: AG EFG HC HE PR
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- Lichtenberg Frank R., 2010. "Are Increasing 5-Year Survival Rates Evidence of Success Against Cancer? A Reexamination Using Data from the U.S. and Australia," Forum for Health Economics & Policy, De Gruyter, vol. 13(2), pages 1-18, August.
- C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
- I12 - Health, Education, and Welfare - - Health - - - Health Production
- J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
- O4 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity
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