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Are Increasing 5-Year Survival Rates Evidence of Success Against Cancer? A Reexamination Using Data from the U.S. and Australia

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  • Lichtenberg Frank R.

    (Columbia University)

Abstract

Previous 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. The purpose of this study was to reexamine the question of whether increasing 5-year survival rates constitute evidence of success against cancer. We estimate the relationship across cancer sites between long-run changes in population-based mortality rates and both (1) changes in 5-year relative survival rates, and (2) changes in incidence rates, using data from both the U.S. and Australia. We analyze two outcome measures, and the relationship between them: the unconditional mortality rate (number of deaths per 100,000 population), and the 5-year relative survival rate. When incidence growth is controlled for, there is a highly significant correlation, in both the U.S. and Australia, 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.

Suggested Citation

  • 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.
    • Handle: RePEc:bpj:fhecpo:v:13:y:2010:i:2:n:11
    DOI: 10.2202/1558-9544.1202
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    1. Frank Lichtenberg, 2009. "The effect of new cancer drug approvals on the life expectancy of American cancer patients, 1978-2004," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 18(5), pages 407-428.
    2. Frank R. Lichtenberg, 2007. "Importation And Innovation," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 16(6), pages 403-417.
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    Cited by:

    1. Kyle, Margaret & Dubois, Pierre, 2016. "The Effects of Pharmaceutical Innovation on Cancer Mortality," CEPR Discussion Papers 11487, C.E.P.R. Discussion Papers.
    2. Hostenkamp, Gisela & Lichtenberg, Frank R., 2015. "The impact of recent chemotherapy innovation on the longevity of myeloma patients: US and international evidence," Social Science & Medicine, Elsevier, vol. 130(C), pages 162-171.
    3. Frank R. Lichtenberg & Billie Pettersson, 2014. "The impact of pharmaceutical innovation on longevity and medical expenditure in Sweden, 1997-2010: evidence from longitudinal, disease-level data," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 23(3), pages 239-273, April.
    4. G. F. Ho & N. A. Taib & R. K. Pritam Singh & C. H. Yip & M. M. Abdullah & T. O. Lim, 2017. "What If All Patients with Breast Cancer in Malaysia Have Access to the Best Available Care: How Many Deaths Are Avoidable?," Global Journal of Health Science, Canadian Center of Science and Education, vol. 9(8), pages 1-32, August.
    5. Dubois, Pierre & Kyle, Margaret, 2016. "The Effects of Pharmaceutical Innovation on Cancer Mortality Rates," TSE Working Papers 16-688, Toulouse School of Economics (TSE).

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    More about this item

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity

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