Understanding Differences in Cancer Survival between Populations: A New Approach and Application to Breast Cancer Survival Differentials between Danish Regions

Marie-Pier Bergeron-Boucher, Jim Oeppen, Niels Vilstrup Holm, Hanne Melgaard Nielsen, Rune Lindahl-Jacobsen and Maarten Jan Wensink
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Marie-Pier Bergeron-Boucher: Interdisciplinary Center on Population Dynamics, University of Southern Denmark, J.B Winsløws Vej 9B, 5000 Odense C, Denmark
Jim Oeppen: Interdisciplinary Center on Population Dynamics, University of Southern Denmark, J.B Winsløws Vej 9B, 5000 Odense C, Denmark
Niels Vilstrup Holm: Department of Oncology, Odense University Hospital, J.B Winsløws Vej 4, 5000 Odense C, Denmark
Hanne Melgaard Nielsen: Department of Oncology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200 Aarhus N, Denmark
Rune Lindahl-Jacobsen: Interdisciplinary Center on Population Dynamics, University of Southern Denmark, J.B Winsløws Vej 9B, 5000 Odense C, Denmark
Maarten Jan Wensink: Interdisciplinary Center on Population Dynamics, University of Southern Denmark, J.B Winsløws Vej 9B, 5000 Odense C, Denmark

IJERPH, 2019, vol. 16, issue 17, 1-16

Abstract: Large variations in cancer survival have been recorded between populations, e.g., between countries or between regions in a country. To understand the determinants of cancer survival differentials between populations, researchers have often applied regression analysis. We here propose the use of a non-parametric decomposition method to quantify the exact contribution of specific components to the absolute difference in cancer survival between two populations. Survival differences are here decomposed into the contributions of differences in stage at diagnosis, population age structure, and stage-and-age-specific survival. We demonstrate the method with the example of differences in one-year and five-year breast cancer survival between Denmark’s five regions. Differences in stage at diagnosis explained 45% and 27%, respectively, of the one- and five-year survival differences between Zealand and Central Denmark for patients diagnosed between 2008 and 2010. We find that the introduced decomposition method provides a powerful complementary analysis and has several advantages compared with regression models: No structural or distributional assumptions are required; aggregated data can be used; and the use of absolute differences allows quantification of the survival that could be gained by improving, for example, stage at diagnosis relative to a reference population, thus feeding directly into health policy evaluation.

Keywords: breast cancer; decomposition; stage at diagnosis; Denmark; regions; survival (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
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