Long-term net survival among women diagnosed with cancer: accuracy of its estimation and evaluation of its determinants.

Schaffar, R; (2018) Long-term net survival among women diagnosed with cancer: accuracy of its estimation and evaluation of its determinants. PhD (research paper style) thesis, London School of Hygiene & Tropical Medicine. DOI: https://doi.org/10.17037/PUBS.04648206

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Breast cancer is a major public health challenge. It affects a very large numbers of women across the globe. Although improvements in its management have dramatically transformed its prognosis at diagnosis, breast cancer remains associated with an increased long-term risk of death, persisting even decades after diagnosis. A comprehensive understanding of this underlying pattern of death from breast cancer in the long-term is currently lacking but increasingly important as the number of long-term survivors rises. The reliability of the cause of death is of particular interest in this context. In this thesis, I use data from the Geneva Cancer Registry to first, determine the best methodology for examining long-term net survival, and second, to evaluate its determinants. Two data settings are available for the estimation of net survival: the cause-specific setting, where the cause of death is required, and the relative-survival setting, where it is not. I first evaluated the accuracy of routinely collected cause of death information and the impact of inaccuracies upon survival estimates. I observed small but non-negligible advantages in using a reviewed cause of death when estimating survival. I then compared the cause-specific to the relative survival setting for the estimation of long-term net survival and demonstrated that the relative-survival setting was less sensitive to violations of the assumptions both for breast cancer patients as well as for patients diagnosed with cancer at three other localisations. I further investigated the long-term effects of key prognostic factors and treatment for women with breast cancer in the relative survival setting using an appropriate strategy for model selection. Although I demonstrated insightful non-linear and time-dependent effects for some prognostic variables, the analyses were limited by issues of convergence and misspecification of the model. High quality population-based data and additional statistical tools are required to understand with greater certainty the determinants of breast cancer long-term excess mortality.

Item Type: Thesis
Thesis Type: Doctoral
Thesis Name: PhD (research paper style)
Contributors: Woods, Lm (Thesis advisor); Rachet, B (Thesis advisor);
Faculty and Department: Faculty of Epidemiology and Population Health > Dept of Non-Communicable Disease Epidemiology
Funders: Swiss Cancer League, Geneva Cancer Registry
Grant number: BIL KFS-3274-08-2013
Copyright Holders: Robin Schaffar
URI: http://researchonline.lshtm.ac.uk/id/eprint/4648206


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