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A latent class model for competing risks
Kings Coll London, Inst Math & Mol Biomed, Hodgkin Bldg, London SE1 1UL, England.;Saddle Point Sci, London, England..
Kings Coll London, Guys Hosp, Canc Epidemiol Grp, London, England..
Kings Coll London, Guys Hosp, Canc Epidemiol Grp, London, England..
Kings Coll London, Guys Hosp, Canc Epidemiol Grp, London, England..
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2017 (English)In: Statistics in Medicine, ISSN 0277-6715, E-ISSN 1097-0258, Vol. 36, no 13, p. 2100-2119Article in journal (Refereed) Published
Abstract [en]

Survival data analysis becomes complex when the proportional hazards assumption is violated at population level or when crude hazard rates are no longer estimators of marginal ones. We develop a Bayesian survival analysis method to deal with these situations, on the basis of assuming that the complexities are induced by latent cohort or disease heterogeneity that is not captured by covariates and that proportional hazards hold at the level of individuals. This leads to a description from which risk-specific marginal hazard rates and survival functions are fully accessible, 'decontaminated' of the effects of informative censoring, and which includes Cox, random effects and latent classmodels as special cases. Simulated data confirm that our approach can map a cohort's substructure and remove heterogeneity-induced informative censoring effects. Application to data from the Uppsala Longitudinal Study of Adult Men cohort leads to plausible alternative explanations for previous counter-intuitive inferences on prostate cancer. The importance of managing cardiovascular disease as a comorbidity in women diagnosed with breast cancer is suggested on application to data from the Swedish Apolipoprotein Mortality Risk Study.

Place, publisher, year, edition, pages
2017. Vol. 36, no 13, p. 2100-2119
Keywords [en]
survival analysis, heterogeneity, informative censoring, competing risks
National Category
Occupational Health and Environmental Health Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:uu:diva-327367DOI: 10.1002/sim.7246ISI: 000402797900007PubMedID: 28233395OAI: oai:DiVA.org:uu-327367DiVA, id: diva2:1133395
Funder
EU, FP7, Seventh Framework ProgrammeAvailable from: 2017-08-15 Created: 2017-08-15 Last updated: 2018-01-13Bibliographically approved

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Grundmark, BirgittaZethelius, Björn

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