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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 class models 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. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This study aimed to add to prospective data on the possible inverse association between coffee consumption and endometrial cancer risk, already supported by several case-control studies. Coffee and tea consumption and possible confounding factors were assessed among 42,270 women aged 30-49 years at enrollment in 1991-1992 in the Swedish Women's Lifestyle and Health cohort study, with complete follow-up through 2009. We calculated caffeine intake per day; Cox proportional hazard models were used to estimate multivariable relative risks (mRR) for endometrial cancer with 95% confidence intervals (CIs). One hundred forty-four endometrial cancers were diagnosed during follow-up. Women with and without endometrial cancer had a similar mean daily coffee consumption (549 vs. 547 g), tea consumption (104 vs. 115 g), and caffeine intake (405 vs. 406 mg). Compared to those consuming <2 cups of coffee per day, women consuming >3 cups had a mRR of 1.56 (95% CI: 0.94-2.59; P for trend = 0.17). Compared with the lowest tertile of caffeine intake, the highest tertile had a mRR of 1.32 (95% CI: 0.87-1.99; P for trend = 0.27). Our study provides no convincing evidence of an association between coffee consumption, tea consumption, or caffeine intake and endometrial cancer risk among middle-aged women.