Most previous studies of prostate cancer have not taken into account that men in the studied populations are also at risk of competing event, and that these men may have different susceptibility to prostate cancer risk. The aim of this study was to investigate heterogeneity in risk of prostate cancer, using a recently developed latent class regression method for competing risks. We further aimed to elucidate the association between type 2 diabetes mellitus (T2DM) and prostate cancer risk, and to compare the results with conventional methods for survival analysis. We analysed the risk of prostate cancer in 126,482 men from the comparison cohort of the Prostate Cancer Data base Sweden (PCBaSe) 3.0. During a mean follow-up of 6 years 6,036 men were diagnosed with prostate cancer and 22,393 men died. We detected heterogeneity in risk of prostate cancer with two distinct latent classes in the study population. The smaller class included 9% of the study population in which men had a higher risk of prostate cancer and the risk was stronger associated with class membership than any of the covariates included in the study. Moreover, we found no association between T2DM and risk of prostate cancer after removal of the effect of informative censoring due to competing risks. The recently developed latent class for competing risks method could be used to provide new insights in precision medicine with the target to classify individuals regarding different susceptibility to a particular disease, reaction to a risk factor or response to treatment. This article is protected by copyright. All rights reserved.
International journal of cancer. 2018 May 09 [Epub ahead of print]
Christel Häggström, Mieke Van Hemelrijck, Hans Garmo, David Robinson, Pär Stattin, Mark Rowley, Anthony C C Coolen, Lars Holmberg
Department of Surgical Sciences, Uppsala University, Uppsala, Sweden., King's College London, School of Cancer and Pharmaceutical Sciences, Translational Oncology & Urology Research (TOUR), London, United Kingdom., Department of Urology, Ryhov Hospital, Jönköping, Sweden., Institute for Mathematical and Molecular Biomedicine, King's College London, London, United Kingdom.