Heterogeneity in risk of prostate cancer: A Swedish population‐based cohort study of competing risks and Type 2 diabetes mellitus |
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| Authors: | Christel Häggström Mieke Van Hemelrijck Hans Garmo David Robinson Pär Stattin Mark Rowley Anthony C.C. Coolen Lars Holmberg |
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| Affiliation: | 1. Department of Surgical Sciences, Uppsala University, Uppsala, Sweden;2. Department of Biobank Research, Ume? University, Ume?, Sweden;3. King's College London, School of Cancer and Pharmaceutical Sciences, Translational Oncology & Urology Research (TOUR), London, United Kingdom;4. Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden;5. Regional Cancer Centre Uppsala/?rebro, Uppsala, Sweden;6. Department of Urology, Ryhov Hospital, J?nk?ping, Sweden;7. Institute for Mathematical and Molecular Biomedicine, King's College London, London, United Kingdom;8. Saddle Point Science, London, United Kingdom |
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| Abstract: | 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 our 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. |
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| Keywords: | survival analysis competing risks latent class prostate cancer Type 2 diabetes mellitus |
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