Estimation of Relative and Absolute Risk in a Competing-Risk Setting Using a Nested Case-Control Study Design: Example From the ProMort Study

We describe the Prognostic factors for Mortality in prostate cancer (ProMort) study, and use it to demonstrate how weighted likelihood method can be used in nested case-control studies to estimate both relative and absolute risks in the competing-risks setting. ProMort is a case-control study nested in the National Prostate Cancer Register (NPCR) of Sweden, comprising 1,710 men diagnosed with low- or intermediate-risk prostate cancer between 1998 and 2011 who died from prostate cancer (cases) and 1,710 matched controls. Cause-specific hazard ratios (HR) and cumulative incidence (CIF) of prostate cancer death were estimated in ProMort using weighted flexible parametric models and compared with the corresponding estimates from the NPCR cohort. We further draw 1,500 random nested case-control subsamples of NPCR and quantified the bias in the HR and CIF estimates. Finally, we compared the ProMort estimates with those obtained by augmenting competing risks cases, and by augmenting both competing risk cases and controls. The HRs of prostate cancer death estimated in ProMort were comparable to those in NPCR. The HRs of dying from other causes were biased, which introduced bias in the CIFs estimated in the competing risks setting. When augmenting both competing risk cases and controls, the bias was reduced.