Survival analyses are commonly applied to study death or other events of interest. In such analyses, so-called competing risks may form an important problem. A competing risk is an event that either hinders the observation of the event of interest or modifies the chance that this event occurs. For example, when studying death on dialysis, receiving a kidney transplant is an event that competes with the event of interest. Conventional methods for survival analysis ignoring the competing event(s), such as the Kaplan–Meier method and standard Cox proportional hazards regression, may be inappropriate in the presence of competing risks, and alternative methods specifically designed for analysing competing risks data should then be applied. This problem deserves more attention in nephrology research and in the current article, we therefore explain the problem of competing risks in survival analysis and how using different techniques may affect study results.

Although primarily recommended for improving bone health, treatment with vitamin D recently has been suggested for other conditions, including cardiovascular disease (CVD).^1-3 Multiple lines of evidence suggest a link between vitamin D and CVD, including experimental studies identifying vitamin D receptors in vascular smooth muscle, endothelial cells, and possibly cardiac tissue^1,4 and observational studies, small clinical trials, and meta-analyses suggesting that vitamin D therapy reduces cardiovascular events.^2,3 Convincing data demonstrating that vitamin D therapy improves cardiovascular health, however, are lacking.