Competing Risks in Clinical Trials: Do They Matter and How Should We Account for Them?

During patient follow-up in a randomized trial, some deaths may occur. Where death (or noncardiovascular death) is not part of an outcome of interest it is termed a competing risk. Conventional analyses (eg, Cox proportional hazards model) handle death similarly to other censored follow-up. Patients still alive are unrealistically assumed to be representative of those who died. The Fine and Gray model has been used to handle competing risks, but is often used inappropriately and can be misleading. We propose an alternative multiple imputation approach that plausibly accounts for the fact that patients who die tend also to be at high risk for the (unobserved) outcome of interest. This provides a logical framework for exploring the impact of a competing risk, recognizing that there is no unique solution. We illustrate these issues in 3 cardiovascular trials and in simulation studies. We conclude with practical recommendations for handling competing risks in future trials. • In CV trials where competing events are rare or well balanced between groups, they are unlikely to cause major problems. • The Fine and Gray model (although useful in certain specific circumstances) is usually best avoided because it is often used inappropriately and can be misleading. • Where sensitivity analyses for competing risks are warranted, a multiple imputation approach is recommended. • There is no single right answer to the competing risk problem; one needs to seek a consistency of conclusions across a range of assumptions. [ABSTRACT FROM AUTHOR]