Weighing risks and benefits in the presence of competing risks.

When competing events occur, there are two main options for handling them analytically that invoke different assumptions: 1) censor person-time after a competing event (which is akin to assuming they could be prevented) to calculate a conditional risk; or 2) do not censor them (allow them to occur) to calculate an unconditional risk. The choice of estimand has implications when weighing the relative frequency of a beneficial outcome and an adverse outcome in a risk-benefit analysis. We review the assumptions and interpretations underlying the two main approaches to analyzing competing risks. Using a popular metric in risk-benefit analyses, the Benefit-Risk Ratio, and a toy dataset, we demonstrated that conclusions about whether a treatment was more beneficial or more harmful can depend on whether one uses conditional or unconditional risks. We argue that unconditional risks are more relevant to decision-making about exposures with competing outcomes than conditional risks.

Déclaration de conflit d'intérêts

Dr. Zalla reports grants from NIH during the conduct of the study, other grants from Viiv Healthcare, and personal fees from Carelon, outside the submitted work. Mr. Joseph reports personal fees from Takeda Pharmaceuticals, outside the submitted work. Other authors have no conflicts of interest to report.