Safety analysis of new medications in clinical trials: a simulation study to assess the differences between cause-specific and subdistribution frameworks in the presence of competing events.

Safety is an essential part of the evaluation of new medications and competing risks that occur in most clinical trials are a well identified challenge in the analysis of adverse events. Two statistical frameworks exist to consider competing risks: the cause-specific and the subdistribution framework. To date, the application of the cause-specific framework is the standard practice in safety analyses. Here we analyze how the safety analysis results of new medications would be affected if instead of the cause-specific the subdistribution framework was chosen. We conducted a simulation study with 600 participants, equally allocated to verum and control groups and a 30 months follow-up period. Simulated trials were analyzed for safety in a competing risk (death) setting using both the cause-specific and subdistribution frameworks. Results show that comparing safety profiles in a subdistribution setting is always more pessimistic than in a cause-specific setting. For the group with the longest survival and a safety advantage in a cause-specific setting, the advantage either disappeared or a disadvantage was found in the subdistribution analysis setting. These observations are not contradictory but show different perspectives. To evaluate the safety of a new medication over its comparator, one needs to understand the origin of both the risks and the benefits associated with each therapy. These requirements are best met with a cause-specific framework. The subdistribution framework seems better suited for clinical prediction, and therefore more relevant for providers or payers, for example.