A hierarchical rank test for crossover trials with censored data

We propose an approach to analyze survival time in a crossover clinical trial by performing a primary ranking on whether events occur and a secondary ranking on event times. This hierarchical ranking method is meant to reflect the idea that the goal of therapy is to prevent a clinical event and, failing that, to delay the occurrence of the event, hopefully for a substantial amount of time. We compare our approach with other methods including one method proposed by Feingold and Gillespie, a recommended procedure. The power is similar in many settings, but the hierarchical ranking can have substantially greater power under certain censoring patterns and also under a cure model, or models where treatment induces a substantial delay in some fraction of patients. We additionally feel that the hierarchical ranking method should be more clinically relevant in many settings. The method can also be applied to continuous outcomes censored by a limit of detection, such as HIV viremia.