Nonparametric group sequential methods for evaluating survival benefit from multiple short-term follow-up windows

This article takes a fresh look at group sequential methods applied to two-sample tests of censored survival data and proposes an alternative method of defining and evaluating treatment benefit. Our method re-purposes traditional censored event time data into a sequence of short-term outcomes taken from (potentially overlapping) follow-up windows. A new two-sample restricted means test based on this restructured follow-up data is proposed along with group sequential methods for its use in the clinical trial setting. This method compares favorably with existing methods for group sequential monitoring of time-to-event outcomes, including methods for monitoring the restricted means test and the logrank test. Our method performs particularly well in cases where there is a delayed treatment effect and/or a subset of cured patients. As part of developing group sequential methods for these analyses, we consider asymmetric error spending approaches that differentially limit the chances of stopping incorrectly for perceived efficacy versus perceived harm attributed to the investigational arm of the trial. Recommendations for how to choose proper group sequential stopping boundaries are given, with supporting simulations and an example from the AIDS Clinical Trial Group.