Blinded sample size reestimation in event-driven clinical trials: Methods and an application in multiple sclerosis.

Abstract

Motivated by a recently completed trial in secondary progressive multiple sclerosis, we developed blinded sample size reestimation procedures for clinical trials with time‐to‐event endpoint and assessed their properties in simulation studies. Assuming independent right‐censoring and proportional hazards for the two treatment groups, we considered event‐driven designs with fixed number of events, which guarantees the power to be at a desired level under a certain alternative. We develop reestimation procedures based on parametric models and show that these maintain the expected duration of the trial at a target length in flexible follow‐up designs across a range of nuisance parameter values by adjusting the number of patients recruited into the trial based on blinded nuisance parameter estimates. Furthermore, we provide convincing evidence from a simulation study that such procedures proposed do not inflate the type I error rate in any practically relevant way, thereby satisfying the standards set by relevant international guidelines. Inspired by practical application of these procedures, we outline a number of extensions including methods for extrapolating the observed survival curve beyond the interim time point, application of reestimation procedures to interval censored data, and situations in which a confirmation of event is required leading to a certain lag time.