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

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.