Comparison Between Two Controlled Multiple Imputation Methods for Sensitivity Analyses of Time-to-Event Data with Possibly Informative Censoring

• Activity Number: 192
• Type: Contributed
• Date/Time: Monday, August 10, 2015 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Kaifeng Lu* and Dayong Li and Gary Koch
• Companies: and Actavis and The University of North Carolina at Chapel Hill
• Keywords: Cox model ; Informative censoring ; Piecewise exponential ; Repeated sampling

Abstract

Controlled imputation methods provide general and flexible sensitivity analyses to address nonignorable missing data. For time-to-event data with possibly informative censoring, we compare two popular methods for imputing the censored event time conditional on the time of follow-up discontinuation. One is the delta-adjusted method which specifies that the hazard of having an event for subjects who discontinued before the time point is increased relative to the hazard for subjects who continued beyond the time point. The other is the reference-based method which specifies that the hazard for experimental treatment subjects who discontinued lies between the hazard for such subjects who continued and the hazard for the reference control (e.g., placebo subjects). We show that both the reference-based and delta-adjusted sensitivity analyses control the one-sided type I error rate (in the direction of a difference favoring the experimental treatment). In addition, the reference-based sensitivity analysis has more power than the delta-adjusted sensitivity analysis for the same underlying treatment effect when the bootstrap variance is used for inference.