title: Sensitivity Analysis of Per-Protocol Time-to-Event Treatment Efficacy in Randomized Clinical Trials.
abstract: Assessing per-protocol treatment effcacy on a time-to-event endpoint is a common objective of randomized clinical trials. The typical analysis uses the same method employed for the intention-to-treat analysis (e.g., standard survival analysis) applied to the subgroup meeting protocol adherence criteria. However, due to potential post-randomization selection bias, this analysis may mislead about treatment efficacy. Moreover, while there is extensive literature on methods for assessing causal treatment effects in compliers, these methods do not apply to a common class of trials where a) the primary objective compares survival curves, b) it is inconceivable to assign participants to be adherent and event-free before adherence is measured, and c) the exclusion restriction assumption fails to hold. HIV vaccine efficacy trials including the recent RV144 trial exemplify this class, because many primary endpoints (e.g., HIV infections) occur before adherence is measured, and nonadherent subjects who receive some of the planned immunizations may be partially protected. Therefore, we develop methods for assessing per-protocol treatment efficacy for this problem class, considering three causal estimands of interest. Because these estimands are not identifiable from the observable data, we develop nonparametric bounds and semiparametric sensitivity analysis methods that yield estimated ignorance and uncertainty intervals. The methods are applied to RV144.
authors.affiliation: Department of Biostatistics, University of Washington and Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, 98109, U.S.A.
authors.forename: Peter B
authors.initials: PB
authors.lastname: Gilbert
authors.forename: Bryan E
authors.initials: BE
authors.lastname: Shepherd
authors.forename: Michael G
authors.initials: MG
authors.lastname: Hudgens
keywords: As-treated; Bounds; Causal inference; Exclusion restriction; Ignorance region; Intention to treat; Principal stratification; Selection bias; Survival analysis