Evaluation of Treatment Effect On Gap Time Using Principal Stratification

Introduction:  Times of sequential event are observed in some clinical trials, and the time from the first to the second event is the gap time. In a randomized control trial of smoking cessation treatments, 943 smokers with military-related post-traumatic stress disorder (PTSD0 were randomized to smoking cessation treatment integrated with mental health care (integrated care; IC) or the usual care of referral to smoking cessation clinics (SCC), and they were followed up for 18 to 48 months (McFall et al. 2010). We are interested in estimating the causal effect of the IC on time to quitting smoking, and then the causal effect of the IC on the gap time of quitting to relapse, compared to the SCC. The treatment effect on relapse suffers from informative censoring and selection bias due to its conditional nature on the occurrence of quitting. Methods: We utilize a principal stratification framework (Frangakis & Rubin 1999, 2002) that precludes the confounding when stratifying on observed post-randomization behavior (i.e., observed quitting). Results: ITT analyses suggest that participants in IC are more likely to quit than participants in SCC; furthermore, participants in IC are less likely to relapse though the differences not significantly different between the treatment groups. Analyses in principal stratification framework suggest no difference in quitting between IC and SCC groups – majority of veterans in the study would have quit under either IC or SCC. However, fewer veterans with severe PTSD are likely to be more successful in quitting smoking on SCC than IC. Among those who would have quit under either treatment groups, there is no difference in time-to-relapse. Conclusion: ITT analyses showed favorable quitting results toward IC than SCC but principal stratification analyses showed no difference in quitting between the treatment groups. It may be important to identify covariates related to responsiveness to IC or SCC to personalize treatment to patients and maximize treatment outcomes.