Clinical trials often allow patients in the control arm to switch to the treatment arm if their physical conditions are worse than certain tolerance levels. For instance, treatment switching arises in the Concorde clinical trial, which aims to assess causal effects on the time-to-disease progression or death of immediate versus deferred treatment with zidovudine among patients with asymptomatic HIV infection. The Intention-To-Treat analysis does not measure the effect of the actual receipt of the treatment and ignores the information on treatment switching. Other existing methods reconstruct the outcome a patient would have had if they had not switched under strong assumptions. Departing from the literature, we re-define the problem of treatment switching using principal stratification and focus on causal effects for patients belonging to subpopulations defined by the switching behavior under control. We use a Bayesian approach to inference, taking into account that (i) switching happens in continuous time; (ii) switching time is not defined for patients who never switch in a particular experiment; and (iii) survival time and switching time are subject to censoring. We apply this framework to analyze synthetic data based on the Concorde study. Our data analysis reveals that immediate treatment with zidovudine increases survival time for never switcher and that treatment effects are highly heterogeneous across different types of patients defined by the switching behavior.

翻译：临床试验通常允许对照组患者在身体状况恶化至超过特定耐受水平时，切换至治疗组。例如，康科德临床试验中即出现了治疗切换现象——该试验旨在评估无症状HIV感染者立即使用齐多夫定治疗与延迟治疗对疾病进展时间或死亡时间的因果效应。意向性治疗分析无法衡量实际接受治疗的效果，且忽略了治疗切换的相关信息。其他现有方法在强假设下重构了患者若未切换治疗时的预后结局。与现有文献不同，我们采用主分层重新定义治疗切换问题，并聚焦于由对照组中切换行为定义的亚群患者的因果效应。我们采用贝叶斯方法进行推断，考虑以下三点：（i）切换发生在连续时间维度；（ii）在特定实验中从未发生切换的患者，其切换时间未定义；（iii）生存时间与切换时间均存在删失。我们应用该框架分析基于康科德研究生成的合成数据。数据分析表明，对从未切换者而言，立即使用齐多夫定治疗可延长生存时间，且不同切换行为定义的患者类型间治疗效果存在高度异质性。