通过主分层评估存在治疗转换时的因果效应
Assessing causal effects in the presence of treatment switching through principal stratification
AI总结：
该研究通过主分层重新定义治疗转换问题，采用贝叶斯方法处理连续时间转换与删失，分析Concorde合成数据，发现立即使用齐多夫定增加从未转换者生存时间且效果异质性高。
摘要：
临床试验通常允许对照组患者在身体状况恶化到超过一定耐受水平时转换到治疗组。例如，在Concorde临床试验中出现了治疗转换，该试验旨在评估无症状HIV感染者中立即使用齐多夫定与延迟使用齐多夫定对疾病进展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，并且忽略了治疗转换的信息。其他现有方法在强假设下重构了患者如果未转换本应出现的结果。与现有文献不同，我们使用主分层重新定义了治疗转换问题，并关注由对照组中转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，同时考虑到：（i）转换发生在连续时间中；（ii）在特定试验中从未转换的患者没有定义转换时间；（iii）生存时间和转换时间都受到删失的影响。我们将该框架应用于基于Concorde研究生成的合成数据分析。我们的数据分析揭示，立即使用齐多夫定治疗增加了从未转换者的生存时间，并且治疗效果在不同类型的患者（由转换行为定义）之间存在高度异质性。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
