The sequential multiple assignment randomized trial (SMART) is the ideal study design for the evaluation of multistage treatment regimes, which comprise sequential decision rules that recommend treatments for a patient at each of a series of decision points based on their evolving characteristics. A common goal is to compare the set of so-called embedded regimes represented in the design on the basis of a primary outcome of interest. In the study of chronic diseases and disorders, this outcome is often a time to an event, and a goal is to compare the distributions of the time-to-event outcome associated with each regime in the set. We present a general statistical framework in which we develop a logrank-type test for comparison of the survival distributions associated with regimes within a specified set based on the data from a SMART with an arbitrary number of stages that allows incorporation of covariate information to enhance efficiency and can also be used with data from an observational study. The framework provides clarification of the assumptions required to yield a principled test procedure, and the proposed test subsumes or offers an improved alternative to existing methods. We demonstrate performance of the methods in a suite of simulation studies. The methods are applied to a SMART in patients with acute promyelocytic leukemia.

翻译：序贯多分配随机试验(SMART)是评估多阶段治疗方案的最佳研究设计，这类方案由一系列序贯决策规则组成，可根据患者不断变化的特征在每个决策节点推荐治疗策略。常见目标是在感兴趣的主要结局指标基础上，比较设计中所包含的所谓嵌入式治疗方案。在慢性疾病研究领域，该结局指标常表现为事件发生时间，核心目标是比较各治疗方案对应的事件发生时间分布。我们提出通用统计框架，开发基于任意阶段数SMART数据的对数秩检验，用于比较指定方案集合中的生存分布。该框架允许纳入协变量信息以提升效能，亦可应用于观察性研究数据。通过阐明构建严谨检验程序所需的假设条件，本检验方法既涵盖现有方法又提供改进方案。通过系列模拟研究验证方法效能，并将所提方法应用于急性早幼粒细胞白血病患者的SMART研究数据。