Tsiatis Anastasios A, Davidian Marie
Department of Statistics, North Carolina State University, Raleigh, NC 27695-8203, United States.
Biometrics. 2024 Oct 3;80(4). doi: 10.1093/biomtc/ujae139.
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.
序贯多重分配随机试验（SMART）是评估多阶段治疗方案的理想研究设计，多阶段治疗方案包含序贯决策规则，这些规则根据患者不断变化的特征，在一系列决策点的每一点为患者推荐治疗方法。一个常见的目标是根据感兴趣的主要结局，比较设计中所代表的一组所谓的嵌入式方案。在慢性病和疾病的研究中，这个结局通常是到事件发生的时间，目标是比较该组中与每个方案相关的事件发生时间结局的分布。我们提出了一个通用的统计框架，在这个框架中，我们基于来自具有任意阶段数的SMART的数据，开发了一种对数秩检验类型，用于比较指定集合内各方案相关的生存分布，该框架允许纳入协变量信息以提高效率，并且也可用于观察性研究的数据。该框架阐明了产生有原则的检验程序所需的假设，并且所提出的检验包含或提供了对现有方法的改进替代方法。我们在一组模拟研究中展示了这些方法的性能。这些方法应用于急性早幼粒细胞白血病患者的SMART。
