Amgen Inc., 1 Amgen Center Drive, Thousand Oaks, CA 91320-1799, USA.
Department of Biostatistics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109-2029, USA.
Biostatistics. 2022 Jan 13;23(1):294-313. doi: 10.1093/biostatistics/kxaa025.
A dynamic treatment regimen (DTR) is a sequence of decision rules that can alter treatments or doses based on outcomes from prior treatment. In the case of two lines of treatment, a DTR specifies first-line treatment, and second-line treatment for responders and treatment for non-responders to the first-line treatment. A sequential, multiple assignment, randomized trial (SMART) is one such type of trial that has been designed to assess DTRs. The primary goal of our project is to identify the treatments, covariates, and their interactions result in the best overall survival rate. Many previously proposed methods to analyze data with survival outcomes from a SMART use inverse probability weighting and provide non-parametric estimation of survival rates, but no other information. Other methods have been proposed to identify and estimate the optimal DTR, but inference issues were seldom addressed. We apply a joint modeling approach to provide unbiased survival estimates as a mechanism to quantify baseline and time-varying covariate effects, treatment effects, and their interactions within regimens. The issue of multiple comparisons at specific time points is addressed using multiple comparisons with the best method.
动态治疗方案（DTR）是一系列决策规则，可以根据先前治疗的结果改变治疗方法或剂量。对于两种治疗方法，DTR 指定一线治疗和二线治疗，一线治疗的 responder 和非 responder 的治疗方法。序贯、多次分配、随机试验（SMART）就是这样一种旨在评估 DTR 的试验。我们项目的主要目标是确定治疗方法、协变量及其相互作用，以获得最佳的总生存率。许多以前提出的用于分析 SMART 中生存结果数据的方法都使用逆概率加权，并提供生存率的非参数估计，但没有其他信息。其他方法已被提出用于识别和估计最佳 DTR，但很少解决推断问题。我们应用联合建模方法提供无偏的生存估计，作为一种量化方案中基线和时变协变量效应、治疗效果及其相互作用的机制。使用最佳方法进行多次比较来解决特定时间点的多次比较问题。
