Chao Yan-Cheng, Braun Thomas M, Tamura Roy N, Kidwell Kelley M
Department of Biostatistics, 51329School of Public Health, University of Michigan, Ann Arbor, MI USA.
Health Informatics Institute, 7831University of South Florida, Tampa, FL USA.
Stat Methods Med Res. 2022 Dec;31(12):2297-2309. doi: 10.1177/09622802221122795. Epub 2022 Sep 9.
A small n, sequential, multiple assignment, randomized trial (snSMART) is a small sample, two-stage design where participants receive up to two treatments sequentially, but the second treatment depends on response to the first treatment. The parameters of interest in an snSMART are the first-stage response rates of the treatments, but outcomes from both stages can be used to obtain more information from a small sample. A novel way to incorporate the outcomes from both stages uses power prior models, in which first stage outcomes from an snSMART are regarded as the primary (internal) data and second stage outcomes are regarded as supplemental data (co-data). We apply existing power prior models to snSMART data, and we also develop new extensions of power prior models. All methods are compared to each other and to the Bayesian joint stage model (BJSM) via simulation studies. By comparing the biases and the efficiency of the response rate estimates among all proposed power prior methods, we suggest application of Fisher's Exact Test or the Bhattacharyya's overlap measure to an snSMART to estimate the response rates in an snSMART, which both have performance mostly as good or better than the BJSM. We describe the situations where each of these suggested approaches is preferred.
小样本、序贯、多重分配、随机试验（snSMART）是一种小样本两阶段设计，参与者依次接受最多两种治疗，但第二种治疗取决于对第一种治疗的反应。snSMART中感兴趣的参数是治疗的第一阶段反应率，但两个阶段的结果都可用于从小样本中获取更多信息。一种整合两个阶段结果的新方法是使用功效先验模型，其中snSMART的第一阶段结果被视为主要（内部）数据，第二阶段结果被视为补充数据（协数据）。我们将现有的功效先验模型应用于snSMART数据，并且还开发了功效先验模型的新扩展。通过模拟研究，将所有方法相互比较，并与贝叶斯联合阶段模型（BJSM）进行比较。通过比较所有提出的功效先验方法中反应率估计的偏差和效率，我们建议将费舍尔精确检验或巴塔查里亚重叠度量应用于snSMART以估计其反应率，这两种方法的性能大多与BJSM一样好或更好。我们描述了每种建议方法更适用的情况。
