In this work, we examine recently developed methods for Bayesian inference of optimal dynamic treatment regimes (DTRs). DTRs are a set of treatment decision rules aimed at tailoring patient care to patient-specific characteristics, thereby falling within the realm of precision medicine. In this field, researchers seek to tailor therapy with the intention of improving health outcomes; therefore, they are most interested in identifying optimal DTRs. Recent work has developed Bayesian methods for identifying optimal DTRs in a family indexed by $\psi$ via Bayesian dynamic marginal structural models (MSMs) (Rodriguez Duque et al., 2022a); we review the proposed estimation procedure and illustrate its use via the new BayesDTR R package. Although methods in (Rodriguez Duque et al., 2022a) can estimate optimal DTRs well, they may lead to biased estimators when the model for the expected outcome if everyone in a population were to follow a given treatment strategy, known as a value function, is misspecified or when a grid search for the optimum is employed. We describe recent work that uses a Gaussian process ($GP$) prior on the value function as a means to robustly identify optimal DTRs (Rodriguez Duque et al., 2022b). We demonstrate how a $GP$ approach may be implemented with the BayesDTR package and contrast it with other value-search approaches to identifying optimal DTRs. We use data from an HIV therapeutic trial in order to illustrate a standard analysis with these methods, using both the original observed trial data and an additional simulated component to showcase a longitudinal (two-stage DTR) analysis.

翻译：本文系统研究了近年来发展的最优动态治疗方案（DTRs）贝叶斯推断方法。DTRs是一组旨在根据患者个体特征定制治疗方案的决策规则，属于精准医学范畴。在该领域，研究者致力于设计个性化治疗方案以改善健康结局，因此识别最优DTRs成为核心目标。近期研究通过贝叶斯动态边际结构模型（MSMs），发展了在参数族$\psi$索引下识别最优DTRs的贝叶斯方法（Rodriguez Duque等，2022a）；我们综述了其提出的估计程序，并通过新开发的BayesDTR R软件包演示具体应用。尽管（Rodriguez Duque等，2022a）的方法能有效估计最优DTRs，但当群体中所有个体遵循给定治疗策略时的期望结局模型（即价值函数）设定错误，或采用网格搜索优化时，可能导致估计偏差。我们进一步描述了利用高斯过程（$GP$）先验对价值函数建模以实现最优DTRs稳健识别的最新研究（Rodriguez Duque等，2022b），演示了如何通过BayesDTR包实施$GP$方法，并与其他价值搜索方法进行对比。为展示这些方法的标准分析流程，我们采用HIV治疗试验数据，在原始观测数据基础上加入模拟成分，进行了纵向（两阶段DTR）分析案例研究。