Department of Biostatistics and Health Data Science, Indiana University, Indianapolis, IN, USA.
Eli Lilly and Company, Indianapolis, IN, USA.
Stat Methods Med Res. 2023 May;32(5):885-894. doi: 10.1177/09622802231158738. Epub 2023 Mar 15.
The "one-size-fits-all'' paradigm is inappropriate for phase II clinical trials evaluating biotherapies, which are often expected to have substantial heterogeneous treatment effects among different subgroups defined by biomarker. For these biotherapies, the objective of phase II clinical trials is often to evaluate subgroup-specific treatment effects. In this article, we propose a simple yet efficient Bayesian adaptive phase II biomarker-guided design, referred to as the Bayesian-order constrained adaptive design, to detect the subgroup-specific treatment effects of biotherapies. The Bayesian order constrained adaptive design combines the features of the enrichment design and sequential design. It starts with a "all-comers" stage, and subsequently switches to an enrichment stage for either the marker-positive subgroup or marker-negative subgroup, depending on the interim analysis results. The go/no go enrichment criteria are determined by two posterior probabilities utilizing the inherent ordering constraint between two subgroups. We also extend the Bayesian-order constrained adaptive design to handle the missing biomarker situation. We conducted comprehensive computer simulation studies to investigate the operating characteristics of the Bayesian order constrained adaptive design, and compared it with other existing and conventional designs. The results shown that the Bayesian order constrained adaptive design yielded the best overall performance in detecting the subgroup-specific treatment effects by jointly considering the efficiency and cost-effectiveness of the trials. The software for simulation and trial implementation are available for free download.
“一刀切”的范式不适合用于评估生物疗法的 II 期临床试验，因为生物疗法通常预期在基于生物标志物定义的不同亚组中具有显著的异质治疗效果。对于这些生物疗法，II 期临床试验的目的通常是评估亚组特异性的治疗效果。在本文中，我们提出了一种简单而有效的贝叶斯自适应 II 期生物标志物指导设计，称为贝叶斯序贯约束自适应设计，用于检测生物疗法的亚组特异性治疗效果。贝叶斯序贯约束自适应设计结合了富集设计和序贯设计的特点。它从“全体入组”阶段开始，然后根据中期分析结果，切换到针对标记阳性亚组或标记阴性亚组的富集阶段。去留富集标准由两个后验概率确定，利用两个亚组之间固有的排序约束。我们还将贝叶斯序贯约束自适应设计扩展到处理缺失的生物标志物情况。我们进行了全面的计算机模拟研究，以研究贝叶斯序贯约束自适应设计的操作特征，并将其与其他现有的和传统的设计进行了比较。结果表明，贝叶斯序贯约束自适应设计通过综合考虑试验的效率和成本效益，在检测亚组特异性治疗效果方面表现出最佳的整体性能。模拟和试验实施的软件可免费下载。
