一种实用的自适应富集设计，用于选择癌症免疫治疗的正确靶人群
A pragmatic adaptive enrichment design for selecting the right target population for cancer immunotherapies
摘要：
验证性试验设计中的一个挑战是处理关于新药最佳目标人群的不确定性。自适应富集设计（AED）允许在中期分析时数据驱动选择一个或多个预先指定的生物标志物亚群，但在这种情况下，AED的实际病例研究仍然相对较少。我们提出了一种AED的设计，在高度动态的癌症免疫治疗环境中具有二元终点。该试验是作为早期三阴性乳腺癌的常规试验启动的，但根据试验外部的新数据修改为AED，表明PD-L1状态可能是预测性生物标志物。讨论了操作特征，包括最小可检测差异的概念，即在AED设置中，在中期或最终分析时，至少在一个目标人群中观察到的最小处理效应将导致统计学显著性结果。
英文摘要：
One of the challenges in the design of confirmatory trials is to deal with uncertainties regarding the optimal target population for a novel drug. Adaptive enrichment designs (AED) which allow for a data-driven selection of one or more pre-specified biomarker subpopulations at an interim analysis have been proposed in this setting but practical case studies of AEDs are still relatively rare. We present the design of an AED with a binary endpoint in the highly dynamic setting of cancer immunotherapy. The trial was initiated as a conventional trial in early triple-negative breast cancer but amended to an AED based on emerging data external to the trial suggesting that PD-L1 status could be a predictive biomarker. Operating characteristics are discussed including the concept of a minimal detectable difference, that is, the smallest observed treatment effect that would lead to a statistically significant result in at least one of the target populations at the interim or the final analysis, respectively, in the setting of AED.
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