Division of Biostatistics, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA.
Ther Innov Regul Sci. 2024 Nov;58(6):1201-1213. doi: 10.1007/s43441-024-00698-3. Epub 2024 Sep 13.
As cancer has become better understood on the molecular level with the evolution of gene sequencing techniques, considerations for individualized therapy using predictive biomarkers (those associated with a treatment's effect) have shifted to a new level. In the last decade or so, randomized "adaptive enrichment" clinical trials have become increasingly utilized to strike a balance between enrolling all patients with a given tumor type, versus enrolling only a subpopulation whose tumors are defined by a potential predictive biomarker related to the mechanism of action of the experimental therapy. In this review article, we review recent innovative design extensions and adaptations to adaptive enrichment designs proposed during the last few years in the clinical trial methodology literature, both from Bayesian and frequentist perspectives.
随着基因测序技术的发展，癌症在分子水平上的认识不断提高，使用预测性生物标志物（与治疗效果相关的标志物）进行个体化治疗的考虑已经上升到一个新的水平。在过去的十年左右的时间里，随机“适应性富集”临床试验越来越多地被用于在招募所有具有特定肿瘤类型的患者与招募仅具有潜在预测性生物标志物的亚组患者之间取得平衡，这些生物标志物与实验治疗的作用机制相关。在这篇综述文章中，我们回顾了过去几年中临床试验方法学文献中提出的适应性富集设计的最新创新设计扩展和改编，包括贝叶斯和频率派的观点。
