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生物标志物驱动的临床试验统计方法综述

Review of Statistical Methods for Biomarker-Driven Clinical Trials.

作者信息

Simon Richard

机构信息

R Simon Consulting, Potomac, MD.

出版信息

JCO Precis Oncol. 2019 Dec;3:1-9. doi: 10.1200/PO.18.00407.

DOI:10.1200/PO.18.00407
PMID:35100721
Abstract

The discovery of somatic driver mutations in kinases and receptors has stimulated the development of molecularly targeted treatments that require companion diagnostics and new approaches to clinical development. This article reviews some of the clinical trial designs that have been developed to address these opportunities, including phase II basket and platform trials as well as phase III enrichment and biomarker adaptive designs. It also re-examines some of the conventional wisdom that previously dominated clinical trial design and discusses development and internal validation of a predictive biomarker as a new paradigm for optimizing the intended-use subset for a treatment. Statistical methods now being used in adaptive biomarker-driven clinical trials are reviewed. Some previous paradigms for clinical trial design can limit the development of more effective methods on the basis of prospectively planned adaptive methods, but useful new methods have been developed for analysis of genome-wide data and for the design of adaptively enriched studies. In many cases, the heterogeneity of populations eligible for clinical trials as traditionally defined makes it unlikely that molecularly targeted treatments will be effective for a majority of the eligible patients. New methods for dealing with patient heterogeneity in therapeutic response should be used in the design of phase III clinical trials.

摘要

激酶和受体中体细胞驱动突变的发现推动了分子靶向治疗的发展,这类治疗需要伴随诊断以及新的临床开发方法。本文回顾了为抓住这些机遇而开发的一些临床试验设计,包括II期篮子试验和平台试验,以及III期富集试验和生物标志物适应性设计。本文还重新审视了一些以往主导临床试验设计的传统观念,并讨论了预测性生物标志物的开发和内部验证,将其作为优化治疗预期适用亚组的一种新范式。本文回顾了目前在适应性生物标志物驱动的临床试验中使用的统计方法。以往一些临床试验设计范式可能会限制基于前瞻性规划的适应性方法开发更有效的方法,但已开发出用于全基因组数据分析和适应性富集研究设计的有用新方法。在许多情况下,按照传统定义符合临床试验条件的人群的异质性使得分子靶向治疗对大多数符合条件的患者不太可能有效。在III期临床试验设计中应采用处理患者治疗反应异质性的新方法。

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