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肿瘤学早期开发单臂研究中的生物标志物富集考量

Biomarker enrichment considerations in oncology early development single-arm studies.

作者信息

Tian Hong, Liu Kevin

机构信息

a Department of Statistics & Decision Sciences, Quantitative Sciences , Janssen Research & Development , Raritan , NJ , USA.

出版信息

J Biopharm Stat. 2018;28(2):282-291. doi: 10.1080/10543406.2017.1379533. Epub 2017 Oct 30.

Abstract

Oncology drug development has been increasingly shaped by molecularly targeted agents (MTAs), which often demonstrate differential effectiveness driven by the biomarker expression levels on tumors. Innovative statistical designs have been proposed to tackle this challenge, e.g., adaptive signature design, biomarker-adaptive threshold design and the cross-validated adaptive signature design. All of these are essentially adaptive confirmatory Phase III designs that combine the testing of treatment effectiveness in the overall population with an alternative pathway for a more restrictive efficacy claim in a sensitive subpopulation. We believe that, in cases that there are strong biological rationales to support that a MTA may provide differential benefit in a general patient population, proof-of-concept (POC) is likely intertwined with predictive enrichment. Therefore, it is imperative that early-phase POC studies be designed to specifically address biomarker-related questions to improve the efficiency of development. In this paper, we propose three strategies for detecting efficacy signals in single-arm studies that allow claiming statistical significance either in the overall population or in a biomarker-enriched subpopulation. None of the three methods requires pre-specification of biomarker thresholds, but still maintains statistical rigor in the presence of multiplicity. The performance of these proposed methods is evaluated with simulation studies.

摘要

肿瘤学药物研发越来越受到分子靶向药物(MTA)的影响,这些药物通常表现出由肿瘤上生物标志物表达水平驱动的差异有效性。人们提出了创新的统计设计来应对这一挑战,例如适应性特征设计、生物标志物适应性阈值设计和交叉验证适应性特征设计。所有这些本质上都是适应性确证性III期设计,将总体人群中治疗有效性的测试与在敏感亚组中提出更严格疗效声明的替代途径相结合。我们认为,在有充分生物学依据支持MTA可能在一般患者人群中提供差异获益的情况下,概念验证(POC)可能与预测性富集相互交织。因此,早期POC研究必须专门设计以解决与生物标志物相关的问题,以提高研发效率。在本文中,我们提出了三种在单臂研究中检测疗效信号的策略,这些策略允许在总体人群或生物标志物富集亚组中声明具有统计学意义。这三种方法都不需要预先设定生物标志物阈值,但在存在多重性的情况下仍保持统计严谨性。通过模拟研究评估了这些方法的性能。

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