具有时间到事件结果测量误差的富集生物标志物设计的样本量。

IF 1.4 4区 医学 Q4 PHARMACOLOGY & PHARMACY
Siyuan Guo, Susan Halabi, Aiyi Liu
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引用次数: 0

摘要

个性化医疗的一个主要重点是对可能从某些治疗药物中受益的患者进行最佳治疗。一种相关的研究设计是目标设计,在该设计中,患者已同意在基线时获取其标本,并在随机化之前将标本送到实验室评估生物标志物状态。在这里,只有生物标志物阳性的患者将被随机分配到实验组或标准护理组。然而,许多生物标志物来源于患者组织标本,这些组织标本具有异质性,导致生物标志物水平和状态的可变性。这种异质性会对强化生物标志物临床试验的有效性产生不利影响。在本文中,我们展示了使用未校正样本量的不利影响,并通过提出一种方法来调整目标设计的错误分类来克服这一挑战。具体来说,我们提出了一个样本量公式来调整错误分类,并将其应用于肾癌和前列腺癌的两个III期临床试验的设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sample Size for Enriched Biomarker Designs With Measurement Error for Time-to-Event Outcomes.

A major emphasis in personalized medicine is to optimally treat subgroups of patients who may benefit from certain therapeutic agents. One relevant study design is the targeted design, in which patients have consented for their specimens to be obtained at baseline and the specimens are sent to a laboratory for assessing the biomarker status prior to randomization. Here, only biomarker-positive patients will be randomized to either an experimental or the standard of care arms. Many biomarkers, however, are derived from patient tissue specimens, which are heterogeneous leading to variability in the biomarker levels and status. This heterogeneity would have an adverse impact on the power of an enriched biomarker clinical trial. In this article, we show the adverse effect of using the uncorrected sample size and overcome this challenge by presenting an approach to adjust for misclassification for the targeted design. Specifically, we propose a sample size formula that adjusts for misclassification and apply it in the design of two phase III clinical trials in renal and prostate cancer.

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来源期刊
Pharmaceutical Statistics
Pharmaceutical Statistics 医学-统计学与概率论
CiteScore
2.70
自引率
6.70%
发文量
90
审稿时长
6-12 weeks
期刊介绍: Pharmaceutical Statistics is an industry-led initiative, tackling real problems in statistical applications. The Journal publishes papers that share experiences in the practical application of statistics within the pharmaceutical industry. It covers all aspects of pharmaceutical statistical applications from discovery, through pre-clinical development, clinical development, post-marketing surveillance, consumer health, production, epidemiology, and health economics. The Journal is both international and multidisciplinary. It includes high quality practical papers, case studies and review papers.
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