An Adaptive Three-Arm Comparative Clinical Endpoint Bioequivalence Study Design With Unblinded Sample Size Re-Estimation and Optimized Allocation Ratio.
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引用次数: 0
Abstract
A three-arm comparative clinical endpoint bioequivalence (BE) study is often used to establish bioequivalence (BE) between a locally acting generic drug (T) and reference drug (R), where superiority needs to be established for T and R over Placebo (P) and equivalence needs to be established for T vs. R. Sometimes, when study design parameters are uncertain, a fixed design study may be under- or over-powered and result in study failure or unnecessary cost. In this paper, we propose a two-stage adaptive clinical endpoint BE study with unblinded sample size re-estimation, standard or maximum combination method, optimized allocation ratio, optional re-estimation of the effect size based on likelihood estimation, and optional re-estimation of the R and P treatment means at interim analysis, which have not been done previously. Our proposed method guarantees control of Type 1 error rate analytically. It helps to reduce the average sample size when the original fixed design is overpowered and increases the sample size and power when the original study and group sequential design are under-powered. Our proposed adaptive design can help generic drug sponsors cut cost and improve success rate, making clinical study endpoint BE studies more affordable and more generic drugs accessible to the public.
三臂比较临床终点生物等效性(BE)研究通常用于确定局部作用仿制药(T)和参比药(R)之间的生物等效性(BE),其中需要确定T和R相对于安慰剂(P)的优越性,以及T相对于R的等效性。有时,当研究设计参数不确定时,固定设计的研究可能功率不足或过高,导致研究失败或不必要的成本。在本文中,我们提出了一种两阶段自适应临床终点 BE 研究,其中包括非盲法样本量重新估计、标准或最大组合法、优化分配比例、基于似然估计的可选效应大小重新估计、中期分析时可选的 R 和 P 治疗均值重新估计,这些都是以前没有做过的。我们提出的方法保证了对第一类错误率的分析控制。当原来的固定设计功率过大时,它有助于减少平均样本量;当原来的研究和分组序列设计功率不足时,它有助于增加样本量和功率。我们提出的自适应设计可以帮助仿制药申办者降低成本,提高成功率,使临床研究终点 BE 研究更加经济实惠,让更多的公众可以获得仿制药。
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.