Two-stage response adaptive randomization designs for multi-arm trials with binary outcome.

IF 1.2 4区 医学 Q4 PHARMACOLOGY & PHARMACY
Xinlin Lu, Guogen Shan
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引用次数: 0

Abstract

In recent years, adaptive randomization methods have gained significant popularity in clinical research and trial design due to their ability to provide both efficiency and flexibility in adjusting the statistical procedures of ongoing clinical trials. For a study to compare multiple treatments, a multi-arm two-stage design could be utilized to select the best treatment from the first stage and further compare that treatment with control in the second stage. The traditional design used equal randomization in both stages. To better utilize the interim results from the first stage, we propose to develop response adaptive randomization two-stage designs for a multi-arm clinical trial with binary outcome. Two allocation methods are considered: (1) an optimal allocation based on a sequential design; (2) the play-the-winner rule. Optimal multi-arm two-stage designs are obtained under three criteria: minimizing the expected number of failures, minimizing the average expected sample size, and minimizing the expected sample size under the null hypothesis. Simulation studies show that the proposed adaptive design based on the play-the-winner rule has good performance. A phase II trial for patients with pancreas adenocarcinoma and a germline BRCA/PALB2 mutation was used to illustrate the application of the proposed response adaptive randomization designs.

二元结果多臂试验的两阶段反应自适应随机化设计。
近年来,自适应随机化方法在临床研究和试验设计中大受欢迎,因为它既能提高效率,又能灵活调整正在进行的临床试验的统计程序。对于比较多种治疗方法的研究,可采用多臂两阶段设计,从第一阶段选择最佳治疗方法,并在第二阶段进一步比较该治疗方法与对照组。传统的设计在两个阶段都采用了相同的随机化。为了更好地利用第一阶段的中期结果,我们建议为二元结果的多臂临床试验开发响应自适应随机化两阶段设计。我们考虑了两种分配方法:(1) 基于顺序设计的最优分配;(2) 胜者为王规则。最优的多臂两阶段设计有三个标准:最小化预期失败次数、最小化平均预期样本量和最小化零假设下的预期样本量。模拟研究表明,基于胜者为王规则提出的自适应设计具有良好的性能。一项针对胰腺腺癌和种系 BRCA/PALB2 基因突变患者的 II 期试验被用来说明所提出的反应自适应随机化设计的应用。
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来源期刊
Journal of Biopharmaceutical Statistics
Journal of Biopharmaceutical Statistics 医学-统计学与概率论
CiteScore
2.50
自引率
18.20%
发文量
71
审稿时长
6-12 weeks
期刊介绍: The Journal of Biopharmaceutical Statistics, a rapid publication journal, discusses quality applications of statistics in biopharmaceutical research and development. Now publishing six times per year, it includes expositions of statistical methodology with immediate applicability to biopharmaceutical research in the form of full-length and short manuscripts, review articles, selected/invited conference papers, short articles, and letters to the editor. Addressing timely and provocative topics important to the biostatistical profession, the journal covers: Drug, device, and biological research and development; Drug screening and drug design; Assessment of pharmacological activity; Pharmaceutical formulation and scale-up; Preclinical safety assessment; Bioavailability, bioequivalence, and pharmacokinetics; Phase, I, II, and III clinical development including complex innovative designs; Premarket approval assessment of clinical safety; Postmarketing surveillance; Big data and artificial intelligence and applications.
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