A systematic approach to adaptive sequential design for clinical trials: using simulations to select a design with desired operating characteristics.

IF 1.2 4区 医学 Q4 PHARMACOLOGY & PHARMACY
Ping Gao, Weidong Zhang
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引用次数: 0

Abstract

The failure rates of phase 3 trials are high. Incorrect sample size due to uncertainty of effect size could be a critical contributing factor. Adaptive sequential design (ASD), which may include one or more sample size re-estimations (SSR), has been a popular approach for dealing with such uncertainties. The operating characteristics (OCs) of ASD, including the unconditional power and mean sample size, can be substantially affected by many factors, including the planned sample size, the interim analysis schedule and choice of critical boundaries and rules for interim analysis. We propose a systematic, comprehensive strategy which uses iterative simulations to investigate the operating characteristics of adaptive designs and help achieve adequate unconditional power and cost-effective mean sample size if the effect size is in a pre-identified range.

临床试验适应性顺序设计的系统方法:利用模拟选择具有理想运行特征的设计。
第三阶段试验的失败率很高。效应大小的不确定性导致的样本量不正确可能是一个关键因素。自适应序列设计(ASD)可能包括一次或多次样本量再估计(SSR),它一直是处理此类不确定性的常用方法。自适应序列设计的运行特征(OCs),包括无条件功率和平均样本量,会受到许多因素的严重影响,包括计划样本量、中期分析时间表以及临界边界和中期分析规则的选择。我们提出了一种系统、全面的策略,利用迭代模拟来研究适应性设计的运行特征,如果效应大小在预先确定的范围内,该策略有助于获得足够的无条件功率和具有成本效益的平均样本量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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