Factorial versus multi-arm multi-stage designs for clinical trials with multiple treatments.
Factorial versus multi-arm multi-stage designs for clinical trials with multiple treatments.
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用于多种治疗的临床试验的析因与多臂多阶段设计。
DOI：
10.1002/sim.7159
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发表时间：
2017-02-20
影响因子：
2
通讯作者：
Vasileiou D
中科院分区：
文献类型：
--
作者：
Jaki T;Vasileiou D
当临床试验中有多种治疗方法可供评估时，可使用不同的设计选项。我们将多组多阶段与析因设计进行比较，特别是，我们将考虑2 × 2析因设计，其中患者组将接受治疗A、B、两者或两者都不接受。我们调查的性能和特点，这两种类型的设计在不同的情况下，并比较它们使用理论和模拟。对于析因设计，我们构建了适当的检验统计量，以检验相对于对照组无治疗效应的假设，并总体控制I类错误。我们研究了分配比率的选择对目标功效的临界值和样本量要求的影响。我们还研究了两种治疗A和B之间的相互作用的可能性如何影响I型和II型错误时，每个治疗效果的显着性测试。我们提出了模拟结果和骨关节炎临床试验的案例研究。我们发现，在最优析因设计中，在最小化相关的临界值，相应的分配比有很大的不同，以平衡设计。我们还发现了证据表明，对于研究设计假设的中度偏离，析因设计的功效可能会大幅损失，而当假设成立时，与多组多阶段设计相比，功效几乎没有增加。© 2016作者。出版社：John Wiley & Sons Ltd
When several treatments are available for evaluation in a clinical trial, different design options are available. We compare multi‐arm multi‐stage with factorial designs, and in particular, we will consider a 2 × 2 factorial design, where groups of patients will either take treatments A, B, both or neither. We investigate the performance and characteristics of both types of designs under different scenarios and compare them using both theory and simulations. For the factorial designs, we construct appropriate test statistics to test the hypothesis of no treatment effect against the control group with overall control of the type I error. We study the effect of the choice of the allocation ratios on the critical value and sample size requirements for a target power. We also study how the possibility of an interaction between the two treatments A and B affects type I and type II errors when testing for significance of each of the treatment effects. We present both simulation results and a case study on an osteoarthritis clinical trial. We discover that in an optimal factorial design in terms of minimising the associated critical value, the corresponding allocation ratios differ substantially to those of a balanced design. We also find evidence of potentially big losses in power in factorial designs for moderate deviations from the study design assumptions and little gain compared with multi‐arm multi‐stage designs when the assumptions hold. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.