Holm Hansen Christian, Warner Pamela, Parker Richard A, Walker Brian R, Critchley Hilary Od, Weir Christopher J
1 MRC Tropical Epidemiology Group, London School of Hygiene & Tropical Medicine, London, UK.
2 Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK.
Stat Methods Med Res. 2017 Dec;26(6):2681-2699. doi: 10.1177/0962280215606155. Epub 2015 Sep 30.
It is often unclear what specific adaptive trial design features lead to an efficient design which is also feasible to implement. This article describes the preparatory simulation study for a Bayesian response-adaptive dose-finding trial design. Dexamethasone for Excessive Menstruation aims to assess the efficacy of Dexamethasone in reducing excessive menstrual bleeding and to determine the best dose for further study. To maximise learning about the dose response, patients receive placebo or an active dose with randomisation probabilities adapting based on evidence from patients already recruited. The dose-response relationship is estimated using a flexible Bayesian Normal Dynamic Linear Model. Several competing design options were considered including: number of doses, proportion assigned to placebo, adaptation criterion, and number and timing of adaptations. We performed a fractional factorial study using SAS software to simulate virtual trial data for candidate adaptive designs under a variety of scenarios and to invoke WinBUGS for Bayesian model estimation. We analysed the simulated trial results using Normal linear models to estimate the effects of each design feature on empirical type I error and statistical power. Our readily-implemented approach using widely available statistical software identified a final design which performed robustly across a range of potential trial scenarios.
通常不清楚具体哪些适应性试验设计特征会产生一个既高效又可行的设计方案。本文描述了一项针对贝叶斯反应适应性剂量探索试验设计的预备性模拟研究。“地塞米松治疗月经过多”旨在评估地塞米松在减少月经过多方面的疗效，并确定进一步研究的最佳剂量。为了最大程度地了解剂量反应，患者接受安慰剂或活性剂量，随机分配概率根据已招募患者的证据进行调整。使用灵活的贝叶斯正态动态线性模型估计剂量反应关系。考虑了几种相互竞争的设计选项，包括：剂量数量、分配给安慰剂的比例、适应性标准以及适应的次数和时间。我们使用SAS软件进行了析因试验研究，以模拟各种情况下候选适应性设计的虚拟试验数据，并调用WinBUGS进行贝叶斯模型估计。我们使用正态线性模型分析模拟试验结果，以估计每个设计特征对经验性I型错误和统计功效的影响。我们使用广泛可用的统计软件的易于实施的方法确定了一个最终设计，该设计在一系列潜在试验场景中表现稳健。
