Abstract:
The use of simulation-based sensitivity analyses is fundamental for evaluating and comparing candidate designs of future clinical trials. In this context, sensitivity analyses are especially useful to assess the dependence of important design operating characteristics with respect to various unknown parameters. Typical examples of operating characteristics include the likelihood of detecting treatment effects and the average study duration, which depend on parameters that are unknown until after the onset of the clinical study, such as the distributions of the primary outcomes and patient profiles. Two crucial components of sensitivity analyses are (i) the choice of a set of plausible simulation scenarios and (ii) the list of operating characteristics of interest. We propose a new approach for choosing the set of scenarios to be included in a sensitivity analysis. We maximize a utility criterion that formalizes whether a specific set of sensitivity scenarios is adequate to summarize how the operating characteristics of the trial design vary across plausible values of the unknown parameters. Then, we use optimization techniques to select the best set of simulation scenarios (according to the criteria specified by the investigator) to exemplify the operating characteristics of the trial design. We illustrate our proposal in three trial designs.
摘要:
使用基于模拟的敏感性分析是评估和比较未来临床试验的候选设计的基础。在这种情况下,灵敏度分析对于评估重要的设计操作特性对各种未知参数的依赖性特别有用。操作特征的典型示例包括检测治疗效果的可能性和平均研究持续时间,这取决于在临床研究开始之前未知的参数,例如主要结局和患者概况的分布。敏感性分析的两个关键组成部分是(i)选择一组合理的模拟方案和(ii)感兴趣的操作特征列表。我们提出了一种新的方法来选择要包括在敏感性分析中的一组方案。我们最大化了一个效用标准,该标准形式化了一组特定的敏感性方案是否足以总结试验设计的运行特性在未知参数的合理值之间的变化。然后,我们使用优化技术选择一组最佳的模拟方案(根据研究者指定的标准)来举例说明试验设计的操作特征.我们在三个试验设计中说明了我们的建议。