Clinical Trials Research Unit, Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, LS2 9JT, UK.
BMC Med Res Methodol. 2024 Oct 2;24(1):226. doi: 10.1186/s12874-024-02351-x.
Whether or not to progress from a pilot study to a definitive trial is often guided by pre-specified quantitative progression criteria with three possible outcomes. Although the choice of these progression criteria will help to determine the statistical properties of the pilot trial, there is a lack of research examining how they, or the pilot sample size, should be determined.
We review three-outcome trial designs originally proposed in the phase II oncology setting and extend these to the case of external pilots, proposing a unified framework based on univariate hypothesis tests and the control of frequentist error rates. We apply this framework to an example and compare against a simple two-outcome alternative.
We find that three-outcome designs can be used in the pilot setting, although they are not generally more efficient than simpler two-outcome alternatives. We show that three-outcome designs can help allow for other sources of information or other stakeholders to feed into progression decisions in the event of a borderline result, but this will come at the cost of a larger pilot sample size than the two-outcome case. We also show that three-outcome designs can be used to allow adjustments to be made to the intervention or trial design before commencing the definitive trial, providing the effect of the adjustment can be accurately predicted at the pilot design stage. An R package, tout, is provided to optimise progression criteria and pilot sample size.
The proposed three-outcome framework provides a way to optimise pilot trial progression criteria and sample size in a way that leads to desired operating characteristics. It can be applied whether or not an adjustment following the pilot trial is anticipated, but will generally lead to larger sample size requirements than simpler two-outcome alternatives.
是否将一项初步研究推进到确定性试验通常取决于预先指定的具有三种可能结果的定量进展标准。尽管这些进展标准的选择将有助于确定初步试验的统计特性,但缺乏研究来检验这些标准或初步样本量应该如何确定。
我们回顾了最初在肿瘤学二期研究中提出的三结局试验设计,并将其扩展到外部初步研究的情况,提出了一个基于单变量假设检验和控制频率主义错误率的统一框架。我们将该框架应用于一个实例,并与简单的两结局替代方案进行比较。
我们发现三结局设计可用于初步研究,但它们通常不如更简单的两结局替代方案有效。我们表明,三结局设计可以帮助允许其他信息来源或其他利益相关者在出现边缘结果时对进展决策进行反馈,但这将以比两结局情况更大的初步样本量为代价。我们还表明,三结局设计可用于在开始确定性试验之前对干预或试验设计进行调整,前提是可以在初步设计阶段准确预测调整的效果。提供了一个名为 tout 的 R 包,用于优化进展标准和初步样本量。
所提出的三结局框架提供了一种优化初步试验进展标准和样本量的方法,从而实现所需的操作特性。无论是否预期在初步试验后进行调整,都可以应用该框架,但通常会导致比更简单的两结局替代方案更大的样本量要求。