Evaluating Personalized (N-of-1) Trials in Rare Diseases: How Much Experimentation Is Enough?
Evaluating Personalized (N-of-1) Trials in Rare Diseases: How Much Experimentation Is Enough?
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DOI：
10.1162/99608f92.e11adff0
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发表时间：
2022
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对于罕见病，由于样本量有限，对新疗法进行大型随机试验可能是不可行的，并且由于治疗效果的异质性，它可能回答错误的科学问题。个性化（N-of-1）试验是多阶段交叉研究，旨在估计个体治疗效果，从而确定个体的最佳治疗方法。本文探讨了评估肌萎缩侧索硬化症（ALS）患者个性化（N-of-1）治疗方案的统计设计问题。我们提出了一个评估框架的基础上的分析模型，在个性化试验中观察到的纵向数据。在这个框架下，我们解决两个设计参数：在每次试验的实验长度和试验所需的数量。对于前者，我们考虑以患者为中心的设计标准，旨在最大限度地提高入组患者的获益。使用理论研究和数值研究，我们证明，从患者的角度来看，实验期的持续时间不应超过整个随访期的三分之一。对于后者，我们提供了分析公式来计算功率测试质量的提高，由于在一个随机化的评估程序中的个性化试验，从而确定所需的试验计划所需的数量。我们应用我们的理论结果来设计一个评估方案，为ALS治疗的试点数据，并表明，实验的长度有一个小的影响功率相对于其他因素，如治疗效果的异质性程度。
For rare diseases, conducting large, randomized trials of new treatments can be infeasible due to limited sample size, and it may answer the wrong scientific questions due to heterogeneity of treatment effects. Personalized (N-of-1) trials are multi-period crossover studies that aim to estimate individual treatment effects, thereby identifying the optimal treatments for individuals. This article examines the statistical design issues of evaluating a personalized (N-of-1) treatment program in people with amyotrophic lateral sclerosis (ALS). We propose an evaluation framework based on an analytical model for longitudinal data observed in a personalized trial. Under this framework, we address two design parameters: length of experimentation in each trial and number of trials needed. For the former, we consider patient-centric design criteria that aim to maximize the benefits of enrolled patients. Using theoretical investigation and numerical studies, we demonstrate that, from a patient’s perspective, the duration of an experimentation period should be no longer than one-third of the entire follow-up period of the trial. For the latter, we provide analytical formulae to calculate the power for testing quality improvement due to personalized trials in a randomized evaluation program and hence determine the required number of trials needed for the program. We apply our theoretical results to design an evaluation program for ALS treatments informed by pilot data and show that the length of experimentation has a small impact on power relative to other factors such as the degree of heterogeneity of treatment effects.