Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, USA.
Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, USA.
J Clin Epidemiol. 2022 Jan;141:141-148. doi: 10.1016/j.jclinepi.2021.10.002. Epub 2021 Oct 11.
Patient reported outcomes (PRO) are widely used in quality of life (QOL) studies, health outcomes research, and clinical trials. The importance of PRO has been advocated by health authorities. Patient Reported Outcomes Measurement Information System (PROMIS) is a collection of standardized measures of PROs using Item Response Theory (IRT). However, in clinical trials with PROs as endpoints, observed scores are routinely used for power estimation rather than IRT scores. This paper aims to fill this gap and estimate power in a two-arm clinical trials with PROMIS measures as endpoints with IRT model.
We conducted a series of simulations to study the IRT power with validated PROMIS measures controlling factors including sample size, effect size, number of items, and missing data proportion.
Our results showed that sample size, effect size, and number of items are important indicators of IRT based power estimation for PROMIS measures. When effect size is small and sample size is limited, IRT model provides higher power than the closed form formula.
IRT based simulation should be used for power estimation in two-armed clinical, especially when there is small effect size or small sample size.
患者报告的结局（PRO）广泛应用于生活质量（QOL）研究、健康结果研究和临床试验中。健康当局提倡 PRO 的重要性。患者报告结局测量信息系统（PROMIS）是使用项目反应理论（IRT）的 PRO 标准化测量的集合。然而，在以 PRO 为终点的临床试验中，观察到的分数通常用于功效估计而不是 IRT 分数。本文旨在通过 IRT 模型填补这一空白，并估计以 PROMIS 测量为终点的两臂临床试验中的功效。
我们进行了一系列模拟研究，以研究具有验证的 PROMIS 措施的 IRT 功效，控制因素包括样本量、效应大小、项目数量和缺失数据比例。
我们的结果表明，样本量、效应大小和项目数量是基于 IRT 的 PROMIS 措施功效估计的重要指标。当效应量较小时且样本量有限时，IRT 模型比闭式公式提供更高的功效。
应该使用基于 IRT 的模拟来进行两臂临床试验的功效估计，特别是当效应量较小或样本量较小时。
