Miller Christopher J, Farrar John T
Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
J Pain. 2025 May;30:104759. doi: 10.1016/j.jpain.2024.104759. Epub 2024 Dec 15.
Minimum clinically important differences (MCIDs) in acute pain intensity have not been well established. Conventional approaches for estimating MCIDs require an independent reference scale, with a threshold that must be presumed to accurately classify meaningful change in pain for all study participants, to serve as an anchor. The double stopwatch technique is the gold standard for measuring the time to meaningful relief, where participants actively press the second stopwatch when they experience pain relief that is meaningful to them. This technique eliminates the problem of misclassification with arbitrary anchors at a single time point, but the censored nature of the data is not amenable for determining MCIDs using standard methods. We propose a stopwatch-based MCID methodology that employs the double stopwatch technique to identify individualized thresholds for meaningful change in pain. This approach enables direct classification of changes in pain for each participant based on whether they perceived the change as meaningful and whether it exceeded the study cut-off being tested. Pain values of participants who do not achieve meaningful relief are incorporated into the analysis to address censoring and avoid bias. The performance (e.g., sensitivity, specificity) of different thresholds to serve as an MCID can be estimated using standard approaches with variance estimates derived by cluster bootstrapping. The advantages of the stopwatch-based MCID methodology are illustrated relative to a conventional approach using data from a randomized trial in third molar extraction. PERSPECTIVE: This article describes a methodology for determining MCIDs using the double stopwatch technique, the gold standard for assessing meaningful changes in acute pain. This methodology can be used to establish MCIDs in different acute pain settings, providing a useful basis to evaluate the meaningfulness of clinical trial results.
急性疼痛强度的最小临床重要差异(MCIDs)尚未得到很好的确立。估计MCIDs的传统方法需要一个独立的参考量表,该量表有一个阈值,必须假定它能准确地对所有研究参与者疼痛的有意义变化进行分类,以此作为参照标准。双秒表技术是测量达到有意义缓解所需时间的金标准,即当参与者体验到对他们来说有意义的疼痛缓解时,他们主动按下第二个秒表。该技术消除了在单个时间点使用任意参照标准导致的错误分类问题,但数据的删失性质不适合使用标准方法来确定MCIDs。我们提出了一种基于秒表的MCID方法,该方法采用双秒表技术来确定疼痛有意义变化的个体化阈值。这种方法能够根据每个参与者是否认为变化有意义以及变化是否超过所测试的研究临界值,直接对其疼痛变化进行分类。未实现有意义缓解的参与者的疼痛值被纳入分析,以处理删失数据并避免偏差。可以使用标准方法并通过聚类自抽样得出方差估计值,来估计用作MCID的不同阈值的性能(如敏感性、特异性)。相对于使用第三磨牙拔除随机试验数据的传统方法,本文阐述了基于秒表的MCID方法的优势。观点:本文描述了一种使用双秒表技术确定MCIDs的方法,双秒表技术是评估急性疼痛有意义变化的金标准。该方法可用于在不同急性疼痛情况下确立MCIDs,为评估临床试验结果的意义提供有用依据。