Women's Health Research Program, Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA.
Pain Med. 2011 Feb;12(2):260-7. doi: 10.1111/j.1526-4637.2010.01047.x. Epub 2011 Jan 25.
The objective of the study was to conduct an analysis of pooled data from pregabalin fibromyalgia clinical trials to determine which fibromyalgia symptom and function domains drive patient perception of improvement.
Data from three double-blind, placebo-controlled trials of pregabalin in fibromyalgia patients were pooled for this analysis. Changes in independent variables, including the Medical Outcomes Study 36-item Short-Form Health Survey, Medical Outcomes Study-Sleep Scale, sleep quality score from the daily sleep diary, pain score from the daily pain diary, Fibromyalgia Impact Questionnaire, and Multidimensional Assessment of Fatigue were analyzed as predictors of outcome on the dependent variable, Patient Global Impression of Change (PGIC). Correlation analysis assessed relationships between the independent variables and PGIC. Cluster analysis identified dependencies among variables, and a shrinkage and selection method and stepwise logistic regression determined rank order of variables.
Improvement in PGIC at endpoint showed highest correlation with pain improvement, fatigue, sleep, and work and physical function (0.4 < r < 0.6). Cluster analysis identified three main clusters of symptoms at endpoint: mood (anxiety and depression), pain and sleep, and function and fatigue. Pain was ranked as the most important outcome explaining variability in PGIC, followed by fatigue and sleep.
Pain, fatigue, and sleep associate most strongly with improvement in PGIC. Physical- and work-related function also correlated with patients' overall assessment of improvement. These domains and their respective outcome measures can be used to improve assessment of patients' response to treatment.
本研究旨在对普瑞巴林纤维肌痛临床试验的汇总数据进行分析,以确定哪些纤维肌痛症状和功能领域能使患者感知到改善。
对普瑞巴林治疗纤维肌痛患者的三项双盲、安慰剂对照临床试验的数据进行汇总,用于本分析。对包括医疗结局研究 36 项简明健康调查问卷、医疗结局研究睡眠量表、日常睡眠日记中的睡眠质量评分、日常疼痛日记中的疼痛评分、纤维肌痛影响问卷和多维疲劳评估在内的自变量的变化进行分析,以预测依赖变量(患者整体变化印象[PGIC])的结果。相关性分析评估了自变量与 PGIC 之间的关系。聚类分析确定了变量之间的依赖关系,收缩和选择方法以及逐步逻辑回归确定了变量的排序。
终点时 PGIC 的改善与疼痛改善、疲劳、睡眠以及工作和身体功能的相关性最高(0.4<r<0.6)。聚类分析在终点确定了三个主要的症状群:情绪(焦虑和抑郁)、疼痛和睡眠以及功能和疲劳。疼痛被列为解释 PGIC 变异性的最重要的结果,其次是疲劳和睡眠。
疼痛、疲劳和睡眠与 PGIC 的改善关联最强。与身体和工作相关的功能也与患者对改善的整体评估相关。这些领域及其各自的结果测量可用于改善对患者对治疗反应的评估。