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基于瞬时评估的疼痛指数组合可预测纤维肌痛综合征患者的安慰剂反应。

A combination of pain indices based on momentary assessments can predict placebo response in patients with fibromyalgia syndrome.

机构信息

Dornsife Center for Self-Report Science, Center for Economic & Social Research, University of Southern California, Los Angeles, CA, United States.

Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité-Universitätsmedizin Berlin, Berlin, Germany.

出版信息

Pain. 2021 Feb 1;162(2):543-551. doi: 10.1097/j.pain.0000000000002025.

Abstract

Many factors are known to affect assay sensitivity; however, limited attention has been devoted to understanding whether characteristics of patients' baseline pain impact assay sensitivity. In this study, we tested whether a combination of 3 baseline pain indices based on ecological momentary assessments (EMA) could detect patients with enhanced responses to placebo. The analysis was conducted with secondary data from 2 clinical trials in fibromyalgia patients (N = 2084). For each patient, pain intensity, pain variability (individual SD), and pain consistency (first-order autocorrelation) were computed from baseline EMA. A latent profile analysis identified 3 subgroups of patients based on these indices. Group 1 (n = 857, 41.3%) showed the lowest pain intensity levels, coupled with the highest consistency and greatest variability of pain. Group 3 (n = 110, 5.3%) showed the opposite pattern, and group 2 (n = 1109, 53.4%) showed intermediate levels on all pain indices. It was then tested whether the subgroups moderated treatment effects (changes in pain for active treatment vs placebo) using repeated-measures analysis of variance. Treatment effects varied significantly between subgroups. Patients in group 3 demonstrated greater reduction in pain in response to placebo then those in groups 1 and 2. Further analysis showed that the removal of patients in class 3 would significantly enhance the observed treatment effect by 8% to 15%. In conclusion, profiles of pain characteristics derived from baseline EMA may be useful for detecting patient subgroups with enhanced placebo responses that can diminish assay sensitivity in pain clinical trials.

摘要

许多因素都已知会影响检测的灵敏度;然而,人们很少关注患者基线疼痛特征是否会影响检测的灵敏度。在这项研究中,我们测试了基于电子病历评估(EMA)的 3 种基线疼痛指数的组合是否可以检测出对安慰剂反应增强的患者。对纤维肌痛患者的 2 项临床试验的二级数据(N=2084)进行了分析。对于每个患者,从基线 EMA 计算疼痛强度、疼痛变异性(个体 SD)和疼痛一致性(一阶自相关)。潜在剖面分析根据这些指数确定了 3 组患者亚组。第 1 组(n=857,41.3%)疼痛强度水平最低,疼痛一致性和变异性最高。第 3 组(n=110,5.3%)表现出相反的模式,第 2 组(n=1109,53.4%)在所有疼痛指数上表现出中等水平。然后使用重复测量方差分析测试亚组是否调节了治疗效果(主动治疗与安慰剂相比疼痛的变化)。治疗效果在亚组之间有显著差异。与第 1 组和第 2 组相比,第 3 组的患者在安慰剂治疗后疼痛减轻更明显。进一步分析表明,去除第 3 组患者将使观察到的治疗效果显著提高 8%至 15%。总之,从基线 EMA 得出的疼痛特征谱可能有助于检测出对安慰剂反应增强的患者亚组,这些患者亚组可能会降低疼痛临床试验的检测灵敏度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/afff/7854765/5c7587791962/nihms-1613854-f0001.jpg

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