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