Scholten Saskia, Herzog Philipp, Glombiewski Julia Anna, Kaiser Tim
Pain and Psychotherapy Research Lab, Department of Psychology, University of Kaiserslautern-Landau, Landau, Germany.
Department of Psychology, Harvard University, Cambridge, MA, United States.
Pain. 2025 Feb 1;166(2):420-427. doi: 10.1097/j.pain.0000000000003363. Epub 2024 Aug 2.
This is the first study to empirically determine the potential for data-driven personalization in the context of chronic primary pain (CPP). Effect sizes of psychological treatments for individuals with CPP are small to moderate on average. Aiming for better treatment outcomes for the individual patient, the call to personalize CPP treatment increased over time. However, empirical evidence that personalization of psychological treatments can optimize treatment outcomes in CPP is needed. This study seeks to estimate heterogeneity of treatment effect for cognitive behavioral therapy (CBT) as the psychological treatment approach for CPP with the greatest evidence base. For this purpose, a Bayesian variance ratio meta-regression is conducted using updated data from 2 recently published meta-analyses with randomized controlled trials comparing CBT delivered face-to-face to treatment-as-usual or waiting list controls. Heterogeneity in patients with CPP would be reflected by a larger overall variance in the post-treatment score compared with the control group. We found first evidence for an individual treatment effect in CBT compared with the control group. The estimate for the intercept was 0.06, indicating a 6% higher variance of end point values in the intervention groups. However, this result warrants careful consideration. Further research is needed to shed light on the heterogeneity of psychological treatment studies and thus to uncover the full potential of data-driven personalized psychotherapy for patients with CPP.A Bayesian variance ratio meta-regression indicates empirical evidence that data-driven personalized psychotherapy for patients with chronic primary pain could increase effects of cognitive behavioral therapy.
这是第一项通过实证确定慢性原发性疼痛（CPP）背景下数据驱动个性化潜力的研究。平均而言，针对CPP患者的心理治疗效果大小为小到中等。为了使个体患者获得更好的治疗效果，随着时间的推移，个性化CPP治疗的呼声越来越高。然而，需要有实证证据证明心理治疗的个性化能够优化CPP的治疗效果。本研究旨在估计认知行为疗法（CBT）作为有最充分证据基础的CPP心理治疗方法的治疗效果异质性。为此，使用来自最近发表的2项荟萃分析的更新数据进行贝叶斯方差比元回归，这些荟萃分析采用随机对照试验，将面对面实施的CBT与常规治疗或等待名单对照进行比较。与对照组相比，CPP患者的异质性将通过治疗后分数中更大的总体方差来体现。我们首次发现与对照组相比，CBT存在个体治疗效果的证据。截距估计值为0.06，表明干预组终点值的方差高6%。然而，这一结果需要谨慎考虑。需要进一步研究以阐明心理治疗研究的异质性，从而揭示数据驱动的个性化心理治疗对CPP患者的全部潜力。贝叶斯方差比元回归表明有实证证据显示，针对慢性原发性疼痛患者的数据驱动个性化心理治疗可增强认知行为疗法的效果。
