The objective of this study is to validate a placebo pill response predictive model—a biosignature—that classifies chronic pain patients into placebo responders (predicted-PTxResp) and nonresponders (predicted-PTxNonR) and test whether it can dissociate placebo and active treatment responses. The model, based on psychological and brain functional connectivity, was derived in our previous study and blindly applied to current trial participants. Ninety-four chronic low back pain (CLBP) patients were classified into predicted-PTxResp or predicted-PTxNonR and randomized into no treatment, placebo treatment, or naproxen treatment. To monitor analgesia, back pain intensity was collected twice a day: 3 weeks baseline, 6 weeks of treatment, and 3 weeks of washout. Eighty-nine CLBP patients were included in the intent-to-treat analyses and 77 CLBP patients in the per-protocol analyses. Both analyses showed similar results. At the group level, the predictive model performed remarkably well, dissociating the separate effect sizes of pure placebo response and pure active treatment response and demonstrating that these effects interacted additively. Pain relief was about 15% stronger in the predicted-PTxResp compared with the predicted-PTxNonR receiving either placebo or naproxen, and the predicted-PTxNonR successfully isolated the active drug effect. At a single subject level, the biosignature better predicted placebo nonresponders, with poor accuracy. One component of the biosignature (dorsolateral prefrontal cortex–precentral gyrus functional connectivity) could be generalized across 3 placebo studies and in 2 different cohorts—CLBP and osteoarthritis pain patients. This study shows that a biosignature can predict placebo response at a group level in the setting of a randomized controlled trial.

本研究的目的是验证安慰剂药丸反应预测模型（一种生物特征），该模型将慢性疼痛患者分为安慰剂反应者 ( predicted-PTxResp ) 和无反应者 ( predicted-PTxNonR )，并测试它是否可以区分安慰剂和主动治疗反应。该模型基于心理和大脑功能连接，是在我们之前的研究中得出的，并盲目应用于当前的试验参与者。94 名慢性腰痛 (CLBP) 患者被分为预测 PTxResp或预测 PTxNonR组，并随机分为不治疗、安慰剂治疗或萘普生治疗。为了监测镇痛效果，每天收集两次背痛强度：3 周基线、6 周治疗和 3 周清除。89 名 CLBP 患者被纳入意向治疗分析，77 名 CLBP 患者被纳入符合方案分析。两项分析都显示出相似的结果。在群体水平上，预测模型表现非常好，分离了纯安慰剂反应和纯主动治疗反应的单独效应大小，并证明这些效应相加地相互作用。与接受安慰剂或萘普生的预测 PTxNonR相比，预测 PTxResp 的疼痛缓解效果强约 15% ，并且预测 PTxNonR成功分离出活性药物作用。在单个受试者水平上，生物特征可以更好地预测安慰剂无反应者，但准确性较差。生物特征的一个组成部分（背外侧前额皮质-中央前回功能连接）可以在 3 项安慰剂研究和 2 个不同队列（CLBP 和骨关节炎疼痛患者）中推广。这项研究表明，在随机对照试验中，生物特征可以预测群体水平上的安慰剂反应。