Supplementary Material for: Multicenter Validation of Individual Preoperative Motor Outcome Prediction for Deep Brain Stimulation in Parkinson’s Disease

Background: Subthalamic nucleus deep brain stimulation (STN DBS) is an established therapy for Parkinson’s disease (PD) patients suffering from motor response fluctuations despite optimal medical treatment, or severe dopaminergic side effects. Despite careful clinical selection and surgical procedures, some patients do not benefit from STN DBS. Preoperative prediction models are suggested to better predict individual motor response after STN DBS. We validate a preregistered model, DBS-PREDICT, in an external multicenter validation cohort. Methods: DBS-PREDICT considered eleven, solely preoperative, clinical characteristics and applied a logistic regression to differentiate between weak and strong motor responders. Weak motor response was defined as no clinically relevant improvement on the Unified Parkinson’s Disease Rating Scale (UPDRS) II, III, or IV, 1 year after surgery, defined as, respectively, 3, 5, and 3 points or more. Lower UPDRS III and IV scores and higher age at disease onset contributed most to weak response predictions. Individual predictions were compared with actual clinical outcomes. Results: 322 PD patients treated with STN DBS from 6 different centers were included. DBS-PREDICT differentiated between weak and strong motor responders with an area under the receiver operator curve of 0.76 and an accuracy up to 77%. Conclusion: Proving generalizability and feasibility of preoperative STN DBS outcome prediction in an external multicenter cohort is an important step in creating clinical impact in DBS with data-driven tools. Future prospective studies are required to overcome several inherent practical and statistical limitations of including clinical decision support systems in DBS care.

背景：对于接受最佳药物治疗但仍遭受运动反应波动或严重多巴胺能副作用的帕金森病（PD）患者，丘脑底核深部脑刺激（STN DBS）已成为一种成熟的治疗方法。尽管经过谨慎的临床选择和手术操作，部分患者并未从STN DBS中获益。术前预测模型被提出，以更好地预测STN DBS后的个体运动反应。本研究对外部多中心验证队列中预先注册的模型DBS-PREDICT进行验证。方法：DBS-PREDICT考虑了十一个仅限于术前的临床特征，并应用逻辑回归区分弱反应和强反应者。弱反应被定义为术后1年，在统一帕金森病评分量表（UPDRS）II、III或IV上无临床相关改善，分别定义为3、5和3分或更多。较低的UPDRS III和IV评分以及较高的疾病发病年龄对弱反应预测贡献最大。个体预测与实际临床结果进行了比较。结果：共有来自6个不同中心的322名接受STN DBS治疗的PD患者被纳入研究。DBS-PREDICT在受试者操作特征曲线下面积为0.76，准确率达到77%的情况下，区分了弱反应和强反应者。结论：证明在外部多中心队列中术前STN DBS结果预测的普适性和可行性，是利用数据驱动工具在DBS治疗中创造临床影响的重要一步。未来的前瞻性研究需要克服将临床决策支持系统纳入DBS护理中的内在实践和统计限制。