Efforts to develop an individualized treatment rule (ITR) to optimize major depressive disorder (MDD) treatment with antidepressant medication (ADM), psychotherapy, or combined ADM-psychotherapy have been hampered by small samples, small predictor sets, and suboptimal analysis methods. Analyses of large administrative databases designed to approximate experiments followed iteratively by pragmatic trials hold promise for resolving these problems. The current report presents a proof-of-concept study using electronic health records (EHR) of n = 43,470 outpatients beginning MDD treatment in Veterans Health Administration Primary Care Mental Health Integration (PC-MHI) clinics, which offer access not only to ADMs but also psychotherapy and combined ADM-psychotherapy. EHR and geospatial databases were used to generate an extensive baseline predictor set (5,865 variables). The outcome was a composite measure of at least one serious negative event (suicide attempt, psychiatric emergency department visit, psychiatric hospitalization, suicide death) over the next 12 months. Best-practices methods were used to adjust for nonrandom treatment assignment and to estimate a preliminary ITR in a 70% training sample and to evaluate the ITR in the 30% test sample. Statistically significant aggregate variation was found in overall probability of the outcome related to baseline predictors (AU-ROC = 0.68, S.E. = 0.01), with test sample outcome prevalence of 32.6% among the 5% of patients having highest predicted risk compared to 7.1% in the remainder of the test sample. The ITR found that psychotherapy-only was the optimal treatment for 56.0% of patients (roughly 20% lower risk of the outcome than if receiving one of the other treatments) and that treatment type was unrelated to outcome risk among other patients. Change in aggregate treatment costs of implementing this ITR would be negligible, as 16.1% fewer patients would be prescribed ADMs and 2.9% more would receive psychotherapy. A pragmatic trial would be needed to confirm the accuracy of the ITR.

制定个体化治疗规则（ITR）以优化抗抑郁药物（ADM）、心理治疗或ADM-心理治疗联合治疗的重度抑郁症（MDD）治疗的努力受到小样本、小预测变量集和次优分析方法的阻碍。对大型管理数据库的分析旨在近似实验，然后迭代进行实用试验，有望解决这些问题。当前的报告提出了一项概念验证研究，使用电子健康记录 (EHR)，对43,470名 在退伍军人健康管理局初级保健心理健康整合 (PC-MHI) 诊所开始 MDD 治疗的门诊患者进行了研究，该诊所不仅提供 ADM 服务，还提供医疗服务。还有心理治疗和 ADM 联合心理治疗。EHR 和地理空间数据库用于生成广泛的基线预测变量集（5,865 个变量）。结果是对未来 12 个月内至少一次严重负面事件（自杀未遂、精神科急诊就诊、精神科住院、自杀死亡）的综合衡量。使用最佳实践方法来调整非随机治疗分配，估计 70% 训练样本中的初步 ITR，并评估 30% 测试样本中的 ITR。与基线预测因子相关的结果总体概率存在统计学上显着的总体变化（AU-ROC = 0.68，SE = 0.01），测试样本结果在 5% 的预测风险最高的患者中的患病率为 32.6%，而预测风险为 7.1%在测试样本的其余部分中。ITR 发现，对于 56.0% 的患者来说，仅进行心理治疗是最佳治疗方法（与接受其他治疗之一相比，结果风险大约降低 20%），并且该治疗类型与其他患者的结果风险无关。实施该 ITR 的总治疗成本变化可以忽略不计，因为接受 ADM 治疗的患者减少了 16.1%，接受心理治疗的患者增加了 2.9%。需要进行务实的试验来确认 ITR 的准确性。