Treating adolescent depression effectively requires providing interventions that are optimally suited to patients’ individual characteristics and needs. Therefore, we aim to develop an algorithm that matches patients with optimal treatment among cognitive-behavioral therapy (CBT), fluoxetine (FLX), and combination treatment (COMB). We leveraged data from a completed clinical trial, the Treatment for adolescents with depression study, where a wide range of demographic, clinical, and psychosocial measures were collected from adolescents diagnosed with major depressive disorder prior to treatment. Machine-learning techniques were employed to derive a model that predicts treatment response (week 12 children’s depression rating scale-revised [CDRS-R]) to CBT, FLX, and COMB. The resulting model successfully identified subgroups of patients that respond preferentially to specific types of treatment. Specifically, our model identified a subgroup of patients (25%) that achieved on average a 16.9 point benefit on the CDRS-R from FLX compared to CBT. The model also identified a subgroup of patients (50%) that achieved an average benefit up to 19.0 points from COMB compared to CBT. Physical illness and disability were identified as overall predictors of response to treatment, regardless of treatment type, whereas baseline CDRS-R, psychosomatic symptoms, school missed, view of self, treatment expectations, and attention problems determined the patients’ response to specific treatments. The model developed in this study provides a critical starting point for personalized treatment planning for adolescent depression.

有效治疗青少年抑郁症需要提供最适合患者个人特征和需求的干预措施。因此，我们的目标是开发一种算法，将患者与认知行为疗法 (CBT)、氟西汀 (FLX) 和联合治疗 (COMB) 之间的最佳治疗相匹配。我们利用了一项已完成的临床试验的数据，即青少年抑郁症治疗研究，该研究从治疗前诊断出患有重度抑郁症的青少年中收集了广泛的人口统计学、临床和心理社会措施。机器学习技术被用来推导出一个模型，该模型预测对 CBT、FLX 和 COMB 的治疗反应（第 12 周儿童抑郁评定量表修订版 [CDRS-R]）。由此产生的模型成功识别出优先响应特定类型治疗的患者亚组。具体而言，我们的模型确定了一个患者亚组 (25%)，与 CBT 相比，FLX 的 CDRS-R 平均获得了 16.9 分的收益。该模型还确定了一个患者亚组 (50%)，与 CBT 相比，这些患者从 COMB 中获得了高达 19.0 分的平均收益。身体疾病和残疾被确定为治疗反应的总体预测因素，无论治疗类型如何，而基线 CDRS-R、心身症状、缺课、自我观、治疗期望和注意力问题决定了患者对特定治疗的反应。本研究中开发的模型为青少年抑郁症的个性化治疗计划提供了一个关键起点。