The development and internal evaluation of a predictive model to identify for whom Mindfulness-Based Cognitive Therapy (MBCT) offers superior relapse prevention for recurrent depression versus maintenance antidepressant medication.
The development and internal evaluation of a predictive model to identify for whom Mindfulness-Based Cognitive Therapy (MBCT) offers superior relapse prevention for recurrent depression versus maintenance antidepressant medication.
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DOI：
10.1177/21677026221076832
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发表时间：
2023-01
期刊：
影响因子：
--
通讯作者：
Schweizer S
中科院分区：
文献类型：
--
作者：
Cohen ZD;DeRubeis RJ;Hayes R;Watkins ER;Lewis G;Byng R;Byford S;Crane C;Kuyken W;Dalgleish T;Schweizer S
即使在成功的药物和/或心理干预之后，抑郁症也很容易复发。我们的目的是开发临床预测模型，以告知患有复发性抑郁症的成年人选择抗抑郁药物（ADM）维持治疗还是转向基于正念的认知治疗（MBCT）。使用之前发布的数据 (N = 424)，我们使用弹性网络回归构建了预后模型，该模型结合了人口统计学、临床和心理因素，以预测 ADM 或 MBCT 下 24 个月的复发。只有 ADM 模型（辨别性能：曲线下面积 [AUC] = .68）比基线抑郁严重程度（AUC = .54；单尾 DeLong 检验：z = 2.8，p = .003）更好地预测复发。与维持 ADM 的个体相比，ADM 预后最差的个体转为 MBCT 的结果更好（分别为 48% 和 70% 的复发；生存时间更长，z = -2.7，p = .008）。对于 ADM 预后为中度至良好的个体，两种治疗导致复发的可能性相似。如果重复的话，结果表明预测模型可以为预防复发性抑郁症复发的临床决策提供信息。
Depression is highly recurrent, even following successful pharmacological and/or psychological intervention. We aimed to develop clinical prediction models to inform adults with recurrent depression choosing between antidepressant medication (ADM) maintenance or switching to mindfulness-based cognitive therapy (MBCT). Using previously published data (N = 424), we constructed prognostic models using elastic-net regression that combined demographic, clinical, and psychological factors to predict relapse at 24 months under ADM or MBCT. Only the ADM model (discrimination performance: area under the curve [AUC] = .68) predicted relapse better than baseline depression severity (AUC = .54; one-tailed DeLong’s test: z = 2.8, p = .003). Individuals with the poorest ADM prognoses who switched to MBCT had better outcomes compared with individuals who maintained ADM (48% vs. 70% relapse, respectively; superior survival times, z = −2.7, p = .008). For individuals with moderate to good ADM prognoses, both treatments resulted in similar likelihood of relapse. If replicated, the results suggest that predictive modeling can inform clinical decision-making around relapse prevention in recurrent depression.
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