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在自然环境中,临床特征对抗抑郁药停药后复发的预测能力较低。

Low predictive power of clinical features for relapse prediction after antidepressant discontinuation in a naturalistic setting.

机构信息

Princeton Neuroscience Institute, Princeton University, Princeton, USA.

Translational Neuromodeling Unit, University of Zurich and ETH Zurich, Zurich, Switzerland.

出版信息

Sci Rep. 2022 Jul 1;12(1):11171. doi: 10.1038/s41598-022-13893-9.

Abstract

The risk of relapse after antidepressant medication (ADM) discontinuation is high. Predictors of relapse could guide clinical decision-making, but are yet to be established. We assessed demographic and clinical variables in a longitudinal observational study before antidepressant discontinuation. State-dependent variables were re-assessed either after discontinuation or before discontinuation after a waiting period. Relapse was assessed during 6 months after discontinuation. We applied logistic general linear models in combination with least absolute shrinkage and selection operator and elastic nets to avoid overfitting in order to identify predictors of relapse and estimated their generalisability using cross-validation. The final sample included 104 patients (age: 34.86 (11.1), 77% female) and 57 healthy controls (age: 34.12 (10.6), 70% female). 36% of the patients experienced a relapse. Treatment by a general practitioner increased the risk of relapse. Although within-sample statistical analyses suggested reasonable sensitivity and specificity, out-of-sample prediction of relapse was at chance level. Residual symptoms increased with discontinuation, but did not relate to relapse. Demographic and standard clinical variables appear to carry little predictive power and therefore are of limited use for patients and clinicians in guiding clinical decision-making.

摘要

抗抑郁药(ADM)停药后复发的风险很高。复发的预测因素可以指导临床决策,但尚未确定。我们在抗抑郁药停药前的纵向观察研究中评估了人口统计学和临床变量。状态相关变量在停药后或停药前等待期后重新评估。停药后 6 个月评估复发。我们应用逻辑一般线性模型结合最小绝对收缩和选择算子和弹性网络,以避免过度拟合,从而识别复发的预测因素,并使用交叉验证估计其普遍性。最终样本包括 104 名患者(年龄:34.86(11.1),77%为女性)和 57 名健康对照者(年龄:34.12(10.6),70%为女性)。36%的患者出现复发。由全科医生治疗会增加复发的风险。虽然样本内统计分析表明具有合理的敏感性和特异性,但复发的样本外预测处于随机水平。停药后残留症状增加,但与复发无关。人口统计学和标准临床变量似乎没有多少预测能力,因此对患者和临床医生在指导临床决策方面的作用有限。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/91cb/9249776/d0d22d5e1a73/41598_2022_13893_Fig1_HTML.jpg

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