RT Journal Article
SR Electronic
T1 Low predictive power of clinical features for relapse prediction after antidepressant discontinuation in a naturalistic setting
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.01.28.922500
DO 10.1101/2020.01.28.922500
A1 Isabel M. Berwian
A1 Julia G. Wenzel
A1 Leonie Kuehn
A1 Inga Schnuerer
A1 Erich Seifritz
A1 Klaas E. Stephan
A1 Henrik Walter
A1 Quentin J. M. Huys
YR 2020
UL http://biorxiv.org/content/early/2020/01/28/2020.01.28.922500.abstract
AB Background 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.Method 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 six 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.Results 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.Conclusion and Relevance 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.