Evidence map›Paper›PMID 35778458›Full record

Observational studyScientific reports2022

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

Isabel M Berwian, Julia G Wenzel, Leonie Kuehn, Inga Schnuerer, Erich Seifritz, Klaas E Stephan, Henrik Walter, Quentin J M Huys

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.9field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 12 citations in OpenAlex.

  1. Do withdrawal symptoms predict depression relapse after antidepressant cessation?European archives of psychiatry and clinical neuroscience · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 4 countries.

Isabel M BerwianPrinceton Neuroscience Institute, Princeton University, Princeton, USA. iberwian@princeton.edu.
Julia G WenzelCharité Universitätsmedizin, Campus Charité Mitte, Berlin, Germany.
Leonie KuehnCharité Universitätsmedizin, Campus Charité Mitte, Berlin, Germany.
Inga SchnuererTranslational Neuromodeling Unit, University of Zurich and ETH Zurich, Zurich, Switzerland.
Erich SeifritzDepartment of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland.
Klaas E StephanTranslational Neuromodeling Unit, University of Zurich and ETH Zurich, Zurich, Switzerland.
Henrik Walter *Charité Universitätsmedizin, Campus Charité Mitte, Berlin, Germany.
Quentin J M Huys *Translational Neuromodeling Unit, University of Zurich and ETH Zurich, Zurich, Switzerland.
Charité - Universitätsmedizin Berlin · DEUniversity of Zurich · CHPrinceton University · USUniversity College London · GB

Funding

Swiss National Science Foundation 320030L_153449/1
6 · The paper itself

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.

Indexed as

Antidepressive AgentsAdultChronic DiseaseDisease ProgressionFemaleHumansLongitudinal StudiesMaleRecurrenceAntidepressive Agents

Identifiers

PMID35778458
PMCPMC9249776
OpenAlexW4283753310

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.