Evidence mapPaperPMID 42108749Full record

Observational studyAddiction biology2026

Investigating Factors Associated With Spontaneous Remission in Individuals With Alcohol Use Disorder-Results From a Multi-Site Longitudinal Cohort Study.

Judith Zaiser, Johannes Nitsche, Sabine Hoffmann, Sina Vetter, Nadja Samia Bahr, Clarissa Grundmann, Samanda Krasniqi, Fabian Arntz, Jens Strehle, Michael Marxen and 9 more

Abstract readMulticenter StudyObservational Study
In one paragraph

Observational study in Addiction biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

19 authors.

Judith ZaiserDepartment of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim/Heidelberg, Germany.ORCID https://orcid.org/0009-0003-2863-8284
Johannes NitscheHector Institute for Artificial Intelligence in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim/Heidelberg, Germany.
Sabine HoffmannDepartment of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim/Heidelberg, Germany.ORCID https://orcid.org/0000-0001-9713-2939
Sina VetterDepartment of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim/Heidelberg, Germany.
Nadja Samia BahrDepartment of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany.ORCID https://orcid.org/0009-0005-9538-6288
Clarissa GrundmannDepartment of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany.
Samanda KrasniqiDepartment of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Fabian ArntzDepartment of Sports and Health Sciences, University of Potsdam, Potsdam, Germany.
Jens StrehleCenter for Information Services and High Performance Computing (ZIH), Technische Universität Dresden, Dresden, Germany.
Michael MarxenDepartment of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany.ORCID https://orcid.org/0000-0001-8870-0041
Sabine Vollstädt-KleinDepartment of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim/Heidelberg, Germany.
Michael A RappSocial and Preventive Medicine, Department of Sports and Health Sciences, Intra-Faculty Unit "Cognitive Sciences", Faculty of Human Science, Faculty of Health Sciences Brandenburg, Research Area Services Research and e-Health, University of Potsdam, Potsdam, Germany.
Bernd LenzDepartment of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim/Heidelberg, Germany.ORCID https://orcid.org/0000-0001-6086-0924
Rainer SpanagelInstitute for Psychopharmacology, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim/Heidelberg, Germany.ORCID https://orcid.org/0000-0003-2151-4521
Michael SmolkaSection of Systems Neuroscience, Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany.ORCID https://orcid.org/0000-0001-5398-5569
Andreas HeinzDepartment of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany.
Emanuel SchwarzHector Institute for Artificial Intelligence in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim/Heidelberg, Germany.
Falk KieferDepartment of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim/Heidelberg, Germany.
Patrick BachDepartment of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim/Heidelberg, Germany.

Funding

Deutsche Forschungsgemeinschaft 402170461 - TRR 265German Center for Mental Health (DZPG) 01EE2504D
6 · The paper itself

Abstract

Alcohol use disorder (AUD) is considered a chronic disorder with a highly variable course. Understanding this variability is crucial for identifying factors associated with persistence versus spontaneous remission. We analysed data from N = 462 individuals with AUD in an observational longitudinal cohort study to identify factors associated with spontaneous remission. All participants met Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria for AUD at study entry and were reassessed after 1 year, in which they were classified as being in spontaneous remission (n = 107), falling below the ≥ 2-criteria threshold for AUD (n = 87) or continuing to meet AUD criteria (n = 296). Groups were compared on socio-demographic, clinical and substance use variables at baseline and after 1 year. Additionally, we used machine learning models to identify baseline characteristics predicting a persistent course of AUD. Between-group comparisons revealed that individuals who experienced spontaneous remission reported significantly lower AUD severity (F(2,459) = 25.17, p < 0.001), lower levels of alcohol intake (F(2,459) = 8.31, p = 0.013) and fewer drinking days (F(2,459) = 11.91, p < 0.001) at baseline and after 1 year. Machine learning analysis demonstrated moderate classification performance (AUC = 0.679), with the Alcohol Use Disorders Identification Test (AUDIT) sum score being the most informative predictor for group classification. Our findings indicate significant differences between spontaneously remitted and non-remitted individuals on key alcohol-related variables, supporting the clinical validity of remission as defined by the National Institute on Alcohol Abuse and Alcoholism (NIAAA). In addition, baseline characteristics may help identify individuals at risk of persistent AUD, enabling earlier identification of those who may benefit from specialized treatment.

trial registrationDRKS number: DRKS00020580.

Indexed as

AlcoholismRemission, SpontaneousAdultCohort StudiesFemaleHumansLongitudinal StudiesMachine LearningMaleMiddle AgedSeverity of Illness Indexaddictionalcohol use disorderAUD criteriaAUDITAUD remissionmachine learning

Identifiers

PMID42108749
PMCPMC13158517

What Socratic holds

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LicenceCC BY
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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 Socratic graph.