Age as a moderating factor of treatment resistance in depression.


Journal

European psychiatry : the journal of the Association of European Psychiatrists
ISSN: 1778-3585
Titre abrégé: Eur Psychiatry
Pays: England
ID NLM: 9111820

Informations de publication

Date de publication:
20 04 2023
Historique:
medline: 9 5 2023
pubmed: 20 4 2023
entrez: 20 04 2023
Statut: epublish

Résumé

Treatment-resistant depression (TRD) is an important clinical challenge and may present differently between age groups. A total of 893 depressed patients recruited within the framework of the European research consortium "Group for the Studies of Resistant Depression" were assessed by generalized linear models regarding age effects (both as numerical and factorial predictors) on treatment outcome, number of lifetime depressive episodes, hospitalization time, and duration of the current episode. Effects of age as numerical predictor on the severity of common depressive symptoms, measured with Montgomery-Åsberg Depression Rating Scale (MADRS) for two-time points, were assessed by linear mixed models, respectively, for patients showing TRD and treatment response. A corrected Overall symptom load reflected by MADRS ( In this naturalistic sample of severely ill depressed patients, antidepressant treatment protocols were equally effective in addressing TRD in old age. However, specific symptoms such as sadness, appetite, and concentration showed an age-dependent presentation, impacting residual symptoms in severely affected TRD patients and calling for a precision approach by a better integration of age profiles in treatment recommendations.

Sections du résumé

BACKGROUND
Treatment-resistant depression (TRD) is an important clinical challenge and may present differently between age groups.
METHODS
A total of 893 depressed patients recruited within the framework of the European research consortium "Group for the Studies of Resistant Depression" were assessed by generalized linear models regarding age effects (both as numerical and factorial predictors) on treatment outcome, number of lifetime depressive episodes, hospitalization time, and duration of the current episode. Effects of age as numerical predictor on the severity of common depressive symptoms, measured with Montgomery-Åsberg Depression Rating Scale (MADRS) for two-time points, were assessed by linear mixed models, respectively, for patients showing TRD and treatment response. A corrected
RESULTS
Overall symptom load reflected by MADRS (
CONCLUSIONS
In this naturalistic sample of severely ill depressed patients, antidepressant treatment protocols were equally effective in addressing TRD in old age. However, specific symptoms such as sadness, appetite, and concentration showed an age-dependent presentation, impacting residual symptoms in severely affected TRD patients and calling for a precision approach by a better integration of age profiles in treatment recommendations.

Identifiants

pubmed: 37078509
doi: 10.1192/j.eurpsy.2023.17
pii: S0924933823000172
pmc: PMC10228354
doi:

Substances chimiques

Antidepressive Agents 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e35

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Auteurs

Alexander Kautzky (A)

Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.

Lucie Bartova (L)

Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.

Gernot Fugger (G)

Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.

Markus Dold (M)

Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.

Daniel Souery (D)

Centre Europèen de Psychologie Medicale, Université Libre de Bruxelles and Psy Pluriel, Brussels, Belgium.

Stuart Montgomery (S)

Imperial College London, University of London, London, UK.

Joseph Zohar (J)

Psychiatric Division, Chaim Sheba Medical Center, Tel HaShomer, Israel.

Julien Mendlewicz (J)

School of Medicine, Free University of Brussels, Brussels, Belgium.

Chiara Fabbri (C)

Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.

Alessandro Serretti (A)

Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.

Dan Rujescu (D)

Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.

Siegfried Kasper (S)

Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
Center for Brain Research, Medical University of Vienna, Vienna, Austria.

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Classifications MeSH