Subtyping negative symptoms in first-episode psychosis: Contrasting persistent negative symptoms with a data-driven approach.

Early intervention service Functioning Group-based trajectory modeling Latent class growth analysis Predict Trajectory

Journal

Schizophrenia research
ISSN: 1573-2509
Titre abrégé: Schizophr Res
Pays: Netherlands
ID NLM: 8804207

Informations de publication

Date de publication:
10 2022
Historique:
received: 28 01 2022
revised: 04 08 2022
accepted: 04 09 2022
pubmed: 16 9 2022
medline: 26 10 2022
entrez: 15 9 2022
Statut: ppublish

Résumé

Persistent negative symptoms (PNS) are linked to poor functional outcomes and may be primary or caused by secondary factors. Although several studies have examined PNS in first-episode psychosis (FEP), a comparison with a data-driven approach is lacking. Here, we compared clinically defined PNS subgroups with class trajectories identified through latent growth modeling (LGM). Patients admitted to an early intervention service (N = 392) were classified as PNS (n = 105), secondary PNS (sPNS; n = 74), or non-PNS (n = 213) based on longitudinal data collected six to twelve months after admission. LGM was used to stratify patients based on similar negative symptom course over the same time period. Using multiple linear regression, we assessed the utility of both approaches in predicting Social and Occupational Functioning Assessment Scale (SOFAS) scores at two-year follow-up. Three negative symptom trajectories were identified: low and remitting (LR; n = 158), moderate and improving (MI; n = 163) and delayed partial response (DR; n = 71). Most non-PNS patients followed the LR trajectory, while patients with PNS or sPNS were generally divided between MI and DR. Both PNS classification and trajectory membership were significant predictors of two-year functional outcomes; the DR and MI trajectories predicted greater increases in SOFAS scores (DR: b = -19.14; MI: b = -11.54) than either sPNS (b = -9.19) or PNS (b = -6.46). These findings demonstrate that combining PNS and symptom-based stratification can predict functional outcomes more accurately than either taxonomy alone. Such a combined approach could yield significant advances in developing more targeted interventions for patients at risk for poor functional outcomes.

Identifiants

pubmed: 36108466
pii: S0920-9964(22)00343-7
doi: 10.1016/j.schres.2022.09.010
pii:
doi:

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

219-227

Subventions

Organisme : CIHR
ID : 68961
Pays : Canada

Informations de copyright

Copyright © 2022 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Conflicts of interest Salary awards include: FRSQ to R.J., and M.L.; a Canada Research Chair to A.M.; and a James McGill Professorship to M.L. M.L. reports grants from Otsuka Lundbeck Alliance and diaMentis, personal fees from Otsuka Canada, personal fees from Lundbeck Canada, grants and personal fees from Janssen, and personal fees from MedAvante-Prophase, outside the submitted work. R.J. reports receipt of grants, as well as speaker's and consultant's honoraria from Janssen, Lundbeck, Otsuka, Pfizer, Shire, Perdue, HLS and Myelin and royalties from Henry Stewart Talks. A.M. reports research funding for an investigator-initiated project from BMS Canada and honoraria for lectures and consulting activities (e.g., advisory board participation) with Otsuka and Lundbeck, all unrelated to the present article. All other authors report no competing interests.

Auteurs

Joshua Unrau (J)

Douglas Mental Health University Institute, Montreal, Canada; Department of Psychology, McGill University, Montreal, Canada.

Olivier Percie du Sert (O)

Douglas Mental Health University Institute, Montreal, Canada; Department of Psychiatry, McGill University, Montreal, Canada.

Ridha Joober (R)

Douglas Mental Health University Institute, Montreal, Canada; Department of Psychiatry, McGill University, Montreal, Canada.

Ashok Malla (A)

Douglas Mental Health University Institute, Montreal, Canada; Department of Psychiatry, McGill University, Montreal, Canada.

Martin Lepage (M)

Douglas Mental Health University Institute, Montreal, Canada; Department of Psychology, McGill University, Montreal, Canada; Department of Psychiatry, McGill University, Montreal, Canada. Electronic address: martin.lepage@mcgill.ca.

Delphine Raucher-Chéné (D)

Douglas Mental Health University Institute, Montreal, Canada; Department of Psychiatry, McGill University, Montreal, Canada; University of Reims Champagne-Ardenne, Cognition, Health, and Society Laboratory (EA 6291), Reims, France; Academic Department of Psychiatry, University Hospital of Reims, EPSM Marne, Reims, France.

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