Predicting early clinical recovery in first-episode psychosis: development and external validation of a clinically interpretable multivariable model

A simple, interpretable logistic regression model based on routine clinical and cognitive variables can predict early recovery in FEP with acceptable generalisability. These findings support the use of transparent, clinically grounded models in early psychosis care and highlight the current limitations of genetic predictors for individualised treatment.

Authors

Institutions

Publication Details

Journal
The British Journal of Psychiatry
Published
2026-03-23
DOI
https://doi.org/10.1192/bjp.2026.10581
Primary Topic
Schizophrenia research and treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predicting early clinical recovery in first-episode psychosis: development and external validation of a clinically interpretable multivariable model

Cristina Romero-López-Alberca, Ángela Adelantado Ibáñez, Concepción de la Cámara, María Juncal-Ruiz et al.
The British Journal of Psychiatry
Schizophrenia research and treatment
article

Predicting early clinical recovery in first-episode psychosis: development and external validation of a clinically interpretable multivariable model

Cristina Romero-López-Alberca, Ángela Adelantado Ibáñez, Concepción de la Cámara, María Juncal-Ruiz, V. Ortíz-García de la Foz, A. Catalan, M. Gomez-Revuelta, C. Spuch, L. Julià, Á. González-Segura, Rosa Ayesa-Arriola, Anna Mané, Alexandra Roldán, Antonio Lobo, Silvia Amoretti, Paula Suárez-Pinilla, Josep Lluis Carrasco, Benedicto Crespo-Facorro, Sergi Mas, Iñaki Zorrilla, Covadonga Martinez Díaz-Caneja, Maria Alemany, Ana González-Pinto, Manuel J. Cuesta, Judith Usall, Javier Vázquez-Bourgon
article en

Abstract

A simple, interpretable logistic regression model based on routine clinical and cognitive variables can predict early recovery in FEP with acceptable generalisability. These findings support the use of transparent, clinically grounded models in early psychosis care and highlight the current limitations of genetic predictors for individualised treatment.

The British Journal of Psychiatry
Universidad Complutense de Madrid (ES), Hebron University (PS), Universidad de Cantabria (ES), University of the Basque Country (ES), Instituto Cajal (ES), Universidad de Zaragoza (ES), Hospital de Sant Pau (ES), Hospital General Universitario Gregorio Marañón (ES), Universidad de Cádiz (ES), Galicia Sur Biomedical Foundation (ES), Hospital de Basurto (ES), Marqués de Valdecilla University Hospital (ES), Vall d'Hebron Institut de Recerca (ES), Hospital Sierrallana (ES), Navarre Institute of Health Research (ES), Instituto de Investigación Marqués de Valdecilla (ES), Hospital Clínic de Barcelona (ES), Universitas Al Washliyah (ID), Sant Joan de Déu Research Foundation (ES), Instituto Ramón y Cajal de Investigación Sanitaria (ES), Parc Sanitari Sant Joan de Déu (ES), Instituto de Biomedicina de Sevilla (ES), Instituto de Investigación Sanitaria Aragón (ES), Community Options (United States) (US), Hospital Universitario Virgen del Rocío (ES), Consorci Institut D'Investigacions Biomediques August Pi I Sunyer (ES), Medical Research Network (US), Universitat de Barcelona (ES), Universidad de Navarra (ES)
Openalex Percentile: Top 22%
Schizophrenia research and treatment
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.