Combining MRI and clinical data to detect high relapse risk after the first episode of psychosis

Solanes, Aleix ; Mezquida, Gisela ; Janssen, Joost ; Amoretti, Silvia ; Lobo, Antonio (Universidad de Zaragoza) ; González-Pinto, Ana ; Arango, Celso ; Vieta, Eduard ; Castro-Fornieles, Josefina ; Bergé, Daniel ; Albacete, Auria ; Giné, Eloi ; Parellada, Mara ; Bernardo, Miguel ; Bioque, Miquel ; Morén, Constanza ; Pina-Camacho, Laura ; Díaz-Caneja, Covadonga M. ; Zorrilla, Iñaki ; Corres, Edurne Garcia ; De-La-Camara, Concepción ; Barcones, Fe ; Escarti, María José ; Aguilar, Eduardo Jesus ; Legido, Teresa ; Martin, Marta ; Verdolini, Norma ; Martinez-Aran, Anabel ; Baeza, Immaculada ; de la Serna, Elena ; Contreras, Fernando ; Bobes, Julio ; García-Portilla, María Paz ; Sanchez-Pastor, Luis ; Rodriguez-Jimenez, Roberto ; Usall, Judith ; Butjosa, Anna ; Salgado-Pineda, Pilar ; Salvador, Raymond ; Pomarol-Clotet, Edith ; Radua, Joaquim

Resumen: Detecting patients at high relapse risk after the first episode of psychosis (HRR-FEP) could help the clinician adjust the preventive treatment. To develop a tool to detect patients at HRR using their baseline clinical and structural MRI, we followed 227 patients with FEP for 18–24 months and applied MRIPredict. We previously optimized the MRI-based machine-learning parameters (combining unmodulated and modulated gray and white matter and using voxel-based ensemble) in two independent datasets. Patients estimated to be at HRR-FEP showed a substantially increased risk of relapse (hazard ratio = 4.58, P < 0.05). Accuracy was poorer when we only used clinical or MRI data. We thus show the potential of combining clinical and MRI data to detect which individuals are more likely to relapse, who may benefit from increased frequency of visits, and which are unlikely, who may be currently receiving unnecessary prophylactic treatments. We also provide an updated version of the MRIPredict software.

Idioma: Inglés

DOI: 10.1038/s41537-022-00309-w

Año: 2022

Publicado en: Schizophrenia 8, 1 (2022), 1-9
ISSN: 2754-6993

Factor impacto JCR: 0.0 (2022)

Categ. JCR: PSYCHIATRY

Financiación: info:eu-repo/grantAgreement/EC/H2020/115916/EU/Psychiatric Ratings using Intermediate Stratified Markers/PRISM
Financiación: info:eu-repo/grantAgreement/EC/H2020/777394/EU/Autism Innovative Medicine Studies – 2 – Trials/AIMS-2-TRIALS
Financiación: info:eu-repo/grantAgreement/ES/MICIU-ISCIII-FEDER/PI08-0208
Financiación: info:eu-repo/grantAgreement/ES/MICIU-ISCIII-FEDER/PI11-00325
Financiación: info:eu-repo/grantAgreement/ES/MICIU-ISCIII-FEDER/PI14-00292
Financiación: info:eu-repo/grantAgreement/ES/MICIU-ISCIII-FEDER/PI14-00612
Financiación: info:eu-repo/grantAgreement/ES/MICIU-ISCIII-FEDER/PI14-01148
Financiación: info:eu-repo/grantAgreement/ES/MICIU-ISCIII-FEDER/PI17-00481
Financiación: info:eu-repo/grantAgreement/ES/MICIU-ISCIII-FEDER/PI17-01997
Financiación: info:eu-repo/grantAgreement/ES/MICIU-ISCIII-FEDER/PI18-01055
Financiación: info:eu-repo/grantAgreement/ES/MICIU-ISCIII-FEDER/PI19-00394
Financiación: info:eu-repo/grantAgreement/ES/MICIU-ISCIII-FEDER/PI19-00766
Financiación: info:eu-repo/grantAgreement/ES/MICIU-ISCIII-FEDER/PI20-00721
Financiación: info:eu-repo/grantAgreement/ES/MICIU-ISCIII-FEDER/PI20-01342
Financiación: info:eu-repo/grantAgreement/ES/MICIU-ISCIII-FEDER/PI21-00713
Financiación: info:eu-repo/grantAgreement/ES/MICIU/ISCIII/PI14-01151

Tipo y forma: Article (Published version)

Área (Departamento): Area Psiquiatría (Dpto. Medicina, Psiqu. y Derm.)