Combining MRI and clinical data to detect high relapse risk after the first episode of psychosis.
dc.contributor.author | Solanes Font, Aleix | |
dc.contributor.author | Mezquida, Gisela | |
dc.contributor.author | Janssen, Joost | |
dc.contributor.author | Amoretti, Silvia | |
dc.contributor.author | Lobo, Antonio | |
dc.contributor.author | González Pinto Arrillaga, Ana María | |
dc.contributor.author | Arango, Celso | |
dc.contributor.author | Vieta, Eduard | |
dc.contributor.author | Castro Fornieles, Josefina | |
dc.contributor.author | Bergé, Daniel | |
dc.contributor.author | Albacete, Auria | |
dc.contributor.author | Giné, Eloi | |
dc.contributor.author | Parellada, Mara | |
dc.contributor.author | Bernardo, Miguel | |
dc.contributor.author | PEPs Group | |
dc.contributor.author | Pomarol Clotet, Edith | |
dc.contributor.author | Radua, Joaquim | |
dc.date.accessioned | 2022-12-16T16:44:55Z | |
dc.date.available | 2022-12-16T16:44:55Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Schizophrenia 8 : (2022) // Article ID 100 | es_ES |
dc.identifier.issn | 2754-6993 | |
dc.identifier.uri | http://hdl.handle.net/10810/58848 | |
dc.description.abstract | 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. | es_ES |
dc.description.sponsorship | We would also like to thank the Instituto de Salud Carlos III, the Spanish Ministry of Science, Innovation, and Universities, the European Regional Development Fund (ERDF/FEDER), European Social Fund, “Investing in your future”, “A way of making Europe” (projects: PI08/0208, PI11/00325, PI14/00292, PI14/00612, PI14/01148, PI14/01151, PI17/00481, PI17/01997, PI18/01055, PI19/00394, PI19/00766, PI20/00721, PI20/01342, and PI21/00713; contracts: CP14/00041, JR19/00024, CPII19/00009, and CD20/00177); CERCA Program; Catalan Government, the Secretariat of Universities and Research of the Department of Enterprise and Knowledge (2017SGR01271, 2017SGR1355, and 2017SGR1365); Institut de Neurociències, Universitat de Barcelona; Madrid Regional Government (B2017/BMD-3740 AGES-CM-2); the University of the Basque Country (2019 321218ELCY GIC18/107); the Basque Government (2017111104); European Union Structural Funds, European Union Seventh Framework Program, European Union H2020 Program under the Innovative Medicines Initiative 2 Joint Undertaking (grant agreement No 115916, Project PRISM, and grant agreement No 777394, Project AIMS-2-TRIALS), Fundación Familia Alonso, Fundación Alicia Koplowitz and Fundación Mutua Madrileña. The funding organizations played no role in the study design, data collection, analysis, or manuscript approval. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Nature | es_ES |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/115916 | es_ES |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/777394 | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.title | Combining MRI and clinical data to detect high relapse risk after the first episode of psychosis. | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | © 2022. The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. | es_ES |
dc.rights.holder | Atribución 3.0 España | * |
dc.relation.publisherversion | https://www.nature.com/articles/s41537-022-00309-w | es_ES |
dc.identifier.doi | 10.1038/s41537-022-00309-w | |
dc.contributor.funder | European Commission | |
dc.departamentoes | Neurociencias | es_ES |
dc.departamentoeu | Neurozientziak | es_ES |
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