Towards precision medicine in psychosis: Benefits and challenges of multimodal multicenter studies - PSYSCAN: translating neuroimaging findings from research into clinical practice
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Tognin, Stefania; Hell, Hendrika H. van; Merritt, Kate; Winter-van Rossum, Inge; Bossong, Matthijs G.; Kempton, Matthew J.; Modinos, Gemma; Fusar-Poli, Paolo; Mechelli, Andrea; Dazzan, Paola; Maat, Arija; De Haan, Lieuwe; Crespo Facorro, Benedicto
Fecha
2020Derechos
Attribution 4.0 International. © The Author(s) 2019. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. This is an Open Access article distributed under the terms of the Creative Commons Attribution License.
Publicado en
Schizophrenia Bulletin, 2020, 46(2), 432-441
Editorial
Oxford University Press
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Palabras clave
Psychosis
First episode of psychosis
Clinical high risk of psychosis
PSYSCAN
Neuroimaging
MRI
Machine learning
Prediction
Resumen/Abstract
In the last 2 decades, several neuroimaging studies investigated brain abnormalities associated with the early stages of psychosis in the hope that these could aid the prediction of onset and clinical outcome. Despite advancements in the field, neuroimaging has yet to deliver. This is in part explained by the use of univariate analytical techniques, small samples and lack of statistical power, lack of external validation of potential biomarkers, and lack of integration of nonimaging measures (eg, genetic, clinical, cognitive data). PSYSCAN is an international, longitudinal, multicenter study on the early stages of psychosis which uses machine learning techniques to analyze imaging, clinical, cognitive, and biological data with the aim of facilitating the prediction of psychosis onset and outcome. In this article, we provide an overview of the PSYSCAN protocol and we discuss benefits and methodological challenges of large multicenter studies that employ neuroimaging measures.
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