Towards Precision Medicine in Psychosis: Benefits and Challenges of Multimodal Multicenter Studies-PSYSCAN: Translating Neuroimaging Findings From Research into Clinical Practice
Tognin, Stefania; van Hell, Hendrika H.; 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; Glenthøj, Birte; Lawrie, Stephen M.; McDonald, Colm; Gruber, Oliver; van Amelsvoort, Therese; Arango, Celso; Kircher, Tilo; Nelson, Barnaby; Galderisi, Silvana; Bressan, Rodrigo; Kwon, Jun S.; Weiser, Mark; Mizrahi, Romina; Sachs, Gabriele; Maatz, Anke; Kahn, René; McGuire, Phillip; PSYSCAN Consortium
(2020) Schizophrenia Bulletin, volume 46, issue 2, pp. 432 - 441
(Article)
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
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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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Keywords: clinical high risk of psychosis, first episode of psychosis, machine learning, MRI, neuroimaging, prediction, psychosis, PSYSCAN, Psychiatry and Mental health, Journal Article
ISSN: 0586-7614
Publisher: Oxford University Press
Note: Publisher Copyright: © The Author(s) 2019. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
(Peer reviewed)