TY - JOUR

T1 - Towards Precision Medicine in Psychosis

T2 - Benefits and Challenges of Multimodal Multicenter Studies-PSYSCAN: Translating Neuroimaging Findings From Research into Clinical Practice

AU - Tognin, Stefania

AU - van Hell, Hendrika H

AU - Merritt, Kate

AU - Winter-van Rossum, Inge

AU - Bossong, Matthijs G

AU - Kempton, Matthew J

AU - Modinos, Gemma

AU - Fusar-Poli, Paolo

AU - Mechelli, Andrea

AU - Dazzan, Paola

AU - Maat, Arija

AU - de Haan, Lieuwe

AU - Crespo-Facorro, Benedicto

AU - Glenthøj, Birte

AU - Lawrie, Stephen M

AU - McDonald, Colm

AU - Gruber, Oliver

AU - van Amelsvoort, Therese

AU - Arango, Celso

AU - Kircher, Tilo

AU - Nelson, Barnaby

AU - Galderisi, Silvana

AU - Bressan, Rodrigo

AU - Kwon, Jun S

AU - Weiser, Mark

AU - Mizrahi, Romina

AU - Sachs, Gabriele

AU - Maatz, Anke

AU - Kahn, René

AU - McGuire, Phillip

AU - PSYSCAN Consortium

PY - 2020

Y1 - 2020

N2 - 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.

AB - 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.

U2 - 10.1093/schbul/sbz067

DO - 10.1093/schbul/sbz067

M3 - Journal article

C2 - 31424555

VL - 46

SP - 432

EP - 441

JO - Schizophrenia Bulletin

JF - Schizophrenia Bulletin

SN - 0586-7614

IS - 2

ER -