Multivariable prediction of functional outcome after first-episode psychosis: a crossover validation approach in EUFEST and PSYSCAN

Autor: Margot I. E. Slot, Maria F. Urquijo Castro, Inge Winter - van Rossum, Hendrika H. van Hell, Dominic Dwyer, Paola Dazzan, Arija Maat, Lieuwe De Haan, Benedicto Crespo-Facorro, Birte Y. Glenthøj, Stephen M. Lawrie, Colm McDonald, Oliver Gruber, Thérèse van Amelsvoort, Celso Arango, Tilo Kircher, Barnaby Nelson, Silvana Galderisi, Mark Weiser, Gabriele Sachs, Matthias Kirschner, the PSYSCAN Consortium, W. Wolfgang Fleischhacker, Philip McGuire, Nikolaos Koutsouleris, René S. Kahn
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Schizophrenia, Vol 10, Iss 1, Pp 1-11 (2024)
Druh dokumentu: article
ISSN: 2754-6993
DOI: 10.1038/s41537-024-00505-w
Popis: Abstract Several multivariate prognostic models have been published to predict outcomes in patients with first episode psychosis (FEP), but it remains unclear whether those predictions generalize to independent populations. Using a subset of demographic and clinical baseline predictors, we aimed to develop and externally validate different models predicting functional outcome after a FEP in the context of a schizophrenia-spectrum disorder (FES), based on a previously published cross-validation and machine learning pipeline. A crossover validation approach was adopted in two large, international cohorts (EUFEST, n = 338, and the PSYSCAN FES cohort, n = 226). Scores on the Global Assessment of Functioning scale (GAF) at 12 month follow-up were dichotomized to differentiate between poor (GAF current
Databáze: Directory of Open Access Journals