Development and Validation of Predictive Model for a Diagnosis of First Episode Psychosis Using the Multinational EU-GEI Case–control Study and Modern Statistical Learning Methods
Authors: Ajnakina Olesya , Fadilah Ihsan , Quattrone Diego , Arango Celso , Berardi Domenico , Bernardo Miguel , Bobes Julio , de Haan Lieuwe , Del-Ben Cristina Marta , Gayer-Anderson Charlotte , Stilo Simona , Jongsma Hannah E , Lasalvia Antonio , Tosato Sarah , Llorca Pierre-Michel , Menezes Paulo Rossi , Rutten Bart P , Santos Jose Luis , Sanjuán Julio , Selten Jean-Paul , Szöke Andrei , Tarricone Ilaria , D’Andrea Giuseppe , Tortelli Andrea , Velthorst Eva , Jones Peter B , Romero Manuel Arrojo , La Cascia Caterina , Kirkbride James B , van Os Jim , O’Donovan Michael , Morgan Craig , di Forti Marta , Murray Robin M ,   EU-GEI WP2 Group, Hubbard Kathryn , Beards Stephanie , Cristofalo Doriana , Parellada Mara , Cuadrado Pedro , Solano José Juan Rodríguez , Fraguas David , Andreu-Bernabeu Álvaro , Carracedo Angel , Bernardo Enrique García , Roldán Laura , López Gonzalo , Amoretti Silvia , Nacher Juan , Garcia-Portilla Paz , Costas Javier , Jiménez-López Estela , Matteis Mario , Castro Marta Rapado , González Emiliano , Martínez Covadonga , Sánchez Emilio , Durán-Cutilla Manuel , Franke Nathalie , Termorshuizen Fabian , van Dam Daniella , van der Ven Elsje , Messchaart Elles , Leboyer Marion , Schürhoff Franck , Jamain Stéphane , Baudin Grégoire , Ferchiou Aziz , Pignon Baptiste , Richard Jean- Romain , Charpeaud Thomas , Tronche Anne-Marie , Frijda Flora , La Barbera Daniele , Marrazzo Giovanna , Sideli Lucia , Sartorio Crocettarachele , Ferraro Laura , Seminerio Fabio , Loureiro Camila Marcelino , Shuhama Rosana , Ruggeri Mirella , LaSalvia Antonio , Bonetto Chiara , Stahl Daniel 
Published: March 2023

Abstract

Background and Hypothesis
It is argued that availability of diagnostic models will facilitate a more rapid identification of individuals who are at a higher risk of first episode psychosis (FEP). Therefore, we developed, evaluated, and validated a diagnostic risk estimation model to classify individual with FEP and controls across six countries.

Study Design
We used data from a large multi-center study encompassing 2627 phenotypically well-defined participants (aged 18–64 years) recruited from six countries spanning 17 research sites, as part of the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions study. To build the diagnostic model and identify which of important factors for estimating an individual risk of FEP, we applied a binary logistic model with regularization by the least absolute shrinkage and selection operator. The model was validated employing the internal-external cross-validation approach. The model performance was assessed with the area under the receiver operating characteristic curve (AUROC), calibration, sensitivity, and specificity.

Study Results
Having included preselected 22 predictor variables, the model was able to discriminate adults with FEP and controls with high accuracy across all six countries (rangesAUROC = 0.84–0.86). Specificity (range = 73.9–78.0%) and sensitivity (range = 75.6–79.3%) were equally good, cumulatively indicating an excellent model accuracy; though, calibration slope for the diagnostic model showed a presence of some overfitting when applied specifically to participants from France, the UK, and The Netherlands.

Conclusions
The new FEP model achieved a good discrimination and good calibration across six countries with different ethnic contributions supporting its robustness and good generalizability.