TY - JOUR
T1 - Towards Clinical Application of Prediction Models for Transition to Psychosis: A Systematic Review and External Validation Study in the PRONIA Sample
AU - Rosen, Marlene
AU - Betz, Linda T
AU - Schultze-Lutter, Frauke
AU - Chisholm, Katharine
AU - Haidl, Theresa K
AU - Kambeitz-Ilankovic, Lana
AU - Bertolino, Alessandro
AU - Borgwardt, Stefan
AU - Brambilla, Paolo
AU - Lencer, Rebekka
AU - Meisenzahl, Eva
AU - Ruhrmann, Stephan
AU - Salokangas, Raimo K R
AU - Upthegrove, Rachel
AU - Wood, Stephen J
AU - Koutsouleris, Nikolaos
AU - Kambeitz, Joseph
PY - 2021/6
Y1 - 2021/6
N2 - A multitude of prediction models for a first psychotic episode in individuals at clinical high-risk (CHR) for psychosis have been proposed, but only rarely validated. We identified transition models based on clinical and neuropsychological data through a registered systematic literature search and evaluated their external validity in 173 CHRs from the Personalised Prognostic Tools for Early Psychosis Management (PRONIA) study. Discrimination performance was assessed with the area under the receiver operating characteristic curve (AUC), and compared to the prediction of clinical raters. External discrimination performance varied considerably across the 22 identified models (AUC 0.40-0.76), with two models showing good discrimination performance. None of the tested models significantly outperformed clinical raters (AUC = 0.75). Combining predictions of clinical raters and the best model descriptively improved discrimination performance (AUC = 0.84). Results show that personalized prediction of transition in CHR is potentially feasible on a global scale. For implementation in clinical practice, further rounds of external validation, impact studies, and development of an ethical framework is necessary.
AB - A multitude of prediction models for a first psychotic episode in individuals at clinical high-risk (CHR) for psychosis have been proposed, but only rarely validated. We identified transition models based on clinical and neuropsychological data through a registered systematic literature search and evaluated their external validity in 173 CHRs from the Personalised Prognostic Tools for Early Psychosis Management (PRONIA) study. Discrimination performance was assessed with the area under the receiver operating characteristic curve (AUC), and compared to the prediction of clinical raters. External discrimination performance varied considerably across the 22 identified models (AUC 0.40-0.76), with two models showing good discrimination performance. None of the tested models significantly outperformed clinical raters (AUC = 0.75). Combining predictions of clinical raters and the best model descriptively improved discrimination performance (AUC = 0.84). Results show that personalized prediction of transition in CHR is potentially feasible on a global scale. For implementation in clinical practice, further rounds of external validation, impact studies, and development of an ethical framework is necessary.
KW - Clinical high-risk
KW - Early intervention
KW - Model validation
KW - Precision medicine
KW - Prediction
KW - Psychosis
KW - Translational psychiatry
UR - https://www.sciencedirect.com/science/article/pii/S0149763421000865?via%3Dihub
UR - http://www.scopus.com/inward/record.url?scp=85102608460&partnerID=8YFLogxK
U2 - 10.1016/j.neubiorev.2021.02.032
DO - 10.1016/j.neubiorev.2021.02.032
M3 - Review article
C2 - 33636198
SN - 0149-7634
VL - 125
SP - 478
EP - 492
JO - Neuroscience and Biobehavioral Reviews
JF - Neuroscience and Biobehavioral Reviews
ER -