Development and Validation of a Dynamic Risk Prediction Model to Forecast Psychosis Onset in Patients at Clinical High Risk

Studerus, Erich and Beck, Katharina and Fusar-Poli, Paolo and Riecher-Rössler, Anita. (2019) Development and Validation of a Dynamic Risk Prediction Model to Forecast Psychosis Onset in Patients at Clinical High Risk. Schizophrenia Bulletin, 46 (2). pp. 252-260.

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Official URL: https://edoc.unibas.ch/71624/

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The prediction of outcomes in patients at Clinical High Risk for Psychosis (CHR-P) almost exclusively relies on static data obtained at a single snapshot in time (ie, baseline data). Although the CHR-P symptoms are intrinsically evolving over time, available prediction models cannot be dynamically updated to reflect these changes. Hence, the aim of this study was to develop and internally validate a dynamic risk prediction model (joint model) and to implement this model in a user-friendly online risk calculator. Furthermore, we aimed to explore the prognostic performance of extended dynamic risk prediction models and to compare static with dynamic prediction. One hundred ninety-six CHR-P patients were recruited as part of the "Basel Früherkennung von Psychosen" (FePsy) study. Psychopathology and transition to psychosis was assessed at regular intervals for up to 5 years using the Brief Psychiatric Rating Scale-Expanded (BPRS-E). Various specifications of joint models were compared with regard to their cross-validated prognostic performance. We developed and internally validated a joint model that predicts psychosis onset from BPRS-E disorganization and years of education at baseline and BPRS-E positive symptoms during the follow-up with good prognostic performance. The model was implemented as online risk calculator (http://www.fepsy.ch/DPRP/). The use of extended joint models slightly increased the prognostic accuracy compared to basic joint models, and dynamic models showed a higher prognostic accuracy than static models. Our results confirm that extended joint modeling could improve the prediction of psychosis in CHR-P patients. We implemented the first online risk calculator that can dynamically update psychosis risk prediction.
Faculties and Departments:03 Faculty of Medicine > Bereich Psychiatrie (Klinik) > Erwachsenenpsychiatrie UPK > Erwachsenenpsychiatrie (Riecher-Rössler)
03 Faculty of Medicine > Departement Klinische Forschung > Bereich Psychiatrie (Klinik) > Erwachsenenpsychiatrie UPK > Erwachsenenpsychiatrie (Riecher-Rössler)
UniBasel Contributors:Studerus, Erich
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Oxford University Press
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:08 Jul 2020 13:22
Deposited On:08 Jul 2020 13:15

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