RT Journal Article
T1 The psychosis metabolic risk calculator (PsyMetRiC) for young people with psychosis: International external validation and site-specific recalibration in two independent European samples.
A1 Perry, Benjamin I
A1 Vandenberghe, Frederik
A1 Garrido-Torres, Nathalia
A1 Osimo, Emanuele F
A1 Piras, Marianna
A1 Vazquez-Bourgon, Javier
A1 Upthegrove, Rachel
A1 Grosu, Claire
A1 De La Foz, Victor Ortiz-Garcia
A1 Jones, Peter B
A1 Laaboub, Nermine
A1 Ruiz-Veguilla, Miguel
A1 Stochl, Jan
A1 Dubath, Celine
A1 Canal-Rivero, Manuel
A1 Mallikarjun, Pavan
A1 Delacrétaz, Aurélie
A1 Ansermot, Nicolas
A1 Fernandez-Egea, Emilio
A1 Crettol, Severine
A1 Gamma, Franziska
A1 Plessen, Kerstin J
A1 Conus, Philippe
A1 Khandaker, Golam M
A1 Murray, Graham K
A1 Eap, Chin B
A1 Crespo-Facorro, Benedicto
K1 Early Intervention
K1 International Validation
K1 Metabolic Syndrome
K1 PAFIP
K1 PsyMetab
K1 Psychosis
K1 Risk Prediction Algorithm
AB Cardiometabolic dysfunction is common in young people with psychosis. Recently, the Psychosis Metabolic Risk Calculator (PsyMetRiC) was developed and externally validated in the UK, predicting up-to six-year risk of metabolic syndrome (MetS) from routinely collected data. The full-model includes age, sex, ethnicity, body-mass index, smoking status, prescription of metabolically-active antipsychotic medication, high-density lipoprotein, and triglyceride concentrations; the partial-model excludes biochemical predictors. To move toward a future internationally-useful tool, we externally validated PsyMetRiC in two independent European samples. We used data from the PsyMetab (Lausanne, Switzerland) and PAFIP (Cantabria, Spain) cohorts, including participants aged 16-35y without MetS at baseline who had 1-6y follow-up. Predictive performance was assessed primarily via discrimination (C-statistic), calibration (calibration plots), and decision curve analysis. Site-specific recalibration was considered. We included 1024 participants (PsyMetab n=558, male=62%, outcome prevalence=19%, mean follow-up=2.48y; PAFIP n=466, male=65%, outcome prevalence=14%, mean follow-up=2.59y). Discrimination was better in the full- compared with partial-model (PsyMetab=full-model C=0.73, 95% C.I., 0.68-0.79, partial-model C=0.68, 95% C.I., 0.62-0.74; PAFIP=full-model C=0.72, 95% C.I., 0.66-0.78; partial-model C=0.66, 95% C.I., 0.60-0.71). As expected, calibration plots revealed varying degrees of miscalibration, which recovered following site-specific recalibration. PsyMetRiC showed net benefit in both new cohorts, more so after recalibration. The study provides evidence of PsyMetRiC's generalizability in Western Europe, although further local and international validation studies are required. In future, PsyMetRiC could help clinicians internationally to identify young people with psychosis who are at higher cardiometabolic risk, so interventions can be directed effectively to reduce long-term morbidity and mortality. NIHR Cambridge Biomedical Research Centre (BRC-1215-20014); The Wellcome Trust (201486/Z/16/Z); Swiss National Research Foundation (320030-120686, 324730- 144064, and 320030-173211); The Carlos III Health Institute (CM20/00015, FIS00/3095, PI020499, PI050427, and PI060507); IDIVAL (INT/A21/10 and INT/A20/04); The Andalusian Regional Government (A1-0055-2020 and A1-0005-2021); SENY Fundacion Research (2005-0308007); Fundacion Marques de Valdecilla (A/02/07, API07/011); Ministry of Economy and Competitiveness and the European Fund for Regional Development (SAF2016-76046-R and SAF2013-46292-R).For the Spanish and French translation of the abstract see Supplementary Materials section.
YR 2022
FD 2022-08-19
LK http://hdl.handle.net/10668/22352
UL http://hdl.handle.net/10668/22352
LA en
DS RISalud
RD Apr 6, 2025