Testing the Transportability of the Psychosis Metabolic Risk Calculator in Canada (Quebec): International External Validation Study

BACKGROUND AND HYPOTHESIS: Cardiometabolic morbidity largely explains premature mortality in people with psychotic disorders and is detectable from psychosis onset. Currently, no accurate cardiometabolic risk prediction tool exists for young people with first-episode psychosis (FEP). The Psychosis Metabolic Risk Calculator (PsyMetRiC) aims to bridge this gap, but its accuracy and potential clinical usefulness in North American populations remain unverified. STUDY DESIGN: The external validity of PsyMetRiC, developed in the United Kingdom to predict the risk of incident metabolic syndrome (MetS) up to 6 years after a FEP, was assessed using the data from the Quebec Psychosis Early Intervention Clinic. PsyMetRiC comprises 2 penalized logistic regression models: a full-model including age, sex, ethnicity, body mass index (BMI), smoking status, prescription of metabolically-active antipsychotic medication, high-density lipoprotein (HDL), and triglyceride concentrations; and a partial-model excluding biochemical predictors. Patients aged 16-35 years, diagnosed with FEP between 2004 and 2023 without pre-existing MetS, and with>12 months follow-up were included. Predictive performance of PsyMetRiC was assessed by discrimination (C-statistic), calibration (calibration plots), and clinical usefulness (decision curve analysis). The race and ethnicity predictor was refined to better represent the North American population. STUDY RESULTS: Among 559 included patients (mean age 24.1 years ±4.1; 22.5% female), 18.2% developed MetS during a mean follow-up of 1.7 ± 1.3 years. Compared with the UK development cohort, the Canadian sample exhibited a higher BMI, lower HDL cholesterol, lower triglycerides, lower blood glucose, and lower systolic blood pressure. Discrimination performance was acceptable (full model C = 0.74, 95% CI, 0.70-0.77; intercept = 0.225; slope = 1.278; partial model C = 0.70, 95% CI, 0.67-0.74; intercept = -0.555; slope = 0.993). After updating the model with a race and ethnicity predictor calibrated to locally representative categories, performance improved slightly (full model C = 0.74, 95% CI, 0.71-0.77; intercept = 0.000; slope = 1.001; partial model C = 0.71, 95% CI, 0.68-0.74; intercept = 0.001; slope = 1.005). CONCLUSIONS: This study provides the first external validation of PsyMetRiC in a North American sample. Further research is essential before routine clinical implementation, but PsyMetRiC offers promise as a tool for early detection of cardiometabolic risk in early psychosis, guiding personalized treatments to diminish long-term physical health impacts.