Metabolic syndrome risk prediction in an Australian sample with first-episode psychosis using the psychosis metabolic risk calculator: A validation study.

Abstract

Objective: To examine the accuracy and likely clinical usefulness of the Psychosis Metabolic Risk Calculator (PsyMetRiC) in predicting up-to six-year risk of incident metabolic syndrome in an Australian sample of young people with first-episode psychosis.

Method: We conducted a retrospective study at a secondary care early psychosis treatment service among people aged 16-35 years, extracting relevant data at the time of antipsychotic commencement and between one-to-six-years later. We assessed algorithm accuracy primarily via discrimination (C-statistic), calibration (calibration plots) and clinical usefulness (decision curve analysis). Model updating and recalibration generated a site-specific (Australian) PsyMetRiC version.

Results: We included 116 people with baseline and follow-up data: 73% male, mean age 20.1 years, mean follow-up 2.6 years, metabolic syndrome prevalence 13%. C-statistics for both partial- (C = 0.71, 95% CI 0.64-0.75) and full-models (C = 0.72, 95% CI 0.65-0.77) were acceptable; however, calibration plots demonstrated consistent under-prediction of risk. Recalibration and updating led to slightly improved C-statistics, greatly improved agreement between observed and predicted risk, and a narrow window of likely clinical usefulness improved significantly.

Conclusion: An updated and recalibrated PsyMetRiC model, PsyMetRiC-Australia, shows promise. Validation in a large sample is required to confirm its accuracy and clinical usefulness for the Australian population.