The Psychosis Metabolic Risk Calculator (PsyMetRiC) was developed to predict the risk for metabolic syndrome among young patients with psychosis. The development of the risk prediction tool was published in Lancet Psychiatry.

Patient data collected for the Birmingham psychosis early intervention service (n=352) and Cambridgeshire and Peterborough Assessing, Managing and Enhancing Outcomes (CAMEO; n=299) studies were used in the development of the risk calculator. The PsyMetRiC tool was validated with data available through the Clinical Records Interactive Search from the South London and Maudsley NHS Foundation Trust (SLaM; n=651) and the Avon Longitudinal Study of Parents and Children (ALSPAC; n=505) studies. Metabolic syndrome risk was associated with clinical and demographic characteristics.

The Birmingham, CAMEO, SLaM, and ALSPAC cohorts comprised 66%, 70%, 69% and 36% men and boys, aged mean 23.76, 25.42, 24.45, and 17.81 years, and 32%, 84%, 30% and 98% were White, respectively.


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The PsyMetRiC full model included age, gender, ethnicity, BMI, smoking status, antipsychotic medication, high-density lipoprotein cholesterol concentration, and triglyceride concentration.

The internal validation of the PsyMetRiC tool had an R2 of 0.25 (95% CI, 0.22-0.28), a C of 0.80 (95% CI, 0.74-0.86), and a Brier score of 0.07 (95% CI, 0.05-0.09).

The performance of the tool for the SLaM cohort was an R2 of 0.21 (95% CI, 0.18-0.25), a C of 0.75 (95% CI, 0.69-0.80), and a Brier score of 0.07 (95% CI, 0.04-0.10). For the ALSPAC dataset, the PsyMetRiC performance was an R2 of 0.20 (95% CI, 0.17-0.23), a C of 0.73 (95% CI, 0.66-0.79), and a Brier score of 0.08 (95% CI, 0.04-0.11).

If an intervention for metabolic syndrome was necessary above a risk score of 0.18, the PsyMetRiC tool had a net benefit of 7.95% (sensitivity, 75%; specificity, 74%), corresponding with 47% of metabolic syndrome cases prevented, or 8 cases among 100 individuals.

The development of the PsyMetRiC tool was limited by the high amount of missing data from the databases.

The study authors concluded that PsyMetRiC had the potential to inform clinicians working with a young patient with psychosis about the best antipsychotics to prescribe, whether or not their patient should be a candidate for cardioprotective drugs or, should the patient be encouraged to make lifestyle changes in order to prevent the onset of metabolic syndrome.

Disclosure: Multiple authors declared affiliations with industry. Please refer to the original article for a full list of disclosures.

Reference

Perry BI, Osimo EF, Upthegrove R, et al. Development and external validation of the Psychosis Metabolic Risk Calculator (PsyMetRiC): a cardiometabolic risk prediction algorithm for young people with psychosis. Lancet Psychiatry. Published online June 1, 2021. doi:10.1016/S2215-0366(21)00114-0