Algorithm predicts risk of incident metabolic syndrome in young people with psychosis
Source / Disclosures
Disclosures: Perry says he received a grant from the National Institute for Health Research during the conduct of this study. Please see the study for relevant financial information from all other authors.
Researchers have developed an age-appropriate algorithm that can predict the risk of incident metabolic syndrome in young people with psychosis, according to the results of a study published in Lancet Psychiatry.
“A recent systematic review explored the relevance of existing cardiometabolic risk prediction algorithms for young people with psychosis” Benjamin I. Perry, MRCPsych, from the Department of Psychiatry at the University of Cambridge in the UK, and colleagues have written. “However, all algorithms were developed on samples of adults whose mean age in the included studies was 50.5 years, and no study included participants under 35 years of age. Most of the included studies did not include relevant predictors, such as antipsychotic drugs, so the review authors concluded that none were likely to be suitable for young people with psychosis. “
In addition, an exploratory analysis that accompanied the previous systematic review demonstrated that existing algorithms considerably underestimate the cardiometabolic risk in young people with or at risk of developing psychosis.
In the present study, Perry and colleagues developed the Metabolic Risk of Psychosis Calculator (PsyMetRiC) to predict up to 6 years of risk of incident metabolic syndrome in 16- to 35-year-old youth with psychosis using data commonly recorded initially. They used the forced entry method to develop a comprehensive model including age, gender, ethnicity, BMI, smoking status, prescription of a metabolically active antipsychotic HDL concentration and concentration. of triglycerides, as well as a partial model that excluded biochemical results. In addition, they used data from two early psychosis intervention services in the UK between January 1, 2013 and November 4, 2020, to develop PsyMetRiC and validated it externally in another early intervention service. in the UK between January 1, 2013 and November 4. , 2020. They conducted a sensitivity analysis among 18-year-old British birth cohort participants who were at risk of developing psychosis.
The researchers included 651 patients in the development samples, 510 in the validation sample and 505 in the sensitivity analysis sample. The results showed a high level of performance for PsyMetRiC during internal and external validation. The researchers noted a “good” calibration of the complete model but found evidence of a slight misalignment of the partial model. PsyMetRiC improved net profit by 7.95% with a sensitivity of 75% and specificity of 74% at a cutoff score of 0.18. This improvement was equivalent to detecting an additional 47% of metabolic syndrome cases.
“PsyMetRiC has the potential to become a valuable resource for healthcare professionals working in [early intervention services] assisting in the informed choice of antipsychotic drugs, the prescription of cardioprotective drugs and non-pharmacological interventions, including lifestyle adjustments to prevent future development of cardiometabolic comorbidities and years of life lost, ”wrote Perry et al. colleagues.