Development and external validation of the Psychosis Metabolic Risk Calculator (PsyMetRiC): a cardiometabolic risk prediction algorithm for young people with psychosis
Year: 2021
Type: article
Abstract: BACKGROUND: Young people with psychosis are at high risk of developing cardiometabolic disorders; however, there is no suitable cardiometabolic risk prediction algorithm for this group. We aimed to develop and externally validate a cardiometabolic risk prediction algorithm for young people with psychosis. METHODS: We developed the Psychosis Metabolic Risk Calculator (PsyMetRiC) to predict up to 6-year risk of incident metabolic syndrome in young people (aged 16-35 years) with psychosis from commonly recorded information at baseline. We developed two PsyMetRiC versions using the forced entry method: a full model (including age, sex, ethnicity, body-mass index, smoking status, prescription of a metabolically active antipsychotic medication, HDL concentration, and triglyceride concentration) and a partial model excluding biochemical results. PsyMetRiC was developed using data from two UK psychosis early intervention services (Jan 1, 2013, to Nov 4, 2020) and externally validated in another UK early intervention service (Jan 1, 2012, to June 3, 2020). A sensitivity analysis was done in UK birth cohort participants (aged 18 years) who were at risk of developing psychosis. Algorithm performance was assessed primarily via discrimination (C statistic) and calibration (calibration plots). We did a decision curve analysis and produced an online data-visualisation app. FINDINGS: 651 patients were included in the development samples, 510 in the validation sample, and 505 in the sensitivity analysis sample. PsyMetRiC performed well at internal (full model: C 0·80, 95% CI 0·74-0·86; partial model: 0·79, 0·73-0·84) and external validation (full model: 0·75, 0·69-0·80; and partial model: 0·74, 0·67-0·79). Calibration of the full model was good, but there was evidence of slight miscalibration of the partial model. At a cutoff score of 0·18, in the full model PsyMetRiC improved net benefit by 7·95% (sensitivity 75%, 95% CI 66-82; specificity 74%, 71-78), equivalent to detecting an additional 47% of metabolic syndrome cases. INTERPRETATION: We have developed an age-appropriate algorithm to predict the risk of incident metabolic syndrome, a precursor of cardiometabolic morbidity and mortality, in young people with psychosis. PsyMetRiC has the potential to become a valuable resource for early intervention service clinicians and could enable personalised, informed health-care decisions regarding choice of antipsychotic medication and lifestyle interventions. FUNDING: National Institute for Health Research and Wellcome Trust.
Source: The Lancet Psychiatry
Institutions: University of Cambridge, Cambridgeshire and Peterborough NHS Foundation Trust, MRC London Institute of Medical Sciences, Imperial College London, University of Birmingham, Birmingham Women’s and Children’s NHS Foundation Trust, Charles University, University of Bristol, Cardiff University, King's College London, MRC Integrative Epidemiology Unit
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $5,000
Funders: Wellcome Trust, University Hospitals Bristol NHS Foundation Trust, National Institute for Health and Care Research, Department of Health and Social Care, King's College London, University of Bristol, Cambridge University Hospitals, BMA Foundation for Medical Research, Medical Research Council, NIHR Imperial Biomedical Research Centre, NIHR Cambridge Biomedical Research Centre
Awards: G1192034430, G1605161196, G1684393010, G1793884970, G1868002148, G1927824909, Psychosis Immune Mechanism Stratified Medicine Study (PIMS), G2474488143, G2533062745, G3507283293, G3512615570, The Avon Longitudinal Study of Parents and Children (ALSPAC): A multi- generation, longitudinal resource focusing on life course health and well- being., G3831911591, G3964678366, G3987754321, G4213003937, G4260143917, G4457484660, The Avon Longitudinal Study for Parents and Children: An international resource for population genomic and lifecourse epidemiology. Core programme support 2014-2019., G4643449984, G4998310206, G5189661712, G5562631338, G5702265173, Early metabolic dysfunction and psychosis: Producing a clinically useful metabolic risk calculator (Psy-MetRiC) for use in people presenting with first-episode psychosis, G6210185106, G6342754709, Tailoring evidence-based psychological therapY for People with common mental disorder including Psychotic EXperiences (TYPPEX), G6680420078, G6848567189, Inflammation and Immunity in Depression: from novel mechanisms towards therapeutics, G710448223, G7708287604, G7785669168, Pathways to psychosis: Investigating environmental, cognitive and genetic mechanisms underlying development of psychotic experiences in young adults, G792825315, The Avon Longitudinal Study of Parents and Children (ALSPAC): A multi-generation, longitudinal resource focusing on life course health and well-being., G8256162305, G8374597115, MICA: Mental Health Data Pathfinder: University of Cambridge, Cambridgeshire & Peterborough NHS Foundation Trust, and Microsoft
OpenAlex ID: W3137052534