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Tytuł pozycji:

Development and external validation of the Psychosis Metabolic Risk Calculator (PsyMetRiC): a cardiometabolic risk prediction algorithm for young people with psychosis.

Tytuł:
Development and external validation of the Psychosis Metabolic Risk Calculator (PsyMetRiC): a cardiometabolic risk prediction algorithm for young people with psychosis.
Autorzy:
Perry BI; Department of Psychiatry, University of Cambridge, Cambridge, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK. Electronic address: .
Osimo EF; Department of Psychiatry, University of Cambridge, Cambridge, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK; MRC London Institute of Medical Sciences, Institute of Clinical Sciences, Imperial College, London, UK.
Upthegrove R; Institute for Mental Health, University of Birmingham, Birmingham, UK.
Mallikarjun PK; Institute for Mental Health, University of Birmingham, Birmingham, UK.
Yorke J; Birmingham Women's and Children's NHS Trust Early Intervention Service, Birmingham, UK.
Stochl J; Department of Psychiatry, University of Cambridge, Cambridge, UK; Department of Kinanthropology, Charles University, Prague, Czech Republic.
Perez J; Department of Psychiatry, University of Cambridge, Cambridge, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK.
Zammit S; Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK.
Howes O; MRC London Institute of Medical Sciences, Institute of Clinical Sciences, Imperial College, London, UK; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Jones PB; Department of Psychiatry, University of Cambridge, Cambridge, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK.
Khandaker GM; Department of Psychiatry, University of Cambridge, Cambridge, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK; Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Źródło:
The lancet. Psychiatry [Lancet Psychiatry] 2021 Jul; Vol. 8 (7), pp. 589-598. Date of Electronic Publication: 2021 Jun 01.
Typ publikacji:
Journal Article; Research Support, Non-U.S. Gov't; Validation Study
Język:
English
Imprint Name(s):
Original Publication: Kidlington, Oxford : Elsevier, [2014]-
MeSH Terms:
Algorithms*
Cardiometabolic Risk Factors*
Psychotic Disorders*/diagnosis
Metabolic Syndrome/*diagnosis
Adolescent ; Adult ; Female ; Humans ; Male ; Reproducibility of Results ; Young Adult
References:
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Grant Information:
MR/L010305/1 United Kingdom MRC_ Medical Research Council; MR/N027078/1 United Kingdom MRC_ Medical Research Council; MC_U120097115 United Kingdom MRC_ Medical Research Council; United Kingdom WT_ Wellcome Trust; MR/M006727/1 United Kingdom MRC_ Medical Research Council; DRF-2018-11-ST2-018 United Kingdom DH_ Department of Health; MC_PC_17213 United Kingdom MRC_ Medical Research Council; MR/S037675/1 United Kingdom MRC_ Medical Research Council
Entry Date(s):
Date Created: 20210604 Date Completed: 20210625 Latest Revision: 20240214
Update Code:
20240214
PubMed Central ID:
PMC8211566
DOI:
10.1016/S2215-0366(21)00114-0
PMID:
34087113
Czasopismo naukowe
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.
Competing Interests: Declaration of interests BIP reports a fellowship grant from the NIHR during the conduct of this study. RU reports personal fees from Sunovion, outside the submitted work. PKM reports personal fees from Recordati and Sunovion, outside the submitted work. OH reports grants and personal fees from Angelini, Autifony, Biogen, Boehringer Ingelheim, Eli Lilly, Heptares, Global Medical Education, Invicro, Janssen, Lundbeck, Mylan, Neurocrine, Otsuka, Sunovion, Rand, Recordati, and Roche, outside the submitted work. All other authors declare no competing interests.
(Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

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