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dc.contributor.authorLeal, Jose
dc.contributor.authorMorrow, Liam Mc
dc.contributor.authorKurshid, Waqar
dc.contributor.authorPagano, Eva
dc.contributor.authorFeenstra, Talitha
dc.date.accessioned20200413
dc.date.available2019-03-22T11:29:46Z
dc.date.issued2019-03-03
dc.identifier.issn1463-1326
dc.identifier.pmid30828927
dc.identifier.doi10.1111/dom.13684
dc.identifier.urihttp://hdl.handle.net/10029/622912
dc.description.abstractWith evidence supporting the use of preventive interventions for prediabetes populations and the use of novel biomarkers to stratify the risk of progression there is a need to evaluate their cost-effectiveness across jurisdictions. Our aim is to summarise and assess the quality and validity of decision models and model-based economic evaluations of populations with prediabetes, evaluate their potential use for the assessment of novel prevention strategies and discuss the knowledge gaps, challenges and opportunities. We searched Medline, Embase, EconLit and NHS EED between 2000 and 2018 for studies reporting computer simulation models of the natural history of individuals with prediabetes and/or used decision models to evaluate the impact of treatment strategies on these populations. Data were extracted following PRISMA guidelines and assessed using modelling checklists. Two reviewers independently assessed 50% of the titles and abstracts to determine whether a full text review was needed. Of these, 10% was assessed by each reviewer to cross-reference the decision to proceed to full review. Using a standardised form, and double extraction, four reviewers each extracted 50% of identified studies. Twenty-nine published decision models that simulate prediabetes populations were identified. Studies showed large variations in the definition of prediabetes and model structure. The inclusion of complications in prediabetes (n=8) and type 2 diabetes (n=17) health states also varied. A minority of studies simulated annual changes in risk factors (glycaemia, HbA1c, blood pressure, BMI, lipids) as individuals progressed in the models (n=7) and accounted for heterogeneity amongst individuals with prediabetes (n=7). Current prediabetes decision models have considerable limitations in terms of their quality and validity and are not equipped to evaluate stratified strategies using novel biomarkers highlighting a clear need for more comprehensive prediabetes decision models. This article is protected by copyright. All rights reserved.en_US
dc.language.isoenen_US
dc.subjectbiomarkeren_US
dc.subjectdecision modelen_US
dc.subjecteconomic evaluationen_US
dc.subjectprediabetesen_US
dc.subjectstratified treatmenten_US
dc.subjectsystematic reviewen_US
dc.titleDecision models of prediabetes populations: a systematic review.en_US
dc.typeArticleen_US
dc.identifier.journalDiabetes Obes Metab 2019; 21(7):1558-69en_US
dc.source.journaltitleDiabetes, obesity & metabolism


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