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Computer simulation models of pre-diabetes populations: a systematic review protocol
  1. Jose Leal1,
  2. Waqar Khurshid1,
  3. Eva Pagano2,
  4. Talitha Feenstra3,4
  1. 1 Nuffield Department of Population Health, Health Economics Research Centre, University of Oxford, Oxford, UK
  2. 2 Unit of Cancer Epidemiology, “Città della Salute e della Scienza” Hospital and CPO Piemonte, Piemonte, Italy
  3. 3 Department of Epidemiology, University Medical Centre Groningen, Groningen, The Netherlands
  4. 4 Department for Prevention and Health Services Research, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
  1. Correspondence to Dr Jose Leal; jose.leal{at}


Introduction Diabetes is a major public health problem and prediabetes (intermediate hyperglycaemia) is associated with a high risk of developing diabetes. With evidence supporting the use of preventive interventions for prediabetes populations and the discovery of novel biomarkers stratifying the risk of progression, there is a need to evaluate their cost-effectiveness across jurisdictions. In diabetes and prediabetes, it is relevant to inform cost-effectiveness analysis using decision models due to their ability to forecast long-term health outcomes and costs beyond the time frame of clinical trials. To support good implementation and reimbursement decisions of interventions in these populations, models should be clinically credible, based on best available evidence, reproducible and validated against clinical data. Our aim is to identify recent studies on computer simulation models and model-based economic evaluations of populations of individuals with prediabetes, qualify them and discuss the knowledge gaps, challenges and opportunities that need to be addressed for future evaluations.

Methods and analysis A systematic review will be conducted in MEDLINE, Embase, EconLit and National Health Service Economic Evaluation Database. We will extract peer-reviewed studies published between 2000 and 2016 that describe computer simulation models of the natural history of individuals with prediabetes and/or decision models to evaluate the impact of interventions, risk stratification and/or screening on these populations. Two reviewers will independently assess each study for inclusion. Data will be extracted using a predefined pro forma developed using best practice. Study quality will be assessed using a modelling checklist. A narrative synthesis of all studies will be presented, focussing on model structure, quality of models and input data, and validation status.

Ethics and dissemination This systematic review is exempt from ethics approval because the work is carried out on published documents. The findings of the review will be disseminated in a related peer-reviewed journal and presented at conferences.

Reviewregistration number CRD42016047228.

  • diabetes
  • economic evaluation
  • decision model
  • systematic review
  • health economics
  • prediabetes

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See:

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  • Contributors JL, TF and EP conceived the initial idea for the study. JL and WK wrote the protocol. TF and EP critically appraised the protocol and also contributed to its development by revising different version. All authors read and approved the final version of the manuscript. JL is the guarantor of the review.

  • Funding This work is supported by Innovative Medicines Initiative 2 Joint Undertaking under grant agreement no 115881. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA.

  • Competing interests None declared.

  • Ethics approval This systematic review is exempt from ethics approval and consent to participate because the work is carried out on published documents.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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