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Published in: Systematic Reviews 1/2017

Open Access 01-12-2017 | Protocol

External validation of type 2 diabetes computer simulation models: definitions, approaches, implications and room for improvement—a protocol for a systematic review

Authors: Katherine Ogurtsova, Thomas L. Heise, Ute Linnenkamp, Charalabos-Markos Dintsios, Stefan K. Lhachimi, Andrea Icks

Published in: Systematic Reviews | Issue 1/2017

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Abstract

Background

Type 2 diabetes mellitus (T2DM), a highly prevalent chronic disease, puts a large burden on individual health and health care systems. Computer simulation models, used to evaluate the clinical and economic effectiveness of various interventions to handle T2DM, have become a well-established tool in diabetes research. Despite the broad consensus about the general importance of validation, especially external validation, as a crucial instrument of assessing and controlling for the quality of these models, there are no systematic reviews comparing such validation of diabetes models. As a result, the main objectives of this systematic review are to identify and appraise the different approaches used for the external validation of existing models covering the development and progression of T2DM.

Methods

We will perform adapted searches by applying respective search strategies to identify suitable studies from 14 electronic databases. Retrieved study records will be included or excluded based on predefined eligibility criteria as defined in this protocol. Among others, a publication filter will exclude studies published before 1995. We will run abstract and full text screenings and then extract data from all selected studies by filling in a predefined data extraction spreadsheet. We will undertake a descriptive, narrative synthesis of findings to address the study objectives. We will pay special attention to aspects of quality of these models in regard to the external validation based upon ISPOR and ADA recommendations as well as Mount Hood Challenge reports. All critical stages within the screening, data extraction and synthesis processes will be conducted by at least two authors. This protocol adheres to PRISMA and PRISMA-P standards.

Discussion

The proposed systematic review will provide a broad overview of the current practice in the external validation of models with respect to T2DM incidence and progression in humans built on simulation techniques.

Systematic review registration

PROSPERO CRD42017069983.
Appendix
Available only for authorised users
Literature
1.
go back to reference Ogurtsova K, da Rocha Fernandes JD, Huang Y, Linnenkamp U, Guariguata L, Cho NH, et al. IDF diabetes atlas: global estimates for the prevalence of diabetes for 2015 and 2040. Diabetes Res Clin Pract. 2017;128:40–50.CrossRefPubMed Ogurtsova K, da Rocha Fernandes JD, Huang Y, Linnenkamp U, Guariguata L, Cho NH, et al. IDF diabetes atlas: global estimates for the prevalence of diabetes for 2015 and 2040. Diabetes Res Clin Pract. 2017;128:40–50.CrossRefPubMed
3.
go back to reference The Diabetes Prevention Program Research Group. The prevalence of retinopathy in impaired glucose tolerance and recent-onset diabetes in the diabetes prevention program. Diabet Med. 2007;24:137–44.CrossRef The Diabetes Prevention Program Research Group. The prevalence of retinopathy in impaired glucose tolerance and recent-onset diabetes in the diabetes prevention program. Diabet Med. 2007;24:137–44.CrossRef
4.
go back to reference Porta M, Curletto G, Cipullo D, Rigault de la Longrais R, Trento M, Passera P, et al. Estimating the delay between onset and diagnosis of type 2 diabetes from the time course of retinopathy prevalence. Diabetes Care. 2014;37:1668–74.CrossRefPubMed Porta M, Curletto G, Cipullo D, Rigault de la Longrais R, Trento M, Passera P, et al. Estimating the delay between onset and diagnosis of type 2 diabetes from the time course of retinopathy prevalence. Diabetes Care. 2014;37:1668–74.CrossRefPubMed
5.
go back to reference Zhang P, Gregg E. Global economic burden of diabetes and its implications. Lancet Diabetes Endocrinol. 2017;5:404–5.CrossRefPubMed Zhang P, Gregg E. Global economic burden of diabetes and its implications. Lancet Diabetes Endocrinol. 2017;5:404–5.CrossRefPubMed
6.
go back to reference Marshall DA, Burgos-Liz L, IJzerman MJ, Crown W, Padula WV, Wong PK, et al. Selecting a dynamic simulation modeling method for health care delivery research-part 2: report of the ISPOR Dynamic Simulation Modeling Emerging Good Practices Task Force. Value Health. 2015;18:147–60.CrossRefPubMed Marshall DA, Burgos-Liz L, IJzerman MJ, Crown W, Padula WV, Wong PK, et al. Selecting a dynamic simulation modeling method for health care delivery research-part 2: report of the ISPOR Dynamic Simulation Modeling Emerging Good Practices Task Force. Value Health. 2015;18:147–60.CrossRefPubMed
7.
go back to reference Briggs ADM, Wolstenholme J, Blakely T, Scarborough P. Choosing an epidemiological model structure for the economic evaluation of non-communicable disease public health interventions. Popul Health Metr. 2016;14:17.CrossRefPubMedPubMedCentral Briggs ADM, Wolstenholme J, Blakely T, Scarborough P. Choosing an epidemiological model structure for the economic evaluation of non-communicable disease public health interventions. Popul Health Metr. 2016;14:17.CrossRefPubMedPubMedCentral
8.
go back to reference Salleh S, Thokala P, Brennan A, Hughes R, Booth A. Simulation modelling in healthcare: an umbrella review of systematic literature reviews. PharmacoEconomics. 2017;35(9):937–49. Salleh S, Thokala P, Brennan A, Hughes R, Booth A. Simulation modelling in healthcare: an umbrella review of systematic literature reviews. PharmacoEconomics. 2017;35(9):937–49.
9.
go back to reference American Diabetes Association Consensus Panel. Guidelines for computer modeling of diabetes and its complications. Diabetes Care. 2004;27:2262–5.CrossRef American Diabetes Association Consensus Panel. Guidelines for computer modeling of diabetes and its complications. Diabetes Care. 2004;27:2262–5.CrossRef
10.
go back to reference Lifetime benefits and costs of intensive therapy as practiced in the diabetes control and complications trial. The Diabetes Control and Complications Trial Research Group. JAMA. 1996;276(17):1409–15. Erratum in: JAMA 1997;278(1):25. Lifetime benefits and costs of intensive therapy as practiced in the diabetes control and complications trial. The Diabetes Control and Complications Trial Research Group. JAMA. 1996;276(17):1409–15. Erratum in: JAMA 1997;278(1):25.
11.
go back to reference Tarride J-E, Hopkins R, Blackhouse G, Bowen JM, Bischof M, Von Keyserlingk C, et al. A review of methods used in long-term cost-effectiveness models of diabetes mellitus treatment. PharmacoEconomics. 2010;28:255–77.CrossRefPubMed Tarride J-E, Hopkins R, Blackhouse G, Bowen JM, Bischof M, Von Keyserlingk C, et al. A review of methods used in long-term cost-effectiveness models of diabetes mellitus treatment. PharmacoEconomics. 2010;28:255–77.CrossRefPubMed
12.
go back to reference Eastman RC, Javitt JC, Herman WH, Dasbach EJ, Zbrozek AS, Dong F, et al. Model of complications of NIDDM: I. Model construction and assumptions. Diabetes Care. 1997;20:725–34.CrossRefPubMed Eastman RC, Javitt JC, Herman WH, Dasbach EJ, Zbrozek AS, Dong F, et al. Model of complications of NIDDM: I. Model construction and assumptions. Diabetes Care. 1997;20:725–34.CrossRefPubMed
13.
go back to reference Yi Y, Philips Z, Bergman G, Burslem K. Economic models in type 2 diabetes. Curr Med Res Opin. 2010;26:2105–18. Yi Y, Philips Z, Bergman G, Burslem K. Economic models in type 2 diabetes. Curr Med Res Opin. 2010;26:2105–18.
14.
go back to reference Charokopou M, Sabater FJ, Townsend R, Roudaut M, McEwan P, Verheggen BG. Methods applied in cost-effectiveness models for treatment strategies in type 2 diabetes mellitus and their use in Health Technology Assessments: a systematic review of the literature from 2008 to 2013. Curr Med Res Opin. 2016;32:207–18.CrossRefPubMed Charokopou M, Sabater FJ, Townsend R, Roudaut M, McEwan P, Verheggen BG. Methods applied in cost-effectiveness models for treatment strategies in type 2 diabetes mellitus and their use in Health Technology Assessments: a systematic review of the literature from 2008 to 2013. Curr Med Res Opin. 2016;32:207–18.CrossRefPubMed
15.
go back to reference Palmer AJ, Hornberger J, Palmer AJ, Mount Hood Modeling Group, Clarke P, Gray A, et al. Computer modeling of diabetes and its complications: a report on the fifth Mount Hood challenge meeting. Value Health 2013;16:453–454. Palmer AJ, Hornberger J, Palmer AJ, Mount Hood Modeling Group, Clarke P, Gray A, et al. Computer modeling of diabetes and its complications: a report on the fifth Mount Hood challenge meeting. Value Health 2013;16:453–454.
16.
go back to reference The Mount Hood 4 Modeling Group. Computer modeling of diabetes and its complications: a report on the fourth Mount Hood challenge meeting. Diabetes Care. 2007;30:1638–46.CrossRef The Mount Hood 4 Modeling Group. Computer modeling of diabetes and its complications: a report on the fourth Mount Hood challenge meeting. Diabetes Care. 2007;30:1638–46.CrossRef
17.
go back to reference Caro JJ, Eddy DM, Kan H, Kaltz C, Patel B, Eldessouki R, et al. Questionnaire to assess relevance and credibility of modeling studies for informing health care decision making: an ISPOR-AMCP-NPC Good Practice Task Force report. Value Health. 2014;17:174–82.CrossRef Caro JJ, Eddy DM, Kan H, Kaltz C, Patel B, Eldessouki R, et al. Questionnaire to assess relevance and credibility of modeling studies for informing health care decision making: an ISPOR-AMCP-NPC Good Practice Task Force report. Value Health. 2014;17:174–82.CrossRef
18.
go back to reference Weinstein MC, O’Brien B, Hornberger J, Jackson J, Johannesson M, McCabe C, et al. Principles of good practice for decision analytic modeling in health-care evaluation: report of the ISPOR task force on good research practices—modeling studies. Value Health. 2003;6:9–17.CrossRefPubMed Weinstein MC, O’Brien B, Hornberger J, Jackson J, Johannesson M, McCabe C, et al. Principles of good practice for decision analytic modeling in health-care evaluation: report of the ISPOR task force on good research practices—modeling studies. Value Health. 2003;6:9–17.CrossRefPubMed
19.
go back to reference Eddy DM, Hollingworth W, Caro JJ, Tsevat J, McDonald KM, Wong JB. Model transparency and validation: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-7. Med Decis Mak. 2012;32:733–43.CrossRef Eddy DM, Hollingworth W, Caro JJ, Tsevat J, McDonald KM, Wong JB. Model transparency and validation: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-7. Med Decis Mak. 2012;32:733–43.CrossRef
20.
go back to reference Brown JB, Palmer AJ, Bisgaard P, Chan W, Pedula K, Russell A. The Mt. Hood challenge: cross-testing two diabetes simulation models. Diabetes Res Clin Pract. 2000;50(Suppl 3):S57–64.CrossRefPubMed Brown JB, Palmer AJ, Bisgaard P, Chan W, Pedula K, Russell A. The Mt. Hood challenge: cross-testing two diabetes simulation models. Diabetes Res Clin Pract. 2000;50(Suppl 3):S57–64.CrossRefPubMed
21.
go back to reference CDC Diabetes Cost-effectiveness Group. Cost-effectiveness of intensive glycemic control, intensified hypertension control, and serum cholesterol level reduction for type 2 diabetes. J Am Med Assoc. 2002;287:2542–51.CrossRef CDC Diabetes Cost-effectiveness Group. Cost-effectiveness of intensive glycemic control, intensified hypertension control, and serum cholesterol level reduction for type 2 diabetes. J Am Med Assoc. 2002;287:2542–51.CrossRef
22.
go back to reference Palmer AJ, Roze SS, Lammert M, Valentine WJ, Minshall ME, Nicklasson L, et al. Comparing the long-term cost-effectiveness of repaglinide plus metformin versus nateglinide plus metformin in type 2 diabetes patients with inadequate glycaemic control: an application of the CORE diabetes model in type 2 diabetes. Curr Med Res Opin. 2004;20(Suppl 1):S41–51.CrossRefPubMed Palmer AJ, Roze SS, Lammert M, Valentine WJ, Minshall ME, Nicklasson L, et al. Comparing the long-term cost-effectiveness of repaglinide plus metformin versus nateglinide plus metformin in type 2 diabetes patients with inadequate glycaemic control: an application of the CORE diabetes model in type 2 diabetes. Curr Med Res Opin. 2004;20(Suppl 1):S41–51.CrossRefPubMed
23.
go back to reference Eddy DM, Schlessinger L, Kahn R. Clinical outcomes and cost-effectiveness of strategies for managing people at high risk for diabetes. Ann Intern Med. 2005;143:251–64.CrossRefPubMed Eddy DM, Schlessinger L, Kahn R. Clinical outcomes and cost-effectiveness of strategies for managing people at high risk for diabetes. Ann Intern Med. 2005;143:251–64.CrossRefPubMed
24.
go back to reference Becker C, Langer A, Leidl R. The quality of three decision-analytic diabetes models: a systematic health economic assessment. Expert Rev Pharmacoecon Outcomes Res. 2011;11:751–62.CrossRefPubMed Becker C, Langer A, Leidl R. The quality of three decision-analytic diabetes models: a systematic health economic assessment. Expert Rev Pharmacoecon Outcomes Res. 2011;11:751–62.CrossRefPubMed
25.
go back to reference Henriksson M, Jindal R, Sternhufvud C, Bergenheim K, Sörstadius E, Willis M. A systematic review of cost-effectiveness models in type 1 diabetes mellitus. PharmacoEconomics. 2016;34:569–85.CrossRefPubMed Henriksson M, Jindal R, Sternhufvud C, Bergenheim K, Sörstadius E, Willis M. A systematic review of cost-effectiveness models in type 1 diabetes mellitus. PharmacoEconomics. 2016;34:569–85.CrossRefPubMed
26.
go back to reference Kirsch F. A systematic review of Markov models evaluating multicomponent disease management programs in diabetes. Expert Rev Pharmacoecon Outcomes Res. 2015;15:961–84.CrossRefPubMed Kirsch F. A systematic review of Markov models evaluating multicomponent disease management programs in diabetes. Expert Rev Pharmacoecon Outcomes Res. 2015;15:961–84.CrossRefPubMed
27.
go back to reference Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JPA, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med. 2009;6:e1000100.CrossRefPubMedPubMedCentral Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JPA, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med. 2009;6:e1000100.CrossRefPubMedPubMedCentral
28.
go back to reference Moher D, Stewart LA, Shekelle P, Ghersi D, Liberati A, Petticrew M, et al. Establishing a new journal for systematic review products. Syst Rev. 2012;1:1.CrossRefPubMedPubMedCentral Moher D, Stewart LA, Shekelle P, Ghersi D, Liberati A, Petticrew M, et al. Establishing a new journal for systematic review products. Syst Rev. 2012;1:1.CrossRefPubMedPubMedCentral
29.
go back to reference Shamseer L, Moher D, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ. 2015;349:g7647.CrossRef Shamseer L, Moher D, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ. 2015;349:g7647.CrossRef
30.
go back to reference McGowan J, Sampson M, Salzwedel DM, Cogo E, Foerster V, Lefebvre C. PRESS peer review of electronic search strategies: 2015 guideline statement. J Clin Epidemiol. 2016;75:40–6.CrossRefPubMed McGowan J, Sampson M, Salzwedel DM, Cogo E, Foerster V, Lefebvre C. PRESS peer review of electronic search strategies: 2015 guideline statement. J Clin Epidemiol. 2016;75:40–6.CrossRefPubMed
34.
go back to reference American diabetes association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2012;35(Suppl 1):64–71.CrossRef American diabetes association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2012;35(Suppl 1):64–71.CrossRef
35.
go back to reference Alberti KGMMG, Zimmet PZZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a {WHO} consultation. Diabet Med a J Br Diabet Assoc. 1998;15:539–53.CrossRef Alberti KGMMG, Zimmet PZZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a {WHO} consultation. Diabet Med a J Br Diabet Assoc. 1998;15:539–53.CrossRef
Metadata
Title
External validation of type 2 diabetes computer simulation models: definitions, approaches, implications and room for improvement—a protocol for a systematic review
Authors
Katherine Ogurtsova
Thomas L. Heise
Ute Linnenkamp
Charalabos-Markos Dintsios
Stefan K. Lhachimi
Andrea Icks
Publication date
01-12-2017
Publisher
BioMed Central
Published in
Systematic Reviews / Issue 1/2017
Electronic ISSN: 2046-4053
DOI
https://doi.org/10.1186/s13643-017-0664-7

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