Prediction models for risk of developing type 2 diabetes: systematic literature search and independent external validation studyBMJ 2012; 345 doi: https://doi.org/10.1136/bmj.e5900 (Published 18 September 2012) Cite this as: BMJ 2012;345:e5900
- Ali Abbasi, PhD fellow123,
- Linda M Peelen, assistant professor3,
- Eva Corpeleijn, assistant professor1,
- Yvonne T van der Schouw, professor of epidemiology of chronic diseases3,
- Ronald P Stolk, professor of clinical epidemiology1,
- Annemieke M W Spijkerman, research associate4,
- Daphne L van der A, research associate5,
- Karel G M Moons, professor of clinical epidemiology3,
- Gerjan Navis, professor of nephrology, internist-nephrologist2,
- Stephan J L Bakker, associate professor, internist-nephrologist/diabetologist2,
- Joline W J Beulens, assistant professor3
- 1Department of Epidemiology, University of Groningen, University Medical Centre Groningen, Groningen, Netherlands
- 2Department of Internal Medicine, University of Groningen, University Medical Centre Groningen, Groningen
- 3Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, Netherlands
- 4Centre for Prevention and Health Services Research, National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
- 5Centre for Nutrition and Health, National Institute for Public Health and the Environment (RIVM), Bilthoven
- Correspondence to: A Abbasi, Department of Epidemiology, University Medical Centre Groningen, Hanzeplein 1, PO Box 30.001, 9700 RB Groningen, Netherlands
- Accepted 27 August 2012
Objective To identify existing prediction models for the risk of development of type 2 diabetes and to externally validate them in a large independent cohort.
Data sources Systematic search of English, German, and Dutch literature in PubMed until February 2011 to identify prediction models for diabetes.
Design Performance of the models was assessed in terms of discrimination (C statistic) and calibration (calibration plots and Hosmer-Lemeshow test).The validation study was a prospective cohort study, with a case cohort study in a random subcohort.
Setting Models were applied to the Dutch cohort of the European Prospective Investigation into Cancer and Nutrition cohort study (EPIC-NL).
Participants 38 379 people aged 20-70 with no diabetes at baseline, 2506 of whom made up the random subcohort.
Outcome measure Incident type 2 diabetes.
Results The review identified 16 studies containing 25 prediction models. We considered 12 models as basic because they were based on variables that can be assessed non-invasively and 13 models as extended because they additionally included conventional biomarkers such as glucose concentration. During a median follow-up of 10.2 years there were 924 cases in the full EPIC-NL cohort and 79 in the random subcohort. The C statistic for the basic models ranged from 0.74 (95% confidence interval 0.73 to 0.75) to 0.84 (0.82 to 0.85) for risk at 7.5 years. For prediction models including biomarkers the C statistic ranged from 0.81 (0.80 to 0.83) to 0.93 (0.92 to 0.94). Most prediction models overestimated the observed risk of diabetes, particularly at higher observed risks. After adjustment for differences in incidence of diabetes, calibration improved considerably.
Conclusions Most basic prediction models can identify people at high risk of developing diabetes in a time frame of five to 10 years. Models including biomarkers classified cases slightly better than basic ones. Most models overestimated the actual risk of diabetes. Existing prediction models therefore perform well to identify those at high risk, but cannot sufficiently quantify actual risk of future diabetes.
We thank Statistics Netherlands and the PHARMO Institute for follow-up data on cancer, cardiovascular disease and vital status.
Contributors: AA, LMP, RPS, KGM, SJLB, and JWJB conceived and designed the study. AA, KGM, LMP, and JWJB analysed the data. AA, LMP, GN, and JWJB wrote the first draft of the manuscript. All authors contributed to the writing of the manuscript and agreed with manuscript results and conclusions. AA, LMP, and JWJB are guarantors.
Funding: This study was funded by the Netherlands Heart Foundation, the Dutch Diabetes Research Foundation and the Dutch Kidney Foundation, the Centre for Translational Molecular Medicine (project PREDICCt, grant 01C-104-07), Europe against Cancer Programme of the European Commission (SANCO), the Dutch Ministry of Health, the Dutch Cancer Society, the Netherlands Organization for Health Research and Development (ZonMW), and World Cancer Research Fund (WCRF), and the Netherlands Organization for Scientific Research project (9120.8004 and 918.10.615). None of the study sponsors had a role in the study design, data collection, analysis and interpretation, report writing, or the decision to submit the report for publication
Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.
Ethical approval: The EPIC-NL cohort complies with the Declaration of Helsinki and was approved by the relevant local medical ethics committees. All participants gave written informed consent before study inclusion.
Data sharing: No additional data available.
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