Tools for Predicting the Risk of Type 2 Diabetes in Daily Practice
Abstract
The discussion about the diagnosis and treatment of type 2 diabetes - and, more generally, dysglycaemia - should be framed in terms of a continuum of risk. A variety of tools have been developed to identify individuals with an increased risk of developing type 2 diabetes and to quantify the probability of type 2 diabetes either cross-sectionally or prospectively. Such scores are based on traditional risk factors for diabetes, such as age, body mass index (BMI), and family history, while others also evaluate metabolic risk factors such as lipid levels. The performance of a diabetes risk-prediction tool is generally assessed by measuring its accuracy, availability, practicability, and costs. This review discusses the validity and use of today's available major risk-prediction tools for clinical practice, and assesses the scope and cost-effectiveness of available tools. Among these prediction tools, American Diabetes Association (ADA) Risk Tools, Finnish Diabetes Risk Score (FINDRISC), National Health and Nutrition Examination Survey (NHANES) Risk Score, and Study to Prevent Non-Insulin Dependents Diabetes Mellitus (STOP-NIDDM) Risk Score were of our concern. We conclude that the FINDRISC tool is currently the best available tool for use in clinical practice in Caucasian populations, but modifications may be required if applied to other ethnic groups.
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FINDRISC is the most commonly evaluated diabetes risk score worldwide and has been recommended as the best available risk assessment tool for clinical practice by a systematic review.
“Moreover, FINDRISC is the most commonly evaluated diabetes risk score worldwide [17,18,19,20,21,22,23,24,25] and has been recommended as the best available risk assessment tool for use in the clinical practice by a systematic review [11].”
From A Novel Testing Model for Opportunistic Screening of Pre-Diabetes and Diabetes among U.S. Adults (2015) · cites this paper as [11]
Oral glucose tolerance test is the most valid tool for diagnosing diabetes.
“Oral glucose tolerance test (OGTT) has been shown to be the most valid tool for diagnosing diabetes [11].”
From A Novel Testing Model for Opportunistic Screening of Pre-Diabetes and Diabetes among U.S. Adults (2015) · cites this paper as [11]
Cited by
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2013 ESC guidelines on the management of stable coronary artery disease
Task Force Members, Montalescot, G., Sechtem, U., Achenbach, S., Andreotti, F., Arden, C., Budaj, A., Bugiardini, R., Crea, F., Cuisset, T., et al. (2013) · European Heart Journal · doi:10.1093/eurheartj/eht296 · Cited by 4,510 · see citing works
Risk assessment tools for identifying individuals at risk of developing type 2 diabetes
Buijsse, B., Simmons, R. K., Griffin, S. J., & Schulze, M. B. (2011) · Epidemiologic Reviews · doi:10.1093/epirev/mxq019 · Cited by 297 · see citing works
Makrilakis, K., Liatis, S., Grammatikou, S., Perrea, D., Stathi, C., Tsiligros, P., & Katsilambros, N. (2011) · Diabetes & Metabolism · doi:10.1016/j.diabet.2010.09.006 · Cited by 199 · see citing works
Rathmann, W., Kowall, B., Heier, M., Herder, C., Holle, R., Thorand, B., Strassburger, K., Peters, A., Wichmann, H. ‐., Giani, G., et al. (2010) · Diabetic Medicine · doi:10.1111/j.1464-5491.2010.03065.x · Cited by 74 · see citing works
Lin, J.-W., Chang, Y.-C., Li, H.-Y., Chien, Y.-F., Wu, M.-Y., Tsai, R.-Y., Hsieh, Y.-C., Chen, Y.-J., Hwang, J.-J., & Chuang, L.-M. (2009) · Diabetes Care · doi:10.2337/dc09-0694 · Cited by 60 · see citing works
“The predictive performance of these DRSs among Taiwanese was comparable to those in other European populations (13).”
ResultA Novel Testing Model for Opportunistic Screening of Pre-Diabetes and Diabetes among U.S. Adults
Zhang, Y., Hu, G., Zhang, L., Mayo, R., & Chen, L. (2015) · PLOS ONE · doi:10.1371/journal.pone.0120382 · Cited by 41 · see citing works
“Oral glucose tolerance test (OGTT) has been shown to be the most valid tool for diagnosing diabetes [11].”
MethodWinkler, G., Hídvégi, T., Vándorfi, G., Balogh, S., & Jermendy, G. (2013) · Medical Science Monitor · doi:10.12659/msm.883747 · Cited by 36 · see citing works
“Taken together, the 2-step screening method (following the completion of the questionnaire, blood glucose determination is carried out only for those at high risk) is recommended [24].”
MethodMansi, I. A., Sumithran, P., & Kinaan, M. (2023) · BMJ · doi:10.1136/bmj-2022-071727 · Cited by 20 · see citing works
- Authors
- Schwarz, P., Li, J., Lindstrom, J., & Tuomilehto, J.
- Affiliations
- University Hospital Carl Gustav Carus (DE)
- Venue
- Hormone and Metabolic Research
- Publisher
- Georg Thieme Verlag KG
- Published
- 2008-11-19
- Volume
- 41
- Issue
- 02
- Pages
- 86-97
- ISSN
- 0018-5043 (ISSN-L)
- 1439-4286
- OpenAlex
- W2014763445
- Cited by
- 213
- References
- 0
- Citations by year
- 2026: 6 · 2025: 3 · 2024: 6 · 2023: 7 · 2022: 14 · 2021: 10 · 2020: 11 · 2019: 12 · 2018: 10 · 2017: 7 · 2016: 17 · 2015: 16 · 2014: 17 · 2013: 17 · 2012: 19
- FWCI
- 9.65
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Hormone and Metabolic Research (publishedVersion)
- PubMed (publishedVersion)
- Site cant be reached (submittedVersion)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Keywords
- type 2 diabetes, diabetes risk prediction, risk scoring, FINDRISC, dysglycemia, body mass index, family history (medicine), serum lipids, cost-effectiveness, ethnic differences, clinical practice
- MeSH terms
- Aged, Diabetes Mellitus, Type 2, Europe, Female, Humans, Male, Middle Aged, Risk Factors, Body Mass Index, Practice Guidelines as Topic, Risk Assessment
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