A Simplified Finnish Diabetes Risk Score to Predict Type 2 Diabetes Risk and Disease Evolution in a German Population
Abstract
Aims The FINDRISC questionnaire is a screening tool to estimate the risks for type 2 diabetes as well as asymptomatic type 2 diabetes. We aimed to evaluate its performance to predict diabetes in a German population and to compare its predictive and detective ability in the same population. Methods A total of 552 subjects with increased risk of type 2 diabetes were investigated. All individuals completed the FINDRISC questionnaires and underwent an oral glucose tolerance test (OGTT). All individuals were followed for 3 years and underwent an OGTT again. The performance of the opportunistic screening was assessed with the area under the receiver operating characteristics curve (AUC). An intervention program was carried out for all diabetic and IFG/IGT patients at baseline. Results For identification, the asymptomatic type 2 DM was named Condition 1; prediction of type 2 DM risk in the follow-up survey as Condition 2; and diabetes risk predicting in a hypothetical case of survey without intervention program as Condition 3. The ROC-AUC in the three condition were AUC (FINDRISC1)=0.745, AUC (FINDRISC2)=0.789, and AUC (FINDRISC3)=0.775, respectively. A significant association between FINDRISC and evolution of disease was found, but the variation of plasma glucose during the three years follow-up was not associated with FINDRISC. People in the intervention group with an improvement of glucose tolerance had a smaller FINDRISC score than persons with an unchanged or progressive condit…
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
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 [18]
No citation lists for this paper
No citation lists for this paper yet — checked again daily.
Cited by 112
- Authors
- Bergmann, A., Li, J., Wang, L., Schulze, J., Bornstein, S., & Schwarz, P.
- Affiliations
- Technische Universität Dresden (DE)
- Venue
- Hormone and Metabolic Research
- Publisher
- Georg Thieme Verlag KG
- Published
- 2007-09
- Volume
- 39
- Issue
- 9
- Pages
- 677-682
- ISSN
- 0018-5043 (ISSN-L)
- 1439-4286
- OpenAlex
- W1970005405
- Cited by
- 112
- References
- 0
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 4 · 2023: 4 · 2022: 5 · 2021: 4 · 2020: 6 · 2019: 9 · 2018: 1 · 2017: 5 · 2016: 7 · 2015: 12 · 2014: 11 · 2013: 11 · 2012: 6
- FWCI
- 3.42
- 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
- FINDRISC, type 2 diabetes prediction, diabetes screening, impaired fasting glucose, impaired glucose tolerance, oral glucose tolerance test, disease progression, preventive interventions, German population
- MeSH terms
- Adult, Aged, Diabetes Mellitus, Type 2, Female, Finland, Germany, Humans, Male, Middle Aged, Population, Prognosis, Research Design, Risk Factors, Sensitivity and Specificity, Disease Progression
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review