ArticleDiabetes care2016
Racial Differences in the Performance of Existing Risk Prediction Models for Incident Type 2 Diabetes: The CARDIA Study.
Article in Diabetes care, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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24 citing papers in PubMed, 35 citations in OpenAlex.
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- Obesity Measures as Predictors of Type 2 Diabetes and Cardiovascular Diseases among the Jordanian Population: A Cross-Sectional Study.International journal of environmental research and public health · 2021Article
- Nomogram Model for Screening the Risk of Type II Diabetes in Western Xinjiang, China.Diabetes, metabolic syndrome and obesity : targets and therapy · 2021Article
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- Association between obesity phenotypes of insulin resistance and risk of type 2 diabetes in African Americans: The Jackson Heart Study.Journal of clinical & translational endocrinology · 2020Article
- Prevalence of Prediabetes Among Adolescents and Young Adults in the United States, 2005-2016.JAMA pediatrics · 2020Article
- Development and Validation of a Novel Model for Predicting the 5-Year Risk of Type 2 Diabetes in Patients with Hypertension: A Retrospective Cohort Study.BioMed research international · 2020Article
- Glycosylated Hemoglobin A1c Improves the Performance of the Nomogram for Predicting the 5-Year Incidence of Type 2 Diabetes.Diabetes, metabolic syndrome and obesity : targets and therapy · 2020Article
- Development and Validation of a Nomogram to Predict Type 2 Diabetes Mellitus in Overweight and Obese Adults: A Prospective Cohort Study from 82938 Adults in China.International journal of endocrinology · 2020Article
- Nomogram prediction for the 3-year risk of type 2 diabetes in healthy mainland China residents.The EPMA journal · 2019Article
- A Review of Diabetes Prediction Equations in African Descent Populations.Frontiers in endocrinology · 2019Review
- Article
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11 authors at 6 institutions in 1 country.
Funding
Abstract
objectiveIn 2010, the American Diabetes Association (ADA) added hemoglobin A1c (A1C) to the guidelines for diagnosing type 2 diabetes. However, existing models for predicting diabetes risk were developed prior to the widespread adoption of A1C. Thus, it remains unknown how well existing diabetes risk prediction models predict incident diabetes defined according to the ADA 2010 guidelines. Accordingly, we examined the performance of an existing diabetes prediction model applied to a cohort of African American (AA) and white adults from the Coronary Artery Risk Development Study in Young Adults (CARDIA). RESEARCH DESIGN AND
methodsWe evaluated the performance of the Atherosclerosis Risk in Communities (ARIC) diabetes risk prediction model among 2,456 participants in CARDIA free of diabetes at the 2005-2006 exam and followed for 5 years. We evaluated model discrimination, calibration, and integrated discrimination improvement with incident diabetes defined by ADA 2010 guidelines before and after adding baseline A1C to the prediction model.
resultsIn the overall cohort, re-estimating the ARIC model in the CARDIA cohort resulted in good discrimination for the prediction of 5-year diabetes risk (area under the curve [AUC] 0.841). Adding baseline A1C as a predictor improved discrimination (AUC 0.841 vs. 0.863, P = 0.03). In race-stratified analyses, model discrimination was significantly higher in whites than AA (AUC AA 0.816 vs. whites 0.902; P = 0.008).
conclusionsAddition of A1C to the ARIC diabetes risk prediction model improved performance overall and in racial subgroups. However, for all models examined, discrimination was better in whites than AA. Additional studies are needed to further improve diabetes risk prediction among AA.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.