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- September 3, 2010 |
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CME on Diabetes is a website built to transmit top-level CME conferences given by international experts in endocrinology, insulin resistance, prediabetes, metabolic syndrome and type 2 diabetes. More than 2.6 million slides have been viewed since the website launch. Thank you for your continued support and commitment!
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"Prediction of Type 2 Diabetes (T2DM) using alternative definitions of Prediabetes"Dr. Ken Williams (biography)
English - 2005-04-14 - 22 minutes
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Summary :
Impaired glucose tolerance (IGT) and impaired fasting glucose (IFG) are commonly used to identify "PreDiabetic" individuals at high risk of developing T2DM. IGT is a simple and strong predictor but requires an unpopular oral glucose tolerance test (OGTT). We compared how well IGT and IFG predict T2DM relative to dichotomized versions of 4 alternative models using common clinical measurements: a published logistic regression model (LR), a tree model (TREE), the National Cholesterol Education Program metabolic syndrome (MetS), and the Enlarged Waist Elevated Triglycerides (EWET) criterion. The TREE yielded a simple rule: individuals are at high risk if they have fasting glucose > 95 mg/dl and either HDL cholesterol < 50 mg/dl or a family history of diabetes. We pooled data from the San Antonio Heart Study, the Mexico City Diabetes Study, and the Insulin Resistance Atherosclerosis Study totaling 379 conversions over 5-8 years among 3798 subjects in 4 different ethnic groups at 5 different centers. LR had the highest area under the Receiver Operating Characteristic curve (aROC) in the overall data set (71.0%) followed by IGT (69.7%), IFG (66.8%), MetS (66.1%), and EWET (61.7%). Only EWET had an aROC significantly different (p < 0.001) from the next higher aROC. LR offers equivalent risk assessment to IGT without requiring an OGTT but does require a programmable calculator. The simple TREE rule provided slightly better risk assessment than IFG with readily available measures.
Learning objectives :
After viewing this presentation, participants will be able to discuss:
- compare and contrast various prediabetes definitions;
- The decision Tree model as a prediabetes definition;
- Sensitivity and false positive rate of various prediabetes definitions in predicting type 2 diabetes.
Bibliographic references :
Report of the Expert Committee on the Diagnosis and Classification of Diabetes MellitusDiabetes Care 20: 1183-1197.
The Expert Committee on the Diagnosis and Classification of Diabetes MellitusReport of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus Diabetes Care 26:S5-S20, 2003
Kahn HS, Valdez R.Metabolic risks identified by the combination of enlarged waist and elevated triacylglycerol concentrationAm J Clin Nutr. 2003 Nov;78(5):928-34.
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