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Two-Step Approach for the Prediction of Future Type 2 Diabetes Risk

På svenska

Author

  • Muhammad A. Abdul-Ghani
  • Tamam Abdul-Ghani
  • Michael P. Stern
  • Jasmina Karavic
  • Tiinamaija Tuomi
  • Insoma Bo
  • Ralph A. DeFronzo
  • Leif Groop

Summary, in English

OBJECTIVE-To develop a model for the prediction of type 2 diabetes mellitus (T2DM) risk on the basis of a multivariate logistic model and 1-h plasma glucose concentration (1-h PG). RESEARCH DESIGN AND METHODS-The model was developed in a cohort of 1,562 non-diabetic subjects from the San Antonio Heart Study (SAHS) and validated in 2,395 nondiabetic subjects in the Botnia Study. A risk score on the basis of anthropometric parameters, plasma glucose and lipid profile, and blood pressure was computed for each subject. Subjects with a risk score above a certain cut point were considered to represent high-risk individuals, and their 1-h PG concentration during the oral glucose tolerance test was used to further refine their future T2DM risk. RESULTS-We used the San Antonio Diabetes Prediction Model (SADPM) to generate the initial risk score. A risk-score value of 0.065 was found to be an optimal cut point for initial screening and selection of high-risk individuals. A 1-h PG concentration >140 mg/dL in high-risk individuals (whose risk score was >0.065) was the optimal cut point for identification of subjects at increased risk. The two cut points had 77.8, 77.4, and 44.8% (for the SAHS) and 75.8, 71.6, and 11.9% (for the Botnia Study) sensitivity, specificity, and positive predictive value, respectively, in the SAHS and Botnia Study. CONCLUSIONS-A two-step model, based on the combination of the SADPM and 1-h PG, is a useful tool for the identification of high-risk Mexican-American and Caucasian individuals. Diabetes Care 34:2108-2112, 2011

Publishing year

2011

Language

English

Pages

2108-2112

Publication/Series

Diabetes Care

Volume

34

Issue

9

Document type

Journal article

Publisher

American Diabetes Association

Topic

  • Endocrinology and Diabetes

Status

Published

Research group

  • Translational Muscle Research

ISBN/ISSN/Other

  • ISSN: 1935-5548