What Is the Best Predictor of Future Type 2 Diabetes?

Author:

Abdul-Ghani Muhammad A.1,Williams Ken1,DeFronzo Ralph A.1,Stern Michael1

Affiliation:

1. From the Divisions of Diabetes and Clinical Epidemiology, University of Texas Health Science Center at San Antonio, San Antonio, Texas

Abstract

OBJECTIVE—We sought to assess insulin secretion/insulin resistance index in predicting the risk for future type 2 diabetes RESEARCH DESIGN AND METHODS—A total of 1,551 nondiabetic subjects from the San Antonio Heart Study received an oral glucose tolerance test (OGTT) with measurement of plasma glucose and insulin concentrations at 0, 30, 60, and 120 min at baseline and after 7–8 years of follow-up. Insulin secretion/insulin resistance index was calculated as the product of Matsuda index and ΔI0–30/ΔG0–30 or ΔI0–120/ΔG0–120. The discriminatory power of various prediction models for development of type 2 diabetes was tested with the area under the receiver-operating characteristic (ROC) curve. RESULTS—Insulin secretion/insulin resistance index (0- to 30- and 0- to 120-min time periods) had the greatest areas under the ROC curve (0.85 and 0.86, respectively), which were significantly greater than the 2-h plasma glucose concentration during the OGTT or the San Antonio Diabetes Prediction Model (SADPM) (P < 0.001 and P < 0.0001, respectively). A model based on the combination of the SADPM and a modified version of the insulin secretion/insulin resistance index or 1-h plasma glucose concentration had equal power to predict the risk for future type 2 diabetes compared with the insulin secretion/insulin resistance index. CONCLUSIONS—The insulin secretion/insulin resistance index is useful as a predictor of future development of type 2 diabetes. A model based on the combination of the SADPM and either a modified version of the insulin secretion/insulin resistance index or 1-h plasma glucose concentration can equally predict future type 2 diabetes.

Publisher

American Diabetes Association

Subject

Advanced and Specialized Nursing,Endocrinology, Diabetes and Metabolism,Internal Medicine

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