What Is the Best Predictor of Future Type 2 Diabetes? (original) (raw)
Cardiovascular and Metabolic Risk| June 01 2007
Muhammad A. Abdul-Ghani, MD, PHD;
Muhammad A. Abdul-Ghani, MD, PHD
From the Divisions of Diabetes and Clinical Epidemiology, University of Texas Health Science Center at San Antonio, San Antonio, Texas
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From the Divisions of Diabetes and Clinical Epidemiology, University of Texas Health Science Center at San Antonio, San Antonio, Texas
Search for other works by this author on:
From the Divisions of Diabetes and Clinical Epidemiology, University of Texas Health Science Center at San Antonio, San Antonio, Texas
Search for other works by this author on:
From the Divisions of Diabetes and Clinical Epidemiology, University of Texas Health Science Center at San Antonio, San Antonio, Texas
Search for other works by this author on:
Address correspondence and reprint requests to Muhammad A. Abdul-Ghani, MD, PhD, Diabetes Division, University of Texas Health Science Center, 7703 Floyd Curl Dr., MS 7886, San Antonio, TX 78229. E-mail: [email protected]
Diabetes Care 2007;30(6):1544–1548
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.
Published ahead of print at http://care.diabetesjournals.org on 23 March 2007. DOI: 10.2337/dc06-1331.
A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
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