Role of Glycated Hemoglobin in the Prediction of Future Risk of T2DM

• Published in: The journal of clinical endocrinology and metabolism Vol. 96; no. 8; pp. 2596 - 2600
• Main Authors: Abdul-Ghani, Muhammad A, Abdul-Ghani, Tamam, Müller, Gabriele, Bergmann, Antje, Fischer, Sabine, Bornstein, Stefan, DeFronzo, Ralph A, Schwarz, Peter
• Format: Journal Article
• Language: English
• Published: Bethesda, MD Endocrine Society 01.08.2011
• Subjects: Biological and medical sciences; Blood Glucose - metabolism; Diabetes Mellitus, Type 2 - diagnosis; Diabetes Mellitus, Type 2 - epidemiology; Diabetes Mellitus, Type 2 - metabolism; Endocrinopathies; Feeding. Feeding behavior; Female; Follow-Up Studies; Fundamental and applied biological sciences. Psychology; Glycated Hemoglobin A - metabolism; Humans; Logistic Models; Male; Medical sciences; Middle Aged; Multivariate Analysis; Predictive Value of Tests; Risk Factors; ROC Curve; Sensitivity and Specificity; Vertebrates: anatomy and physiology, studies on body, several organs or systems; Vertebrates: endocrinology; Prospective; Obesity; Nutrition; Nutrition disorder; Risk factor; Prediction; Metabolic diseases; Risk; Glycated hemoglobin; Predictive factor; Endocrinology; Nutritional status
• ISSN: 0021-972X; 1945-7197
• DOI: 10.1210/jc.2010-1698

Aim: The aim of this study was to assess the predictive power of glycated hemoglobin (HbA1c) for future type 2 diabetes risk. Research Design and Methods: Six hundred eighty-seven subjects who were free of type 2 diabetes mellitus (T2DM) participated in the study. Each subject received a 75-g oral glucose tolerance test at baseline and 624 received a repeat oral glucose tolerance test after 3.5 ± 0.1 yr of follow-up. Anthropometric measurements, lipid profile, and HbA1c were measured during the baseline visit. Logistic multivariate models were created with T2DM status at follow-up as the dependent variable and other parameters as the independent variables. The receiver-operating characteristic (ROC) was used to assess the predictive discrimination of the various models. Results: HbA1c was a significant predictor of future T2DM risk (area under the ROC curve = 0.73, P < 0.0001). A HbA1c cut point of 5.65% had the maximal sum of sensitivity and specificity. Although the area under the ROC curve of HbA1c was smaller than the area under the ROC curve of both the 1-h plasma glucose concentration and a multivariate logistic model (including anthropometric parameters, lipid profile, and fasting plasma glucose), the addition of HbA1c to both the 1-h plasma glucose and the multivariate logistic model significantly increased their predictive power. Conclusion: Although HbA1c alone is a weaker predictor of future T2DM risk compared with the 1-h plasma glucose, it provides additive information about future T2DM risk when added to previously published prediction models.