Performance of A1C for the Classification and Prediction of Diabetes

Abstract

OBJECTIVE Although A1C is now recommended to diagnose diabetes, its test performance for diagnosis and prognosis is uncertain. Our objective was to assess the test performance of A1C against single and repeat glucose measurements for diagnosis of prevalent diabetes and for prediction of incident diabetes. RESEARCH DESIGN AND METHODS We conducted population-based analyses of 12,485 participants in the Atherosclerosis Risk in Communities (ARIC) study and a subpopulation of 691 participants in the Third National Health and Nutrition Examination Survey (NHANES III) with repeat test results. RESULTS Against a single fasting glucose ≥126 mg/dl, the sensitivity and specificity of A1C ≥6.5% for detection of prevalent diabetes were 47 and 98%, respectively (area under the curve 0.892). Against repeated fasting glucose (3 years apart) ≥126 mg/dl, sensitivity improved to 67% and specificity remained high (97%) (AUC 0.936). Similar results were obtained in NHANES III against repeated fasting glucose 2 weeks apart. The accuracy of A1C was consistent across age, BMI, and race groups. For individuals with fasting glucose ≥126 mg/dl and A1C ≥6.5% at baseline, the 10-year risk of diagnosed diabetes was 88% compared with 55% among those individuals with fasting glucose ≥126 mg/dl and A1C 5.7–<6.5%. CONCLUSIONS A1C performs well as a diagnostic tool when diabetes definitions that most closely resemble those used in clinical practice are used as the “gold standard.” The high risk of diabetes among individuals with both elevated fasting glucose and A1C suggests a dual role for fasting glucose and A1C for prediction of diabetes. Although A1C is now recommended for the diagnosis of diabetes (1,2), its precise test performance is uncertain. The lack of a single, clear “gold standard” poses a challenge for determining the performance of A1C. Previous diagnostic studies of A1C have relied exclusively on a single elevated fasting or 2-h glucose values as gold standards (3–5). However, because glucose determinations are inherently more variable than A1C (6), these convenient gold standards are likely to reduce the apparent accuracy of A1C as a diagnostic test. A stronger gold standard would rely on repeated glucose determinations on different days (2), i.e., the recommended approach to diagnosis of diabetes in clinical practice. Alternatively, A1C and fasting glucose can be compared head-to-head against the subsequent development of clinically diagnosed diabetes as the gold standard. We hypothesized that 1) A1C would perform well as a diagnostic and prognostic test for diabetes across its full range and at the American Diabetes Association–recommended threshold of 6.5% and 2) that its performance would be best when judged against stronger, most clinically relevant gold standards