Cardiovascular risk prediction in diabetic men and women using hemoglobin A1c vs diabetes as a high-risk equivalent.

BACKGROUND: It is unclear whether models that include hemoglobin A(1c) (HbA(1c)) levels only for diabetic patients improve the ability to predict cardiovascular disease (CVD) risk compared with the currently recommended classification of diabetes as a cardiovascular risk equivalent.

METHODS: A total of 24 674 women (including 685 diabetic participants at baseline) and 11 280 men (including 563 diabetic participants at baseline) were followed up prospectively for cardiovascular disease (CVD). One hundred twenty-five CVD events occurred in diabetic women (666 in nondiabetic women), and 170 events occurred in diabetic men (1382 in nondiabetic men). Models for CVD risk were generated separately for men and women using the traditional CVD risk factors with the addition of a term for HbA(1c) levels only for diabetic individuals. In diabetic participants, the resulting predicted risks were compared with classification of diabetes as a cardiovascular risk equivalent (10-year CVD risk of at least 20%).

RESULTS: In women, the models including HbA(1c) levels in diabetic participants improved the C statistic by 0.177 (P < .001) over the risk equivalence model and showed improved reclassification (net reclassification improvement [NRI] of 26.7% [P = .001]). In men, the improvements were more modest but still statistically significant (C statistic change of 0.039 [P = .02]; NRI of 9.2% [P = .04]). Including HbA(1c) levels also improved prediction over a dichotomous term for diabetes in women (NRI of 11.8% [P = .03]) but not in men.

CONCLUSIONS: In both women and men with diabetes at baseline, we observed significant improvements in predictive ability of CVD risk using models incorporating HbA(1c) levels compared with classification of diabetes as a cardiovascular risk equivalent.