Glycated hemoglobin measurement and prediction of cardiovascular disease

Abstract

IMPORTANCE The value of measuring levels of glycated hemoglobin (HbA1c) for the prediction of first cardiovascular events is uncertain. OBJECTIVE To determine whether adding information on HbA1c values to conventional cardiovascular risk factors is associated with improvement in prediction of cardiovascular disease (CVD) risk. DESIGN, SETTING, AND PARTICIPANTS Analysis of individual-participant data available from 73 prospective studies involving 294 998 participants without a known history of diabetes mellitus or CVD at the baseline assessment. MAIN OUTCOMES AND MEASURES Measures of risk discrimination for CVD outcomes (eg, C-index) and reclassification (eg, net reclassification improvement) of participants across predicted 10-year risk categories of low (<5%), intermediate (5% to <7.5%), and high (≥7.5%) risk. RESULTS During a median follow-up of 9.9 (interquartile range, 7.6-13.2) years, 20 840 incident fatal and nonfatal CVD outcomes (13 237 coronary heart disease and 7603 stroke outcomes) were recorded. In analyses adjusted for several conventional cardiovascular risk factors, there was an approximately J-shaped association between HbA1c values and CVD risk. The association between HbA1c values and CVD risk changed only slightly after adjustment for total cholesterol and triglyceride concentrations or estimated glomerular filtration rate, but this association attenuated somewhat after adjustment for concentrations of high-density lipoprotein cholesterol and C-reactive protein. The C-index for a CVD risk prediction model containing conventional cardiovascular risk factors alone was 0.7434 (95% CI, 0.7350 to 0.7517). The addition of information on HbA1c was associated with a C-index change of 0.0018 (0.0003 to 0.0033) and a net reclassification improvement of 0.42 (−0.63 to 1.48) for the categories of predicted 10-year CVD risk. The improvement provided by HbA1c assessment in prediction of CVD risk was equal to or better than estimated improvements for measurement of fasting, random, or postload plasma glucose levels. CONCLUSIONS AND RELEVANCE In a study of individuals without known CVD or diabetes, additional assessment of HbA1c values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk. To help achieve reductions in diabetes-specific microvascular complications, guidelines recommend screening people for diabetes mellitus by assessing glycemia measures, such as fasting blood glucose levels and levels of glycated hemoglobin (HbA1c), a measure of glucose exposure over the previous 2 to 3 months.1,2 Furthermore, because higher levels of glycemia measures have also been associated with higher cardiovascular disease (CVD) incidence,3,4 it has been proposed that including information on glycemia measures in algorithms used to predict the risk of CVD might be associated with improvements in the ability to predict CVD.5- 7 The 2010 American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines concluded that measurement of HbA1c levels may be reasonable for CVD risk assessment in asymptomatic adults without a diagnosis of diabetes.8 In 2012 the Canadian Cardiovascular Society suggested that measurement of levels of fasting glucose, HbA1c, or both might be of value for CVD risk stratification.9 The Reynolds Risk Score for prediction of CVD risk incorporates information on HbA1c, although only for use in people known to have diabetes.10 However, measurement of glycemia measures was not recommended in the 2013 American College of Cardiology/American Heart Association Guideline on the Assessment of Cardiovascular Risk.11 The current study aimed to determine whether adding information on HbA1c levels to prognostic models containing conventional cardiovascular risk factors is associated with improvements in the prediction of first-onset CVD outcomes in middle-aged and older adults without a known history of diabetes. Additionally, we compared HbA1c measurement with assessment of other frequently used glycemia measures, ie, fasting, random, or postload glucose levels.