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Interpreting Hemoglobin A1C in Combination With Conventional Risk Factors for Prediction of Cardiovascular Risk.

ABSTRACT: Hemoglobin A1C (HbA1C) is associated with increased risk of cardiovascular events, but its use for prediction of cardiovascular disease (CVD) events in combination with conventional risk factors has not been well defined.To understand the effect of HbA1C on CVD risk in the context of other CVD risk factors, we analyzed HbA1C and other CVD risk factor measurements in 2000 individuals aged 40 to 79 years without pre-existing diabetes mellitus or CVD from the 2011 to 2012 National Health and Nutrition Examination Surveys survey. The resulting regression model was used to predict the HbA1C distribution based on individual patient characteristics. We then calculated post-test 10-year atherosclerotic CVD risk incorporating the actual versus predicted HbA1C, according to established methods, for a set of example scenarios. Age, sex, race/ethnicity, and traditional cardiovascular risk factors were significant predictors of HbA1C in our model, with the expected HbA1C distribution being significantly higher in non-Hispanic black, non-Hispanic Asian, and Hispanic individuals than that in non-Hispanic white/other individuals. Incorporating the expected HbA1C distribution into pretest atherosclerotic CVD risk has a modest effect on post-test atherosclerotic CVD risk. In the patient examples, we assessed that having an HbA1C of <5.7% reduced post-test risk by 0.4% to 2.0% points, whereas having an HbA1C of ?6.5% increased post-test risk by 1.0% to 2.5% points, depending on the scenario. The post-test risk increase from having an HbA1C of ?6.5% tends to approximate the risk increase from being 5 years older.HbA1C has modest effects on predicted atherosclerotic CVD risk when considered in the context of conventional risk factors.

SUBMITTER: Jarmul JA

PROVIDER: S-EPMC4703493 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

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Interpreting Hemoglobin A1C in Combination With Conventional Risk Factors for Prediction of Cardiovascular Risk.

Jarmul Jamie A JA Pignone Michael M Pletcher Mark J MJ

Circulation. Cardiovascular quality and outcomes 20150901 5

<h4>Background</h4>Hemoglobin A1C (HbA1C) is associated with increased risk of cardiovascular events, but its use for prediction of cardiovascular disease (CVD) events in combination with conventional risk factors has not been well defined.<h4>Methods and results</h4>To understand the effect of HbA1C on CVD risk in the context of other CVD risk factors, we analyzed HbA1C and other CVD risk factor measurements in 2000 individuals aged 40 to 79 years without pre-existing diabetes mellitus or CVD f ...[more]

PMID: 26349840

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Project description:the purpose of this study was to assess the predictive accuracy of conventional cardiovascular risk factors for incident heart failure and atrial fibrillation, and the added benefit of multiple biomarkers reflecting diverse pathophysiological pathways.heart failure and atrial fibrillation are interrelated cardiac diseases associated with substantial morbidity and mortality and increasing incidence. Data on prediction and prevention of these diseases in healthy individuals are limited.in 5,187 individuals from the community-based MDCS (Malmö Diet and Cancer Study), we studied the performance of conventional risk factors and 6 biomarkers including midregional pro-atrial natriuretic peptide (MR-proANP), N-terminal pro-B-type natriuretic peptide (NT-proBNP), midregional pro-adrenomedullin, cystatin C, C-reactive protein (CRP), and copeptin.during a mean follow-up of 14 years, 112 individuals were diagnosed with heart failure and 284 individuals with atrial fibrillation. NT-proBNP (hazard ratio [HR]: 1.63 per SD, 95% confidence interval [CI]: 1.29 to 2.06, p < 0.001), CRP (HR: 1.57 per SD, 95% CI: 1.28 to 1.94, p < 0.001), and MR-proANP (HR: 1.26 per SD, 95% CI: 1.02 to 1.56, p = 0.03) predicted incident heart failure independently of conventional risk factors and other biomarkers. MR-proANP (HR: 1.62, 95% CI: 1.42 to 1.84, p < 0.001) and CRP (HR: 1.18, 95% CI: 1.03 to 1.34, p = 0.01) independently predicted atrial fibrillation. Addition of biomarkers to conventional risk factors improved c-statistics from 0.815 to 0.842 for heart failure and from 0.732 to 0.753 for atrial fibrillation and the integrated discrimination improvement for both diseases (p < 0.001). Net reclassification improvement (NRI) with biomarkers was observed in 22% of individuals for heart failure (NRI, p < 0.001) and in 7% for atrial fibrillation (NRI, p = 0.06), mainly due to up-classification of individuals who developed disease (heart failure: 29%, atrial fibrillation: 19%). Addition of CRP to natriuretic peptides did not improve discrimination or reclassification.conventional cardiovascular risk factors predict incident heart failure and atrial fibrillation with reasonable accuracy in middle-age individuals free from disease. Natriuretic peptides, but not other biomarkers, improve discrimination modestly for both diseases above and beyond conventional risk factors and substantially improve risk classification for heart failure.

Project description: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.

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Interpreting Hemoglobin A1C in Combination With Conventional Risk Factors for Prediction of Cardiovascular Risk.

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Interpreting Hemoglobin A1C in Combination With Conventional Risk Factors for Prediction of Cardiovascular Risk.

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