HbA1c levels are increasingly measured in screening for diabetes; we investigated whether HbA1c may simultaneously improve cardiovascular disease (CVD) risk assessment, using QRISK3, American College of Cardiology/American Heart Association (ACC/AHA), and Systematic COronary Risk Evaluation (SCORE) scoring systems.
RESEARCH DESIGN AND METHODS
UK Biobank participants without baseline CVD or known diabetes (n = 357,833) were included. Associations of HbA1c with CVD was assessed using Cox models adjusting for classical risk factors. Predictive utility was determined by the C-index and net reclassification index (NRI). A separate analysis was conducted in 16,596 participants with known baseline diabetes.
Incident fatal or nonfatal CVD, as defined in the QRISK3 prediction model, occurred in 12,877 participants over 8.9 years. Of participants, 3.3% (n = 11,665) had prediabetes (42.0 47.9 mmol/mol [6.0 6.4%]) and 0.7% (n = 2,573) had undiagnosed diabetes (≥48.0 mmol/mol [≥6.5%]). In unadjusted models, compared with the reference group (<42.0 mmol/mol [<6.0%]), those with prediabetes and undiagnosed diabetes were at higher CVD risk: hazard ratio (HR) 1.83 (95% CI 1.69 1.97) and 2.26 (95% CI 1.96 2.60), respectively. After adjustment for classical risk factors, these attenuated to HR 1.11 (95% CI 1.03 1.20) and 1.20 (1.04 1.38), respectively. Adding HbA1c to the QRISK3 CVD risk prediction model (C-index 0.7392) yielded a small improvement in discrimination (C-index increase of 0.0004 [95% CI 0.0001 0.0007]). The NRI showed no improvement. Results were similar for models based on the ACC/AHA and SCORE risk models.
The near twofold higher unadjusted risk for CVD in people with prediabetes is driven mainly by abnormal levels of conventional CVD risk factors. While HbA1c adds minimally to cardiovascular risk prediction, those with prediabetes should have their conventional cardiovascular risk factors appropriately measured and managed.
Associations of blood biomarkers with cardiovascular disease and related cardiometabolic outcomes and risk prediction in the clinical setting
In UK Biobank planned blood tests are important in helping detect early signs of groups of related diseases in the heart, blood vessels, brain, as well as early signs of diabetes. We will investigate to what extent these blood tests tell us about how likely someone is to develop these conditions, how these conditions develop, and whether we can intervene. For instance, adding information from these tests might improve our ability to predict the risk of a person having a heart attack. By harnessing the power of genes, we will test whether some of these new markers cause disease. This project will aim to assess avenues to improve health care throughout the population by investigating the improvement of CVD risk scores. More sensitive CVD and related risk scores may lead to better targeting of treatment and a reduction in the burden of CVD in the population. Biomarker measurement in UK biobank has been commenced, and the first tranche of biomarkers to be measured are now known. We will assess whether these markers are associated with, and predict, risk of cardiovascular and metabolic-related conditions. Biomarkers of interest include:
Lipids and lipoproteins (different measures of blood cholesterol), markers of inflammation, markers, of liver function, markers of renal function, sex hormones, markers of glucose control, and markers of bone health. Each of these has plausible biological mechanisms linking them to risk of cardiovascular and metabolic diseases. The full cohort with available data will be explored to maximise generalisability to the whole adult population.
|Lead investigator:||Professor Naveed Sattar|
|Lead institution:||University of Glasgow|
4 related Returns
|Return ID||App ID||Description||Archive Date|
|2617||9310||Association of Total and Differential Leukocyte Counts With Cardiovascular Disease and Mortality in the UK Biobank||28 Oct 2020|
|2845||9310||Comparison of Conventional Lipoprotein Tests and Apolipoproteins in the Prediction of Cardiovascular Disease||23 Nov 2020|
|3638||9310||Glomerular filtration rate by differing measures, albuminuria and prediction of cardiovascular disease, mortality and end-stage kidney disease||9 Jul 2021|
|2844||9310||Urinary Sodium Excretion, Blood Pressure, and Risk of Future Cardiovascular Disease and Mortality in Subjects Without Prior Cardiovascular Disease||23 Nov 2020|