Quantifying Importance of Major Risk Factors for Coronary Heart Disease

Abstract

Background: To optimize preventive strategies for coronary heart disease (CHD), it is essential to understand and appropriately quantify the contribution of its key risk factors. Our objective was to compare the associations of key modifiable CHD risk factors-specifically lipids, systolic blood pressure (SBP), diabetes mellitus, and smoking-with incident CHD events based on their prognostic performance, attributable risk fractions, and treatment benefits, overall and by age.

Methods: Pooled participant-level data from 4 observational cohort studies sponsored by the National Heart, Lung, and Blood Institute were used to create a cohort of 22 626 individuals aged 45 to 84 years who were initially free of cardiovascular disease. Individuals were followed for 10 years from baseline evaluation for incident CHD. Proportional hazards regression was used to estimate metrics of prognostic model performance (likelihood ratio, C index, net reclassification, discrimination slope), hazard ratios, and population attributable fractions for SBP, non-high-density lipoprotein cholesterol (non-HDL-C), diabetes mellitus, and smoking. Expected absolute risk reductions for antihypertensive and lipid-lowering treatment were assessed.

Results: Age, sex, and race capture 63% to 80% of the prognostic performance of cardiovascular risk models. In contrast, adding either SBP, non-HDL-C, diabetes mellitus, or smoking to a model with other risk factors increases the C index by only 0.004 to 0.013. However, primordial prevention could have a substantial effect as demonstrated by population attributable fractions of 28% for SBP≥130 mm Hg and 17% for non-HDL-C≥130 mg/dL. Similarly, lowering the SBP of all individuals to <130 mm Hg or lowering low-density lipoprotein cholesterol by 30% would be expected to lower a baseline 10-year CHD risk of 10.7% to 7.0 and 8.0, respectively (absolute risk reductions: 3.7% and 2.7%, respectively). Prognostic performance decreases with age (C indices for age groups 45-54, 55-64, 65-74, 75-84 are 0.75, 0.72, 0.66, and 0.62, respectively), whereas absolute risk reductions increase (SBP: 1.1%, 2.3%, 5.4%, 10.3%, respectively; non-HDL-C: 1.1%, 2.0%, 3.7%, 5.9%, respectively).

Conclusions: Although individual modifiable CHD risk factors contribute only modestly to prognostic performance, our models indicate that eliminating or controlling these individual factors would lead to substantial reductions in total population CHD events. Metrics used to judge importance of risk factors should be tailored to the research objectives.

Keywords: blood pressure; cholesterol, LDL; coronary disease; lipoproteins, HDL2; population; risk factors.

Figure 1.

Prognostic performance of the full risk model and absolute risk reductions associated with lowering of systolic blood pressure (SBP) and non–high-density lipoprotein cholesterol (non–HDL-C) by age group. A, C index of models with all risk factors (age, sex, race, SBP, non–HDL-C, diabetes mellitus, and smoking). B, Expected absolute risk reduction associated with lowering SBP below 130 mm Hg. C, Expected absolute risk reduction associated with lowering the low-density lipoprotein cholesterol portion of non–HDL-C by 30%.

Figure 2.

Population attributable fraction (PAF) for blood pressure and lipids as a function of percentage of individuals below the classification threshold. The 2 curves present PAFs as a function of risk factor level threshold (ie, the percentage of coronary heart disease risk that could be eliminated if systolic blood pressure [SBP] or non–high-density lipoprotein cholesterol levels never exceeded the numbers given in the table at the bottom [which correspond to the percentiles of risk factor distribution in our sample]). For example, the PAF associated with keeping SBP <125 mm Hg (40th percentile) is 29.9%, but it drops to 21.8% for SBP <142 mm Hg (60th percentile).