Integrating Lung Function Parameters into the Framingham Score for Improved CVD Risk Prediction in COPD: A Cross-Sectional Study Based on NHANES 2007-2012.

Abstract

Individuals with Chronic Obstructive Pulmonary Disease (COPD) constitute a high-risk population for Cardiovascular Disease (CVD). There is growing concern that standard risk assessment tools like the Framingham Risk Score (FRS) may be subject to underestimation of CVD risk in COPD patients. Therefore, the potential of combining lung function parameters with the FRS to improve risk prediction warrants further exploration. To determine whether the integration of lung function parameters with the Framingham Risk Score enhances the prediction of prevalent cardiovascular disease among individuals with COPD. We performed a cross-sectional analysis of adults with COPD from the 2007-2012 NHANES cycles. COPD was defined as a post-bronchodilator FEV₁/FVC < 0.70 or a self-reported physician diagnosis of emphysema or chronic bronchitis. Cardiovascular disease (CVD) was defined as a self-reported history of coronary heart disease, congestive heart failure, heart attack, or angina. The primary predictors were the Framingham Risk Score (FRS) and multiple spirometric parameters, including FEV₁, FVC, FEV₁%pred, FVC%pred and FEV₁/FVC. The FRS, which estimates an individual's 10-year risk of developing CVD, was calculated using the established algorithm that incorporates sex, age, total and high-density lipoprotein (HDL) cholesterol levels, systolic blood pressure, antihypertensive medication use, smoking status, and diabetes status. We used multivariable logistic regression to assess their association with prevalent CVD. Model discrimination was evaluated using the area under the receiver operating characteristic curve (AUC), and the incremental value of adding lung function parameters to the FRS was formally tested with DeLong's test. Subgroup analyses were conducted to test the consistency of the main findings across different demographic and clinical strata. The integration of lung function parameters with the Framingham Risk Score (FRS) improved predictive discrimination. The AUC for the FRS-alone model was 0.646. This increased to 0.681 for FRS + FEV₁%pred, 0.702 for FRS + FVC%pred, and 0.724 for FRS + FEV₁/FVC. The addition of each spirometric measure provided statistically significant incremental value over the FRS alone (all *p* < 0.01 by DeLong's test), with the greatest improvement observed for the FEV₁/FVC.