Key result
Higher FVC is linked to ~15% lower 10-year CVD mortality and enhances PREVENT risk prediction.
Why the study?
The impact of adding spirometry metrics to the American Heart Association Predicting Risk of Cardiovascular Disease Events (PREVENT) equations model for predicting CVD mortality needed evaluation.
Does adding spirometry metrics (FVC and FEV1) to the PREVENT equations improve the prediction of composite CVD-related mortality in U.S. adults without prevalent atherosclerotic CVD or pulmonary disease?
Cohort (n=5,019)
Does adding spirometry metrics (FVC and FEV1) to the PREVENT equations improve the prediction of composite CVD-related mortality in U.S. adults without prevalent atherosclerotic CVD or pulmonary disease?
Hazard Ratio: 0.85 (95% CI 0.79–0.9)
Adding spirometry metrics, particularly FVC, to the AHA PREVENT equations modestly improves discrimination and reclassification for 10-year cardiovascular mortality in adults without baseline cardiovascular or pulmonary disease.
Higher FVC associated with lower CVD mortality; extends PREVENT equations but hypothesis-generating and should not change practice.
Aim To evaluate the impact of adding spirometry metrics to the American Heart Association Predicting Risk of Cardiovascular Disease Events (PREVENT) equations model on CVD mortality. Methods This study used data from a nationally representative sample of U.S. adults without prevalent atherosclerotic CVD or pulmonary disease who underwent spirometry in the National Health and Nutrition Examination Survey (NHANES) 2007 to 2012 data cycles. The association of forced vital capacity (FVC) and forced expired volume in 1-second (FEV 1 ) with composite CVD-related mortality was assessed. Cox proportional hazard models were used to estimate hazard ratios (HR). Harrell's c-statistic, net reclassification improvement, area under the receiver operator characteristic curve (ROC-AUC), and precision-recall analyses were used to compare incremental contributions of each spirometry measure when added to PREVENT. Results The study cohort included 5019 adult individuals, when accounting for NHANES complex survey design, represented 72.8 million individuals. At 10 years of follow-up, composite CVD occurred in 2% of the cohort. In adjusted analyses, higher FVC and FEV 1 were associated with lower CVD mortality (HR: 0.85, 95%CI: 0.79–0.90 and HR: 0.81, 95%CI: 0.74–0.90, respectively). Adding FVC to PREVENT predicted CVD mortality (HR: 1.06, 95%CI: 1.05–1.07). The addition of FVC to PREVENT enhanced discrimination (0.005, 95%CI: 0.001–0.009), ROC-AUC, reclassification (0.086, 95%CI: 0.018–0.156), and positive prediction value (0.004, 95%CI: 0.018–0.156) compared to using the PREVENT model as reference. Conclusions The inclusion of spirometry in the PREVENT model may enhance accuracy of CVD mortality risk.
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Smith et al. (2026) conducted a cohort in Cardiovascular mortality risk in adults without prevalent atherosclerotic CVD or pulmonary disease (n=5,019). Spirometry metrics (FVC and FEV1) added to PREVENT equations vs. PREVENT model alone was evaluated on Composite CVD-related mortality (HR 0.85, 95% CI 0.79-0.90). Higher FVC was associated with lower 10-year CVD mortality (HR 0.85, 95% CI 0.79-0.90) and improved PREVENT model discrimination and reclassification.
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