Can spirometry improve the performance of cardiovascular risk model in high-risk Eastern European countries?

AIMS: Impaired lung function has been strongly associated with cardiovascular disease (CVD) events. We aimed to assess the additive prognostic value of spirometry indices to the risk estimation of CVD events in Eastern European populations in this study. METHODS: We randomly selected 14,061 individuals with a mean age of 59 ± 7.3 years without a previous history of cardiovascular and pulmonary diseases from population registers in the Czechia, Poland, and Lithuania. Predictive values of standardised Z-scores of forced expiratory volume measured in 1 s (FEV1), forced vital capacity (FVC), and FEV1 divided by height cubed (FEV1/ht(3)) were tested. Cox proportional hazards models were used to estimate hazard ratios (HRs) of CVD events of various spirometry indices over the Framingham Risk Score (FRS) model. The model performance was evaluated using Harrell’s C-statistics, likelihood ratio tests, and Bayesian information criterion. RESULTS: All spirometry indices had a strong linear relation with the incidence of CVD events (HR ranged from 1.10 to 1.12 between indices). The model stratified by FEV1/ht(3) tertiles had a stronger link with CVD events than FEV1 and FVC. The risk of CVD event for the lowest vs. highest FEV1/ht(3) tertile among people with low FRS was higher (HR: 2.35; 95% confidence interval: 1.96–2.81) than among those with high FRS. The addition of spirometry indices showed a small but statistically significant improvement of the FRS model. CONCLUSIONS: The addition of spirometry indices might improve the prediction of incident CVD events particularly in the low-risk group. FEV1/ht(3) is a more sensitive predictor compared to other spirometry indices.