Individual FEV₁ Trajectories Can Be Identified from a COPD Cohort

Abstract

Objective: We aim to make use of clinical spirometry data in order to identify individual COPD-patients with divergent trajectories of lung function over time. Study Design and Setting: Hospital-based COPD cohort (N = 607) was followed on average 4.6 years. Each patient had a mean of 8.4 spirometries available. We used a Hierarchical Bayesian Model (HBM) to identify the individuals presenting constant trends in lung function. Results: At a probability level of 95%, one third of the patients (180/607) presented rapidly declining FEV₁ (mean -78 ml/year, 95% CI -73 to -83 ml) compared to that in the rest of the patients (mean -26 ml/year, 95% CI -23 to -29 ml, p ≤ 2.2 × 10^-16). Constant improvement of FEV₁ was very rare. The rapid decliners more frequently suffered from exacerbations measured by various outcome markers. Conclusion: Clinical data of unique patients can be utilized to identify diverging trajectories of FEV₁ with a high probability. Frequent exacerbations were more prevalent in FEV₁-decliners than in the rest of the patients. The result confirmed previously reported association between FEV₁ decline and exacerbation rate and further suggested that in clinical practice HBM could improve the identification of high-risk individuals at early stages of the disease.

Keywords:

• COPD
• FEV₁ development
• FEV₁ slope
• hierarchical Bayesian model
• rapid decline