Novel Trajectories for Identifying Asthma Phenotypes: A Longitudinal Study in Korean Asthma Cohort, COREA

Abstract

Background: Unbiased cluster analysis has identified several asthma phenotypes. However, these phenotypes did not consistently predict disease prognosis and reflect temporal variability in airway inflammation.

Objective: We aimed to identify longitudinal trajectories in terms of pulmonary function parameters and investigated whether the trajectories are associated with prognosis.

Methods: Data were extracted from the Cohort for Reality and Evolution of Adult Asthma in Korea (COREA). Three-year pulmonary function test results were used to apply finite mixture models for group-based trajectory in 486 patients with eligible data set.

Results: Two main sets of longitudinal trajectories were identified in terms of FEV₁% predicted, and FEV₁ variability. In the 4 trajectories determined with FEV₁% predicted, the pulmonary function showed a consistent course in 4 stratified levels during 3 years of follow-up, which was associated with unexpected hospital visits and the use of steroid bursts due to exacerbation. The variability in pulmonary function showed 3 different patterns, and we found that higher blood and sputum eosinophil levels were associated with the higher variability in pulmonary function and more exacerbations.

Conclusions: Trajectory analysis is a novel method that provides longitudinal asthma phenotypes and aids in prediction of future risk of exacerbation. Further analysis is needed to validate the usefulness of these trajectories in an independent population.

Keywords: Asthma; Cluster analysis; Phenotypes; Trajectory.