Identification and validation of asthma phenotypes in Chinese population using cluster analysis

Abstract

BackgroundAsthma is a heterogeneous airway disease, so it is crucial to clearly identify clinical phenotypes to achieve better asthma management. ObjectiveTo identify and prospectively validate asthma clusters in a Chinese population. MethodsTwo hundred eighty-four patients were consecutively recruited and 18 sociodemographic and clinical variables were collected. Hierarchical cluster analysis was performed by the Ward method followed by k-means cluster analysis. Then, a prospective 12-month cohort study was used to validate the identified clusters. ResultsFive clusters were successfully identified. Clusters 1 (n = 71) and 3 (n = 81) were mild asthma phenotypes with slight airway obstruction and low exacerbation risk, but with a sex differential. Cluster 2 (n = 65) described an “allergic” phenotype, cluster 4 (n = 33) featured a “fixed airflow limitation” phenotype with smoking, and cluster 5 (n = 34) was a “low socioeconomic status” phenotype. Patients in clusters 2, 4, and 5 had distinctly lower socioeconomic status and more psychological symptoms. Cluster 2 had a significantly increased risk of exacerbations (risk ratio [RR] 1.13, 95% confidence interval [CI] 1.03–1.25), unplanned visits for asthma (RR 1.98, 95% CI 1.07–3.66), and emergency visits for asthma (RR 7.17, 95% CI 1.26–40.80). Cluster 4 had an increased risk of unplanned visits (RR 2.22, 95% CI 1.02–4.81), and cluster 5 had increased emergency visits (RR 12.72, 95% CI 1.95–69.78). Kaplan-Meier analysis confirmed that cluster grouping was predictive of time to the first asthma exacerbation, unplanned visit, emergency visit, and hospital admission (P < .0001 for all comparisons). ConclusionWe identified 3 clinical clusters as “allergic asthma,” “fixed airflow limitation,” and “low socioeconomic status” phenotypes that are at high risk of severe asthma exacerbations and that have management implications for clinical practice in developing countries.