Clusters of Severe Eosinophilic Asthma in a Korean Asthma Cohort

Ji Hyang Lee, Jin An, Ha Kyeong Won, Bomi Seo, Jung Hyun Kim, So Young Park, Min Hye Kim, Yoo Seob Shin, Jae Woo Jung, Woo Jung Song, Taehoon Lee, Hyouk Soo Kwon, Jae Hyun Lee, Joo Hee Kim, Sae Hoon Kim, Yoon Seok Chang, You Sook Cho, Dong Ho Nahm, An Soo Jang, Jung Won ParkHo Joo Yoon, Sang Heon Cho, Young Joo Cho, Byoung Whui Choi, Hee Bom Moon, Tae Bum Kim

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Targeted therapies have broadened the available treatment options for patients with severe eosinophilic asthma (SEA). However, differences in the magnitude of treatment responses among patients indicate the presence of various underlying pathophysiological processes and patient subgroups. Objectives: We aimed to describe the characteristics of SEA and identify its patient subgroups. Methods: Clinical data from the Cohort for Reality and Evolution of Adult Asthma in Korea were analyzed. Cluster analysis was performed among those with SEA using 5 variables, namely, prebronchodilator forced expiratory volume in 1 s, body mass index, age at symptom onset, smoking amount, and blood eosinophil counts. Results: Patients with SEA showed prevalent sensitization to aeroallergens, decreased lung function, and poor asthma control status. Cluster analysis revealed 3 distinctive subgroups among patients with SEA. Cluster 1 (n = 177) consisted of patients reporting the lowest blood eosinophils (median, 346.8 cells/μL) and modest severe asthma with preserved lung function during the 12-month treatment period. Cluster 2 (n = 42) predominantly included smoking males with severe persistent airway obstruction and moderate eosinophilia (median, 451.8 cells/μL). Lastly, cluster 3 (n = 95) included patients with the most severe asthma, the highest eosinophil levels (median, 817.5 cells/μL), and good treatment response in terms of improved lung function and control status. Conclusions: Three subgroups were identified in SEA through the cluster analysis. The distinctive features of each cluster may help physicians predict patients who will respond to biologics with greater magnitude of clinical improvement. Further research regarding the underlying pathophysiology and clinical importance of each subgroup is warranted.

Original languageEnglish
Pages (from-to)465-475
Number of pages11
JournalRespiration
Volume101
Issue number5
DOIs
StatePublished - 1 May 2022

Keywords

  • Asthma
  • Biologics
  • Cluster analysis
  • Severe eosinophilic asthma

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