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Longitudinal multi-trajectory phenotypes of severe eosinophilic asthma on type 2 biologics treatmentopen access

Authors
Pham,, Duong DucLee,, Ji-HyangKwon,, Hyouk-SooSong,, Woo-JungCho,, You SookKim,, HyunkyoungKwon,, Jae-WooPark,, So-YoungKim,, SujeongHur,, Gyu YoungKim,, Byung KeunNam,, Young-HeeYang,, Min-SukKim,, Mi-YeongKim,, Sae-HoonLee,, Byung-JaeLee,, TaehoonPark,, So YoungKim,, Min-HyeCho,, Young-JooPark,, ChanSunJung,, Jae-WooPark,, Han KiKim,, Joo-HeeMoon,, Ji-YongBhavsar, PankajAdcock,, Ian M.Chung,, Kian FanKim,, Tae-Bum
Issue Date
Dec-2024
Publisher
Elsevier Inc.
Keywords
Multi-trajectory analysis; Severe eosinophilic asthma; Type 2 biologics
Citation
World Allergy Organization Journal, v.17, no.12, pp 1 - 13
Pages
13
Indexed
SCIE
SCOPUS
Journal Title
World Allergy Organization Journal
Volume
17
Number
12
Start Page
1
End Page
13
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/211689
DOI
10.1016/j.waojou.2024.101000
ISSN
1939-4551
Abstract
Background: Limited understanding exists regarding the progression trajectory of severe eosinophilic asthma (SEA) patients on type 2 biologics therapies. Objective: We aim to explore distinct longitudinal phenotypes of these patients based on crucial asthma biomarkers. Methods: We enrolled 101 adult patients with SEA. Of these, 51 were treated with anti-IL5/IL5Rα or anti-IL5/IL5RαR antibody, and 50 with anti-IL-4Rα antibody. Multi-trajectory analysis, an extension of univariate group-based trajectory modeling, was used to categorize patients based on their trajectories of forced expiratory volume in 1 s (FEV1), blood eosinophil counts (BEC), and fractional exhaled nitric oxide (FeNO) levels at baseline, and after 1, 6, and 12 months of treatment. Associations between trajectory-based clusters and clinical parameters were examined. Results: Among anti-IL5/IL5Rα antibody-treated patients, 2 clusters were identified. The cluster characterized by higher baseline BEC and lower FEV1 showed a better response, with improvements in FEV1 and reductions in BEC over time. Among anti-IL-4Rα antibody-treated, 3 clusters were identified. Clusters with moderate BEC and FeNO at baseline demonstrated better improvements in FEV1 and reductions in FeNO, despite increased BEC during follow-up. Conversely, individuals with extremely low FeNO and high BEC at baseline were more likely to experience poorer progression, demonstrating an increase in FeNO and a reduction in FEV1. Conclusion: To optimally monitor treatment response in SEA patients on type 2 biologics, integrating longitudinal biomarker features is essential.
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