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. 2021 Mar;9(3):1285-1294.e6.
doi: 10.1016/j.jaip.2020.09.055. Epub 2020 Oct 10.

Longitudinal Outcomes of Severe Asthma: Real-World Evidence of Multidimensional Analyses

Youngsoo Lee  1 , Youjin Park  2 , Chungsoo Kim  2 , Eunyoung Lee  3 , Hyun Young Lee  4 , Seong-Dae Woo  1 , Seng Chan You  5 , Rae Woong Park  6 , Hae-Sim Park  7
Affiliations

Longitudinal Outcomes of Severe Asthma: Real-World Evidence of Multidimensional Analyses

Youngsoo Lee et al. J Allergy Clin Immunol Pract. 2021 Mar.

Erratum in

  • Corrections.
    [No authors listed] [No authors listed] J Allergy Clin Immunol Pract. 2021 Jun;9(6):2553. doi: 10.1016/j.jaip.2021.04.004. J Allergy Clin Immunol Pract. 2021. PMID: 34112496 No abstract available.

Abstract

Background: There have been few studies assessing long-term outcomes of asthma based on regular follow-up data.

Objective: We aimed to demonstrate clinical outcomes of asthma by multidimensional analyses of a long-term real-world database and a prediction model of severe asthma using machine learning.

Methods: The database included 567 severe and 1337 nonsevere adult asthmatics, who had been monitored during a follow-up of up to 10 years. We evaluated longitudinal changes in eosinophilic inflammation, lung function, and the annual number of asthma exacerbations (AEs) using a linear mixed effects model. Least absolute shrinkage and selection operator logistic regression was used to develop a prediction model for severe asthma. Model performance was evaluated and validated.

Results: Severe asthmatics had higher blood eosinophil (P = .02) and neutrophil (P < .001) counts at baseline than nonsevere asthmatics; blood eosinophil counts showed significantly slower declines in severe asthmatics than nonsevere asthmatics throughout the follow-up (P = .009). Severe asthmatics had a lower level of forced expiratory volume in 1 second (P < .001), which declined faster than nonsevere asthmatics (P = .033). Severe asthmatics showed a higher annual number of severe AEs than nonsevere asthmatics. The prediction model for severe asthma consisted of 17 variables, including novel biomarkers.

Conclusions: Severe asthma is a distinct phenotype of asthma with persistent eosinophilia, progressive lung function decline, and frequent severe AEs even on regular asthma medication. We suggest a useful prediction model of severe asthma for research and clinical purposes.

Keywords: Asthma exacerbation; Clinical outcome; Eosinophil; Inflammation; Real-world evidence; Severe asthma.

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