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

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dc.contributor.authorLee, Y-
dc.contributor.authorPark, Y-
dc.contributor.authorKim, C-
dc.contributor.authorLee, E-
dc.contributor.authorLee, HY-
dc.contributor.authorWoo, SD-
dc.contributor.authorYou, SC-
dc.contributor.authorPark, RW-
dc.contributor.authorPark, HS-
dc.date.accessioned2023-01-05T03:03:11Z-
dc.date.available2023-01-05T03:03:11Z-
dc.date.issued2021-
dc.identifier.issn2213-2198-
dc.identifier.urihttp://repository.ajou.ac.kr/handle/201003/23630-
dc.description.abstractBackground: 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.-
dc.language.isoen-
dc.subject.MESHAdult-
dc.subject.MESHAsthma-
dc.subject.MESHEosinophilia-
dc.subject.MESHEosinophils-
dc.subject.MESHForced Expiratory Volume-
dc.subject.MESHHumans-
dc.subject.MESHRespiratory Function Tests-
dc.titleLongitudinal Outcomes of Severe Asthma: Real-World Evidence of Multidimensional Analyses-
dc.typeArticle-
dc.identifier.pmid33049391-
dc.subject.keywordAsthma exacerbation-
dc.subject.keywordClinical outcome-
dc.subject.keywordEosinophil-
dc.subject.keywordInflammation-
dc.subject.keywordReal-world evidence-
dc.subject.keywordSevere asthma-
dc.contributor.affiliatedAuthorLee, Y-
dc.contributor.affiliatedAuthorPark, RW-
dc.contributor.affiliatedAuthorPark, HS-
dc.type.localJournal Papers-
dc.identifier.doi10.1016/j.jaip.2020.09.055-
dc.citation.titleThe journal of allergy and clinical immunology. In practice-
dc.citation.volume9-
dc.citation.number3-
dc.citation.date2021-
dc.citation.startPage1285-
dc.citation.endPage1294.e1-e6-
dc.identifier.bibliographicCitationThe journal of allergy and clinical immunology. In practice, 9(3). : 1285-1294.e1-e6, 2021-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.identifier.eissn2213-2201-
dc.relation.journalidJ022132198-
Appears in Collections:
Journal Papers > School of Medicine / Graduate School of Medicine > Allergy
Journal Papers > School of Medicine / Graduate School of Medicine > Biomedical Informatics
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