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Response to Biologics Along a Gradient of T2 Involvement in Patients With Severe Asthma: A Data-Driven Biomarker Clustering Approach

Wang, E. ; Bjermer, L. LU ; Tunsäter, A. LU and Price, D.B. (2025) In Journal of Allergy and Clinical Immunology: In Practice 13(12). p.3296-3315
Abstract
Background: Asthma with low levels of type 2 (T2) biomarkers is poorly understood. Objective: To characterize severe asthma phenotypes and compare changes in asthma outcomes from pre- to postbiologic treatment along a gradient of T2 involvement. Methods: This was a registry-based cohort study including data from 24 countries. Biomarker distribution (blood eosinophil count, fractional exhaled nitric oxide, and IgE) was quantified before biologic initiation. Clusters were identified using a 5-component Gaussian finite mixture model and phenotypically characterized. Changes in asthma and health care utilization outcomes between 1-year pre- and postbiologic initiation were compared between clusters and by biologic class. Results: Among 3675... (More)
Background: Asthma with low levels of type 2 (T2) biomarkers is poorly understood. Objective: To characterize severe asthma phenotypes and compare changes in asthma outcomes from pre- to postbiologic treatment along a gradient of T2 involvement. Methods: This was a registry-based cohort study including data from 24 countries. Biomarker distribution (blood eosinophil count, fractional exhaled nitric oxide, and IgE) was quantified before biologic initiation. Clusters were identified using a 5-component Gaussian finite mixture model and phenotypically characterized. Changes in asthma and health care utilization outcomes between 1-year pre- and postbiologic initiation were compared between clusters and by biologic class. Results: Among 3675 patients, 5 biomarker clusters were identified along a gradient of T2 involvement: cluster A with the lowest T2 involvement (16.4%), cluster B (20.4%), cluster C (22.9%), cluster D (30.3%), and cluster E with the highest T2 involvement (10.0%). In multivariable analysis, biologic use was associated with improved outcomes in all clusters but tended to be better at the higher end of the T2 spectrum. For example, patients in cluster C had a significantly greater increase in forced expiratory volume in 1 second compared with cluster A (difference 0.16 L [95% confidence interval: 0.08, 0.25]; P (Less)
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keywords
BEC, Benralizumab, Dupilumab, Effectiveness, FeNO, IgE, Mepolizumab, Omalizumab, Real-life, Reslizumab, Adult, Anti-Asthmatic Agents, Asthma, Biological Products, Biomarkers, Cluster Analysis, Cohort Studies, Eosinophils, Female, Humans, Immunoglobulin E, Leukocyte Count, Male, Middle Aged, Registries, Severity of Illness Index, Treatment Outcome, biological marker, biological product, corticosteroid, macrolide, theophylline, antiasthmatic agent, immunoglobulin E, adult, aged, Article, Asthma Control Questionnaire, Asthma Control Test, asthma related hospitalization, blood eosinophil count, body mass, cluster analysis, cohort analysis, controlled study, data driven biomarker clustering approach, eosinophil count, female, forced expiratory volume, forced vital capacity, gastroesophageal reflux, health care utilization, hospitalization, human, lung function, major clinical study, male, obesity, outcome assessment, people by smoking status, phenotype, sensitivity analysis, severe asthma, underweight, asthma, blood, drug therapy, eosinophil, immunology, leukocyte count, metabolism, middle aged, register, severity of illness index, treatment outcome
in
Journal of Allergy and Clinical Immunology: In Practice
volume
13
issue
12
pages
20 pages
publisher
American Academy of Allergy, Asthma and Immunology
external identifiers
  • scopus:105018976011
  • pmid:40902942
ISSN
2213-2198
DOI
10.1016/j.jaip.2025.08.021
language
English
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yes
id
bd973802-adfd-411f-aabd-d2a73e0e52bb
date added to LUP
2026-03-26 12:35:54
date last changed
2026-03-27 03:00:02
@article{bd973802-adfd-411f-aabd-d2a73e0e52bb,
  abstract     = {{Background: Asthma with low levels of type 2 (T2) biomarkers is poorly understood. Objective: To characterize severe asthma phenotypes and compare changes in asthma outcomes from pre- to postbiologic treatment along a gradient of T2 involvement. Methods: This was a registry-based cohort study including data from 24 countries. Biomarker distribution (blood eosinophil count, fractional exhaled nitric oxide, and IgE) was quantified before biologic initiation. Clusters were identified using a 5-component Gaussian finite mixture model and phenotypically characterized. Changes in asthma and health care utilization outcomes between 1-year pre- and postbiologic initiation were compared between clusters and by biologic class. Results: Among 3675 patients, 5 biomarker clusters were identified along a gradient of T2 involvement: cluster A with the lowest T2 involvement (16.4%), cluster B (20.4%), cluster C (22.9%), cluster D (30.3%), and cluster E with the highest T2 involvement (10.0%). In multivariable analysis, biologic use was associated with improved outcomes in all clusters but tended to be better at the higher end of the T2 spectrum. For example, patients in cluster C had a significantly greater increase in forced expiratory volume in 1 second compared with cluster A (difference 0.16 L [95% confidence interval: 0.08, 0.25]; P}},
  author       = {{Wang, E. and Bjermer, L. and Tunsäter, A. and Price, D.B.}},
  issn         = {{2213-2198}},
  keywords     = {{BEC; Benralizumab; Dupilumab; Effectiveness; FeNO; IgE; Mepolizumab; Omalizumab; Real-life; Reslizumab; Adult; Anti-Asthmatic Agents; Asthma; Biological Products; Biomarkers; Cluster Analysis; Cohort Studies; Eosinophils; Female; Humans; Immunoglobulin E; Leukocyte Count; Male; Middle Aged; Registries; Severity of Illness Index; Treatment Outcome; biological marker; biological product; corticosteroid; macrolide; theophylline; antiasthmatic agent; immunoglobulin E; adult; aged; Article; Asthma Control Questionnaire; Asthma Control Test; asthma related hospitalization; blood eosinophil count; body mass; cluster analysis; cohort analysis; controlled study; data driven biomarker clustering approach; eosinophil count; female; forced expiratory volume; forced vital capacity; gastroesophageal reflux; health care utilization; hospitalization; human; lung function; major clinical study; male; obesity; outcome assessment; people by smoking status; phenotype; sensitivity analysis; severe asthma; underweight; asthma; blood; drug therapy; eosinophil; immunology; leukocyte count; metabolism; middle aged; register; severity of illness index; treatment outcome}},
  language     = {{eng}},
  number       = {{12}},
  pages        = {{3296--3315}},
  publisher    = {{American Academy of Allergy, Asthma and Immunology}},
  series       = {{Journal of Allergy and Clinical Immunology: In Practice}},
  title        = {{Response to Biologics Along a Gradient of T2 Involvement in Patients With Severe Asthma: A Data-Driven Biomarker Clustering Approach}},
  url          = {{http://dx.doi.org/10.1016/j.jaip.2025.08.021}},
  doi          = {{10.1016/j.jaip.2025.08.021}},
  volume       = {{13}},
  year         = {{2025}},
}