Abstract
Background: Multidisciplinary systematic assessment improves outcomes in difficult-to-treat asthma, but without clear response predictors. Using a treatable-traits framework, we stratified patients by trait profile, examining clinical impact and treatment responsiveness to systematic assessment. Methods: We performed latent class analysis using 12 traits on difficult-to-treat asthma patients undergoing systematic assessment at our institution. We examined Asthma Control Questionnaire (ACQ-6) and Asthma Quality of Life Questionnaire (AQLQ) scores, FEV1, exacerbation frequency, and maintenance oral corticosteroid (mOCS) dose, at baseline and following systematic assessment. Results: Among 241 patients, two airway-centric profiles were characterized by early-onset with allergic rhinitis (n = 46) and adult onset with eosinophilia/chronic rhinosinusitis (n = 60), respectively, with minimal comorbid or psychosocial traits; three non-airway-centric profiles exhibited either comorbid (obesity, vocal cord dysfunction, dysfunctional breathing) dominance (n = 51), psychosocial (anxiety, depression, smoking, unemployment) dominance (n = 72), or multi-domain impairment (n = 12). Compared to airway-centric profiles, non-airway-centric profiles had worse baseline ACQ-6 (2.7 vs. 2.2, p <.001) and AQLQ (3.8 vs. 4.5, p <.001) scores. Following systematic assessment, the cohort showed overall improvements across all outcomes. However, airway-centric profiles had more FEV1 improvement (5.6% vs. 2.2% predicted, p <.05) while non-airway-centric profiles trended to greater exacerbation reduction (1.7 vs. 1.0, p =.07); mOCS dose reduction was similar (3.1 mg vs. 3.5 mg, p =.782). Conclusion: Distinct trait profiles in difficult-to-treat asthma are associated with different clinical outcomes and treatment responsiveness to systematic assessment. These findings yield clinical and mechanistic insights into difficult-to-treat asthma, offer a conceptual framework to address disease heterogeneity, and highlight areas responsive to targeted intervention.
| Original language | English |
|---|---|
| Pages (from-to) | 2418-2427 |
| Number of pages | 10 |
| Journal | Allergy |
| Volume | 78 |
| Issue number | 9 |
| DOIs | |
| Publication status | Published - Sept 2023 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 8 Decent Work and Economic Growth
Keywords
- asthma phenotype
- difficult-to-treat asthma
- latent class analysis
- treatable traits
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