Trait profiles in difficult-to-treat asthma: Clinical impact and response to systematic assessment

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.

Keywords: asthma phenotype; difficult-to-treat asthma; latent class analysis; treatable traits.