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Multivariate Cluster Analyses to Characterize Asthma Heterogeneity and Benralizumab Responsiveness. | LitMetric

AI Article Synopsis

  • The study aimed to enhance understanding of how different types of severe asthma affect the response to benralizumab, a treatment for asthma.
  • Researchers analyzed data from two major clinical trials, categorizing patients into groups based on 11 clinical characteristics to understand their treatment responses and health outcomes.
  • Results showed that benralizumab significantly reduced asthma exacerbations and improved lung function mainly in patients with late-onset severe asthma, underscoring the importance of identifying asthma subphenotypes for better treatment strategies.

Article Abstract

Background: An improved understanding of how severe asthma heterogeneity affects response could inform treatment decisions.

Objectives: Characterize heterogeneity and benralizumab responsiveness in patients grouped by predefined Severe Asthma Research Program clusters using a multivariate approach.

Methods: In post-hoc analyses of the randomized, double-blind, placebo-controlled phase III SIROCCO (NCT01928771) and CALIMA (NCT01914757) studies, patients with severe asthma who received benralizumab or placebo were assigned to clusters using an established discriminant function to analyze 11 clinical characteristics simultaneously. The annualized asthma exacerbation rate, exacerbation incidence, and lung function were analyzed across clusters.

Results: Patients (n = 2,281) met criteria for four of five clusters: cluster 2 (early-onset moderate asthma, n = 393), cluster 4 (early-onset severe asthma, n = 386), cluster 3 (late-onset severe asthma, n = 641), and cluster 5 (late-onset severe, obstructed asthma, n = 861); no patients met cluster 1 criteria. Exacerbation rate reductions were significant in late-onset severe asthma (-48% [95% CI, -61% to -31%]; P < .0001) and late-onset severe, obstructed asthma (-50% [95% CI, -59% to -38%]; P < .0001), with nonsignificant reductions in early-onset clusters. These differences could not be fully explained by blood eosinophil count differences. Values for improvements in FEV were significant in late-onset severe asthma (+133 mL [95% CI, 66-200]; P = .0001) and late-onset severe, obstructed asthma (+160 mL [95% CI, 85-235]; P < .0001) while maintaining acute bronchodilator responsiveness.

Conclusions: Benralizumab reduced exacerbations and improved lung function, primarily in late-onset asthma clusters. This multivariate approach to identify subphenotypes, potentially reflecting pathobiological mechanisms, can guide therapy beyond univariate approaches.

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Source
http://dx.doi.org/10.1016/j.jaip.2024.04.026DOI Listing

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