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To compare the efficacy of tezepelumab with other approved biologics via indirect treatment comparisons (ITCs) in patients aged ≥ 12 years with severe uncontrolled asthma. Data from randomized controlled trials (RCTs) identified from a systematic literature review were synthesized using two different ITC approaches: network meta-analysis (NMA) and simulated treatment comparison (STC). Outcomes of interest were annualized asthma exacerbation rate (AAER) and AAER for exacerbations leading to hospitalization or emergency room visit. To address potential heterogeneity between study populations, various subgroup analyses were performed for the NMA (based on blood eosinophil count, fractional exhaled nitric oxide level, and presence of allergic asthma), and for the STC, models were adjusted for potential treatment effect modifiers. Sensitivity analyses were performed to assess the impact of study design (exclusion of non-placebo-controlled studies and non-phase 3 or 4 studies). Results were reported as rate ratios (RRs) with 95% credible/confidence intervals and ranking statistics were computed for the NMAs. Sixteen RCTs were included in at least one of the ITCs. All biologics (tezepelumab, dupilumab, benralizumab, mepolizumab, reslizumab, and omalizumab) had similar efficacy, with no statistically significant RRs for either exacerbation outcome; however, tezepelumab was favorably associated with numerically lower AAERs and was ranked first in the network for both types of exacerbation outcome. This trend was consistent in the subgroup and sensitivity analyses. As with the primary NMA, the STC results did not demonstrate any significant differences between biologics, but point estimates were favorable towards tezepelumab. Heterogeneity between trials was observed among eligibility criteria and clinically important patient characteristics; however, the impact on findings is expected to be low, based on consistency across analyses. Findings from both ITCs (NMA and STC) support the use of tezepelumab in a broad patient population of severe uncontrolled asthma of any phenotype.

Background: Allergy, eosinophilic inflammation, and epithelial dysregulation are implicated in severe asthma pathogenesis. Objective: We characterized biomarker expression in adults with severe asthma. Methods: Within the International Severe Asthma Registry (ISAR), we analyzed data from 10 countries in North America, Europe, and Asia, with prespecified thresholds for biomarker positivity (serum IgE ≥ 75 kU/L, blood eosinophils ≥ 300 cells/μL, and FeNO ≥ 25 ppb), and with hierarchical cluster analysis using biomarkers as continuous variables. Results: Of 1,175 patients; 64% were female, age (mean ± SD) 53 ± 15 years, body mass index (BMI) 30 ± 8, postbronchodilator forced expiratory volume in 1 second (FEV1) predicted 72% ± 20%. By prespecified thresholds, 59% were IgE positive, 57% eosinophil positive, and 58% FeNO positive. There was substantial inflammatory biomarker overlap; 59% were positive for either 2 or 3 biomarkers. Five distinct clusters were identified: cluster 1 (61%, low-to-medium biomarkers) comprised highly symptomatic, older females with elevated BMI and frequent exacerbations; cluster 2 (18%, elevated eosinophils and FeNO) older females with lower BMI and frequent exacerbations; cluster 3 (14%, extremely high FeNO) older, highly symptomatic, lower BMI, and preserved lung function; cluster 4 (6%, extremely high IgE) younger, long duration of asthma, elevated BMI, and poor lung function; cluster 5 (1.2%, extremely high eosinophils) younger males with low BMI, poor lung function, and high burden of sinonasal disease and polyposis. Conclusions: There is significant overlap of biomarker positivity in severe asthma. Distinct clusters according to biomarker expression exhibit unique clinical characteristics, suggesting the occurrence of discrete patterns of underlying inflammatory pathway activation and providing pathogenic insights relevant to the era of monoclonal biologics.