Benralizumab for allergic asthma: a randomised, double-blind, placebo-controlled trial
Bibliographic record
Abstract
BACKGROUND: Benralizumab induces rapid and near-complete depletion of eosinophils from blood and lung tissue. We investigated whether benralizumab could attenuate the allergen-induced late asthmatic response (LAR) in participants with allergic asthma. METHODS: Participants with allergic asthma who demonstrated increased sputum eosinophils and LAR at screening were randomised to benralizumab 30 mg or matched placebo given every 4 weeks for 8 weeks (3 doses). Allergen challenges were performed at weeks 9 and 12 when blood, sputum, bone marrow and bronchial tissue eosinophils and LAR were assessed. RESULTS: 46 participants (mean age 30.9 years) were randomised to benralizumab (n=23) or placebo (n=23). Eosinophils were significantly reduced in the benralizumab group compared with placebo in blood at 4 weeks and sputum and bone marrow at 9 weeks after treatment initiation. At 7 h after an allergen challenge at week 9, sputum eosinophilia was significantly attenuated in the benralizumab group compared to placebo (least squares mean difference -5.81%, 95% CI -10.69- -0.94%; p=0.021); however, the LAR was not significantly different (least squares mean difference 2.54%, 95% CI 3.05-8.12%; p=0.363). Adverse events were reported for seven (30.4%) and 14 (60.9%) participants in the benralizumab and placebo groups, respectively. CONCLUSION: Benralizumab administration over 8 weeks resulted in a significant attenuation of blood, bone marrow and sputum eosinophilia in participants with mild allergic asthma; however, there was no change in the LAR, suggesting that eosinophils alone are not a key component of allergen-induced bronchoconstriction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".