Early Asthma Control Improvement with Benralizumab: 8-Week Integrated Analysis from the Real-World XALOC-2 Study
Bibliographic record
Abstract
Rationale Benralizumab depletes blood eosinophils (bEOS) within 24 hours, which translates in clinical trials to early benefits in patients with severe eosinophilic asthma (SEA). Our aim was to understand the real-world effectiveness of benralizumab on asthma control from 1 week after treatment initiation. Methods XALOC-2 is a prospective real-world study of benralizumab in patients with SEA in Canada, Belgium, Germany and Switzerland. This integrated interim analysis assessed Asthma Control Questionnaire (ACQ-6) score change from baseline to Week 8, stratified by baseline characteristics. Results 413 patients were included, 40% were male, 34% with CRSwNP, 66% using maintenance OCS. Mean (SD) age 56 (15) years, age of first asthma diagnosis 37 (20) years, bEOS 645 (542) cells/µL and 3.0 (3.4) exacerbations in the past year. There was a least squares (LS) mean reduction in ACQ-6 over the first 8 weeks of benralizumab treatment, from –0.7 (95% CI –0.8, –0.6) at Week 1 to –1.2 (95% CI –1.3, –1.1) at Week 8. An improvement of≥0.5 (the minimally clinically important difference [MCID]) was seen in 58% of patients (220/378) at Week 1. At Week 8, 70% (263/376) showed an improvement of≥1xMCID, and 55% (208/376) of≥2xMCID. ACQ-6 improvements were more pronounced in patients with CRSwNP (LS mean change –1.5 [95% CI –1.7, –1.3]) and with bEOS≥500 cells/µL (LS mean change –1.4 [95 CI –1.6, –1.2]) at Week 8. Conclusions Targeting eosinophilic inflammation in SEA with benralizumab is associated with an early response beginning at Week 1 in asthma symptom control across subgroups. Publication History Article published online: 09 March 2023 © 2023. Thieme. All rights reserved. Georg Thieme Verlag Rüdigerstraße 14, 70469 Stuttgart, Germany
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".