Benralizumab in severe eosinophilic asthma by previous biologic use and key clinical subgroups: real-world XALOC-1 programme
Bibliographic record
Abstract
BACKGROUND: Pivotal phase 3 trials and real-world studies have demonstrated benralizumab's overall efficacy and safety in severe eosinophilic asthma (SEA). Additional large-cohort data are needed to confirm its real-world effectiveness in SEA according to previous biologic use and key baseline characteristics important for treatment selection. METHODS: XALOC-1 is a large, multinational, retrospective, observational, real-world study programme of benralizumab in adults with SEA. This 48-week integrated analysis assessed annualised exacerbation rate (AER), maintenance oral corticosteroid (mOCS) use, asthma symptom control and lung function during a 12-month baseline period and up to 48 weeks after benralizumab initiation. Subgroup analyses were based on previous biologic use and key baseline clinical characteristics (mOCS use, blood eosinophil count, exacerbation history, age at asthma diagnosis, fractional exhaled nitric oxide level and presence of atopy and chronic rhinosinusitis with nasal polyps). RESULTS: 17.2% at baseline); relative reduction in AER was 82.7% overall and 72.9% in biologic-experienced patients; rates were maintained across all key clinical characteristic subgroups. Of patients using mOCS at baseline (n=274), 47.4% (130 out of 274) eliminated their use by week 48; the mean reduction from baseline in daily dose was 51.2% and, notably, 34.9% in biologic-experienced patients (n=115). Clinically significant improvements in asthma symptom control and lung function were observed. CONCLUSION: In this large, real-world programme, SEA patients treated with benralizumab had substantial improvements in clinical outcomes irrespective of previous biologic use and key clinical characteristics important to therapeutic decision-making in clinical practice.
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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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".