Early and continued asthma control improvement in patients with severe eosinophilic asthma (SEA) over 1 year post benralizumab initiation: real-world XALOC-2 programme
Bibliographic record
Abstract
Background: Benralizumab depletes blood eosinophils in <24 hrs and may lead to rapid improvements in patients (pts) with SEA. Aim: To understand the real-world effectiveness of benralizumab on asthma symptom control from 1 to 56 weeks (Wk) post initiation. Methods: XALOC-2 comprises prospective, real-world studies (Belgium, Canada, Germany and Switzerland) of benralizumab in pts with SEA. This 56-Wk integrated analysis assessed longitudinal changes in ACQ score. Results: Of 535 pts (median age: 58 yrs; 49% female) mean (SD) ACQ score at baseline (BL) was 3.0 (1.2) decreasing to 1.5 (1.2) by Wk 56. The greatest improvement in ACQ score occurred between BL and Wk 1 and further improved up to Wk 56 (Fig 1A). Clinically meaningful improvements (minimal clinically-important difference [MCID] threshold=‒0.5) were seen in 58% of pts (282/486) at Wk 1. At Wk 56, 79% (276/351) had an improvement ≥1xMCID, and 62% (218/351) ≥2xMCID. Significantly improved asthma control was seen across all clinically relevant BL characteristic subgroups (Fig 1B). Conclusions: Clinically meaningful improvements in asthma symptom control began from 1 Wk post benralizumab initiation or earlier and further improved over 1 yr. Benefits were seen in the overall population and were consistent across key subgroups important to therapeutic decision-making in daily practice. erj;64/suppl_68/PA5358/F1 F1 F1
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".