Clinical remission by BMI in patients with severe eosinophilic asthma (SEA) over 1 year post benralizumab: real-world XALOC-2 programme
Bibliographic record
Abstract
Background: Clinical remission is a viable goal in patients (pts) with SEA using biologics. Obesity can independently drive respiratory symptoms and potentially impact asthma control. Aim: Describe clinical remission in pts with SEA 12 months post-benralizumab initiation by baseline (BL) BMI. Methods: The XALOC-2 prospective, real-world programme includes pts with SEA treated with benralizumab in Belgium, Canada, Germany and Switzerland. This integrated analysis assessed clinical remission at Week (Wk) 0 and 56, defined as: exacerbation-free during assessment period (52-Wk BL; 56-Wk follow-up); no maintenance oral corticosteroid (mOCS) use; asthma symptom control (ACQ<1.5). Results: Of 535 pts (median age: 58 years; 49% female), 68% at BL were overweight (BMI ≥25-<30kg/m2; 34%) or obese (BMI ≥30kg/m2; 34%). At BL, 99% of pts had exacerbations, 38% had mOCS use and 90% had poorly controlled asthma. Overall, 0% (0/374) and 42% (111/262) met remission criteria at Wk 0 and 56, respectively (Fig 1A). Remission was lower in pts with obesity (30%) than with normal BMI (51%), largely due to inadequately improved asthma symptom control (Fig 1B). Conclusions: Clinical remission is a realistic goal in pts with SEA receiving benralizumab in the real-world. Pts with higher BMI were less likely to achieve symptom control as measured by ACQ and thus less likely to meet remission criteria.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".