Mepolizumab in patients with severe asthma and blood eosinophil counts between 150 and 300 cells per µL: benefits at two years
Bibliographic record
Abstract
Background Although clinical trial evidence exists, there is limited awareness of the real-world effectiveness of mepolizumab in patients with severe asthma and blood eosinophil counts (BEC) ≥150–<300 cells·μL −1 . Methods REALITI-A, an international, prospective, single-arm, observational cohort study enrolled patients with severe asthma initiating mepolizumab. Outcomes assessed over 2 years pre- versus post-mepolizumab exposure included clinically significant exacerbations (CSEs), maintenance oral corticosteroid (mOCS) use, Asthma Control Questionnaire (ACQ)-5 scores and forced expiratory volume in 1 s (FEV 1 ). Results After 2 years of mepolizumab treatment, compared with pre-exposure, the proportion of patients with BEC ≥150–<300 cells·μL −1 (n=84) experiencing CSEs decreased from 95% to 63%, and the proportion experiencing exacerbations requiring hospitalisation or emergency department visits decreased from 43% to 19%. The rate of CSEs reduced from 4.53 to 1.47 per year (rate ratio 0.32, 95% CI 0.25, 0.41). After 2 years of mepolizumab exposure, the mean (95% CI) clinic pre-bronchodilator % predicted FEV 1 was 80.1 (69.4, 90.7) compared with 62.6 (54.1, 71.1) at baseline (28% relative increase). The median average daily dose of mOCS decreased from 10.0 to 1.5 mg·day −1 (85% relative reduction from baseline); 44% of patients discontinued completely. The minimum clinically important difference in ACQ-5 (improvement ≥0.5) was achieved by 82% of patients, with a mean (95% CI) reduction of 1.76 (2.34, 1.19). Conclusions These real-world findings provide evidence for the 2-year sustained benefit following initiation of mepolizumab in patients with severe asthma who have poor disease control and BEC ≥150–<300 cells·μL −1 .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".