One year mepolizumab outcomes in severe, uncontrolled CRSwNP: a real-life study.
Bibliographic record
Abstract
BACKGROUND: This study aimed to evaluate the effectiveness of mepolizumab in the treatment of severe, uncontrolled chronic rhinosinusitis with nasal polyps (CRSwNP) as add-on therapy to intranasal corticosteroids (INCS) in a real-life setting over the first year of treatment. METHODOLOGY: We included 50 patients (28 males; mean age: 56.4 years, range 35-77) who received mepolizumab 100 mg every 4 weeks. The primary objective of this study was to evaluate the reduction in nasal polyp size and improvement in patients' quality of life, measured through symptom-based questionnaires. The secondary objective was to evaluate improvements in smell dysfunction, severity of comorbidities, blood eosinophilia, and the need for surgery or systemic steroids. RESULTS: After 12 months of treatment, the median nasal polyp score (NPS) decreased from 5 to 2 and the mean sino-nasal outcome test-22 (SNOT-22) score decreased from 58.4±21 to 26.1±17.5. Olfaction only slightly improved with a median VAS score decreasing from 10 at baseline to 6 at 12 months. Seven patients remained uncontrolled and required systemic steroids and in 5 cases also endoscopic sinus surgery. CONCLUSIONS: The results support the use of mepolizumab as an effective option in the current standard of care for patients affected by severe, uncontrolled CRSwNP especially in decreasing nasal polyps’ size and improving quality of life, although a minor impact was observed on recovery of smell.
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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) | 0.001 | 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 | 0.000 |
| 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".