Mepolizumab for chronic rhinosinusitis with nasal polyps: Treatment efficacy by comorbidity and blood eosinophil count
Bibliographic record
Abstract
BACKGROUND: In the phase III SYNAPSE study, mepolizumab reduced nasal polyp (NP) size and nasal obstruction in chronic rhinosinusitis with NP. OBJECTIVE: We sought to assess the efficacy of mepolizumab in patients from SYNAPSE grouped by comorbid asthma, aspirin-exacerbated respiratory disease (AERD), and baseline blood eosinophil count (BEC). METHODS: SYNAPSE, a randomized, double-blind, 52-week study (NCT03085797), included patients with severe bilateral chronic rhinosinusitis with NP eligible for surgery despite intranasal corticosteroid treatment. Patients received 4-weekly subcutaneous mepolizumab 100 mg or placebo plus standard of care for 52 weeks. Coprimary end points were change in total endoscopic NP score (week 52) and nasal obstruction visual analog scale score (weeks 49-52). Subgroup analyses by comorbid asthma and AERD status, and post hoc by BEC, were exploratory. RESULTS: Analyses included 407 patients (289 with asthma; 108 with AERD; 371 and 278 with BEC counts ≥150 or ≥300 cells/μL, respectively). The proportion of patients with greater than or equal to 1-point improvement from baseline in NP score was higher with mepolizumab versus placebo across comorbid diseases (asthma: 52.9% vs 29.5%; AERD: 51.1% vs 20.6%) and baseline BEC subgroups (<150 cells/μL: 55.0% vs 31.3%; ≥150 cells/μL: 49.5% vs 28.1%; <300 cells/μL: 50.7% vs 29.0%; ≥300 cells/μL: 50.4% vs 28.1%). A similar trend was observed in patients without comorbid asthma or AERD. More patients had more than 3-point improvement in nasal obstruction VAS score with mepolizumab versus placebo across comorbid subgroups. CONCLUSIONS: Mepolizumab reduced polyp size and nasal obstruction in chronic rhinosinusitis with NP regardless of the presence of comorbid asthma or AERD.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".