Dupilumab reduces systemic corticosteroid use and sinonasal surgery rate in CRSwNP
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Chronic rhinosinusitis with nasal polyps (CRSwNP) is a type 2 inflammatory disease with a high symptom burden and poor quality of life. Treatment options include recurrent surgeries and/or frequent systemic corticosteroids (SCS). Dupilumab, a fully human monoclonal antibody, blocks the shared receptor component for interleukin-4 and interleukin-13, key drivers of type 2-mediated inflammation. We report results of pooled analyses from 2 randomised, double-blind, placebo-controlled phase 3 studies (SINUS 24 [NCT02912468]; SINUS-52 [NCT02898454]) to evaluate dupilumab effect versus placebo in adults with CRSwNP with/without SCS use and sinonasal surgery. METHODOLOGY: SINUS-24 patients were randomised 1:1 to subcutaneous dupilumab 300 mg (n=143) or placebo (n=133) every 2 weeks (q2w) for 24 weeks. SINUS-52 patients were randomised 1:1:1 to 52 weeks of subcutaneous dupilumab 300 mg q2w (n=150), 24 weeks q2w followed by 28 weeks of dupilumab 300 mg every 4 weeks (n=145) or 52 weeks of placebo q2w (n=153). RESULTS: Dupilumab reduced the number of patients undergoing sinonasal surgery (82.6%), the need for in-study SCS use (73.9%), and SCS courses (75.3%). Significant improvements were observed with dupilumab vs placebo regardless of prior sinonasal surgery or SCS use in nasal polyp, nasal congestion, Lund-MacKay, and Sinonasal Outcome Test (22-items) scores, and the University of Pennsylvania Smell Identification Test. CONCLUSIONS: Dupilumab demonstrated significant improvements in disease signs and symptoms and reduced the need for sino-nasal surgery and SCS use versus placebo in patients with severe CRSwNP, regardless of SCS use in the previous 2 years, or prior sinonasal surgery.
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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 | 0.001 |
| 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 it