Dupilumab shows rapid and sustained suppression of inflammatory biomarkers in asthma patients in LIBERTY ASTHMA QUEST
Bibliographic record
Abstract
Background: Dupilumab (DPL), a fully human anti-IL-4Rα mAb that inhibits IL-4/IL-13, is approved for treatment of adults with inadequately controlled moderate-to-severe atopic dermatitis. DPL previously suppressed type 2 inflammatory biomarkers during 24 weeks of treatment (NCT01854047). In a phase 3 study (NCT02414854), asthma patients (pts) aged ≥12 years, with no minimum baseline (BL) eosinophil requirement, uncontrolled with medium-to-high-dose ICS, plus 1 or 2 controllers received DPL 200/300mg or placebo (PBO) every 2 weeks for 52 weeks. DPL reduced severe asthma exacerbations, improved FEV1 and quality of life measures, and was generally well tolerated. Aim: Report effect of DPL on pharmacodynamic (PD) parameters. Methods: PD parameters: change from BL in FeNO, eotaxin-3, total IgE, periostin and TARC at Weeks 12 and 52. Results: BL biomarker values were elevated and comparable in all groups (Table). Pts receiving DPL demonstrated a statistically significant decrease in biomarkers concomitant with efficacy. A near-maximal effect was observed by Week 12 and sustained over the 52-week treatment period. Most common AE, with higher frequency in 200/300mg DPL vs PBO, was injection-site reactions (21%/24% vs 6%/14%). Conclusion: DPL showed rapid and sustained suppression of systemic and airway type 2 inflammatory biomarkers (including FeNO and IgE) in asthma pts, and was generally well tolerated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".