Dupilumab Demonstrates Rapid Onset of Response Across Three Type 2 Inflammatory Diseases
Bibliographic record
Abstract
Background Type 2 inflammatory diseases often coexist in patients. Dupilumab targets type 2 inflammation and has demonstrated treatment benefits in patients with atopic dermatitis (AD), asthma, and chronic rhinosinusitis with nasal polyps (CRSwNP) with an acceptable safety profile. Objective This post hoc analysis across five phase 3 studies in patients with moderate to severe AD or asthma, or severe CRSwNP, evaluated time of onset and duration of the treatment response. Methods Patients received subcutaneous dupilumab 200/300 mg or placebo. Assessments included the Eczema Area and Severity Index, Peak Pruritus Numerical Rating Scale, and Dermatology Life Quality Index in AD; pre-bronchodilator FEV 1 , daily morning peak expiratory flow, and symptom scores in asthma; and University of Pennsylvania Smell Identification Test, daily nasal congestion, and loss of smell scores in CRSwNP. Results At week 2 after the initiation of dupilumab versus placebo, 67.8% versus 36.5% of AD patients achieved a clinically meaningful benefit (Eczema Area and Severity Index: 50% or greater improvement; Peak Pruritus Numerical Rating Scale: 3 point or greater improvement; or Dermatology Life Quality Index: 4 point or greater improvement) ( P < .001). Moreover, 61.6% versus 39.9% of asthma patients achieved improvements in pre-bronchodilator FEV 1 of 100 mL or greater and 48.8% versus 26.3% achieved 200 mL or greater improvement (both P < .001); 33.2% versus 5.6% of CRSwNP patients regained a sense of smell ( P < .001). Treatment effects further improved or were sustained to the end of treatment. Conclusions Clinically meaningful responses were achieved rapidly after the first dupilumab dose in AD, asthma, or CRSwNP and were sustained throughout treatment (see Video in this article's Online Repository at www.jaci-inpractice.org).
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".