733 - Nemolizumab elicits fast itch response in atopic dermatitis within 2 days: a post hoc analysis of ARCADIA 1 and 2 data
Bibliographic record
Abstract
Abstract Background Itch is the most burdensome symptom of atopic dermatitis (AD) that severely affects sleep and overall and quality of life.1,2 Rapid control of itch could be instrumental in minimizing disease symptoms and the associated burden for patients.3,4 Nemolizumab, an interleukin-31 (IL-31) alpha antagonist, inhibits the IL-31 pathway of itch and inflammation in AD.5 Objectives To evaluate speed of onset of itch relief and sleep improvements with nemolizumab in moderate-to-severe AD. Methods ARCADIA-1 and ARCADIA-2 were two identical, randomized, double-blinded, placebo-controlled studies. Patients (≥12 years) with moderate-to-severe AD and inadequate response to topical corticosteroids (TCS) were randomized (2:1) to receive nemolizumab 30mg every 4 weeks (60mg baseline loading dose) or matching placebo, both with background TCS of low/medium potency with/without topical calcineurin inhibitors (TCI). Results Significant improvements in itch (least squares [LS] mean±standard error [SE] change from baseline [CFB] in Peak Pruritus Numeric Rating Scale [PP-NRS]) were noted in nemolizumab-treated vs placebo-treated patients by Day 1 in ARCADIA-1 (-0.9±0.08 vs -0.4±0.10) and ARCADIA-2 (-1.1±0.09 vs -0.4±0.12), reaching -2.4±0.08 vs -1.2±0.11 and -2.3 ±0.09 vs -0.9±0.12 respectively at Day 14 (p<0.001 for all). Significantly greater proportions of nemolizumab-treated vs placebo-treated patients achieved ≥4-point improvement in PP-NRS by Day 2 in ARCADIA-1 (9.4% vs 3.4%, p<0.01) and Day 1 in ARCADIA-2 (8.2% vs 1.9%, p<0.001) and through Day 14 (ARCADIA-1: 22.7% vs 10.6%, p<0.0001; ARCADIA-2: 23.4% vs 6.8%, p<0.0001). Conclusions Treatment with nemolizumab plus TCS/TCI resulted in rapid, statistically and clinically significant improvements in itch in moderate-to-severe AD.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".