526 - Efficacy of upadacitinib vs dupilumab for moderate-to-severe atopic dermatitis: analysis of time spent in itch response state from the Heads Up study
Bibliographic record
Abstract
Abstract Introduction/Background Atopic dermatitis is a chronic inflammatory skin disease characterized by intense and debilitating pruritus – its most burdensome symptom – and requires long-term control. Results from the Heads Up trial (NCT03738397) found that upadacitinib (UPA) 30 mg was superior to dupilumab (DUPI) 300 mg for improving itch as indicated by increases in the percent of improvement from baseline for Worst Pruritus NRS scores (WP-NRS). Objective This analysis compared the proportion of days patients treated with UPA or DUPI spent in itch response states indicated by WP-NRS. Methods Heads Up was a 24-week head-to-head phase 3b multicenter, randomized, double-blind study comparing UPA 30 mg to DUPI 300 mg in adults with moderate-to-severe AD. We compared the proportion of days patients treated with UPA or DUPI spent in an improved-itch state (WP-NRS improvement ≥4 relative to baseline; among patients with baseline WP-NRS ≥4) or a state of no/minimal itch (WP-NRS 0/1; among patients with baseline WP-NRS >1). Results Participants included 673 patients randomized into two groups: those taking UPA (N=342) or DUPI (N=331). At 4 and 16 weeks, patients treated with UPA vs DUPI spent a greater proportion of days in an improved-itch state (week 4: 50.0% vs 19.3%; week 16: 60.4% vs 35.7%), and in a state of no/minimal itch (week 4: 22.1% vs 4.3%; week 16: 34.4% vs 11.4%). Conclusions Treatment of moderate-to-severe AD with UPA 30 mg daily resulted in a greater proportion of days spent with meaningful itch improvement (WP-NRS improvement ≥4) and more time with no/minimal itch (WP-NRS 0/1) compared to treatment with DUPI over 4 and 16 weeks.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".