Ruxolitinib cream demonstrated rapid reductions in itch and atopic dermatitis signs that correlated with biomarkers
Bibliographic record
Abstract
To address the need for rapid reduction of atopic dermatitis (AD) clinical manifestations, this study investigated the time course of the effects of ruxolitinib (selective JAK1/JAK2 inhibitor) cream on itch and associated changes in skin and serum biomarkers in adults with AD. In the open-label SCRATCH-AD study (NCT04839380), patients with AD, an Investigator's Global Assessment score ≥2, and a Peak Pruritus Numerical Rating Scale score ≥4 applied 1.5% ruxolitinib cream to all affected areas (except palms, soles, scalp, genitals, and folds; ≤20% body surface area) twice daily for 28 days. Among 46 patients, the mean change from baseline in Peak Pruritus Numerical Rating Scale was -3.4 on day 2 (worst itch, 24-hour recall; primary endpoint) and -5.7 on day 29. Mean change from baseline in modified Peak Pruritus Numerical Rating Scale (current itch) was -2.3 by 15 minutes. Skin (sampled with tape strips) and serum biomarkers associated with AD, such as CCL17 and matrix metalloproteinase 12, were downregulated with ruxolitinib cream and correlated with improvements in disease and symptom severity. There were no serious treatment-emergent adverse events. In summary, patients with AD who applied 1.5% ruxolitinib cream experienced rapid and sustained improvement in itch and clinical improvements that correlated with changes in AD biomarkers.
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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 | 0.000 | 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) | 0.001 | 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".