Effects of ruxolitinib cream on pruritus and quality of life in atopic dermatitis: Results from a phase 2, randomized, dose-ranging, vehicle- and active-controlled study
Bibliographic record
Abstract
BACKGROUND: Atopic dermatitis (AD), a chronic, highly pruritic skin disorder, impairs quality of life (QoL). Janus kinase inhibitors suppress inflammatory and pruritus-associated cytokine signaling in AD. OBJECTIVE: To report the effects of ruxolitinib (RUX) cream on itch and QoL in AD. METHODS: A total of 307 adult patients with an Investigator's Global Assessment (score of 2 or 3) and 3% to 20% affected body surface area were randomly assigned for 8 weeks to receive double-blind treatment with RUX (1.5% twice daily, 1.5% once daily, 0.5% once daily, or 0.15% once daily), vehicle twice daily, or triamcinolone cream (0.1% twice daily for 4 weeks then vehicle for 4 weeks). Itch was measured by using the numerical rating scale, and patient QoL was assessed with Skindex-16. RESULTS: Improvements in itch numerical rating scale and Skindex-16 were observed with RUX cream. Overall, 42.5% of patients who applied 1.5% RUX twice daily experienced minimal clinically important difference in itch within 36 hours of treatment (vehicle, 13.6%; P < .01); near-maximal improvement was observed by week 4. Itch reduction was associated with improved QoL burden (Pearson correlation, 0.67; P < .001). Significant improvements in Skindex-16 overall scores were noted at week 2. LIMITATIONS: Facial AD lesions were not treated. CONCLUSION: RUX cream provides a clinically meaningful reduction in itch and QoL burden.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| 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) | 0.003 | 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".