Topical tofacitinib for atopic dermatitis: a phase <scp>II</scp> a randomized trial
Bibliographic record
Abstract
BACKGROUND: Despite unmet need, 15 years have passed since a topical therapy with a new mechanism of action for atopic dermatitis (AD) has been approved. Janus kinase (JAK) inhibitor treatment effect via topical application in patients with AD is unknown. OBJECTIVES: Tofacitinib, a small-molecule JAK inhibitor, was investigated for the topical treatment of AD. METHODS: In this 4-week, phase IIa, randomized, double-blind, vehicle-controlled study (NCT02001181), 69 adults with mild-to-moderate AD were randomized 1:1 to 2% tofacitinib or vehicle ointment twice daily. Percentage change from baseline (CFB) in Eczema Area and Severity Index (EASI) score at week 4 was the primary end point. Secondary efficacy end points included percentage CFB in body surface area (BSA), CFB in EASI Clinical Signs Severity Sum Score, proportion of patients with Physician's Global Assessment (PGA) response and CFB in patient-reported pruritus. Safety, local tolerability and pharmacokinetics were monitored. RESULTS: The mean percentage CFB at week 4 in EASI score was significantly greater (P < 0·001) for tofacitinib (-81·7%) vs. vehicle (-29·9%). Patients treated with tofacitinib showed significant (P < 0·001) improvements vs. vehicle across all prespecified efficacy end points and for pruritus at week 4. Significant improvements in EASI, PGA and BSA were observed by week 1 and improvements in pruritus were observed by day 2. Safety/local tolerability were generally similar for both treatments, although more adverse events were observed for vehicle vs. tofacitinib. CONCLUSIONS: Tofacitinib ointment showed significantly greater efficacy vs. vehicle across end points, with early onset of effect and comparable safety/local tolerability to vehicle. JAK inhibition through topical delivery is potentially a promising therapeutic target for 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".