Flexible Dosing of Abrocitinib in Patients With Moderate-to-Severe Atopic Dermatitis: Initial Results From the Real-World–Simulating Expanded Access Protocol Study, JADE REAL
Bibliographic record
Abstract
Introduction: Abrocitinib, an oral, once-daily, JAK1-selective inhibitor, is approved in patients aged ≥12 years at the recommended doses of 100 mg and 200 mg for the treatment of moderate-to-severe atopic dermatitis (AD). JADE REAL (NCT04564755) was a global, open-label expanded access protocol initiated in 2020 (completed September 2024) to provide access to abrocitinib for patients with moderate-to-severe AD. This analysis evaluated dosing patterns and incidence of treatment-emergent adverse events (TEAEs) leading to a change in dose of abrocitinib inpatients with moderate-to-severe AD in an expanded access protocol simulating real-world use of abrocitinib. Procedure/Study: Eligible patients aged ≥12 years with moderate-to-severe AD initiated once-daily abrocitinib 100 mg or 200 mg (plus topical medication as needed). The dose could be changed throughout the treatment period. Initial dosing and the proportion of patients with continuous dosing, ≥1 dose change and >1 dose change were assessed. Safety was assessed via TEAE monitoring. Results: Of 312 patients, 120 (38.5%) and 192 (61.5%) patients initiated abrocitinib 100 mg and 200 mg, respectively (mean [SD] treatment duration: 379.1 days [203.3]). More patients of ages ≥12–18 and ≥65 years, Black/African American race, and with moderate AD initiated abrocitinib 100 mg, while more patients of ages ≥18–<65 years, Asian race, and with severe AD initiated abrocitinib 200 mg. Of patients who initiated abrocitinib 100 mg and 200 mg, 78 (65.0%) and 119 (62.0%) received continuous dosing, and 42 (35.0%) and 73 (38.0%) patients had ≥1 dose change, including 12 (28.6%) and 33 (45.2%) patients with >1 dose change, respectively. TEAEs led to dose reduction in 27 patients (8.7%), notably nausea (n=4 [1.3%]), thrombocytopenia (n=4 [1.3%]), acne (n=3 [1.0%]), fatigue (n=3 [1.0%]), and folliculitis (n=3 [1.0%]). TEAEs led to a dose escalation in 12 patients (3.8%); AD was the only TEAE that occurred in ≥1% of patients (n=10 [3.2%]) which led to a dose escalation. Conclusion: Most patients received consistent abrocitinib dosing throughout the study. TEAEs were not the primary reason leading to dosage reduction. These results may support clinical decision making around initial dose selection and dosage changes. JADE REAL demonstrated the potential benefits of flexible dosing and may simulate the real-world use of oral Janus kinase inhibitors. Funding/Disclosures: This study was funded by Pfizer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".