Tailoring Abrocitinib Treatment for Moderate-to-Severe Atopic Dermatitis to Patient Disease Course: A Narrative Review
Bibliographic record
Abstract
Atopic dermatitis (AD) is a chronic inflammatory skin condition characterized by intense itching, redness, and eczema. It significantly impacts the quality of life of affected individuals, often requiring long-term management strategies. Abrocitinib, an oral Janus kinase 1 (JAK1) inhibitor, is approved for the treatment of moderate-to-severe AD. Phase 2 and phase 3 abrocitinib randomized clinical trials in the JAK1 Atopic Dermatitis Efficacy and Safety (JADE) clinical development program have demonstrated the efficacy and safety of abrocitinib in both adults and adolescents with moderate-to-severe AD. This review article explores the benefit-risk profile of a flexible abrocitinib dosing approach, tailoring dose based on individualized treatment of patients and highlighting the available supportive data from the JADE randomized clinical trials for healthcare professionals as part of joint provider-patient decision making. Dosing flexibility and maintenance with the lowest effective dose is necessary to treat patients according to their individual disease course while minimizing safety risks. Safety data indicate that incidence of treatment-emergent adverse events is reflective of the current dosage, with no carry-over risk from a previous higher dosage. Overall, abrocitinib represents a valuable AD therapy that can be administered according to individual patient needs.Graphical abstract available for this article.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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 | 0.000 |
| 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".