Emerging systemic JAK inhibitors in the treatment of atopic dermatitis: a review of abrocitinib, baricitinib, and upadacitinib
Bibliographic record
Abstract
The Janus kinases (JAK) are a group of molecules, composed of JAK1, JAK2, JAK3, and tyrosine kinase 2 (TYK2), which are key components within the JAK-signal transducers and activators of transcription pathway, where cytokine receptor signaling takes place. These molecules play a foundational role in the underlying pathogenesis of multiple immune-related conditions such as atopic dermatitis (AD), rheumatoid arthritis, psoriatic arthritis, inflammatory bowel disease, and others. Thus far, JAK inhibitors for inflammatory conditions have only been marketed for the treatment of rheumatoid arthritis and psoriatic arthritis, but ongoing phase II and phase III clinical trials for other immune-mediated diseases, such as AD, have also shown promising results. This review summarizes the clinical data available from various trials and reports on the safety and efficacy of abrocitinib, baricitinib, and upadacitinib, the three oral systemic JAK inhibitors used in the treatment of AD. The safety and efficacy of JAK inhibitors for the treatment of AD are emerging in the literature. It is important that dermatologists are aware of any potential adverse events or risks associated with the use of JAK inhibitors in order to promote a higher standard of treatment and quality of living.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".