The Use of Janus Kinase Inhibitors in Alopecia Areata: A Review of the Literature
Bibliographic record
Abstract
Alopecia areata (AA) is a chronic, immune-mediated disorder that targets hair follicle epithelium, thereby restricting hair growth in localized patches. Although several therapies for AA have been tested, responses with traditional therapies have been limited. In recent years, numerous reports have been published of patients with AA responding to Janus kinase (JAK) inhibitors. This literature review aims to describe AA pathophysiology, explore how and why JAK inhibitors can be used for AA treatment, and review published case reports, case series, and open-label studies published to date. Pathogenesis of AA includes interactions between genetic, environmental, and immune factors and is mediated by the cytokines interferon-γ and interleukin (IL)-15. JAK inhibition resulting in hair regrowth in some cases supports that AA is associated with the Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathway. The emergence of JAK inhibitors for AA therapy is changing the way health care providers think about and treat AA. A mixture of animal model studies and human case studies have reported the use of baricitinib (JAK 1/2), ruxolitinib (JAK 1/2), and tofacitinib (JAK 1/3) for the management of AA. JAK inhibition has shown potential as an effective AA therapy when used in case studies, case series, and open-label trials. Formal clinical trials are ongoing and will yield more definitive conclusions about the safety and efficacy of JAK inhibitors.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".