Systematic review of newer agents for the management of alopecia areata in adults: Janus kinase inhibitors, biologics and phosphodiesterase‐4 inhibitors
Bibliographic record
Abstract
Management options for moderate-to-severe alopecia areata (AA) are limited owing to a lack of safe and effective treatments suitable for long-term use. However, newer agents have the potential to induce and maintain hair regrowth in patients with a better side-effects profile compared to systemic steroids or conventional systemic agents. In this article, we conducted a systematic review of newer agents, including Janus kinase (JAK) inhibitors, biologics and phosphodiesterase-4 (PDE-4) inhibitors, for the treatment of AA in adult patients evaluated in randomized controlled trials (RCTs) using the Severity of Alopecia Tool score. A literature search was performed on PubMed and ClinicalTrials.gov, which identified 106 items with 12 RCTs eligible for review. Information regarding the treatment regimen, duration, endpoints, efficacy and adverse events were extracted; product monograph information was also summarized for approved agents with or without indications for AA. Overall, current data suggest the oral JAK inhibitors (baricitinib, ritlecitinib, deuruxolitinib, brepocitinib) as a promising new class of agents that can induce significant hair regrowth, with mild to moderate adverse effects. Baricitinib recently received US FDA approval for the treatment of severe AA, while ritlecitinib and deuruxolitinib have received the breakthrough therapy designation for AA. In contrast, PDE-4 inhibitors (apremilast) and the biologics (dupilumab, secukinumab and aldesleukin) appear to have limited efficacy thus far. Results from ongoing and future long-term studies could shed light on the utility of the newer agents in altering the progression of AA.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.001 | 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".