ReviewFrontiers in medicine2026
A consensus-based treatment algorithm for alopecia areata in adolescents and adults: integrating severity, quality of life, and disease dynamics.
Review in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Alopecia areata (AA) is an autoimmune, inflammatory condition characterized by non-scarring hair loss on the scalp, face, or body. It can significantly affect a person's quality of life (QoL) and mental health. Methods: Using a modified Delphi method, a panel of expert dermatologists developed a practical treatment algorithm to help clinicians deliver personalized, safe care to diverse patients with AA. Results: The approach to the algorithm introduces a broader definition of disease severity, incorporating not only Severity of Alopecia Tool (SALT) scores but also quality-of-life impact and the rate of disease progression. Discussion: Recent therapeutic advances have expanded access to effective, safe treatments for a broader population of AA patients. Ritlecitinib, a Janus kinase 3/TEC inhibitor, is currently the only oral Janus kinase inhibitor approved for adolescents and adults aged 12 years and older, whereas baricitinib, a Janus kinase1/2 inhibitor, is approved for adults aged 18 years and older. However, questions on the long-term safety of these therapies, access, and personalization still need to be addressed. Conclusion: Future efforts should validate and refine the algorithm across real-world cohorts and ensure equitable access to personalized treatment for patients with AA.
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