Trial reportAllergy2025
Multiomics Analysis of the Response to Ritlecitinib in Alopecia Areata Subtypes and Correlation With Efficacy.
Trial report in Allergy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02974868 (A PHASE 2A RANDOMIZED, DOUBLE-BLIND, PLACEBO-CONTROLLED, MULTICENTER STUDY TO EVALUATE THE EFFICACY AND SAFETY PROFILE OF PF-06651600 AND PF-06700841 IN SUBJECTS WITH MODERATE TO SEVERE ALOPECIA AREATA WITH A SINGLE-BLIND EXTENSION PERIOD AND A CROSS-OVER OPEN LABEL EXTENSION PERIOD), which is not on this map. Cited by 4 papers.
What it found
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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.
A phase 2a randomized, double-blind, placebo-controlled, multicenter study to evaluate the efficacy and safety profile of pf-06651600 and pf-06700841 in subjects with moderate to severe alopecia areata with a single-blind extension period and a cross-over open label extension period
Who cites it
4 citing papers in PubMed.
- Non-Invasive Scalp Tape-Strip RNA Sequencing Captures Disease Activity and Treatment-Response Signatures in Alopecia Areata.Allergy · 2026Article
- Immunopathogenesis and Experimental Models of Alopecia Areata: From Mechanistic Insights to Translational Platforms.Clinical reviews in allergy & immunology · 2026Review
- JAK Inhibitors for Alopecia Areata: Approved Therapies, Efficacy, and Unanswered Questions.Drug design, development and therapy · 2026Review
- Clinical characteristics and factors associated with different BASP subtypes of androgenetic alopecia.Frontiers in medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundAlopecia areata (AA) is an autoimmune disease characterized by hair loss. This study examined changes in molecular signatures in lesional scalp of patients with AA subtypes (patchy-type AA [AAP] or alopecia totalis/alopecia universalis [AT/AU]) in response to treatment with JAK3/TEC family kinase inhibitor ritlecitinib and evaluated correlations between potential biomarker levels/changes and scalp hair regrowth.
methodsThis was a post hoc analysis of a biopsy substudy from a phase 2a trial of ritlecitinib in patients with AA and ≥ 50% scalp hair loss. Transcriptomic expression profiles from scalp samples of patients with AAP or AT/AU were analyzed using microarray. Changes from baseline in transcriptional and serum protein expression were evaluated, as were correlations between both these changes and the baseline profile with clinical response (scalp hair regrowth).
resultsFollowing 12 and 24 weeks of treatment, ritlecitinib downregulated key Type I (CCL5, CD8A, and GZMB) and Type II immunity-related genes (CCL13, CCL18, and IL13RA1), downregulated genes related to ritlecitinib's mechanism of action (ITK, JAK3, and BTK), and upregulated hair keratin genes in AAP and AT/AU lesions, with a lesser extent in AT/AU than AAP lesions. Baseline expression levels and changes from baseline to Weeks 12 and/or 24 in levels of genes and serum proteins related to Type I and II immunity, hair structure/function, and ritlecitinib's mechanism of action significantly correlated with clinical response at Weeks 12 and/or 24.
conclusionThese results provide support that treatment with ritlecitinib improves the gene expression profile in AA lesional scalp and is correlated with subsequent hair regrowth response.
trial registrationNCT02974868.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.