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Record W4417419178 · doi:10.1093/bjd/ljaf485

Open-label treatment extension of ruxolitinib cream in vitiligo: findings from the Topical Ruxolitinib Evaluation in Vitiligo (TRuE-V) long-term extension phase III study

2025· article· en· W4417419178 on OpenAlexaff
John E. Harris, Kim Papp, Khaled Ezzedine, Michael Sebastian, Amit G. Pandya, Julien Sénéschal, Mark Amster, Maryam Shayesteh Alam, Seth Forman, Jacek Zdybski, Anthony A. Nuara, Deanna Kornacki, Shaoceng Wei, Thierry Passeron, David Rosmarin

Bibliographic record

VenueBritish Journal of Dermatology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicmelanin and skin pigmentation
Canadian institutionsProbity Medical ResearchBarrie Urology GroupUniversity of Toronto
FundersIncyte
KeywordsRuxolitinibVitiligoClinical trialDuration (music)Cohort

Abstract

fetched live from OpenAlex

We present data from the Topical Ruxolitinib Evaluation in Vitiligo (TRuE-V) long-term extension (LTE) study evaluating repigmentation outcomes with continued 1.5% ruxolitinib cream treatment in patients who did not achieve near-complete facial repigmentation in TRuE-V1/TRuE-V2. Among patients in the TRuE-V1/TRuE-V2 trials who applied ruxolitinib cream from day 1, approximately 66% achieved F-VASI 75 (indicative of treatment success) at week 104, increasing from nearly 31% at week 52 (TRuE-V LTE baseline); similar repigmentation improvements were reported in patients who switched from vehicle to ruxolitinib cream after TRuE-V1/TRuE-V2 at week 24, albeit with lower overall response rates due to the shorter duration of ruxolitinib cream application. These findings indicate that continued ruxolitinib cream treatment allows further repigmentation in many patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.041
GPT teacher head0.376
Teacher spread0.336 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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