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Record W4415040496 · doi:10.1080/09546634.2025.2555984

Assessment of vitiligo in clinical practice: a cross-sectional survey among experts

2025· article· en· W4415040496 on OpenAlexaff
Jolien Duponselle, Marlide R. Jukema, Albert Wolkerstorfer, Khaled Ezzedine, Iltefat Hamzavi, Julien Sénéschal, Viktoria Eleftheriadou, Amit G. Pandya, Amit Garg, Anand K. Ganesan, Boon Kee Goh, Davinder Parsad, Deepti Ghia, David Rosmarin, Giovanni Leone, Henry W. Lim, Hyun Jeong Ju, Jung Min Bae, John Ferguson, Laïla Benzekri, Marwa Abdallah, Markus Böhm, Mauro Picardo, Mehdi Rashighi, M Ramam, Michelle Rodrigues, Noufal Raboobee, Phyllis I. Spuls, Samia Esmat, Steven Tien Guan Thng, Thierry Passeron, Victor Huang, Reinhart Speeckaert, Nanja van Geel

Bibliographic record

VenueJournal of Dermatological Treatment · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicmelanin and skin pigmentation
Canadian institutionsSt. Thomas HospitalSKiN Health
FundersLEO PharmaIncyteLes Laboratories Pierre FabreSanofiVlaamse regeringPfizerEli Lilly and CompanyBristol-Myers Squibb
KeywordsVitiligoClinical PracticeMEDLINEClinical trialQuality of life (healthcare)Depigmentation

Abstract

fetched live from OpenAlex

BACKGROUND: The assessment of patient-centered outcomes in clinical practice is essential for optimal care. While a core domain set (CDS) for vitiligo clinical trials was established in 2015 (CDS for trials) to standardize outcomes, no CDS currently exists for clinical practice, resulting in inconsistent assessment complicating effective disease management. OBJECTIVE: This study aimed to investigate outcomes and characteristics currently assessed by vitiligo experts in clinical practice and represents one of the steps toward developing a core outcome set (COS) including outcomes and outcome measurement instruments for clinical practice. METHODS: A cross-sectional survey was conducted among 31 vitiligo experts from six continents. The survey consisted of 28 predefined outcomes and characteristics. Participants were given the opportunity to propose additional options, which were considered 'generally assessed' when assessed by ≥ 70%. RESULTS: Six outcomes and 21 characteristics were 'generally assessed'. The most frequently chosen outcomes included vitiligo evolution, tolerability of treatment/adverse events, followed by disease activity and vitiligo extent. CONCLUSION: This study shows similarities but also remarkable differences in assessed outcomes compared to the CDS for clinical trials. These results serve as a preparatory step toward developing a COS for clinical practice with the involvement of expert and non-expert dermatologists and 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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.280

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.051
GPT teacher head0.468
Teacher spread0.416 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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