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ALL SUBCOMPONENTS OF THE CUTANEOUS LUPUS ERYTHEMATOSUS DISEASE AREA AND SEVERITY INDEX-ACTIVITY (CLASI-A) ARE RELEVANT TO IDENTIFY AND DETECT CHANGES IN SKIN ACTIVITY

2025· article· en· W4410513111 on OpenAlexvenueno aff
Victoria P. Werth, Joseph F. Merola, Qianyun Li, Yang Wei-hong, Catherine Barbey

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCutaneous Lupus ErythematosusDermatologyLupus erythematosusConnective tissue diseaseSeverity of illnessDiseaseInternal medicineAutoimmune diseaseImmunologyAntibody

Abstract

fetched live from OpenAlex

PV068 / #344 Poster Topic: AS07 - Cutaneous Lupus Background/Purpose Part B of the Phase 2 LILAC study ( NCT02847598 ) demonstrated the efficacy of litifilimab vs placebo, with a significant decrease in percent change from baseline in CLASI-A score at Week 16 in participants with active cutaneous lupus erythematosus (CLE) with or without systemic manifestations.[1] CLASI-A measures disease activity in CLE across several anatomical locations, based on 5 clinical subcomponents: erythema, scale/hypertrophy, mucous membrane lesions, recent hair loss (preceding 30 days), and non-scarring alopecia.[2] This exploratory analysis examined the contribution of all 5 CLASI-A subcomponents or anatomical locations in the total scoring change and explored the association between sunlight-exposed body areas and severity of the symptom. Methods The study design and participants’ baseline characteristics for LILAC Part B have been reported previously.[1] The distribution of the CLASI-A clinical subcomponents for the pooled Part B population (all litifilimab doses and placebo; N = 132) was analyzed by anatomical location at baseline and at Week 16. Change in CLASI-A scores by clinical subcomponent for the pooled study population at Week 16 was evaluated using point improvement/worsening from baseline at each anatomical location. Reported changes in CLASI-A subcomponent point scores could fall into the following ranges: erythema (from −3 to +3), scale/hypertrophy (from −2 to +2), mucous membrane lesions and recent hair loss (from −1 to +1), and non-scarring alopecia (from −3 to +3). Data are reported as observed; no imputation of missing data was conducted. Results At baseline, a higher proportion of participants reported ‘red’ (score 2) and ‘dark red’ (score 3) erythema in the more sunlight-exposed areas of the frontal V-neck area, ears, arms, nose (including malar area), and rest of the face (ranges across these anatomical areas: 25.0%–34.1% [‘red’], 2.3%–18.9% [‘dark red’]) than in the less-exposed areas of the feet, legs, and abdomen (ranges: 4.5%–6.1% [‘red’], 0.8%–3.8% [‘dark red’]) (Table 1). At Week 16, changes in CLASI-A scores by subcomponents were observed at all anatomical locations and were consistent with the distribution of scores at baseline, with the greatest improvements observed in the more highly exposed areas (Table 2). Both 1-point and 2-point improvements in the erythema subcomponent score were reported at all anatomical locations, in up to 33.3% and 12.4% of participants per location, respectively. A 3-point improvement in erythema was observed at almost all locations, in up to 2.9% of participants per location. Similar findings were observed for scale/hypertrophy. Table 1: Distribution of CLASI-A subcomponent scores for each anatomical location at baseline Table 2: Distribution of change from baseline in CLASI-A subcomponent scores for each anatomical location at Week 16 Conclusions No single subcomponent of the measure drives the CLASI-A score or the CLASI-A score changes. CLASI-A is able to identify skin activity in terms of both the overall severity and changes in the visible and uncovered areas that are most vulnerable to photosensitivity and that are important to patients. This further supports the relevance of all 5 subcomponents of CLASI-A in describing disease activity in CLE. References: [1.] Werth V. N Engl J Med 2022;387:321-31. [2.] Albrecht J. J Invest Dermatol 2005;125:889-94. Funding: This study was funded by Biogen (Cambridge, MA, USA). Writing and editorial support were provided by Selene Medical Communications (Macclesfield, UK), funded by Biogen.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.002

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 head0.023
GPT teacher head0.311
Teacher spread0.288 · 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 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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