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
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".