ERYTHEMA AND SCALE INFLUENCE QUALITY OF LIFE AND IMPRESSION OF DISEASE PROGRESSION IN CUTANEOUS LUPUS PATIENTS
Notice bibliographique
Résumé
O017 / #393 Topic: AS07 - Cutaneous Lupus ABSTRACT CONCURRENT SESSION 02: SLE METRICS – IMPROVING OUTCOMES & MEASURES 22-05-2025 1:40 PM - 2:40 PM Background/Purpose The Cutaneous Lupus Erythematosus Disease Area and Severity Index (CLASI) evaluates disease activity (CLASI-A) by assessing signs including erythema and scale in patients with cutaneous lupus erythematosus (CLE). While erythema and scale have been frequently mentioned as significant signs from patient interviews, their impact on how CLE patients feel about their skin disease has not been studied in larger patient cohorts. Understanding whether erythema and/or scale are important to patients would further justify their inclusion as scoring drivers in CLASI-A. Methods We conducted a prospective study investigating the relationships between CLASI-A erythema and scale scores and patient-reported outcome measures (PROMs) at baseline, and changes in these scores over 6 months. 131 CLE patients were recruited in outpatient dermatology clinics at University of Texas Southwestern Medical Center, Parkland Health, and University of Pennsylvania between July 2018 and November 2023. Examined PROMs included the CLE Quality of Life Index (CLEQoL), Dermatology Quality of Life Index (DLQI), Patient Impression of Disease Progression (PIDP), and Analogue Pain, Itch, and Fatigue Scales (APIFS). Spearman correlation analyses were performed to examine relationships between CLASI-A erythema or scale and PROMs. To compare the degree of association between CLASI-A erythema and scale vs PROMs, Spearman’s rho between erythema vs scale and PROMS were compared using paired t-test after Fisher’s transformation separately at baseline and then after 6 months. Results At baseline (N = 131), CLASI-A erythema had significant correlation to all PROMs, whereas scale directly correlated to all PROMs excluding the photosensitivity domain in CLEQoL (Table 1). Skin health from APIFS had the strongest correlation to erythema (r=-0.38, p<0.01) and scale (r=-0.32, p<0.01). After 6 months (N = 107), PIDP scores were most notably correlated to change in erythema (ρ = -0.41, p < 0.01) and scale (r = -0.23, p = 0.02) (Figure 1). The association between erythema and PROMs was not statistically different from that between scale and PROMs at baseline (p = 0.42) or after 6 months (p = 0.22). Table 1. Correlation Between CLASI-A Erythema and Scale vs. Patient-Reported Outcome Measures at Baseline Figure 1. Erythema and scale are correlated to PIDP scores after six months. Conclusions At baseline, erythema and scale had a significant correlation to nearly all PROMs, which validate the importance of both signs in affecting CLE patient lives. We also found that changes in erythema and scale were significantly correlated to PIDP after 6 months, suggesting that erythema and scale can contribute greatly to disease progression that matter to patients. These results affirm the substantial impact of erythema and scale in quality of life in CLE patients and demonstrate that improvement in erythema and scale can result in clinically meaningful benefit for CLE patients. They also justify the greater weighting of erythema in CLASI-A scoring, which can be responsive to treatments.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».