TREATMENT ADHERENCE AND ASSOCIATED FACTORS IN PATIENTS WITH CUTANEOUS LUPUS, A PROSPECTIVE MULTICENTER STUDY
Notice bibliographique
Résumé
PV081 / #18 Poster Topic: AS11 - Epidemiology and Public Health Background/Purpose Cutaneous lupus erythematosus (CLE) is an autoimmune disease with a significant impact on quality of life. Many patients with CLE do not improve with conventional treatments. While poor adherence to treatment is well-documented in systemic lupus, data on adherence in CLE is lacking. The aim of this study was to evaluate therapeutic adherence in CLE, and to identify factors associated with poor adherence. Methods This is a prospective, cross-sectional, multicenter study. Patients with CLE completed validated adherence assessment questionnaires (MASRI and MMAS4) at a follow-up visit. According to the MASRI, adherence was defined by a visual analog scale (VAS) greater than or equal to 80%. According to the MMAS4, adherence was defined by a maximum score of 4 out of 4. The CLASI score, which evaluates disease activity (CLASI-A) and damage (CLASI-D), was used to assess the severity of CLE. Quality of life (DLQI), anxiety and depression (HAD), opinion of medication (BMQ), feeling of illness (EVA), and quality of the doctor-patient relationship (CARE and CollaboRATE) were also assessed. Factors associated with adherence (according to MASRI and MMAS4) were assessed by multivariate analysis using logistic regression. Relationships between the different variables were examined using a correlation matrix. Results We included 108 patients with CLE from 3 university hospitals in France. Treatment adherence was 88% according to MASRI and 44.8% according to MMAS4. Younger age (p = 0.0233), presence of discoid lupus (p = 0.0004), disease severity (p = 0.0004) and number of therapy lines (p = 0.0209) were significantly associated with poorer adherence according to MMAS4. A higher number of physicians consulted (r_s = 0.23) and the presence of anxiety and depressive symptoms (r_s = 0.21) were correlated with lower adherence. Severity of cutaneous lupus was correlated with higher anxiety and depressive symptoms (r_s = 0.24) and greater impairment of quality of life (r_s = 0.28). Physician empathy (r_s = 0.26) and shared decision making (r_s = 0.22) were correlated with lower anxiety and depressive symptoms. Conclusions Adherence appears to be significantly impaired in patients CLE. The difference between the 2 adherence scores may be explained by the greater sensitivity of the MMAS4. In our study, there was a significant correlation between the 2 scores (Figure 1). Lower adherence is associated with more severe CLE, both in terms of activity and scarring. It would be interesting to improve the empathic dimension of the doctor-patient relationship and shared decision making, and to assess adherence during follow-up. Figure 1: Distribution of adherence according to the MASRI EVA and the MMAS4.
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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».