A EULAR/ACR (2019) SLE CLASSIFICATION CRITERIA SCORE ≥20 IS A MARKER OF SEVERE DISEASE IN A PREVALENT SLE COHORT FROM THE PORTUGUESE REUMA.PT REGISTRY
Notice bibliographique
Résumé
PV214 / #533 Poster Topic: AS23 - SLE-Diagnosis, Manifestations, & Outcomes Background/Purpose Recently, a EULAR/ACR 2019 systemic lupus erythematosus (SLE) classification criteria (EULAR/ACR 2019) score≥20 was identified in a SLE inception cohort with less than 2 years from diagnosis as a marker for more severe disease, including higher disease activity, more frequent flares, higher use of immunosuppressants, lower probability of achieving remission, and more damage accrual. However, this analysis has not been performed in SLE patients with longer disease duration.[1] The aim of our study was to assess a EULAR/ACR 2019 score ≥20 as a marker for severe disease in a prevalent SLE cohort. Methods We performed a cross-sectional multicenter study of patients fulfilling the EULAR/ACR 2019 classification criteria for SLE in the Portuguese registry of rheumatic diseases (Reuma.pt). Disease activity (SLE-DAS) and the EULAR/ACR score were assessed at the last visit, between June 2023 and March 2024. Groups of patients with EULAR/ACR 2019 score ≥20 or <20 were compared for demographic, clinical and treatment features, with parametric and non-parametric tests, as appropriate. Separate models were tested using different definitions of severe SLE (dependent variable), as present/absent: (1) cumulative SLE major organ involvement; (2) moderate/severe disease activity, defined as SLE-DAS>7.64; (3) ongoing immunosuppressants; (4) ongoing systemic prednisolone>7.5 mg/day; (5) organ damage, defined as SLICC/ACR Damage Index (SDI) ≥ 1. Predictors for each of these definitions were assessed in a 2-step approach with logistic regression (LR) univariate analysis, followed by multivariate LR models including variables with p<0.10 in the first step, while excluding variables with multicollinearity. Multivariate analysis was used to identify independent predictors and estimate the respective adjusted odds ratios (OR) with 95% confidence intervals. Results There were 2459 patients registered in Reuma.pt, from 37 participating centers. A total of 709 patients, from 18 centers, who had data on and fulfilled the EULAR/ACR 2019 classification criteria and had a SLE-DAS scoring were included, 65.6% having an EULAR/ACR 2019 score≥20. These patients were younger at diagnosis (p<0.001), had longer disease duration (p<0.001), higher SLE-DAS score (p=0.001), received less frequently antimalarials (p=0.004), and were more frequently treated with synthetic and/or biologic immunosuppressants (p<0.001) and glucocorticoids (p<0.001). On univariate LR analysis, a EULAR/ACR 2019 score≥20 was associated with all definitions of severe disease (Table 1). On multivariate LR analysis, a EULAR/ACR 2019 score≥20 was an independent predictor of cumulative major organ involvement (OR 7.30, 95% CI 4.86-10.95, p<0.001), moderate/severe disease activity (OR 7.36, 95% CI 2.18-24.82, p=0.001), ongoing immunosuppressants (OR 2.73, 95% CI 1.82-4.09, p<0.001), and ongoing systemic prednisolone>7.5 mg/day (OR 2.71, 95% CI 1.29-5.69, p=0.009), adjusted for significant covariates. In the multivariate LR, a EULAR/ACR score≥20 was not associated with organ damage, defined as SDI≥1. Table 1 Univariate and multivariate logistic regression analysis for severe SLE Conclusions A EULAR/ACR 2019 score ≥20 is associated with severe disease in a prevalent SLE cohort. Although this is not surprising, given the similarity and close relationship between items included in all instruments, this score may, in association with measures of disease activity, contribute to management in clinical practice, stratification of cases in observational studies and selection of patients for clinical trials. References: [1.] Whittall-Garcia LP. Ann Rheum Dis. 2021;80(6):767-74. * Carolina Mazeda and Beatriz Mendes contributed equally and share first authorship.
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) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».