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Enregistrement W4411428363 · doi:10.1016/j.ard.2025.06.1547

ABS0512 STABLE PATIENT-REPORTED OUTCOMES DESPITE IMPROVING CLINICAL OUTCOMES OVER 25 YEARS. THE EARLY UNDIFFERENTIATED POLYARTHRITIS (EUPA) COHORT

2025· article· en· W4411428363 sur OpenAlexaffabout
Nathalie Carrier, Javier Marrugo, Sophie Roux, Ariel Masetto, Artur de Brum‐Fernandes, Patrick Liang, M. Maoui, Gilles Boire

Notice bibliographique

RevueAnnals of the Rheumatic Diseases · 2025
Typearticle
Langueen
DomaineMedicine
ThématiquePharmaceutical studies and practices
Établissements canadiensCentres Intégré Universitaires de Santé et de Services SociauxEion (Canada)Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalCentre Hospitalier Universitaire de SherbrookeUniversité de Sherbrooke
Organismes subventionnairesnon disponible
Mots-clésMedicinePolyarthritisCohortCohort studyPediatricsPhysical therapyArthritisInternal medicineFamily medicine

Résumé

récupéré en direct d'OpenAlex

Background: Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic synovitis, joint damage, functional impairment, and extra-articular manifestations. Over the past two decades, RA outcomes have improved due to advancements in treatment, including biologics, treat-to-target (T2T) strategies, and earlier intervention. Recent findings from the Early Undifferentiated PolyArthritis (EUPA) cohort revealed changes in baseline characteristics of RA patients, such as lower inflammation and reduced erosive damage, alongside increased comorbidities [1]. Objectives: We investigated whether ongoing changes in the characteristics of patients with early rheumatoid arthritis over two decades contributed to improved outcomes. Methods: The EUPA cohort, initiated in 1998, consecutively recruited adults with synovitis affecting at least three joints for one to twelve months. Patients were recruited from an academic health center, the sole rheumatology referral institution serving a population of 500,000, and provided consent to participate in a longitudinal observational study. Patients with bacterial or crystal-induced arthritis, connective tissue disease, or systemic vasculitis according to ACR criteria were excluded. Time of onset of arthritis was defined as the week or month during which joint symptoms appeared or, in patients with prior musculoskeletal complaints, when new signs or symptoms of inflammatory arthritis were reported. This study included patients meeting 1987 and/or 2010 RA criteria at baseline or within the first 18 months (90% of the recruited EUPA patients over 24 years). Evaluations were scheduled relative to symptom onset to ensure homogeneity in disease duration at follow-up, regardless of symptom duration at baseline. Treatment was individualized with the objective of sustained control of synovitis, with rheumatologists aiming for zero swollen joints. Patients were assessed at baseline and during follow-up visits scheduled at 12, 18, 30, 42, and 60 months after the onset of arthritis symptoms. A trained coordinator performed structured interviews at baseline and each follow-up visit. Assessed variables comprised demographic, clinical, and laboratory data including joint counts, C-reactive protein (CRP), erythrocyte sedimentation rate, serology, and HLA-DR locus genotyping. Radiographs were scored using the Sharp-van der Heijde method for joint space narrowing and erosions. Functional status was assessed using the Modified Health Assessment Questionnaire (M-HAQ), and disease activity was measured using the Simple Disease Activity Index (SDAI). Patient-reported outcomes (PROs) included the CES-D and visual analog scales for pain, fatigue, and sleep. Comorbidities were evaluated using the Rheumatic Disease Comorbidity Index (RDCI). Patients were classified into three time periods: (1) 1998–2004 (pre-biologics), (2) 2005–2010 (before T2T and 2010 RA criteria), and (3) 2011–2022 (post-T2T and expanded biologic access). Baseline characteristics were compared using Kruskal-Wallis and Chi-Square or Fisher Exact tests. Time-dependent outcomes across the three groups were analyzed using generalized estimating equations (GEE) and linear mixed models with repeated measures. Continuous variables were transformed for normal distribution, and multivariate GEE models adjusted for baseline and visit-specific variables. Statistical significance was set at p<0.05, with Benjamini-Hochberg correction for multiple comparisons. Results: The study cohort comprised 840 patients, categorized into three time periods: 245 patients (1998–2004), 266 patients (2005–2010), and 329 patients (2011–2022). At baseline, active smoking, seropositivity, CRP levels, erosive status, and pain levels decreased across the periods, while education levels and comorbidities increased.The use of high-dose methotrexate and biologics rose after 2005 but stabilized in subsequent periods. Early corticosteroid use increased over time, with tapering during follow-up accelerated across each period. Over a 5-year follow-up, erosive status progressed more slowly, and ACR/EULAR remission occurred significantly faster and became more prevalent, particularly after 2011 (Figure 1). However, improvement curves for functional status and other PROs remained consistent between periods (Figure 2). After adjusting for baseline variables and changes in treatment strategies, recruitment during the two most recent periods (2005–2010 and 2011–2022) was significantly associated with protection against erosive status and a higher likelihood of remission after 2011. Conclusion: The evolving intrinsic characteristics of early RA patients recruited in more recent periods contribute to higher remission rates and reduced erosive damage, complementing advancements in treatment strategies. However, functional outcomes and other PROs did not show parallel improvement during the first 5 years of disease. REFERENCES: [1] Carrier N, et al. Early Rheumatoid Arthritis Patients at Presentation Are Changing . J Rheumatol 2024. Acknowledgements: We thank the staff rheumatologists Dr. Pierre Dagenais, Dr. Guylaine Arsenault, Dr. Hugues Allard-Chamard, Dr. Lyne Bissonnette, and Dr. Alessandra Bruns and for their contribution to the recruitment and follow up of EUPA patients. We also thank our dedicated research assistants Chantal Guillet, Noémie Poirier and Christine Rosa for their long-term contribution to the EUPA study. Disclosure of Interests: Nathalie Carrier: None declared, Javier Marrugo: None declared, Sophie Roux: None declared, Ariel Masetto Dr. Masetto has received honoraria for presentations from AbbVie Canada and Novartis Canada, Dr. Masetto has received honoraria for participation in advisory boards from Johnson & Johnson, AbbVie Canada, and Novartis Canada, Dr. Masetto has received support for attending a meeting from Pfizer Canada, Artur De Brum-Fernandes: None declared, Patrick Liang Dr. Liang holds shares in Merck and Procter & Gamble, Dr. Liang has received honoraria for participation in advisory boards from Janssen Canada, Dr. Liang has received support for attending a meeting from Janssen Canada, Meryem Maoui Ms. Maoui was formerly employed by Bristol-Myers Squibb Canada, Gilles Boire Dr. Boire has received honoraria for presentations from Orimed Pharma and Viatris Canada, Dr. Boire has received honoraria for participation in advisory boards from AbbVie Canada, Janssen Canada, Eli Lilly, Mylan Canada, Novartis Canada, Otsuka Canada, Pfizer Canada, Sanofi Canada, Teva Canada, and Viatris Canada, Dr. Boire has received grant support through the CRCHUS from Biocon Canada and Pfizer Canada. © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,010

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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.

Tête enseignante Opus0,072
Tête enseignante GPT0,408
Écart entre enseignants0,336 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission2
Résumé présentoui

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Même revueAnnals of the Rheumatic DiseasesMême sujetPharmaceutical studies and practicesTravaux en français237 207