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Enregistrement W4411416212 · doi:10.1016/j.ard.2025.06.119

POS0759 CHARACTERISTICS OF RELAPSES AND THERAPEUTIC MANAGEMENTS IN GIANT CELL ARTERITIS IN MODERN ERA, NEWTON STUDY

2025· article· en· W4411416212 sur OpenAlexaff
A. Kante, G. Peyrac, N. Lomba Goncalves, P. Cacoub, Karim Sacré, D. Saadoun, T. Papo, J.F. Alexandra, V. Pagis, V. Bourdin, P. Richette, A. Vanjak, A. Latourte, D. Elessa, R. Burlacu, K. Champion, Blanca Amador Borrero, Ana Rita Lopes, A. Depond, Pierre Bonnin, Alexandre Boutigny, F. Paycha, Anne Couvelard, H. Adle, P. Reiner, Aude Couturier, A. Régent, B. Chaigne, Yann Nguyen, A. Lefort, O. Bory, E. Aslangul, S. Mouly, D. Sène, Viet‐Thi Tran, C. Comarmond

Notice bibliographique

RevueAnnals of the Rheumatic Diseases · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueVasculitis and related conditions
Établissements canadiensHotel Dieu Hospital
Organismes subventionnairesnon disponible
Mots-clésMedicineGiant cell arteritisArteritisImmunologyPathologyVasculitisDisease

Résumé

récupéré en direct d'OpenAlex

Background: The management of giant cell arteritis (GCA) has evolved with the arrival of tocilizumab (TCZ) and the use of PET/CT. In modern era, a double clinical challenge persists: to reduce relapse rate and glucocorticoids (GC) exposure. Objectives: Our objective is to describe the characteristics of relapses and outcomes of patients with recent diagnosis of GCA in current care. Methods: The NEWTON cohort is a French multicentric retrospective cohort based on data collected from GCA patients diagnosed after 2016 and who satisfied the ACR/EULAR 2022 criteria. Relapse definition was 1/ clinical symptom related to GCA and/or elevated C-reactive protein and/or worsening or new vascular lesion, in a patient previously in remission, and 2/ the need for the reinstitution or an increase in prednisone, and/or the addition of, or a change in, immunosuppressive drug (IS). Relapse characteristics, outcomes, factor associated with the first relapse and therapeutic managements were analysed. Results: We identified 211 GCA diagnosed between 2017 and 2023, with a mean (± SD) age at diagnosis of 77.2 (± 9.58) years, female predominance (n=142; 67.3%) and followed up for a median duration [IQR Q1; Q3] of 35 [19; 56] months. GCA relapse occurred in 109/211 (51.6%) patients with 240 relapses. The median time at first relapse was 261 [125; 468] days, following GCA diagnosis. Most relapses occurred when GC therapy was still not discontinued (Figure 1). At relapse, prednisone discontinuation was observed in 40/240 (16.7%), the median dose of prednisone was 6.5 [0; 12.5] mg daily, increased to 20 [10; 35] mg daily after therapeutic intensification. Relapses characteristics included clinical and biological criteria in 82/240 (34%), clinical criteria alone in 69/240 (29%), biological criteria alone in 36/240 (15%), clinical and imaging criteria in 15/240 (6%), imaging and biological criteria in 7/240 (3%) or imaging criteria alone in 7/240 (3%). Therapeutic intensifications following relapse included reinstitution or increase in GC alone in 43%, GC and IS intensification in 32%, and addition of IS alone in 25%. During the disease course, 64/211 (30%) patients received TCZ either from diagnosis in 16/64 (25%), either at relapse in 48/64 (75%). Subcutaneous TCZ was used in 41/64 (64%) and intravenous TCZ in 23/64 (36%). Among them, 31 (48%) patients discontinued TCZ, 19 (30%) because of remission while 12 (18%) patients discontinued because of TCZ adverse events. After TCZ discontinuation with a median follow-up of 17.5 [11.5; 31] months, 11/31 (35.5%) patients relapsed in a median time of 133 [90; 303.5] days. Twenty (64.5%) patients did not relapse after TCZ cessation with a median follow-up of 511 [153.3; 611.5] days. Multivariable Cox regression model, including clinical symptom and age at GCA diagnosis, gender, vascular lesion in different topography related to GCA as covariates, showed that only limb arteries involvement (HR 1.9 [1.23-2.98], P<0.01) at diagnosis was associated with GCA relapse (Figure 2). Conclusion: Relapses occur mainly during the year following diagnosis, despite GC are not discontinued. The use of TCZ concerns a third of GCA recently diagnosed, however more than one third relapsed after TCZ cessation. Limb arteries involvement at GCA diagnosis is a predictor of relapse. REFERENCES: [1] Goncalves L, Tran V-T, Chauffier J, Bourdin V, Nassarmadji K, Vanjak A, et al. [Clinical characteristics and follow-up of 60 patients with recent diagnosis of giant cell arteritis, NEWTON study]. Rev Med Interne 2024:S0248-8663(23)01322-X. [2] Alba MA, Kermani TA, Unizony S, Murgia G, Prieto-González S, Salvarani C, et al. Relapses in giant cell arteritis: Updated review for clinical practice. Autoimmun Rev 2024;23:103580. [3] Hellmich B, Agueda A, Monti S, Buttgereit F, Boysson H de, Brouwer E, et al. 2018 Update of the EULAR recommendations for the management of large vessel vasculitis. Ann Rheum Dis 2020;79:19–30. [4] Maz M, Chung SA, Abril A, Langford CA, Gorelik M, Guyatt G, et al. 2021 American College of Rheumatology/Vasculitis Foundation Guideline for the Management of Giant Cell Arteritis and Takayasu Arteritis. Arthritis Rheumatol 2021;73:1349–1365. [5] Boysson H de, Devauchelle-Pensec V, Agard C, André M, Bienvenu B, Bonnotte B, et al. French protocol for the diagnosis and management of giant cell arteritis. Rev Med Interne 2024:S0248-8663(24)00810–5. Figure 1Curves and bars proportion of study population according to relapse status and GC therapy discontinuation during follow-up. Light green area (1 ) represents the proportion of ACG patients with no relapse and discontinuation of GC therapy, red area (2 ) = the proportion of ACG patients who relapse when GC therapy is discontinued, orange area (3 ) = the proportion of ACG patients who relapse under GC therapy and dark green area (4 ) = the proportion of ACG patients with no relapse under GC therapy. Figure 2Kaplan-Meier curves of study population. Patients with limb arteries involvement at GCA diagnosis (green curve _1) had higher rates of relapse than patients without limb arteries involvement (blue curve _0) (log-rank; P < 0.01). Acknowledgements: SNFMI, FAI2R, Chugaï Pharma. Disclosure of Interests: None declared . © 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 enseignants0,002
Score d'incertitude au seuil0,007

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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.

Tête enseignante Opus0,017
Tête enseignante GPT0,287
Écart entre enseignants0,270 · 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'admission1
Résumé présentoui

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