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Enregistrement W4411429448 · doi:10.1016/j.ard.2025.05.120

OP0098 Assessing the Frequency of Difficult-to-Manage (D2M) and Treatment-Refractory (TR-axSpA) Cases in the RABBIT-SpA Register: An Analysis Based on Recent ASAS Definitions

2025· article· en· W4411429448 sur OpenAlexaff
F. Proft, S Lembke, Anja Weiß, H Kellner, Xenofon Baraliakos, Denis Poddubnyy, Anne C. Regierer

Notice bibliographique

RevueAnnals of the Rheumatic Diseases · 2025
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueHealth Systems, Economic Evaluations, Quality of Life
Établissements canadiensUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésMedicineRegister (sociolinguistics)Refractory (planetary science)Family medicineInternal medicinePediatricsLinguistics

Résumé

récupéré en direct d'OpenAlex

Background: Despite advances in therapeutic strategies, a subset of axSpA patients continues to experience persistent disease activity or inadequate response to treatment, underscoring the need to better characterize these challenging cases. Recent criteria proposed by the Assessment of SpondyloArthritis International Society (ASAS) define two clinically relevant subgroups within axSpA and inadequate treatment response: Difficult-to-Manage (D2M-) and treatment-refractory (TR-) axSpA [1]. Objectives: This analysis aimed to determine the frequency of axSpA patients meeting the recently proposed D2M- and TR-axSpA criteria as well as to describe patient characteristics at the time point of initiating the first b/tsDMARD treatment. Methods: Utilizing data from RABBIT-SpA, a German prospective longitudinal register, this analysis included b/tsDMARD-naïve axSpA patients initiating b/tsDMARD therapies, with at least 12 months of follow-up. The analysis applied the new ASAS criteria to identify D2M-axSpA and TR-axSpA cases. To qualify for inclusion in the D2M group from our preselected cohort, patients must meet the first criterion of the D2M definition, which requires that a patient must have experienced treatment failure of ≥2 b/tsDMARDs with different modes of action. To evaluate insufficient control of signs and symptoms – the second component of the D2M definition – the following criteria were assessed: high disease activity: ASDAS ≥2.1; signs and symptoms suggestive of active disease: arthritis joint count ≥1, enthesitis ≥1, BASDAI question-2 (axial involvement) ≥4, new onset of uveitis, psoriasis, or inflammatory bowel disease; CRP ≥5 mg/L; active inflammation on MRI of the sacroiliac joints (SIJ) and/or spine or patient global assessment (PtGA) ≥4. The third D2M criterion was fulfilled if either the physician global assessment (PhGA) or PtGA was ≥4. Treatment refractory (TR-axSpA) status was defined as patients meeting the D2M criteria with explicit evidence of high disease activity (ASDAS ≥2.1) AND either active inflammation on MRI of the SIJ/spine OR an elevated CRP (≥5 mg/L). Results: From 1850 patients, 881 (48%) were b/tsDMARD-naïve at inclusion in the RABBIT-SpA registry and met the predefined follow-up. Among them, 137 (16%) patients underwent treatment with at least two different modes of action. Seventy-five patients (8.5% of the 881 selected pts.) met the ASAS criteria for D2M axSpA (Figure 1). D2M patients were predominantly females, with a lower education level, they were less likely to be HLA-B27 positive and displayed more frequent clinical signs of enthesitis and arthritis but fewer objective signs such as MRI-detected inflammation in the spine or elevated CRP levels. All patient reported outcomes (PRO) were worse in this group. Twenty-two of these (2.5% of the 881 selected pts.) also met the TR criteria, characterized by persistent active disease and objective signs of inflammation. This specific subgroup also showed higher rates of elevated CRP levels and SIJ/spinal inflammation on MRI at baseline. Additionally, they had a lower likelihood of being HLA-B27 positive and were more frequently smokers (Table 1). Conclusion: Approximately 8.5% of b/tsDMARD-naïve axSpA patients met the D2M criteria, and 2.5% qualified as TR. D2M-axSpA patients were more often female and less likely to be HLA-B27 positive, when compared to those patients not fulfilling these definitions. Furthermore, D2M-axSpA was associated with higher peripheral involvement and worse PROs at initiation of their first b/tsDMARD treatment. REFERENCES: [1] Poddubnyy D. et al.; The Assessment of SpondyloArthritis International Society (ASAS) Definition of Difficult-to-Manage Axial Spondyloarthritis [abstract]. Arthritis Rheumatol. 2024; 76 (suppl 9). Figure 1Flow Chart of Patient Selection Table 1Baseline characteristics of b/tsDMARDs naive axSpA patients with at least 12 months follow up time in RABBIT-SpA.b/tsDMARD naive axSpA patientsn=881nD2M/nTRn=806D2Mn=75→TRn=22Gender (Female)n (%)339 (42.1)40 (53.3)9 (40.9)AgeMean (SD)42.4 (13)45 (12)42.7 (12.6)Symptom duration (years)Mean (SD)10.7 (10.8)11.1 (9.9)10.6 (8.5)Smoking (yes)n (%)282 (39.3)28 (42.4)8 (50)Years of education (≥ 10 years)n (%)581 (80.6)47 (71.2)14 (82.4)Enthesitis (current)n (%)138 (17.2)20 (26.7)6 (27.3)Arthritis (current)n (%)219 (27.3)25 (33.3)5 (22.7)HLA-B27 (positive)n (%)608 (77.2)49 (68.1)12 (54.5)PhGA (NRS 0-10)Mean (SD)5.7 (1.7)6.3 (1.6)6.2 (1.6)PtGA (NRS 0-10)Mean (SD)5.8 (2.4)6.8 (1.7)6.8 (1.3)BASDAI (NRS 0-10)Mean (SD)4.6 (1.9)5.3 (1.8)5.1 (2)BASFI (NRS 0-10)Mean (SD)3.7 (2.3)4.3 (2.2)3.7 (1.9)ASDASMean (SD)2.9 (1)2.9 (0.6)3.1 (0.8)CRP (positive, ≥ 5mg/L)n (%)434 (57.7)36 (50)16 (72.7)Active inflammation MRI SIJ (yes)n (%)482 (80.3)40 (80)10 (83.3)Active inflammation MRI spine (yes)n (%)252 (57.8)24 (51.1)9 (64.3)Comorbidities (≥ 3)n (%)115 (14.3)12 (16)3 (13.6)Depression (yes)n (%)36 (4.5)5 (6.7)1 (4.5)WHO5 (moderate/severe)n (%)194 (27.1)24 (36.4)9 (52.9) Acknowledgements: RABBIT-SpA is supported by a joint, unconditional grant from AbbVie, Amgen, Biocon Biologics, Biogen, Celltrion, Janssen-Cilag, Lilly, Novartis, Pfizer, and UCB. We thank all participating patients and rheumatologists. Disclosure of Interests: Fabian Proft Speakers bureau with payments made directly to me for: AbbVie, AMGEN, BMS, Celgene, Eli Lilly, Hexal, Janssen, Medscape, MSD, Novartis, Pfizer, Roche and UCB, Consultancy with payments made directly to me for: AbbVie, BMS, Janssen, Novartis, Pfizer and UCB, Grant/research support from Novartis, Eli Lilly and UCB with payments made via my institution, Stephanie Lembke: None declared, Anja Weiß: None declared, Herbert L Kellner: None declared, Xenofon Baraliakos Research Grants, Consultant, Scientific Advisory Board: Abbvie, Alphasigma, Amgen, BMS, Cesas, Celltrion, Galapagos, Janssen, Lilly, Moonlake, Novartis, Pfizer, Roche, Sandoz, Springer, Stada, Takeda, UCB, Zuellig; Funding: Abbvie, Janssen, Novartis, Celltrion, See above, See above, Denis Poddubnyy speaker fees from AbbVie, Canon, DKSH, Eli Lilly, Janssen, MSD, Medscape, Novartis, Peervoice, Pfizer, and UCB, consulting fees from AbbVie, Biocad, Bristol-Myers Squibb, Eli Lilly, Janssen, Moonlake, Novartis, Pfizer, and UCB, received research support from AbbVie, Eli Lilly, Janssen, Novartis, Pfizer, UCB, Anne Regierer Amgen, BMS, Novartis, Pfizer, Roche, none personal. © 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)0,003
score de la tête « metaresearch » (Gemma)0,006
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 enseignants0,004
Score d'incertitude au seuil0,015

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,006
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0030,004
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,000
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 Opus0,429
Tête enseignante GPT0,462
Écart entre enseignants0,033 · 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

Citations1
Publié2025
Routes d'admission1
Résumé présentoui

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