O07 Randomised, open labelled clinical trial to investigate synovial mechanisms determining response: resistance to rituximab versus tocilizumab in RA patients failing TNF inhibitor therapy
Notice bibliographique
Résumé
Abstract Background Biologic therapies have transformed the outlook for RA but the significant health economic impact of these therapies has highlighted the need to define predictive markers of response. Rituximab (RTX) is licensed for use following failure of csDMARDs and TNF inhibitor (TNFi) therapy. However, in this increasing therapeutically resistant cohort only 30% of patients achieve an ACR50 response. The observation in early RA that 50% of patients show low/absence of synovial B-cells prompted us to test the hypothesis that in these patients a biologic agent targeting alternative pathways maybe more effective. We report results from the first pathobiology-driven randomised controlled trial (RCT) in RA (R4RA) evaluating whether patient stratification according to the synovial B-cell rich/poor status enriches for response/non response to RTX. Methods R4RA is a phase IV open-label RCT conducted in 19 European centres recruiting patients failing or intolerant to csDMARD therapy and at least one TNFi. Synovial tissue was obtained at trial entry and used to classify patients as B-cell rich or poor using both histological and RNA-seq classification criteria. Patients were randomised to receive RTX or tocilizumab (TCZ). The study was powered to test in the B cell poor population superiority of TCZ over RTX at 16 weeks. The primary and co-primary end-points were defined respectively as Clinical Disease Activity Index (CDAI) ≥50% improvement from baseline and Major Treatment response (MTR)= CDAI improvement ≥ 50% and CDAI ≤10.1. Results The trial recruited to target (n = 164) with a power of 89.5%. In the B cell poor cohort a numerically higher number of patients achieved the primary endpoint and a significantly higher number of patients achieved co-primary endpoint (MTR). Classification of patients as B cell poor/rich according to RNA-seq criteria enhanced the difference between TCZ and RTX, with a significantly higher number of TCZ treated patients reaching both CDAI 50% improvement and CDAI MTR in the B-cell poor group. Conclusion In a RA B cell poor population failing csDMARDs and TNFi therapy, TCZ is more effective than RTX. This first biopsy-driven RCT suggests clinical utility for integrating molecular pathology profiling into treatment algorithms to allocate targeted therapies. Disclosures F. Humby: Honoraria; Roche, Pfizer. Grants/research support; Pfizer. P. Durez: BMS,Bristol-Myers Squibb, Celltrion, Eli Lilly, Hospira, Mundipharma, Pfizer, Samsung, Sanofi, UCB. M. Buch: Consultancies; Pfizer, Roche, UCB, AbbVie, Eli Lilly, Sandoz, and Sanofi. Grants/research support; Pfizer, Roche, UCB, AbbVie, Eli Lilly, Sandoz, and Sanofi. M. Lewis: None. M. Bombardieri: None. H. Rizvi: None. S. Kelly: None. L. Fossati: None. R. Hands: None. G. Giorli: None. A. Mahto: None. C. Montecucco: None. B. Lauwerys: None. V.C. Romao: None. A.G. Pratt: Member of speakers’ bureau; Eli Lilly and Janssen-Cilag Ltd. Grants/research support; Pfizer. S. Bugatti: None. N. Ng: None. F. Rivellese: None. P. Ho: None. M. Bellan: None. P. Sainaghi: None. P. Verschueren: None. N. Gendi: None. B. Dasgupta: Abbvie, BMS, GSK, Roche, Roche Chugai, Sanofi, Sanofi Aventis, Sanofi-Aventis. A. Cauli: BMS, Celgene, Lilly, Lilly MSD, MSD, Novartis, Pfizer, Sanofi, Sigma Wesseumen, UCB. C. John: None. A. Nerviani: None. G. Thornborn: None. D. Holroyd: None. M. Congia: None. C. Thompson: None. P. Reynolds: None. J. Cañete: None. R. J. Moots: Biogen, Bristol-Myers Squibb, Chugai, Novartis, Pfizer Inc, Roche, Sandoz, UCB. P.C. Taylor: AbbVie, Biogen, Celgene, Eli Lilly and Company, Fresenius, Fresenius SE & Co, Galapagos, Gilead. GlaxoSmithKline, Janssen, Lilly, Nordic Pharma, Pfizer, Pfizer Inc, Roche, Sanofi, UCB. C. Edwards: Abbvie, Biogen, BMS, Fresenius, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, UCB. J. Isaacs: None. P. Sasieni: None. J. E. Fonesca: None. E. Choy: AbbVie, Abbvie, Roche, Chugai, Amgen, Eli Lilly, Janssen, Novartis, Regeneron, R-Pharm and Sanofi, Amgen, Amgen, Roche, Chugai, Bristol-Myers Squibb, Eli-Lilly Janssen, Pfizer, Regeneron, Sanofi and UCB., AstraZeneca, Bio-Cancer, Bio-Cancer, Biogen, Novartis, Sanofi, Roche, Pfizer and UCB ,Biogen, BMS, Boehringer Ingelheim, Celgene, Chugai Pharma, Eli Lilly, Ferring Pharmaceuticals, GSK, Hospira, Janssen, Jazz Pharmaceuticals, Merck Sharp & Dohme, Merrimack Pharmaceutical, Napp, Novartis, Novimmune, ObsEva, Pfizer, Regeneron, Roche, R-Pharm, Sanofi, SynAct Pharma, Tonix, Union Chimique Belge. C. Pitzalis: None. NIHR have funded the study.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».