OA16 Bimekizumab treatment resulted in improvements in MRI inflammatory and structural lesions in the sacroiliac joints of patients with axial spondyloarthritis: 52-week results and post hoc analyses from two Phase 3 studies
Notice bibliographique
Résumé
Abstract Background/Aims The impact of dual inhibition of interleukin (IL)17F in addition to IL-17A with bimekizumab (BKZ) on structural lesions in axial spondyloarthritis (axSpA) patients has not yet been shown. We report BKZ impact on MRI inflammatory and structural lesions in sacroiliac joints (SIJ) of non-radiographic and radiographic (nr-/r-)axSpA patients to week (wk) 52 in the phase 3 studies BE MOBILE 1/2 (NCT03928704/NCT03928743). Methods In BE MOBILE 1/2 (nr-axSpA/r-axSpA), patients were randomised to BKZ 160mg every 4 wks or placebo (PBO); all patients received BKZ from Wk16-52. Spondyloarthritis Research Consortium of Canada (SPARCC) SIJ inflammation score and SPARCC SIJ Structural Scores (SSS: erosion/backfill/fat lesions/ankylosis) were assessed at baseline, wk 16 and wk 52 in MRI sub-studies. MRIs were assessed centrally by two independent experts (disagreement adjudicated). Inflammatory and structural lesions were assessed by different readers. All readers were blinded to timepoint/clinical data; structural lesions were analysed post hoc. For patients with valid MRI assessments at all three timepoints, we report patient proportions with baseline inflammation scores ≥2 achieving MRI remission (score <2), mean absolute inflammation scores and wk 16/52 change from baseline in SPARCC SSS (observed case). Results 60% (152/254) and 42% (139/332) of nr- and r-axSpA patients were enrolled in MRI sub-studies; at all three timepoints, 76% (115/152) and 78% (109/139) had valid SPARCC SIJ inflammation assessments, respectively, and 84% (128/152) and 83% (116/139) had valid SPARCC SSS assessments. Among those with valid SPARCC SIJ inflammation assessments at all three timepoints and baseline inflammation scores ≥2 (nr-axSpA: PBO: 32, BKZ: 39; ra-xSpA: PBO: 18, BKZ: 36), a larger proportion of BKZ- vs PBO-randomised patients achieved MRI remission at wk 16 (nr-axSpA: PBO: 9/32 [28.1%], BKZ: 26/39 [66.7]; r-axSpA: PBO: 3/18 [16.7%], BKZ: 21/36 [58.3%]). Proportions of continuous BKZ patients and patients switching from PBO to BKZ at wk 16 (PBO-switchers) achieving MRI remission increased from wk 16-wk 52 (nr-axSpA: PBO-switchers: 18/32 [56.3%], continuous BKZ: 31/39 [79.5%]; r-axSpA: PBO-switchers: 12/18 [66.7%], 27/36 [75.0%]). Substantial reductions in wk 16 mean absolute SPARCC SIJ inflammation scores (nr-axSpA: 1.6; r-axSpA: 1.2) were maintained to wk 52 for continuous BKZ patients (nr-axSpA: 1.0; Wk52 r-axSpA: 0.9); PBO-switchers reached similar levels of improvement as the BKZ-continuous group at wk 52 (nr-axSpA: 1.8; r-axSpA: 0.9). Reductions in SSS for erosions and increases in backfill and fat lesions were observed with BKZ vs PBO at wk 16, with further improvements mostly observed to wk 52 in continuous BKZ patients; similar changes were observed in PBO-switchers. No or minimal changes in SSS for ankylosis were observed following BKZ treatment in nr- and r-axSpA patients, respectively, to wk 52. Conclusion BKZ had a substantial impact on SIJ MRI inflammation and structural lesions, indicating potential tissue repair after only 16 wks of treatment. This continued to improve from wk 16 to wk 52. Disclosure W.P. Maksymowych: Honoraria; Honoraria/consulting fees from AbbVie, BMS, Boehringer Ingelheim, Celgene, Eli Lilly, Galapagos, Johnson & Johnson Innovative Medicine, Novartis, Pfizer and UCB. Grants/research support; Research grants from AbbVie, Galapagos, Pfizer and UCB; educational grants from AbbVie, Johnson & Johnson Innovative Medicine, Novartis and Pfizer. Other; Chief Medical Officer for CARE ARTHRITIS. S. Ramiro: Consultancies; Consulting fees from AbbVie, Eli Lilly, Galapagos, Johnson & Johnson Innovative Medicine, Novartis, Pfizer, Sanofi and UCB. Grants/research support; Grants from AbbVie, Galapagos, MSD, Novartis, Pfizer and UCB. D. Poddubnyy: Consultancies; Consultant for AbbVie, Biocad, Eli Lilly, Gilead, GSK, MSD, MoonLake, Novartis, Pfizer, Samsung Bioepis and UCB. Member of speakers’ bureau; Speaker for AbbVie, BMS, Eli Lilly, MSD, Novartis, Pfizer and UCB. Grants/research support; Grant/research support from AbbVie, Eli Lilly, MSD, Novartis and Pfizer. X. Baraliakos: Consultancies; Consultant for AbbVie, BMS, Chugai, Eli Lilly, Galapagos, Gilead, Novartis, Pfizer and UCB. Member of speakers’ bureau; Speakers bureau from AbbVie, BMS, Chugai, Eli Lilly, Galapagos, MSD, Novartis, Pfizer and UCB. Grants/research support; Grant/research support from Novartis and UCB. Other; Paid instructor for AbbVie, BMS, Chugai, Eli Lilly, Galapagos, MSD, Novartis, Pfizer and UCB. R.G. Lambert: Consultancies; Consultant for CARE Arthritis and Image Analysis Group. U. Massow: Corporate appointments; Employee of UCB. T. Vaux: Corporate appointments; Employee and shareholder of UCB. C. Prajapati: Corporate appointments; Contractor for UCB and employee of Veramed. A. Marten: Corporate appointments; Employee of UCB. N. de Peyrecave: Corporate appointments; Employee of UCB. M. Østergaard: Consultancies; Consulting fees from Abbott, Pfizer, Merck, Roche and UCB. Member of speakers’ bureau; Speakers bureau for Abbott, BMS, Merck, Mundipharma, Pfizer and UCB. Grants/research support; Research grants from Abbott, Pfizer and Centocor.
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 | 0,004 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,004 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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.
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 ».