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
Bibliographic record
Abstract
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".