P163 Low uveitis rates in patients with axial spondyloarthritis treated with bimekizumab: pooled results from phase 2b/3 trials
Bibliographic record
Abstract
Abstract Background/Aims Acute anterior uveitis (‘uveitis’) is a common extra musculoskeletal manifestation of axial spondyloarthritis (axSpA). Interleukin (IL)-17 has been implicated in uveitis pathogenesis; however, inhibition of IL-17A alone may not be optimal for uveitis management. We report the incidence of uveitis following IL-17A and IL17F inhibition with bimekizumab (BKZ) in patients with axSpA. Methods Data were pooled for patients randomised to placebo (PBO) or BKZ 160mg every 4 weeks (Q4W) in the double-blind treatment period (DBTP) of the phase (ph)3 studies BE MOBILE 1 (NCT03928704; non-radiographic axSpA) and 2 (NCT03928743; radiographic axSpA [i.e. ankylosing spondylitis]). Data were also pooled for all patients treated with BKZ in BE MOBILE 1, BE MOBILE 2, BE MOVING (NCT04436640; open-label extension [OLE] of BE MOBILE 1 and 2), the ph2b study BE AGILE (NCT02963506; r-axSpA) and its OLE BE AGILE 2 (NCT03355573; data cut-off 4 July 2022). Uveitis events were identified using the preferred terms “autoimmune uveitis,” “iridocyclitis,” “iritis” and “uveitis,” and are reported as exposure adjusted incidence rates (EAIRs) per 100 patient-years (PY) for all patients who received ≥1 BKZ dose. Results Baseline characteristics of the axSpA study populations are shown in the Table. In the DBTP of BE MOBILE 1 and 2, uveitis events occurred in 11/237 (4.6%; EAIR/100 PY [95% CI]: 15.4 [7.7, 27.5]) and 2/349 (0.6%; 1.8 [0.2, 6.7]) patients randomised to PBO and BKZ (percentage difference [95% CI]: 4.1 [1.7, 7.6]), respectively. In 45 PBO-randomised (19.0%) and 52 BKZ-randomised (14.9%) patients with history of uveitis, uveitis occurred in 20.0% (EAIR/100 PY [95% CI]: 70.4 [32.2, 133.7]) and 1.9% (6.2 [0.2, 34.8]) of patients, respectively. In the ph2b/3 pool (N = 848) total BKZ exposure was 2,034.4 PY and 130 (15.3%) patients had history of uveitis. Uveitis occurred in 25 (2.9%; EAIR/100 PY [95% CI]: 1.2 [0.8, 1.8]) and 14 (10.8%; 4.6 [2.5, 7.7]) patients overall and with history of uveitis, respectively. All uveitis events were mild/moderate; one led to discontinuation. Conclusion Incidence of uveitis was lower to Week 16 in patients with axSpA randomised to BKZ 160mg Q4W versus PBO and remained low at 1.2/100 PY in the largest ph2b/3 pool. Disclosure M. Rudwaleit: Consultancies; AbbVie, Eli Lilly, Novartis and UCB Pharma. Member of speakers’ bureau; AbbVie, Boehringer Ingelheim, Chugai, Eli Lilly, Janssen, Novartis, Pfizer and UCB Pharma. M.A. Brown: Consultancies; Clementia, Grey Wolf Therapeutics, Incyte, Ipsen, Pfizer, Regeneron and Xinthera. Member of speakers’ bureau; Novartis and Pfizer. Grants/research support; UCB Pharma. F. van Gaalen: Grants/research support; Jacobus Stichting, Novartis, Stichting ASAS, Stichting Vrienden van Sole Mio and UCB Pharma. Other; fees from Novartis; personal fees from AbbVie, BMS, Eli Lilly and MSD. N. Haroon: Consultancies; AbbVie, Eli Lilly, Janssen, Novartis and UCB Pharma. L.S. Gensler: Consultancies; AbbVie, Acelyrin, Eli Lilly, Fresenius Kabi, Janssen, Novartis, Pfizer and UCB Pharma. Grants/research support; Novartis and UCB Pharma paid to institution. C. Fleurinck: Other; Employee of UCB Pharma. A. Marten: Other; Employee of UCB Pharma. U. Massow: Other; Employee of UCB Pharma. N. de Peyrecave: Other; Employee of UCB Pharma. T. Vaux: Other; Employee of UCB Pharma. K. White: Shareholder/stock ownership; UCB Pharma. Other; Employee of UCB Pharma. A. Deodhar: Consultancies; AbbVie, BMS, Eli Lilly, Janssen, MoonLake, Novartis, Pfizer and UCB Pharma. Member of speakers’ bureau; Janssen, Novartis and Pfizer. Grants/research support; AbbVie, BMS, Celgene, Eli Lilly, MoonLake, Novartis, Pfizer and UCB Pharma. D. McGonagle: Consultancies; AbbVie, Celgene, Janssen, Merck, Novartis, Pfizer and UCB Pharma. Honoraria; AbbVie, Celgene, Janssen, Merck, Novartis, Pfizer and UCB Pharma. Member of speakers’ bureau; AbbVie, Celgene, Janssen, Merck, Novartis, Pfizer and UCB Pharma. Grants/research support; AbbVie, Celgene, Janssen, Merck and Pfizer. I. van der Horst-Bruinsma: Consultancies; Abbvie, Eli Lilly, MSD, Novartis and UCB Pharma. Other; unrestricted grants received for investigator-initiated studies from AbbVie, MSD, Pfizer and UCB Pharma; fees received for lectures from AbbVie, BMS, MSD and Pfizer.
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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 | 0.017 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.013 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".