Low uveitis rates in patients with axial spondyloarthritis treated with bimekizumab: pooled results from phase 2b/3 trials
Bibliographic record
Abstract
OBJECTIVES: Acute anterior uveitis ('uveitis') is a common axial spondyloarthritis (axSpA) extramusculoskeletal manifestation. Interleukin (IL)-17 is implicated in its pathogenesis, however, there is conflicting evidence for IL-17A inhibition in uveitis management. We report pooled analyses of uveitis incidence in patients receiving bimekizumab (BKZ), a monoclonal IgG1 antibody that selectively inhibits IL-17F in addition to IL-17A, from phase 2b/3 trials. METHODS: Data were pooled for patients receiving BKZ 160 mg or placebo in the double-blind treatment period of the phase 3 BE MOBILE 1 (NCT03928704; non-radiographic axSpA) and BE MOBILE 2 (NCT03928743; radiographic axSpA) trials. Data were separately pooled for patients treated with at least one BKZ dose in the BE MOBILE trials and their ongoing open-label extension (OLE; NCT04436640), and the phase 2b BE AGILE trial (NCT02963506; radiographic axSpA) and its ongoing OLE (NCT03355573). Uveitis rates and exposure-adjusted incidence rates (EAIR)/100 patient-years (PYs) are reported. RESULTS: In the BE MOBILE 1 and 2 double-blind treatment period, 0.6% (2/349) of patients receiving BKZ experienced uveitis vs 4.6% (11/237) receiving placebo (nominal p=0.001; EAIR (95% CI): 1.8/100 PYs (0.2 to 6.7) vs 15.4/100 PYs (95% CI 7.7 to 27.5)). In patients with history of uveitis, EAIR was lower in patients receiving BKZ (6.2/100 PYs (95% CI 0.2 to 34.8); 1.9%) vs placebo (70.4/100 PYs (95% CI 32.2 to 133.7); 20.0%; nominal p=0.004). In the phase 2b/3 pool (N=848; BKZ exposure: 2034.4 PYs), EAIR remained low (1.2/100 PYs (95% CI 0.8 to 1.8)). CONCLUSIONS: Bimekizumab, a dual-IL-17A/F inhibitor, may confer protective effects for uveitis in patients with axSpA.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.011 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".