Matching-Adjusted Indirect Comparison of the 52-Week Efficacy of Bimekizumab Versus Secukinumab and Ixekizumab for the Treatment of Radiographic Axial Spondyloarthritis
Bibliographic record
Abstract
INTRODUCTION: A previous network meta-analysis established 16-week relative efficacy with bimekizumab, an inhibitor of interleukin (IL)-17F in addition to IL-17A, versus other treatments for patients with radiographic axial spondyloarthritis (r-axSpA; i.e., ankylosing spondylitis), including the IL-17A inhibitors secukinumab and ixekizumab. This matching-adjusted indirect comparison (MAIC) assessed 52-week relative efficacy of bimekizumab versus secukinumab and ixekizumab. METHODS: Individual patient data from BE MOBILE 2 (bimekizumab 160 mg; N = 220) were matched to pooled summary data from MEASURE 1/2/3/4 (secukinumab 150 mg), MEASURE 3 (secukinumab 300 mg; escalated dose for inadequate responders), COAST-V (ixekizumab) and COAST-V/-W (ixekizumab). BE MOBILE 2 patients were reweighted using propensity score weights based on age, sex, ethnicity, tumor necrosis factor inhibitor (TNFi) exposure, weight, baseline ASDAS and BASFI (secukinumab) and baseline BASDAI (ixekizumab), and 52-week efficacy outcomes from the trial recalculated. Odds ratios (OR) or mean difference for unanchored comparisons are reported with 95% confidence intervals (CI). RESULTS: At week 52, MAIC demonstrated that patients may have higher likelihood of improvement in key efficacy outcomes with bimekizumab versus secukinumab 150 mg (e.g., ASAS40: [OR (95% CI): 1.48 (1.05, 2.10); p = 0.026]; effective sample size [ESS] = 177). Differences in 52-week efficacy outcomes between bimekizumab and secukinumab 300 mg dose escalation were non-significant (ESS = 120). Bimekizumab versus ixekizumab 80 mg comparisons (COAST-V only; ESS = 84) also suggested that differences were non-significant for most key efficacy outcomes. Other ixekizumab comparisons (COAST-V/-W; ESS = 45) suggested bimekizumab may have higher comparative efficacy for many of the same efficacy outcomes, however ixekizumab analyses were limited by poor population overlap, likely due to the greater proportion of patients with previous TNFi exposure. CONCLUSIONS: Patients treated with bimekizumab may have a higher likelihood of achieving improved longer-term efficacy versus secukinumab 150 mg, suggesting bimekizumab may be a favorable therapeutic option for r-axSpA. Differences in efficacy outcomes with bimekizumab versus ixekizumab 80 mg were mostly non-significant, depending on the populations considered.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".