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Record W4411395227 · doi:10.1016/j.ard.2025.06.275

POS0920 BIMEKIZUMAB DEMONSTRATES COMPARABLE ONE-YEAR EFFICACY IN MALE AND FEMALE PATIENTS WITH AXIAL SPONDYLOARTHRITIS: RESULTS FROM TWO PHASE 3 STUDIES

2025· article· en· W4411395227 on OpenAlexaff
Martín Rudwaleit, S. Ramiro, Denis Poddubnyy, M. Magrey, Irene van der Horst‐Bruinsma, Atul Deodhar, V. Taieb, D. Voiniciuc, Natasha de Peyrecave, Lianne S. Gensler

Bibliographic record

VenueAnnals of the Rheumatic Diseases · 2025
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineAxial spondyloarthritisPhase (matter)Internal medicinePhysical therapyFamily medicineAnkylosing spondylitisSacroiliitis

Abstract

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Background: Bimekizumab (BKZ) is a monoclonal IgG1 antibody that selectively inhibits interleukin (IL)-17F in addition to IL-17A. BKZ has demonstrated sustained efficacy to Week 52 in patients with non-radiographic (nr-) and radiographic (r-)axial spondyloarthritis (axSpA) in the phase 3 studies BE MOBILE 1 and 2.[1,2] Studies have shown that male and female patients with axSpA can experience different disease manifestations, clinical burden and treatment efficacy. For example, female patients typically have delayed diagnosis and higher disease burden but less radiographic progression.[3] Objectives: To assess the efficacy of BKZ treatment to Week 52 in patients across the full disease spectrum of axSpA, focusing on potential sex-based differences in treatment response. Methods: BE MOBILE 1 (NCT03928704) and BE MOBILE 2 (NCT03928743) both comprised a 16-week double-blind period followed by a 36-week maintenance period. In both studies, patients were randomised to receive subcutaneous BKZ 160 mg every 4 weeks (Q4W) or placebo (PBO); from Week 16, all patients received BKZ 160 mg Q4W. We report efficacy outcomes from the BE MOBILE studies to Week 52, stratified by sex. Outcomes reported include ASAS40, ASDAS <2.1, BASDAI, Ankylosing Spondylitis Quality of Life Questionnaire (ASQoL) and objective signs of inflammation (OSI; MRI SPARCC SIJ, MRI Berlin spine and hs-CRP). Binary endpoints are presented using non-responder imputation and continuous outcomes are reported using multiple imputation; OSI measures are reported using observed case. To compare BKZ vs PBO efficacy (treatment effect) between male vs female patients at Week 16, adjusted relative odds ratios (rOR) and relative differences (RD) were calculated using logistic regression and ANCOVA, respectively. All rOR and RD analyses were adjusted for region, age, HLA-B27 status and, for the continuous endpoints, their baseline values. Additionally, in patients with nr-axSpA, analyses were adjusted for MRI/CRP classification and, in patients with r-axSpA, for prior TNF inhibitor exposure and hs-CRP. Since all analyses were post-hoc, no formal p values are provided. Results: 254 patients with nr-axSpA were randomized in BE MOBILE 1 and 332 patients with r-axSpA were randomized in BE MOBILE 2; of these, 220/254 (male: 124/138 [89.9%]; female: 96/116 [82.8%]) and 298/332 (male: 215/240 [89.6%]; female: 83/92 [90.2%]) completed to Week 52. Key baseline differences between males and females included longer mean symptom duration (years) in females ( nr-axSpA : 7.2 vs 11.1; r-axSpA : 12.9 vs 15.0) and lower HLA-B27 positivity (%) in females ( nr-axSpA : 84.8 vs 69.0; r-axSpA : 88.3 vs 78.3). Across BKZ and PBO-randomised patients, males had lower mean ASQoL scores vs females ( nr-axSpA: BKZ: 8.5 vs 10.8, PBO: 8.6 vs 10.2; r-axSpA: BKZ: 8.3 vs 11.1, PBO: 8.4 vs 9.0), and generally had higher OSI values at baseline. Across ASAS40, ASDAS <2.1 and BASDAI, there was a pattern of higher BKZ vs PBO treatment effect in males vs females at Week 16, which was reflected in the rORs and RDs at this timepoint (Figure 1). At Week 52, response rates were higher in males vs females with nr-axSpA but comparable in patients with r-axSpA. Overall, at Week 52 both males and females responded well in both trials, with >50% of BKZ-randomized patients achieving ASAS40 ( nr-axSpA : 64.4 vs 56.4; r-axSpA: 59.4 vs 55.7), and >40% achieving ASDAS <2.1 ( nr-axSpA: 72.0 vs 47.4; r-axSpA: 57.7 vs 55.8). BKZ-randomised males and females also showed good overall response in mean improvements in BASDAI scores at Week 52 ( nr-axSpA: −4.0 vs −3.6; r-axSpA: −3.6 vs −3.4; Figure 1). For ASQoL, both males and females demonstrated substantial improvements with BKZ treatment at Week 16 ( nr-axSpA : −5.5 vs −4.8; r-axSpA : −4.8 vs −5.5) compared with PBO treatment ( nr-axSpA : −2.1 vs −2.9; r-axSpA : −3.1 vs −3.7). Improvements continued to Week 52 with BKZ treatment ( nr-axSpA: BKZ: −5.7 vs −6.2, PBO/BKZ: −5.5 vs −5.1; r-axSpA: BKZ: −5.4 vs −6.5, PBO/BKZ: −5.5 vs −5.8). For change from baseline in OSI outcomes, RDs generally indicated a higher BKZ vs PBO treatment effect in males vs females at Week 16 (Figure 2). However, absolute OSI values in males and females were generally comparable at Week 16, with values maintained or improved to Week 52 with BKZ treatment (Figure 2). Conclusion: The treatment effect of BKZ vs PBO at Week 16 tended to be higher among male patients with axSpA compared to their female counterparts. However, at Week 52 female patients showed marked improvement in longer-term treatment response to BKZ, with efficacy comparable to those seen in male patients at this timepoint. Overall, the efficacy of BKZ in clinical, patient-reported, and OSI outcomes was demonstrated in both male and female patients across the full disease spectrum of axSpA. REFERENCES: [1] van der Heijde D. Ann Rheum Dis 2023;82(4):515–26. [2] Baraliakos X. Ann Rheum Dis 2024;83(2):199–213. [3] van der Horst-Bruinsma. Ann Rheum Dis 2013;72(7):1221–4. Acknowledgements: Funded by UCB. Medical writing support provided by Costello Medical and funded by UCB. Disclosure of Interests: Martin Rudwaleit Speakers bureau from AbbVie, Boehringer Ingelheim, Chugai, Eli Lilly, Janssen, Novartis, Pfizer and UCB, Consultant of AbbVie, Eli Lilly, Novartis and UCB, Sofia Ramiro Consultant for AbbVie, Eli Lilly, Galapagos/Alfasigma, Janssen, Novartis, Pfizer, Sanofi and UCB, Grants from AbbVie, Galapagos/Alfasigma, MSD, Novartis, Pfizer and UCB, Denis Poddubnyy Speaker for AbbVie, BMS, Eli Lilly, MSD, Novartis, Pfizer and UCB, Consultant for AbbVie, Biocad, Eli Lilly, Gilead, GSK, MSD, Moonlake, Novartis, Pfizer, Samsung Bioepis and UCB, Grant/research support from AbbVie, Lilly, MSD, Novartis and Pfizer, Marina Magrey Consultancy fees from AbbVie, BMS, Eli Lilly, Novartis, Pfizer and UCB, Research grants from AbbVie, BMS and UCB, Irene van der Horst-Bruinsma Fees received for Lectures from AbbVie, BMS, MSD and Pfizer, Consultant for AbbVie, Eli Lilly, MSD, Novartis and UCB, Unrestricted Grants received for investigator-initiated studies from AbbVie, MSD, Pfizer and UCB, Atul Deodhar Speaker for Eli Lilly, J&J, Novartis, Pfizer and UCB, Consultant for BMS, Eli Lilly, J&J, MoonLake, Novartis, Pfizer and UCB, Grant/research support from BMS, Eli Lilly, J&J, Novartis, Pfizer and UCB, Vanessa Taieb Shareholder of UCB, Employee of UCB, Diana Voiniciuc Contractor for UCB and employee of Veramed, Natasha de Peyrecave Employee of UCB, Lianne S Gensler Consulting fees from Acelyrin, Eli Lilly, Janssen, Novartis, Pfizer and UCB, Grants from UCB paid to institution. © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.043
GPT teacher head0.340
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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