Background
B-cell maturation antigen (BCMA) bispecific antibodies have advanced treatment of relapsed/refractory multiple myeloma (RRMM), but comparative data are lacking.
Methods
An unanchored matching-adjusted indirect comparison (MAIC) was conducted between linvoseltamab and teclistamab in triple-class exposed (TCE) RRMM using patient-level data from LINKER-MM1 (117 patients, linvoseltamab 200 mg, data cutoff 1/2024, median follow-up [mFU] 14.3 months) and aggregate data from MajesTEC-1 (165 patients, teclistamab 1.5 mg/kg, data cutoff 2/2022, mFU 14.1 months). Ten LINKER-MM1 patients with prior BCMA antibody-drug conjugate exposure were excluded to match MajesTEC-1 eligibility criteria. LINKER-MM1 patients were weighted to match MajesTEC-1 on 6 prespecified prognostic factors considered most important by an international MM expert panel.
Results
After matching (effective sample size = 83.0), linvoseltamab showed significantly longer progression-free survival (PFS, P = .004), overall survival (OS, P = .039), and time to next treatment (P = .028), and numerically longer duration of response ((P = .100) than teclistamab based on hazard ratios. Linvoseltamab demonstrated numerically higher objective response rate, very good partial response or better, complete response or better (≥CR), and minimal residual disease-negativity (10-5 threshold) rates versus teclistamab based on odds ratios. Additional MAICs matching all prognostic factors available in both trials showed significantly longer PFS (P = .038) and OS (P = .039), significantly higher ≥CR (P = .043), and favorable trends for all other outcomes.
Conclusion
This analysis demonstrated statistically improved PFS and OS and numerically favorable results for all other outcomes for linvoseltamab versus teclistamab in the treatment of TCE RRMM.
Associated People
Mirko Fillbrunn
Dr. Fillbrunn specializes in health economics and outcomes research (HEOR), biostatistics, and epidemiology. His expertise includes strategically developing and guiding the implementation of analytics throughout the entire product life cycle, including analyses of clinical trials and real-world health care data such as insurance claims, electronic health records, medical charts, and surveys. Dr. Fillbrunn’s contributions have informed clinical regulators and health care payers in both the US and global markets. His research has been published in several peer-reviewed journals and presented at clinical and health economic conferences. Prior to joining Analysis Group, Dr. Fillbrunn was a postdoctoral fellow at Harvard Medical School and Massachusetts General Hospital.