Safety and efficacy of elranatamab in combination with iberdomide in patients with relapsed or refractory multiple myeloma: Results from the phase 1b MagnetisMM-30 trial
Bibliographic record
Abstract
Abstract Background Elranatamab (ELRA), a B-cell maturation antigen (BCMA)-CD3 bispecific antibody, induced deep and durable responses with a manageable safety profile in the phase 2 registrational MagnetisMM-3 study (NCT04649359) in patients (pts) with relapsed or refractory multiple myeloma (RRMM) (Prince et al, ASH2024). Among pts with no prior BCMA-directed therapy, the objective response rate (ORR) was 61.0% and 37.4% achieved complete response (CR) or better (median follow-up 33.9 mo estimated by reverse Kaplan-Meier [KM]). Oral iberdomide (IBER) is a novel CELMoD agent that enhances antimyeloma tumoricidal and immunomodulatory activity in pts with RRMM (Lonial et al, Lancet Haematol 2022). MagnetisMM-30 (NCT06215118) is a phase 1b, open-label, multicenter, dose escalation (Part 1) and dose optimization (Part 2) prospective study evaluating the safety, efficacy, and pharmacokinetics (PK) of ELRA + IBER in pts with RRMM. Here we present preliminary data from Part 1 of MagnetisMM-30. Methods Eligible pts were aged ≥18 years with a diagnosis of MM per IMWG criteria, ECOG performance status of 0 or 1, adequate organ and bone marrow function, and disease relapsed or refractory to the last antimyeloma regimen per IMWG criteria. For Part 1, pts received 2 to 4 prior lines of therapy (LOT). All pts must have received ≥2 consecutive cycles of an immunomodulatory drug-containing regimen and ≥2 consecutive cycles of a proteasome inhibitor (PI) or PI-containing regimen. Key exclusion criteria included stem cell transplant ≤12 weeks prior to enrollment; active, uncontrolled infection; prior treatment with BCMA-directed or CD3 redirecting therapy or prior CELMoD agents. Part 1 of MagnetisMM-30 was guided by a Bayesian Optimal Interval Design for dose-escalation. After receiving 2 step-up priming doses of subcutaneous (SC) ELRA (12 mg on day 1 and 32 mg on day 4) and the first full dose of ELRA on day 8 (76 mg), pts received SC ELRA at dose level (DL) 1 or DL2 in 28-day cycles. In DL1, pts received a starting dose of ELRA at 76 mg QW while in DL2, pts received a starting dose of ELRA at 76 mg Q2W. IBER was given daily for 21 days of each cycle (DL-1: 0.75 mg, DL1: 1.0 mg, DL2: 1.3 mg). The primary endpoint of Part 1 was dose-limiting toxicities (DLTs) during the first cycle of treatment. Secondary endpoints included adverse events and laboratory abnormalities, ORR, CR rate, time-to-event outcomes, PK, minimal residual disease negativity rate, and immunogenicity. Results Of the 22 pts in Part 1 (DL1: 13, DL−1: 9), the median age was 68 y (range, 46-83), 10 (45.5%) were male, 4 (18.2%) had extramedullary disease, 9 (40.9%) had high-risk cytogenetics, defined as t(4;14), t(14;16), or del(17p), 1 (4.5%) had R-ISS stage III, and 2 (9.1%) had ≥50% baseline bone marrow plasma cells. Pts had a median of 2.5 prior LOT (range, 2-4), and 11 (50%) had triple-class refractory disease. At data cutoff (June 23, 2025), the median (range) ELRA treatment duration was 3.1 mo (0.5-7.2) overall and 6.1 mo (0.5-7.2) for DL1 and 1.9 mo (1.5-3.3) for DL−1. IBER treatment duration was 2.6 mo (0.1-6.7) overall and 5.7 mo (0.1-6.7) for DL1 and 1.6 mo (0.7-3.0) for DL−1. ELRA + IBER was ongoing in 77.3% (DL1: 8, DL−1: 9) of pts. Four pts had DLTs; 2 in DL1 (1 grade [G]3 anorexia; 1 G4 neutropenia) and 2 in DL−1 (1 G3 febrile neutropenia; 1 G4 neutropenia). Treatment-emergent adverse events (TEAEs) were reported in 100% (G3/4 68.2%) of pts. The most frequent TEAEs (any G ≥45% or G3/4 ≥10%) were cytokine release syndrome (68.2%, all ≤G2), fatigue (63.6%, all ≤G2), neutropenia (59.1%, G3/4 59.1%), diarrhea (45.5%, all ≤G2), anemia (31.8%, G3/4 13.6%), and thrombocytopenia (27.3%, G3/4 13.6%). Infections were reported in 40.9% (G3/4 4.5%) of pts and immune effector cell–associated neurotoxicity syndrome events were reported in 2 pts (9.1%, 1 G1 and 1 G2). At a median follow-up of 6.1 mo (95% CI, 2.8-7.1), estimated by reverse Kaplan-Meier, the unconfirmed ORR was 90.9% (95% CI, 70.8-98.9) in 20/22 pts; 45.5% (10/22) had CR or better and 68.2% (15/22) had very good partial response or better. The confirmed ORR was 77.3% (17/22) with a median time to response of 1.1 mo (range, 0.5-2.4). Conclusions ELRA + IBER demonstrated a favorable safety profile and encouraging efficacy. The study continues enrolling and will explore ELRA + IBER in a larger group of pts with RRMM. Results from a longer follow-up will be presented.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".