The Effect of Elranatamab on Patient-Reported Outcomes in Patients with Relapsed/Refractory Multiple Myeloma Naïve and Exposed to B-Cell Maturation Antigen (BCMA)-Directed Therapies: Updated Follow-Up from the MagnetisMM-3 Study
Bibliographic record
Abstract
BACKGROUND Elranatamab is a humanized bispecific antibody that targets both B-cell maturation antigen (BCMA)-expressing multiple myeloma (MM) cells and CD3-expressing T cells. Elranatamab is currently approved for the treatment of relapsed/refractory MM (RRMM) in the US, Europe, and several additional countries. The registrational MagnetisMM-3 trial (NCT04649359) is an open-label, multicenter, non-randomized, phase 2 study that evaluated the safety and efficacy of elranatamab monotherapy in patients with RRMM. Patient-reported outcomes (PROs) from the most recent data cut (26 March 2024), which represents more than 28 months of follow-up, are reported here. METHODS MagnetisMM-3 enrolled two cohorts of patients (Cohort A: BCMA-naïve; Cohort B: BCMA-exposed) who were refractory to at least 1 proteasome inhibitor, 1 immunomodulatory drug, and 1 anti-CD38 antibody. Patients received subcutaneous elranatamab 76 mg QW on a 28-day cycle with a 2-step-up priming dose regimen (12 mg and 32 mg) administered during the first week. If a patient received QW elranatamab for at least 6 cycles and achieved an IMWG response category of partial response or better with responses persisting for ≥2 months, then the dose interval was changed from QW to Q2W (eg, beginning on day (D) 1 of cycle (C) 7 [C7D1]) and from Q2W to Q4W after at least 6 Q2W cycles. PROs included the EORTC QLQ-C30, the EORTC MY20, and the EQ-5D-5L generic quality of life (QoL) questionnaire. PROs were assessed on D1 and D15 of the first 3 cycles, D1 of each subsequent cycle through C12, and at D1 of every third cycle afterwards (ie, C15D1, C18D1, etc) with C30D1 being the last cycle included in this analysis. At each visit, PRO assessments were made prior to the administration of elranatamab. Analyses were based on repeated measures longitudinal models. RESULTS 123 and 64 patients were enrolled and treated with elranatamab in Cohort A and B, respectively. The median age was 68.0 and 67.0 years, 55.3% and 46.9% were male, 58.5% and 68.8% were White. At baseline, 25.2% and 20.3% had high risk cytogenetics, 15.4% and 23.4% had R-ISS III, 5.7% and 6.3% had an ECOG performance score of 2, and 31.7% and 57.8% had extramedullary disease. The median number of prior treatment lines was 5.0 (range: 2-22) and 7.5 (3-19). Among patients in Cohort A, a transient worsening in the global health score (QLQ-C30) and the side effects domain (MY20) relative to baseline was observed through C2D15 (least square mean [LSM] change=-5.9 [95%CI: -10.7, -1.1] and 4.3 [1.4, 7.2], respectively); both scores reverted to baseline levels by C3D1 and generally showed (non-significant) improvement from baseline starting at C7D1/C8D1. These levels remained through C30D1 (6.1 [-5.2, 17.4] and -1.8 [-7.6, 4.0]). Significant reductions in pain (QLQ-C30) and disease symptoms (MY20) were observed starting at C4D1 (-6.6 [-12.8, -0.4]) and C5D1 (-6.9 [-10.6, -3.1], respectively) and were largely maintained, though pain scores trended back toward baseline levels at C30D1 (-1.5 [-10.9, 7.9]). Overall QoL (EQ-5D-5L utility scores, using UK preference weights) significantly improved by C11D1 (0.06 [0.02, 0.09]) and this level was maintained through C30D1 (0.07 [-0.03, 0.17]). Cohort B results were largely similar, though, due to small sample sizes, significant differences were less frequent. Only a modest (non-significant) worsening in the global health score was observed with the nadir at C1D15 (-2.0 [-8.0, 4.0]) followed by a (non-significant) improvement relative to baseline by C2D15 (5.2 [-2.6, 13.0]) which was maintained through C30D1 (15.0 [-10.8, 40.8]). A reduction (significant at select time points) of pain and disease symptoms was observed starting at C2D1 (-5.1 [-12.9, 2.8] and -9.9 [-17.4, -2.4], respectively) and generally maintained beyond this point, though small sample sizes (<10) after C12D1 limited interpretability. CONCLUSIONS Despite occasional early transient decreases, the results suggest that subcutaneous 76 mg elranatamab can improve the symptom and overall QoL of patients with RRMM, regardless of prior BCMA-targeted treatment. Improvement in QoL likely reflects the effective disease control with elranatamab monotherapy. For those who remain on treatment, these changes were largely maintained for over two years.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".