MétaCan
Menu
← Retour à la cohorte
Enregistrement W4417009494 · doi:10.1182/blood-2025-4058

Safety and efficacy of elranatamab + nirogacestat in patients with relapsed or refractory multiple myeloma: Results from the Phase 1b MagnetisMM-4 study

2025· article· en· W4417009494 sur OpenAlexaff
Ola Landgren, Suzanne Trudel, Jacalyn Rosenblatt, Arleigh McCurdy, Sumit Madan, Syed Abbas Ali, Nizar J. Bahlis, Eli Gabayan, Robert Vescio, Melissa O’Gorman, Shinta Cheng, Sibo Jiang, Margaret Hoyle, J. Jojo Cheng, Erik Vandendries, Noopur Raje

Notice bibliographique

RevueBlood · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensUniversity of CalgaryOttawa HospitalPrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésRefractory (planetary science)Multiple myelomaPhases of clinical researchBone marrowBortezomibProgressive diseaseLogistic regression

Résumé

récupéré en direct d'OpenAlex

Abstract Background Elranatamab (ELRA) is a bispecific antibody (BsAb) targeting B-cell maturation antigen (BCMA) on myeloma cells and CD3 on T cells. In the phase 2 MagnetisMM-3 study (NCT04649359), ELRA demonstrated deep, durable responses (objective response rate [ORR] 61.0%) with manageable safety in patients (pts) with relapsed or refractory multiple myeloma (RRMM) and no prior BCMA-directed therapy (Lesokhin et al, Nat Med 2023). MagnetisMM-4 (NCT05090566) is a phase 1b/2 umbrella trial evaluating ELRA in combination with other anti-cancer treatments for pts with MM. Gamma-secretase inhibitors (GSIs) block BCMA cleavage, potentially enhancing efficacy of BCMA-directed therapy (Pont et al, Blood 2019). Here, we present phase 1b safety, tolerability, and dose optimization results from MM-4 sub-study A evaluating ELRA plus the GSI nirogacestat (NIRO) in pts with RRMM. Methods Eligible pts (age ≥18 years) for sub-study A had ≥3 prior lines of therapy, RRMM refractory to ≥1 immunomodulatory drug, ≥1 proteasome inhibitor, and ≥1 anti-CD38 antibody, ECOG performance status ≤1, adequate liver, renal and bone marrow function, and no prior BCMA-BsAb treatment. Dose escalation followed a Bayesian logistic regression model. Dose level (DL) 1 pts received a 4-mg ELRA priming dose subcutaneously on day (D) 1, cycle (C) 0, then 4 mg weekly (QW) from C1D1, in 28-day cycles. DL2 pts received 2 step-up priming doses of ELRA 4/8 mg on C0D1/D4, then 12 mg QW from C1D1. DL3 pts received ELRA 12/32 mg on C0D1/D4, then 32 mg QW from C1D1. All DL1-DL3 pts received NIRO 100 mg orally twice daily from C1D1. In DL3A, ELRA dosing matched DL3 but NIRO was reduced to 100 mg once daily (QD). DL4A pts received ELRA 12/32 mg on C0D1/D4, then 76 mg QW from C1D1, with NIRO 100 mg QD. The primary endpoint was dose-limiting toxicities (DLTs) in C0 and C1, approximately 35 days after the initial dose. Secondary endpoints included safety and efficacy measures including ORR and complete response rate (CRR) per IMWG criteria by investigator. Results Pts in DL1 (n=2), DL2 (n=6), DL3 (n=10), DL3A (n=10) and DL4A (n=6) had a median (range) age of 61.0 (59-63), 55.0 (42-67), 68.0 (44-78), 69.5 (59-80), and 67.5 (57-79) years, respectively. Zero, 1 (16.7%), 2 (20.0%), 2 (20.0%), and 0 pts in DL1-DL4A had R-ISS stage III disease; high-risk cytogenetics [any of the following chromosomal abnormalities t(4;14), t(14;16), del(17p)] were present in 0, 2 (33.3%), 5 (50.0%), 3 (30.0%), and 3 (50.0%) pts. Median (range) prior lines of therapy (LOTs) were 5.5 (5-6), 3.5 (3-5), 5.0 (4-12), 5.0 (3-11), and 5.0 (4-8). DLTs were evaluable in 2 (100%), 4 (66.7%), 8 (80.0%), 7 (70.0%) and 5 (83.3%) pts in DL1 to DL4A and 6 DLTs were reported in 2 dose levels. In DL3, DLTs were reported in 4 (50.0%) pts, including 1 pt with grade (G) 3 pneumonia, 2 pts with G3 diarrhea, and 1 pt with G3 fatigue and G4 neutropenia. In DL4A, DLTs were reported in 2 (40.0%) pts (1 pt with G3 diarrhea, 1 pt with G3 decreased appetite and G3 dehydration). The optimal dose level for the combination with no DLT was identified as DL3A (32 mg QW ELRA + 100 mg QD NIRO). At data cutoff (March 14, 2025), the median (range) duration of treatment was 11.1 (11.1-11.1), 19.1 (1.9-161.3), 34.4 (3.7-115.4), 20.4 (5.0-39.3) and 12.8 (5.0-19.0) weeks; ELRA/NIRO treatment was ongoing in 0, 2 (33.3%), 2 (20.0%), 4 (40.0%), and 4 (66.7%) pts from DL1 to DL4A. TEAEs were reported in 100% of pts (G3/4 73.5%). The most frequent TEAEs (any grade ≥40%) were diarrhea (64.7%, G3/4 23.5%), neutropenia (58.8%, G3/4 52.9%), infections (55.9%, G3/4 14.7%), anemia (47.1%, G3/4 29.4%), cytokine release syndrome (47.1%, G3/4 0%), thrombocytopenia (41.2%, G3/4 29.4%), hypokalemia (41.2%, G3/4 23.5%), and nausea (41.2%, G3/4 11.8%). Immune effector cell-associated neurotoxicity syndrome occurred in 5.9% (G1 only) of pts. With a median follow-up of 8.5 (95% CI, 3.8-20.4) months, estimated by reverse Kaplan-Meier, ORR (95% CI) was 61.8% (43.6-77.8) overall; 50.0% (1.3-98.7) for DL1, 50.0% (11.8-88.2) for DL2, 70.0% (34.8-93.3) for DL3, 60.0% (26.2-87.8) for DL3A, and 66.7% (22.3-95.7) for DL4A. CRRs (95% CI) were 0.0% (0.0-84.2), 33.3% (4.3-77.7), 40.0% (12.2-73.8), 30.0% (6.7-65.2), and 16.7% (0.4-64.1), respectively. Conclusions Across 5 evaluated dose levels, the combination of ELRA plus NIRO yielded response rates of 50.0% to 70.0%. These initial results suggest careful evaluation is warranted when combining BCMA-targeted BsAbs with a GSI.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai non randomisé · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,010

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,002
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,014
Tête enseignante GPT0,291
Écart entre enseignants0,276 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeEssai non randomisé
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueBlood→Même sujetMultiple Myeloma Research and Treatments→Travaux en français237 207→