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Enregistrement W4400982166 · doi:10.1002/hem3.136

Long‐term survival and safety of elranatamab in patients with relapsed or refractory multiple myeloma: Update from the MagnetisMM‐3 study

2024· article· en· W4400982166 sur OpenAlexaff
Michael H. Tomasson, Shinsuke Iida, Rubén Niesvizky, Mohamad Mohty, Nizar J. Bahlis, Joaquín Martínez‐López, Guenther Koehne, Paula Rodríguez‐Otero, H. Miles Prince, Andrea Viqueira, Eric Leip, Umberto Conte, Sharon T. Sullivan, Alexander M. Lesokhin

Notice bibliographique

RevueHemaSphere · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensUniversity of Calgary
Organismes subventionnairesNational Cancer InstitutePfizer
Mots-clésMultiple myelomaTerm (time)Refractory (planetary science)MedicineOncologyInternal medicineBiologyPhysics

Résumé

récupéré en direct d'OpenAlex

Targeting B-cell maturation antigen (BCMA) on myeloma cells has led to improved clinical benefit in heavily pretreated patients with relapsed or refractory multiple myeloma (RRMM), including those patients with triple-class exposed disease.1 Elranatamab, a humanized BCMA-CD3 bispecific antibody, was approved for the treatment of patients with RRMM based on the results from the registrational MagnetisMM-3 study, which enrolled patients previously treated with at least one immunomodulatory drug, one proteasome inhibitor, and one anti-CD38 monoclonal antibody.2, 3 Among BCMA-naive patients (n = 123), treatment with elranatamab led to an objective response rate (ORR) of 61.0%, with 35.0% of patients achieving a complete response (CR) or better.4 After a descriptive median follow-up of 14.7 months (data cutoff approximately 14 months after the last patient's initial dose), the median progression-free survival (PFS) and overall survival (OS) had not been reached, making it difficult to contextualize the survival outcomes in the treatment landscape for RRMM.4 Here, we report updated results, including Kaplan–Meier estimates of PFS and OS after a longer follow-up. As of the data cutoff of March 26, 2024 (approximately 26 months after the last patient's initial dose), with a median follow-up of 28.4 months (95% confidence interval [CI], 28.0–29.0; estimated by reverse Kaplan–Meier), the ORR was 61.0%, with 37.4% of patients achieving CR or better. Among responders, the median duration of response was not yet reached, and the probability of maintaining response at 24 months was 66.9% (95% CI, 54.4–76.7). The median PFS was 17.2 months (95% CI, 9.8–not-estimable [NE]) (Figure 1) and the median OS was 24.6 months (95% CI, 13.4–NE) (Figure 2). No new safety signals emerged with longer follow-up. Hematologic adverse events in ≥25% (any grade, maximum grade 3/4) of the patient population included neutropenia (49.6%, 49.6%), anemia (48.8%, 37.4%), thrombocytopenia (31.7%, 23.6%), and lymphopenia (26.8%, 25.2%). Other adverse events of interest observed in patients included infections (70.7%; 42.3% maximum grade 3/4; 6.5% grade 5), cytokine release syndrome (57.7%; all grade ≤2), and immune effector cell–associated neurotoxicity (4.9%; all grade ≤2). Elranatamab monotherapy continues to improve survival outcomes without new safety signals. Despite the refractory patient population with a high percentage of patients with poor prognostic features in MagnetisMM-3, the median PFS of 17.2 months and the median OS of 24.6 months observed with additional follow-up are promising among bispecific antibodies currently approved for RRMM. In an analysis of MajesTEC-1 with a median follow-up of 23 months, BCMA-naive patients treated with teclistamab had a median PFS of 11.3 months (95% CI, 8.8–16.4) and a median OS of 21.9 months (95% CI, 15.1–NE).5 In the MonumenTAL-1 trial, talquetamab, a bispecific antibody against CD3 and G-protein-coupled receptor, class C, group 5, member D (GPRC5D) showed a median PFS of 7.5 and 11.9 (61% censored) months in the once-weekly and once every 2 weeks dosing cohorts after a median follow-up of 14.9 and 8.6 months, respectively.6 The observed safety profile with elranatamab is consistent with that of teclistamab as well as other BCMA-targeted bispecific antibodies.5, 7-10 In conclusion, extended follow-up from the ongoing phase 2 MagnetisMM-3 trial of elranatamab in BCMA-naive patients with heavily pretreated RRMM demonstrated sustained clinical efficacy and no new safety signals. We wish to thank the patients who participated in the trial and medical staff of participating centers. Medical writing support was provided by William Clafshenkel, PharmD, PhD, of Nucleus Global and was funded by Pfizer. All authors were involved in the trial conception/design or the acquisition, analysis, or interpretation of data. All authors contributed to the drafting of the manuscript and approved the final version. Michael H. Tomasson: consulting or advisory roles for Janssen. Shinsuke Iida: honoraria from Bristol Myers Squibb, Celgene, Janssen, Pfizer, Sanofi, and Takeda; consulting or advisory roles for Janssen, Sanofi, and Takeda; and research funding from AbbVie, Amgen, Bristol Myers Squibb, Caelum Biosciences, Celgene, Daiichi Sankyo, Janssen, Ono, Otsuka, Sanofi, and Takeda. Ruben Niesvizky: consulting or advisory roles for Bristol Myers Squibb, GSK, Janssen, Karyopharm Therapeutics, and Takeda and research funding from Bristol Myers Squibb, GSK, Janssen, Karyopharm Therapeutics, and Takeda. Mohamad Mohty: honoraria from Amgen, Celgene; consulting or advisory roles for Adaptive Biotechnologies, GSK, Jazz Pharmaceuticals, MaaT Pharma, Novartis, Sanofi, and Xenikos; personal fees from Amgen, Astellas, Bristol Myers Squibb, Celgene, Pfizer, Stemline-Menarini and Takeda; and speakers bureau roles for Janssen, Jazz Pharmaceuticals, and Sanofi. Nizar J. Bahlis: honoraria from AbbVie, Amgen, Celgene, Genentech/Roche, GSK, Janssen, Karyopharm Therapeutics, Sanofi, and Takeda; consulting or advisory roles for Amgen, Celgene, Janssen, Karyopharm Therapeutics, Pfizer, Sanofi, and Takeda; personal fees from AbbVie, Amgen, Celgene, Genentech/Roche, GSK, Janssen, Karyopharm Therapeutics, Sanofi, and Takeda; and patents, royalties, and/or other intellectual property interests with Celgene and Janssen. Joaquin Martinez-Lopez: consulting or advisory roles for Bristol Myers Squibb, Janssen, and Novartis; research funding from Astellas and Bristol Myers Squibb; and speakers bureau roles for Bristol Myers Squibb, Janssen-Cilag, and Roche. Paula Rodriguez-Otero: consulting or advisory roles for AbbVie, Bristol Myers Squibb, GSK, Janssen, Pfizer, and Sanofi; personal fees from AbbVie, Celgene, GSK, H3 Biomedicine, Janssen, Pfizer, and Sanofi; travel and accommodations expenses paid by Pfizer; and speakers bureau roles for Bristol Myers Squibb, GSK, Janssen, and Sanofi. Alexander M. Lesokhin: honoraria from iTeos Therapeutics, Janssen, Legend Biotech, Pfizer, Sanofi, and Trillium Therapeutics; consulting or advisory roles for Pfizer, Trillium Therapeutics, and Arcellx; personal fees from iTeos Therapeutics, Janssen, Legend Biotech, Pfizer, Sanofi, and Trillium Therapeutics; research funding from Bristol Myers Squibb, Genentech, Janssen, Pfizer, Sanofi, and Trillium Therapeutics; and patents, royalties and/or other intellectual property interests with Serametrix. Andrea Viqueira, Eric Leip, Umberto Conte, and Sharon T. Sullivan: employment and stock ownership at Pfizer. Guenther Koehne: has no conflicts of interest. This study was conducted in accordance with the International Council for Harmonisation guidelines for Good Clinical Practice and the principles of the Declaration of Helsinki. The study protocol was approved by local or independent institutional review boards or ethics committees at participating sites. This study was funded by Pfizer. Upon request, and subject to review, Pfizer will provide the data that support the findings of this study. Subject to certain criteria, conditions, and exceptions, Pfizer may also provide access to the related individual de-identified patient data. See https://www.pfizer.com/science/clinical-trials/trial-data-and-results for more information.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,038
Score d'incertitude au seuil0,964

Scores Codex et Gemma par catégorie

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

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 Opus0,017
Tête enseignante GPT0,275
Écart entre enseignants0,258 · 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 tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
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

Citations61
Publié2024
Routes d'admission1
Résumé présentoui

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