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Efficacy and safety of elranatamab (PF-06863135), a B-cell maturation antigen (BCMA)-CD3 bispecific antibody, in patients with relapsed or refractory multiple myeloma (MM).

2021· article· en· W3168407158 on OpenAlexaff
Nizar J. Bahlis, Noopur Raje, Caitlin Costello, Bhagirathbhai Dholaria, Melhem Solh, Moshe Levy, Michael H. Tomasson, Harman Dube, Feng Liu, Ken Liao, Cynthia Basu, Athanasia Skoura, Edward M. Chan, Suzanne Trudel, Andrzej Jakubowiak, Michael P. Chu, Cristina Gasparetto, Andrew Dalovisio, Michaël Sébag, Alexander M. Lesokhin

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkInstitute of Cancer ResearchMcGill University Health CentreUniversity of Calgary
FundersPfizer
KeywordsMedicineCytokine release syndromeCommon Terminology Criteria for Adverse EventsAdverse effectNeutropeniaInternal medicineMultiple myelomaGastroenterologyAnemiaToxicityChimeric antigen receptorOncologyImmunologyCancerImmunotherapy

Abstract

fetched live from OpenAlex

8006 Background: Elranatamab (PF-06863135) is a humanized bispecific monoclonal antibody (IgG2a) that targets BCMA, a member of the tumor necrosis factor receptor superfamily expressed in MM, and CD3 on T cells. We reported results for intravenous (IV) dosing (Raje et al. Blood. 2019;134(S1):1869) and now update for subcutaneous (SC) dosing from the ongoing Phase 1 study (MagnetisMM-1). Methods: Patients (pts) received elranatamab at 80, 130, 215, 360, 600, and 1000μg/kg SC weekly. A modified toxicity probability interval method was used for escalation, with monitoring for dose-limiting toxicity (DLT) to end of the first cycle. Treatment-emergent adverse events (TEAEs) were graded by Common Terminology Criteria for Adverse Events (v4.03), and cytokine release syndrome (CRS) by American Society for Transplantation and Cellular Therapy criteria (Lee et al. Biol Blood Marrow Transplant. 2019;25:625). Response was assessed by International Myeloma Working Group criteria. Pharmacokinetics, cytokine profiling, and T cell immunophenotyping were performed. Results: 30 pts had received elranatamab as of 4-Aug-2020 at 80 (n = 6), 130 (n = 4), 215 (n = 4), 360 (n = 4), 600 (n = 6), or 1000 (n = 6) μg/kg SC weekly. Pts had a median of 8 prior treatments; 87% had triple refractory disease, 97% had prior anti-CD38 therapy, and 23% had prior BCMA-directed antibody drug conjugate or chimeric antigen receptor T cell therapy. The most common all causality TEAEs included lymphopenia (n = 24, 80%; 20% G3, 60% G4), CRS (n = 22, 73%; none > G2), anemia (n = 17, 57%; 43% G3, 3% G4), injection site reaction (n = 16, 53%; none > G2), thrombocytopenia (n = 16, 53%; 23% G3, 17% G4), and neutropenia (n = 12, 40%; 17% G3, 17% G4). Both CRS and immune effector cell-associated neurotoxicity syndrome (n = 6, 20%) were limited to ≤G2 with median durations of 2 and 1.5 days, respectively. No DLT was observed. Exposure increased with dose, and T max ranged from 3–7 days. Cytokine increases occurred with the first dose, and increased T-cell proliferation was observed in peripheral blood. The overall response rate (ORR) for doses ≥215μg/kg was 75% (n = 15/20) including partial response (PR; n = 6), very good PR (VGPR; n = 3), complete response (CR; n = 1), and stringent CR (sCR; n = 5). Median time to response was 22 days, and 3 of 4 pts (75%) with prior BCMA-directed therapy achieved response (VGPR, n = 2 and sCR, n = 1). Updated data, including duration of response, will be presented. Conclusions: Elranatamab demonstrated a manageable safety profile, and SC doses ≥215μg/kg achieved ORR of 75% with CR/sCR rate of 30%. These results demonstrate the safety and efficacy of SC elranatamab in this relapsed/refractory population and support ongoing development of elranatamab for pts with MM, both as monotherapy and in combination with standard or novel therapies. Clinical trial information: NCT03269136.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.069
GPT teacher head0.427
Teacher spread0.358 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations42
Published2021
Admission routes1
Has abstractyes

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