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P897: UPDATED RESULTS FROM THE ONGOING PHASE 1 STUDY OF ELRANATAMAB, A BCMA TARGETED T-CELL REDIRECTING IMMUNOTHERAPY, FOR PATIENTS WITH RELAPSED OR REFRACTORY MULTIPLE MYELOMA

2022· article· en· W4283376400 on OpenAlexaff
Andrew Dalovisio, Nizar J. Bahlis, Noopur Raje, Caitlin Costello, Bhagirathbhai Dholaria, Melhem Solh, Moshe Levy, Michael H. Tomasson, H. Dube, M. Damore, Sibo Jiang, Cynthia Basu, Athanasia Skoura, Edward M. Chan, S. Trudel, A. Jakubowiak, M. Chu, Cristina Gasparetto, Michaël Sébag, Alexander M. Lesokhin

Bibliographic record

VenueHemaSphere · 2022
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkMcGill University Health CentreUniversity of CalgaryInstitute of Cancer Research
Fundersnot available
KeywordsMedicineMultiple myelomaInternal medicineCytokine release syndromeAdverse effectCommon Terminology Criteria for Adverse EventsMinimal residual diseaseOncologyTransplantationImmunologyGastroenterologyImmunotherapyCancerChimeric antigen receptorBone marrow

Abstract

fetched live from OpenAlex

Background: Elranatamab (PF-06863135), a bispecific molecule that engages B-cell maturation antigen (BCMA) on multiple myeloma (MM) and CD3 on T-cells, induces targeted proliferation and activation of T cells to redirect the immune response against MM. Aims: The Phase 1 study, MagnetisMM-1 (NCT03269136), aims to characterize the safety, pharmacokinetics (PK), pharmacodynamics and efficacy of elranatamab as a single agent or in combination with immunomodulatory agents for patients (pts) with relapsed or refractory MM. Methods: After informed consent, elranatamab was given subcutaneously weekly or every 2 weeks (Q2W) at doses from 80 to 1000µg/kg. A subset of pts received a single priming dose (600µg/kg or 44mg equivalent) followed 1 week later by the recommended Phase 2 dose (RP2D; 1000µg/kg or 76mg equivalent) thereafter. 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. PK, cytokine and soluble BCMA profiling, and lymphocyte subset analyses were performed. Response was evaluated by International Myeloma Working Group (IMWG) criteria. Minimal residual disease (MRD) was assessed by next generation sequencing at a sensitivity of 1×10-5 in accordance with IMWG criteria. Results: A total of 55 pts received elranatamab monotherapy at doses ≥215µg/kg as of 1-Nov-2021. Median age was 64 years (range 42-80), 27% of pts were Black/African American or Asian, and 27% had high risk cytogenetics at baseline. Median number of prior lines of therapy was 6 (range 2-15), 91% were triple-class refractory, 22% received prior BCMA-targeted therapy, and 56% had prior stem cell transplant. The most common TEAEs (all causality) were CRS, neutropenia, anemia, injection site reaction, and lymphopenia. With a single priming dose and premedication, the incidence of CRS at the RP2D was 67% and divided equally between Grade 1 and 2, with no events greater than Grade 2. PK exposure was dose dependent, and elranatamab 1000µg/kg Q2W achieved exposure associated with anti-myeloma activity. Elranatamab therapy induced peripheral T-cell proliferation with a median time to response of 36 days (range 7-73), and the level of soluble BCMA decreased with disease response. With a median follow up of 8.1 months (range 0.3-21) and including only IMWG confirmed responses, overall response rate (ORR) was 64% (95% CI 50-75%), and 31% of pts achieved complete response or better. For responders (n=35), the probability of being event free at 6 months was 91% (95% CI 73-97%). Single-agent elranatamab induced durable clinical and molecular responses, and updated results including serial MRD assessment will be presented. Summary/Conclusion: Elranatamab demonstrates a manageable safety profile and achieves durable clinical and molecular responses for pts with relapsed or refractory MM.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.933

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.292
Teacher spread0.268 · 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 designRandomized trial
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".

Quick stats

Citations5
Published2022
Admission routes1
Has abstractyes

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