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MagnetisMM-30: A phase 1b, open-label study of elranatamab in combination with iberdomide in patients with relapsed or refractory multiple myeloma (RRMM).

2024· article· en· W4399480918 on OpenAlexaff
Alexander M. Lesokhin, Muhammed Saleem Raza, Jorge Acosta‐Reyes, Patrick Muller, Ashleigh O’Connell, Anne Yver, Carolyn Lou, Gregory Finn

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsDr. Everett Chalmers Regional Hospital
Fundersnot available
KeywordsMedicineLenalidomideMultiple myelomaRefractory (planetary science)OncologyInternal medicine

Abstract

fetched live from OpenAlex

TPS7577 Background: Elranatamab (ELRA) is a humanized B-cell maturation antigen (BCMA)–CD3 bispecific antibody (BsAb). Single-agent ELRA induced deep and durable responses with a manageable safety profile in patients (pts) with RRMM enrolled in the phase 2 registrational MagnetisMM-3 study (NCT04649359; Lesokhin et al, Nat Med 2023). Iberdomide (IBER) is a novel CELMoD[TM] agent that induces enhanced antimyeloma tumoricidal and immunomodulatory activity in pts with RRMM (Lonial et al, Lancet Haematol 2022). While IBER in combination with ELRA has not been evaluated clinically, it may provide additional benefit to pts with RRMM based on the mechanisms of action of this novel combination. Methods: MagnetisMM-30 is a phase 1b, open-label, prospective study evaluating the safety, efficacy, and pharmacokinetics of ELRA in combination with IBER in pts with RRMM. The study has 2 parts: Part 1 for dose-escalation and Part 2, randomized for dose optimization. After 2 step-up priming doses of ELRA, pts will receive subcutaneous ELRA weekly with IBER given daily for 21 days of each 28-day cycle. After ≥6 months (cycles) of treatment, pts with a partial response or better for ≥2 months are eligible for reduced dosing frequency of ELRA. Once the 2 combination dose levels (dose levels A and B) are selected from Part 1 as the recommended phase 2 doses for ELRA and IBER, pts in Part 2 will be randomized 1:1 (stratified by the number of prior lines of therapy [LOTs; 1 vs >1]) to dose levels A and B. Key inclusion criteria are pts aged ≥18 years with a MM diagnosis per IMWG criteria, Eastern Cooperative Oncology Group performance status of 0-1, adequate organ and bone marrow function, and disease relapsed or refractory to the last antimyeloma regimen per IMWG response criteria. Pts who received 2-4 or 1-3 prior LOTs, including ≥1 immunomodulatory drug (IMiD) and ≥1 proteasome inhibitor (PI), are eligible for Parts 1 and 2, respectively. All pts must have received ≥2 consecutive cycles of an IMiD-containing regimen and ≥2 consecutive cycles of a PI or PI-containing regimen. Key exclusion criteria are pts with stem cell transplant ≤12 weeks prior to enrollment; active, uncontrolled infection; prior treatment with BCMA-directed or CD3 redirecting therapy or prior CELMoD agents (ie, IBER or mezigdomide). This study is ongoing; Part 1 and Part 2 will enroll approximately 27 and 60 pts, respectively. Study endpoints are listed in the table. Clinical trial information: NCT06215118 . [Table: see text]

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.002

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 head0.131
GPT teacher head0.488
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized 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
Published2024
Admission routes1
Has abstractyes

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