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Elranatamab, a B-cell maturation antigen (BCMA)-CD3 bispecific antibody, for patients (pts) with relapsed/refractory multiple myeloma (RRMM): Extended follow up and biweekly administration from the MagnetisMM-3 study.

2023· article· en· W4379282038 on OpenAlexaff
Mohamad Mohty, Michael H. Tomasson, Bertrand Arnulf, Nizar J. Bahlis, H. Miles Prince, Rubén Niesvizky, Paula Rodríguez‐Otero, Joaquín Martínez‐López, Guenther Koehne, Yogesh Jethava, Afshin Eli Gabayan, Don A. Stevens, Ajay K. Nooka, Noopur Raje, Shinsuke Iida, Eric Leip, Umberto Conte, Akos Czibere, Andrea Viqueira, Alexander M. Lesokhin

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsInstitute of Cancer ResearchUniversity of Calgary
FundersPfizer
KeywordsMedicineInternal medicineDiscontinuationRefractory (planetary science)Adverse effectGastroenterologySurgery

Abstract

fetched live from OpenAlex

8039 Background: MagnetisMM-3 (NCT04649359) is an open-label, multicenter, registrational phase 2 study evaluating the efficacy and safety of elranatamab monotherapy in pts with RRMM; pts naïve to BCMA-directed therapies were enrolled in Cohort A. Methods: Eligible pts were refractory to at least 1 PI, 1 IMiD, and 1 anti-CD38 antibody. Pts received SC elranatamab in 28-d cycles with step-up doses of 12 mg on C1D1 and 32 mg on C1D4 followed by 76 mg QW beginning C1D8. Pts treated for 6 cycles and achieving partial response (PR) or better with response persisting ≥2 mo were switched to 76 mg Q2W, 46 and 58 pts are included in the Q2W efficacy and safety analyses, respectively. Results: Overall, 123 pts received elranatamab. Median pt age was 68.0 y (range, 36−89), 63.4% of pts had an ECOG PS ≥1 and median prior lines of therapy was 5.0 (2−22); 96.7% and 42.3% of pts were triple-class- and penta-drug refractory, respectively. At data cutoff (~12 mo after last pt initial dose), the median follow up was 12.8 mo (0.2−22.7); 34.1% of pts remained on treatment. Most common reasons for permanent treatment discontinuation were progressive disease (39.0%) and adverse events (AE; 13.8%). Objective response rate per blinded independent central review (BICR) was 61% (95% CI 51.8−69.6), with 39 (31.7%) pts with complete response (CR) or stringent CR (sCR); very good partial response (VGPR) and PR were achieved in 29 (23.6%) and 7 (5.7%) pts, respectively. MRD-negativity (threshold 10–5) was achieved by 92.0% (n = 23/25) of evaluable pts. Median duration of response (mDOR) has not been reached (95% CI 12.9−NE) and DOR at 12 mo was 74.1% (95% CI 60.5−83.6). In pts with CR/sCR or VGPR, mDOR was not reached by 12 mo; in pts with PR, mDOR was 5.2 mo (95% CI 1.6−NE). There were 46 responders by BICR who switched to Q2W dosing ≥24 wk prior to the data cut-off; among these pts, 80.4% maintained/improved their response ≥24 wk after the switch. Median progression-free and overall survival have not been reached by 12 mo, and the respective rates (95% CI) at 12 mo were 57.1% (47.2−65.9) and 62.0% (52.8−70.0). Most common Grade 3/4 treatment emergent AEs were hematologic; Grade 3/4 non-hematologic events reported in ≥5% of pts were COVID-pneumonia (10.6%), hypokalemia (9.8%), pneumonia (7.3%), sepsis (6.5%), hypertension (6.5%), ALT increased (5.7%), and SARS-COV-2 test positive (5.7%). Among pts who switched to Q2W dosing, the incidence of Grade 3/4 AEs decreased by > 10% after the switch. Conclusions: Elranatamab remains efficacious and well tolerated in pts with RRMM after > 1 y of follow-up. Updated analysis with a median follow up of ~15 mo, the longest of all phase 2 BCMA-CD3 bispecific antibody studies, including the outcome of pts who switched to the Q2W dosing, will be presented. These results support continued elranatamab development for pts with MM. Clinical trial information: NCT04649359 .

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)0.001
metaresearch head score (Gemma)0.000
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.092
GPT teacher head0.432
Teacher spread0.339 · 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

Citations14
Published2023
Admission routes1
Has abstractyes

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