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Efficacy and safety of elranatamab in patients with relapsed/refractory multiple myeloma (RRMM) and prior B-cell maturation antigen (BCMA)-directed therapies: A pooled analysis from MagnetisMM studies.

2023· article· en· W4379341611 on OpenAlexaff
Ajay K. Nooka, Alexander M. Lesokhin, Mohamad Mohty, Rubén Niesvizky, Christopher Maisel, Bertrand Arnulf, Sarah Larson, Asya Varshavsky Yanovsky, Xavier Leleu, Lionel Karlin, David H. Vesole, Nizar J. Bahlis, Carlos Fernández de Larrea, Noopur Raje, Eric Leip, Umberto Conte, Mohamed Elmeliegy, Andrea Viqueira, Salomon Manier

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsInstitute of Cancer ResearchUniversity of Calgary
FundersPfizer
KeywordsMedicineInternal medicineRefractory (planetary science)Multiple myelomaAdverse effectSurgeryGastroenterologyOncology

Abstract

fetched live from OpenAlex

8008 Background: Studies in the MagnetisMM program (MM-1, NCT03269136; MM-3, NCT04649359; MM-9, NCT05014412) enrolled pts treated with prior BCMA-directed therapies. A pooled analysis from these studies evaluated the efficacy and safety of elranatamab in pts with RRMM and prior exposure to BCMA-directed therapy. Methods: Eligible pts received at least 1 PI, 1 IMiD, 1 anti-CD38 antibody, and 1 BCMA-directed therapy (ADC and/or CAR-T cells). Pooled analysis included pts in MM-1 (n = 13) who received SC elranatamab 215−1000 µg/kg; MM-3 (n = 64) and MM-9 (n = 9) who received the RP2D, SC 76 mg QW. Efficacy endpoints were assessed by investigator per IMWG criteria. TEAEs were graded by CTCAE (MM-1, v4.03; MM-3 & MM-9, v5.0); CRS and ICANS were graded by ASTCT criteria. Results include data up through ~10 months after last pt initial dose in all pooled studies. Results: In total, 86 pts were included. Median age was 66.0 y (range, 40−84); 47.7% male. At baseline, 69.8% had an ECOG PS ≥1; 24.4% had high risk cytogenetics; 54.7% had extramedullary disease. Pts received a median of 7.0 (3−19) prior lines of therapy, including BCMA-directed ADC (67.4%), CAR T-cells (41.9%), 9.3% received both. 96.5% and 54.7% of pts were triple-class and penta-drug refractory, respectively; among pts who received ADC and CAR-T cells respectively, 79.3% and 27.8% were refractory to ADC and CAR-T cells. After a median follow-up of 10.3 mo (0.3−32.3), median duration of treatment was 3.3 mo (0.03−30.4). At data cut-off, 24.4% of pts remained on treatment; most common reason for permanent treatment discontinuation was progressive disease (44.2%). ORR was 45.3% (95% CI 34.6−56.5), with ≥CR achieved in 17.4% of pts. ORR for pts with prior BCMA-directed ADC and CAR-T cells was 41.4% (95% CI 28.6−55.1) and 52.8% (95% CI 35.5−69.6), respectively. Among responders, median time to objective response was 1.9 mo (0.3−9.3). Median DOR was not reached by 10 mo; the DOR rate at 9 mo was 72.4% (95% CI 54.7−84.2). DOR rate (95% CI) for pts with prior BCMA-directed ADC and CAR-T cells were 67.3% (43.1−83.0) and 78.9% (53.2−91.5) at 9 mo, respectively. Median PFS was 4.8 mo (95% CI 1.9−7.7), and median OS was not reached by 10 mo, with a rate of 60.1% (95% CI 48.9−69.6) at 9 mo. Most common (≥25% of pts) TEAEs were CRS (65.1% [G3 1.2%]), anemia (59.3% [G3/4, 46.5%]), neutropenia (44.2% [G3/4, 40.7%]), thrombocytopenia (40.7% [G3/4, 29.1%]), diarrhea (33.7% [G3/4, 0%], and lymphopenia (32.6% [G3/4, 30.2%]). ICANS was reported in 5.8% (G3, 2.3%) of pts. Conclusions: In pts with RRMM and prior exposure to BCMA-directed therapies, elranatamab was efficacious and well tolerated; no new safety signals were observed vs the BCMA-naïve population. Results support treatment with elranatamab in pts with RRMM post BCMA-directed therapy. Clinical trial information: NCT03269136 , NCT04649359 , NCT05014412 .

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)0.010
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.015
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.057
GPT teacher head0.404
Teacher spread0.347 · 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 designMeta-analysis
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
Published2023
Admission routes1
Has abstractyes

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