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Record W4405044954 · doi:10.1182/blood-2024-205608

Phase 3 Study of Teclistamab (Tec) in Combination with Lenalidomide (Len) and Tec Alone Versus Len Alone in Newly Diagnosed Multiple Myeloma (NDMM) As Maintenance Therapy Following Autologous Stem Cell Transplantation (ASCT): Safety Run-in (SRI) Results from the Majestec-4/EMN30 Trial

2024· article· en· W4405044954 on OpenAlexaff
Elena Zamagni, Tobias Silzle, Ivan Špıčka, Sabrin Tahri, Sarah Lonergan, Inger S. Nijhof, Antonietta Falcone, Evangelos Terpos, Jakub Radocha, Roberto Mina, Güldane Cengiz Seval, Meral Beksaç, Cesar Rodriguez, Marcelo C. Pasquini, Michel Delforge, Vânia Hungria, Donna Reece, Philippe Moreau, Yaël C. Cohen, Kihyun Kım, Dominik Dytfeld, Jiří Minařík, Irene Straßl, Jelena Bila, Martin Schreder, Janusz Krawczyk, Fredrik Schjesvold, Caroline Cicin‐Sain, Christoph Driessen, Gordon Cook, Lugui Qiu, Gonzalo Garate, Agoston Gyula Szabo, Roman Hájek, Marc S. Raab, Silvia Mangiacavalli, Hermann Einsele, Andrew Spencer, Mario Boccadoro, Helen Vassalou, Lixia Pei, Yingqi Shi, Maria Krevvata, Ryan B. Gruber, Caline Sakabedoyan, Margaret M. Cobb, Jagoda Jasielec, Himal Amin, Rachel Kobos, Pieter Sonneveld, Niels W.C.J. van de Donk

Bibliographic record

VenueBlood · 2024
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineTECLenalidomideInternal medicineOncologyMultiple myelomaCohortAutologous stem-cell transplantationSurgery

Abstract

fetched live from OpenAlex

Introduction: Len maintenance after ASCT has significant progression-free and overall survival benefits and is considered standard-of-care for transplant-eligible NDMM. However, patients (pts) eventually relapse, supporting the need for novel maintenance strategies to improve outcomes. Tec, a first-in-class B-cell maturation antigen × CD3 bispecific antibody, demonstrated deep and durable responses in multiple myeloma (MM), leading to its approval for triple-class exposed relapsed and refractory MM. Based on preclinical results, Tec and Len may have synergistic antimyeloma effects. MajesTEC-4/EMN30 is a multicenter, randomized, open-label, Phase 3 study evaluating Tec-Len, Tec, and Len maintenance therapy in NDMM after induction and ASCT, ± consolidation. Here, we report initial SRI results. Methods: Eligible pts were aged ≥18 y, had NDMM (per International Myeloma Working Group [IMWG] criteria), received 4-6 cycles of 3- or 4-drug induction that included a proteasome inhibitor and/or an immunomodulatory drug ± an anti-CD38 antibody and a single or tandem ASCT ± consolidation, and achieved a partial response or better per IMWG 2016 response criteria. Three cohorts at different Tec dose frequencies were evaluated: Cohort 1 (Tec-Len) with Tec dosing at 1.5 mg/kg QW for 2 cycles (C), followed by 3 mg/kg Q2W in C3-6, and 3 mg/kg Q4W in C7+; Cohort 2 (Tec-Len) with Tec dosing at 1.5 mg/kg on Days 8 and 15 in C1, followed by 3 mg/kg Q4W in C2+; and Cohort 3 (Tec) dosing at 1.5 mg/kg on Days 8 and 15 in C1, followed by 3 mg/kg Q4W in C2+. All pts received the same inpatient Tec step-up schedule in C1 (0.06 mg/kg; 0.3 mg/kg). Len 10 mg QD in C2-4 (if tolerated, 15 mg thereafter) was given in Tec-Len cohorts. Treatment duration was 2 y for all pts; in Tec-Len cohorts, Tec was stopped after 13 cycles of treatment if complete response or better (≥CR) was achieved. Adverse events (AEs) were graded per Common Terminology Criteria for Adverse Events v5.0. Cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) were graded per American Society for Transplantation and Cellular Therapy guidelines. Investigator-assessed response was based on IMWG 2016 criteria. Results: Across 3 cohorts, 94 pts were enrolled (Cohort 1, n=32; Cohort 2, n=32; Cohort 3, n=30). At a median follow-up of 14.4, 5.0, and 4.9 mo, 97% of pts in each cohort (n=31, 31, 29, respectively) remained on treatment. Baseline characteristics were generally balanced between cohorts with a median age of 58-59 y. Pts in Cohort 1, 2, and 3 had received a median of 15, 6, and 6 maintenance cycles, respectively. Neutropenia and infections were the most common Grade 3/4 treatment-emergent AEs (TEAEs). Compared with Cohort 1, the cumulative incidence of any grade and Grade 3/4 neutropenia at 4 mo showed a decreased trend in Cohorts 2 and 3 with less frequent Tec dosing (Cohort 1: any grade/Grade 3/4 incidence, 69%/66%; Cohort 2: 44%/41%; Cohort 3: 37%/28%). A similar trend was observed for all grade infections with less frequent Tec dosing (Cohort 1: 78%; Cohort 2: 63%; Cohort 3: 61%). Among 68/94 (72.3%) pts who had any grade hypogammaglobulinemia, 63/68 (92.6%) received ≥1 dose of IVIg. The overall CRS rate was 43.6%, with 6.4% Grade 2 and no high-grade events. The CRS rate following the first treatment dose of Tec (1.5 mg/kg) was low at 7.4%. No ICANS were reported. TEAEs led to treatment discontinuations in 2 pts (1 each in Cohorts 2 and 3) and death in 1 pt (Cohort 2; due to COVID-19 during C1, prior to the start of Len). In Cohort 1, all 28 pts with MRD assessments at 12 mo were in MRD negative CR. Among MRD positive pts at study entry, 10 (100%) converted to MRD negative CR during treatment. Among 16 pts who had Conclusions: Overall, Tec-Len and Tec can be safely administered as maintenance therapy following ASCT in NDMM. Cohorts 2 and 3 showed a trend for improved early safety outcomes with less frequent Tec dosing compared with Cohort 1. Tec-Len demonstrated deepening of responses and 100% MRD negative CR rate at 12 mo in Cohort 1 evaluable pts. These data informed the randomized part of MajesTEC-4/EMN30, which is actively enrolling.

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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.026
GPT teacher head0.299
Teacher spread0.273 · 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 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".

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Citations27
Published2024
Admission routes1
Has abstractyes

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