MétaCan
Menu
Back to cohort

P939: SYNERGISTIC EFFECTS OF LOW DOSE BELANTAMAB MAFODOTIN IN COMBINATION WITH A GAMMA-SECRETASE INHIBITOR (NIROGACESTAT) IN PATIENTS WITH RELAPSED/REFRACTORY MULTIPLE MYELOMA (RRMM): DREAMM-5 STUDY

2022· article· en· W4283397661 on OpenAlexaff
A. Nooka, Sagar Lonial, Sebastian Grosicki, Marek Hus, Kyungchul Song, Thierry Façon, Natalie S. Callander, V. Ribrag, Katarina Uttervall, Hang Quach, Vladimir Vorobyev, Chang‐Ki Min, Songtao Cheng, L. M. Smith, Jing Yu, Therese Collingwood, Beata Holkova, Brandon E. Kremer, Ira Gupta, PG Richardson, Monique C. Minnema

Bibliographic record

VenueHemaSphere · 2022
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsVancouver General Hospital
Fundersnot available
KeywordsMedicineMultiple myelomaRefractory (planetary science)CohortAdverse effectInternal medicinePharmacologyCombination therapyOncologyGastroenterology

Abstract

fetched live from OpenAlex

Background: Preclinical data demonstrate that nirogacestat, a gamma-secretase inhibitor, may increase cell-surface levels of a B-cell maturation antigen (BCMA) and reduce soluble BCMA levels, which could enhance anti-BCMA agent activity in multiple myeloma. In the DREAMM-5 (NCT04126200) Phase I/II platform trial belantamab mafodotin (belamaf; BLENREP), a BCMA-targeting antibody-drug conjugate, is being evaluated in combination with nirogacestat. Aims: The aim of this study is to determine if the combination can result in similar efficacy and an improved ocular safety profile compared to the currently approved belamaf schedule (single agent dose 2.5 mg/kg Q3W) in patients with RRMM which showed a 31% overall response rate (ORR) and 44.5% Gr3/4 keratopathy (BLENREP US prescribing information). Methods: This cohort within the DREAMM-5 nirogacestat combination sub-study has a sequential dose-exploration (DE) phase evaluating 0.95 mg/kg Q3W belamaf with 100 mg BID nirogacestat continuously, followed by a randomized cohort expansion (CE) comparing the combination to a belamaf 2.5 mg/kg Q3W arm. Results: Preliminary results from the 10 patients in the DE cohort with low-dose belamaf + nirogacestat, are presented in this abstract. Patients had a median (range) of 4.5 (3–10) prior lines of therapy. At time of data cut-off (Nov 15, 2021), patients received a median (range) of 7 cycles (1–26). The ORR was 60% (n=6/10) and 20% (n=2) achieved a very good partial response (Table). The key emergent adverse events (AEs) included ocular events (n=7 [70%]; ≥Grade [Gr] 3, n=2 [20%] of which Gr 3 keratopathy was reported in 1 patient [10%]), diarrhea (n=7 [70%]; Gr3, n=1 [10%]) and hypophosphatemia (n=7 [70%]; Gr3, n=1, [10%]). There were 2 Grade 5 AEs, neither of which were related to study treatment. No patient permanently discontinued study due to treatment related AEs. Image:Summary/Conclusion: Encouraging clinical activity and a manageable safety profile is observed with low dose belamaf (0.95 mg/kg Q3W) + nirogacestat (100 mg BID continuously) in patients with RRMM. This ongoing sub-study is actively recruiting patients and will continue to evaluate belamaf + nirogacestat efficacy and safety. Updated results will be reported at the congress. Funding Statement: GSK (208887); drug linker technology licensed from Seagen Inc.; mAb produced using POTELLIGENT Technology licensed from BioWa. This abstract was previously submitted to the American Society of Clinical Oncology (ASCO) Annual Meeting, June 3–7, 2022, and is submitted on behalf of the original authors with their permission. ©2022 American Society of Clinical Oncology, Inc. Reused with permission. All rights reserved.

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)0.001
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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.007
GPT teacher head0.233
Teacher spread0.226 · 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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueHemaSphereSame topicMultiple Myeloma Research and TreatmentsFrench-language works237,207