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Record W4405049126 · doi:10.1182/blood-2024-203317

Indolent Lymphoma: Well Tolerated, Fixed Duration Treatment Involving Bendamustine, Rituximab and Acalabrutinib for Front-Line Waldenström's Macroglobulinaemia That Induce Deep Clinical Responses

2024· article· en· W4405049126 on OpenAlexaffabout
Adam Suleman, Kim Roos, Kathryn Mangoff, Yidi Jiang, Gail Klein, Rebecca F. McClure, Nicholas Forward, Mona Shafey, Anna Nikonova, Michaël Sébag, David Macdonald, Diego Villa, Irwindeep Sandhu, Mohammed A. Aljama, Jean-François Larouche, Heidi Simmons, Monica Gallucci, George Tomlinson, Neil L. Berinstein

Bibliographic record

VenueBlood · 2024
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsUniversité LavalSpinal Cord Injury BCUniversity Health NetworkOttawa HospitalConcordia UniversityMcGill University Health CentreMcGill UniversityUniversity of CalgaryUniversity of TorontoHealth Sciences NorthJuravinski Cancer CentreSunnybrook Health Science CentreQueen Elizabeth II Health Sciences Centre
Fundersnot available
KeywordsBendamustineMedicineRituximabIbrutinibLymphoplasmacytic LymphomaInternal medicineLymphomaOncologyWaldenstrom macroglobulinemiaChronic lymphocytic leukemiaLeukemia

Abstract

fetched live from OpenAlex

Background: Waldenström's macroglobulinaemia (WM) is an uncommon lymphoproliferative disorder. An optimal first-line therapy for WM has not been defined. We postulated that combining bendamustine and rituximab (BR) with the second generation covalent BTK inhibitor Acalabrutinib would result in deeper responses as measured by complete response (CR) and very good partial response (VGPR) rates, and provide a longer duration of response. Objectives: The primary objective of this trial is to document the CR and VGPR rates. Methods: The BRAWM clinical trial (NCT04624906) combines BR with acalabrutinib in a one-year, fixed duration treatment course of six 28-day cycles BR and 365 days of concurrent acalabrutinib. This ongoing trial is taking place at 9 clinical sites across Canada. The Intent to Treat (ITT) population includes all participants who have started treatment and were evaluable for safety. Participants who reached cycle 7 were evaluable for response. The sample size was calculated to be able to detect a CR + VGPR rate whose lower level of confidence is greater that the historically defined CR + VGPR rates of 23%. Clinical responses were defined using 6th IWWM. Minimal residual disease (MRD) negativity, assessed with clonoSEQ assay, was a secondary endpoint. Mutational analysis of screening biopsy samples from participants with adequate sample for assessment (n=56), showed 50 with MYD88 L265P mutation, 16 with a CXCR4 mutation of which 8 were S338fs, and 1 with a TP53 l195T mutation. Preliminary minimal residual disease (MRD) analysis of peripheral blood (PB) and bone marrow (BM), using next generation sequencing with a sensitivity of 10-6, shows that most evaluable participants (those with MRD samples at two or more time-points) have become MRD negative in PB, with increasing rates of BM MRD negativity over time. From baseline screening levels, there was a median log reduction in the PB of 4.42 (IQR 1.32) by cycle 7, 4.11 (IQR 1.25) by cycle 12, and 4.06 (IQR 0.81) by month 18. Uni- and multi-variate analyses of clinical variables that may be associated with clinical and MRD outcomes are underway. Conclusions: Bendamustine, rituximab and acalabrutinib front-line therapy for WM is safe and well tolerated in a relatively elderly population with a toxicity profile consistent with the utilized drugs and not greater than that seen with BR and Placebo in the randomized ECHO trial in untreated Mantle Cell Lymphoma. Initial clinical results show that this treatment is associated with a very high proportion of CR + VGPRs as well as MRD negativity.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.067
GPT teacher head0.366
Teacher spread0.299 · 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 designObservational
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

Citations1
Published2024
Admission routes2
Has abstractyes

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