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Record W4411333669 · doi:10.1002/hon.70093_136

136 | MINIMAL RESIDUAL DISEASE WITH BENDAMUSTINE‐RITUXIMAB WITH OR WITHOUT ACALABRUTINIB IN PATIENTS WITH PREVIOUSLY UNTREATED MANTLE CELL LYMPHOMA: RESULTS FROM THE ECHO TRIAL

2025· article· en· W4411333669 on OpenAlexaff
Pier Luigi Zinzani, S. Spurgeon, Miguel Arturo Pavlovsky, Chan Y. Cheah, Diego Villa, S. Luminari, V. Otero, G. De Jesus, Robin Lesley, M. L. Wang

Bibliographic record

VenueHematological Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsUniversity of British Columbia
FundersAstraZeneca
KeywordsBendamustineMantle cell lymphomaRituximabMedicineMinimal residual diseaseOncologyInternal medicineLymphomaCancer researchBone marrow

Abstract

fetched live from OpenAlex

Introduction: The combination of acalabrutinib with bendamustine-rituximab (ABR) significantly improved progression-free survival (PFS) versus placebo with BR (PBR) in the phase 3 ECHO trial (NCT02972840) in older patients (pts) with previously untreated mantle cell lymphoma (MCL) (Wang M, et al. EHA 2024. Abstract #LB3439). Minimal residual disease (MRD) has been shown to be an impactful prognostic factor for outcomes in MCL. Previously presented data from the trial showed that a lower percentage of pts receiving ABR had molecular relapse during the maintenance period than pts receiving PBR (Dreyling M, et al. Blood. 2024;144(Suppl 1):1626). Herein, we examine the association between MRD status and clinical outcomes in the ECHO trial. Methods: Pts aged ≥ 65 years with previously untreated MCL and Eastern Cooperative Oncology Group performance status ≤ 2 were randomly assigned 1:1 to receive ABR or PBR. BR was given for 6 cycles (induction) followed by rituximab maintenance for 2 years in pts achieving a partial or complete response (CR). Acalabrutinib (100 mg twice daily) or placebo was administered until disease progression or unacceptable toxicity. Crossover to acalabrutinib was permitted at disease progression. The primary endpoint was PFS per independent review committee. MRD (10−5) was assessed in peripheral blood every 24 weeks and at CR or progressive disease using the ClonoSEQ assay (Adaptive Biotechnologies). Results: At the February 15, 2024 data cutoff, 266 pts in the ABR arm and 252 pts in the PBR arm were evaluable for MRD (89.0% and 84.3%, respectively). Pts who did not achieve MRD negativity at any time had a median PFS and overall survival (OS) of 13.8 and 22.8 months, respectively, while pts achieving MRD negativity had a median PFS of 66.7 months (hazard ratio [HR] 0.22; p < 0.0001) and median OS was not reached (HR: 0.31; p = 0.00015); pts who did not achieve MRD negativity were 4.5 times more likely to experience disease progression. Pts who became MRD negative at any time also had better outcomes with or without clinical complete response versus those who remained MRD positive (Figure). The probability of maintaining MRD negativity after induction was 2.3-fold greater for pts in the ABR arm (HR: 0.44; p = 0.022). Among all pts, those who maintained MRD negativity after 24 weeks had improved outcomes (median PFS 70.2 months) versus those who converted from MRD negative at 24 weeks to MRD positive during the maintenance period (median PFS 44.2 months; HR: 1.96; p < 0.0001). Conclusions: In the phase 3 ECHO trial, achieving MRD negativity was associated with improved PFS. MRD was a stronger prognostic factor for outcome than clinical response. Continuous therapy with acalabrutinib increased the probability of maintaining MRD negativity after induction, and sustained MRD negativity was associated with improved PFS, suggesting potential benefit of continuous acalabrutinib therapy after chemoimmunotherapy induction. Research funding declaration: Study funded by AstraZeneca. Encore Abstract: EHA 2025 Keywords: non-Hodgkin; combination therapies; ongoing trials Potential sources of conflict of interest: P. L. Zinzani Consultant or advisory role: BMS, Gilead, Roche, Kyowa Kirin, Sobi, Incyte, Novartis, Beigene, Janssen, AbbVie Honoraria: BMS, Gilead, Roche, Kyowa Kirin, Sobi, Incyte, Novartis, Beigene, Janssen, AbbVie S. Spurgeon Consultant or advisory role: Genentech, Janssen, Beigene, ADC Therapeutics Other remuneration: Research Funding: Beigene, Celgene/BMS, Incyte, Janssen, ADC Therapeutics, Shrodinger, Merck, Profound Bio, Gilead, Acutar. Expert Witness: AbbVie M. Pavlovsky Consultant or advisory role: Beigene, AstraZeneca, Ascentage Pharma Honoraria: AbbVie, Janssen, AstraZeneca Educational grants: Sanofi, Roche, AstraZeneca, Beigene C. Y. Cheah Consultant or advisory role: Roche, Janssen, Gilead, AstraZeneca, Lilly, Beigene, Menarini, Dizal, AbbVie, Genmab, Sobi, CRISPR Therapeutics, BMS, Regeneron Honoraria: Roche, Janssen, Gilead, AstraZeneca, Lilly, Beigene, Menarini, Dizal, AbbVie, Genmab, Sobi, CRISPR Therapeutics, BMS, Regeneron Educational grants: Lilly, Beigene Other remuneration: Speaker’s bureau: Janssen, AstraZeneca, Beigene, Genmab, AbbVie, Roche, MSD. Research funding: BMS, Roche, AbbVie D. Villa Consultant or advisory role: AstraZeneca, Janssen, BeiGene, AbbVie, Kite/Gilead, BMS/Celgene, InCyte, Merck, Novartis, Zetagen Honoraria: AstraZeneca, Janssen, BeiGene, AbbVie, Kite/Gilead, BMS/Celgene, InCyte, Merck, Novartis, Zetagen Other remuneration: Research funding (institution): AstraZeneca, Roche S. Luminari Consultant or advisory role: Roche, AstraZeneca, Incyte, Kite, Novartis, BMS, Sobi, Regeneron, AbbVie, Beigene V. Otero Employment or leadership position: AstraZeneca Stock ownership: AstraZeneca G. De Jesus Employment or leadership position: AstraZeneca R. Lesley Employment or leadership position: AstraZeneca Stock ownership: AstraZeneca, Amgen M. L. Wang Consultant or advisory role: Acerta Pharma, AstraZeneca, Bristol Myers Squibb, Boxer Capital, Galapagos NV, Genmab, InnoCare, Janssen, Kite Pharma, Lilly, Merck, PER, Pfizer, Oncternal Honoraria: AstraZeneca, BeiGene, Binaytara Foundation, Bristol Myers Squibb, CAHON, Editorial Medica AWWE SA, East Virtinia Medical School, Instituto Scientifico Romagnolo, Janssen, Kite Pharma, Mayo Clinic, MJH Life Sciences, Merck, MSC National Research Institute of Oncolgy, Pfizer, Physicians Education Resources (PER), Plexus Communications, PromCon S.R.E., Research to Practice, Studio ER Congressi, South African Clinical Hematology Society, Medscape/WebMD, VJHem Other remuneration: Research: AbbVie, Acerta Pharma, AstraZeneca, Bantam Pharma, BeiGene, BioInvent, Celgene, Genmab, Genentech, Innocare, Janssen, Juno Therapeutics, Kite Pharma, Lilly, Loxo Oncology, Molecular Templates, Nurix Therapeutics, Oncternal, Pharmacyclics, Velosbio, Vincerx

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.052
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.311
Teacher spread0.288 · 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 teacher head, 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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Citations1
Published2025
Admission routes1
Has abstractyes

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