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Record W4252862210 · doi:10.1182/blood-2019-124217

Bendamustine and Rituximab As Induction Therapy in Both Transplant Eligible and Ineligible Patients with Mantle Cell Lymphoma

2019· article· en· W4252862210 on OpenAlexaff
Diego Villa, Laurie H. Sehn, Kerry J. Savage, Cynthia L. Toze, Kevin Song, Wendie L den Brok, Ciara L. Freeman, David W. Scott, Alina S. Gerrie

Bibliographic record

VenueBlood · 2019
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsLeukemia & Lymphoma Society of CanadaUniversity of British ColumbiaSpinal Cord Injury BC
Fundersnot available
KeywordsBendamustineMedicineRituximabMantle cell lymphomaInternal medicineRegimenOncologyTransplantationChemotherapy regimenMaintenance therapySurgeryCancerLymphomaChemotherapy

Abstract

fetched live from OpenAlex

Background Mantle cell lymphoma (MCL) is an incurable B-cell non-Hodgkin lymphoma associated with poor outcomes. First-line treatment incorporates cytotoxic chemotherapy and rituximab, but there is no single standard of care regimen. In British Columbia (BC), between January 2003 and May 2013, R-CHOP was the preferred induction regimen. Based on results from the STIL-1 trial (Rummel et al, Lancet 2013) demonstrating improved CR rate and prolonged progression-free survival (PFS) of bendamustine and rituximab (BR) compared with R-CHOP, in June 2013, BR became the standard first-line therapy for all patients with MCL regardless of age. In both eras, fit patients generally ≤65 years of age responding to induction were eligible for high-dose BEAM and autologous stem cell transplantation (ASCT). Maintenance rituximab (MR) has been offered to responding patients post ASCT since 2004 and for transplant ineligible patients since 2012. The aim of this study was to assess the efficacy of BR as an induction regimen for MCL. Methods Patients with MCL treated with first-line BR were identified in the BC Cancer clinical and pathology databases as well as the Leukemia/BMT Program of BC transplant database. BR was initiated no later than December 2018. Treatment received was verified using the BC Cancer Provincial Pharmacy database, and clinical characteristics were verified using the BC Cancer Information System. Radiotherapy for localized disease, splenectomy, or a period of observation prior to systemic therapy were permitted. PFS and overall survival (OS) were calculated from the date of initiation of systemic therapy. In the subgroup of patients ≤65 years of age, results were compared to a historical cohort uniformly treated with R-CHOP. Baseline and treatment characteristics associated with PFS or OS (p<0.05) as well as the treatment variable (BR vs. R-CHOP) were included in Cox regression multivariate models using a backward likelihood ratio approach. Results A total of 190 BR-treated patients were identified. Table 1 shows clinical and treatment characteristics. Excluding 4 patients with an unknown response to BR, 101 (54%) patients achieved a complete response and 62 (33%) a partial response, for an 87% overall response rate. 23 (12%) patients progressed during or within 3 months after BR, and all had highly proliferative MCL (Ki-67 ≥30%) or blastoid/pleomorphic histology. Among the 89 BR-treated patients ≤65 years of age, 60 (67%) underwent ASCT and 29 (33%) did not (10 PD, 10 patient preference, 7 comorbidities, 2 pending). Among the 101 patients >65 years old, 9 underwent ASCT (age 66-71) and 92 did not. 63/69 patients received MR after ASCT, and 77/121 received MR after BR (without ASCT). Reasons for not receiving MR (6 after ASCT, 44 after BR) were 25 PD, 10 ASCT/BR toxicity, 7 pending, 3 patient preference, 3 early deaths, 2 physician preference. With a median follow-up of 2.4y (range 0.2 - 6.1) in living patients the 3y OS was 69.5% (95% CI 69.4-70.6) and 3y PFS 62.8% (95% CI 62.4-63.6). Baseline characteristics and outcomes were similar between patients ≤65y treated with BR vs. R-CHOP (Table 1, Figure 1A and 1B). 81/140 (58%) patients treated with R-CHOP underwent ASCT. In the subgroup of patients who underwent ASCT, outcomes calculated from the point of ASCT were not statistically different between BR vs. R-CHOP. In univariate analysis, age >65y, ECOG performance status >1, elevated LDH, blastoid/pleomorphic morphology, no ASCT, and no MR were associated with worse PFS and OS. In multivariate analysis including these variables as well as chemoimmunotherapy regimen, treatment with BR was not associated with PFS or OS. Conclusions In this population-based analysis, BR is an effective induction regimen for both transplant eligible and ineligible patients. ASCT is feasible in patients treated with BR induction. Even though BR was associated with a numerical improvement in PFS compared to R-CHOP in patients ≤65y, differences in PFS and OS were not statistically significant. Longer follow-up is necessary to fully understand the impact of BR in the frontline setting. We observed PD in 12% patients, suggesting that BR may not be an optimal induction regimen across all patients with MCL, particularly in those with aggressive or highly proliferative disease. Disclosures Villa: Roche, Abbvie, Celgene, Seattle Genetics, Lundbeck, AstraZeneca, Nanostring, Janssen, Gilead: Consultancy, Honoraria. Sehn:Morphosys: Consultancy, Honoraria; Kite Pharma: Consultancy, Honoraria; Merck: Consultancy, Honoraria; TG Therapeutics: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Merck: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Acerta: Consultancy, Honoraria; TG Therapeutics: Consultancy, Honoraria; Apobiologix: Consultancy, Honoraria; Janssen-Ortho: Consultancy, Honoraria; Astra Zeneca: Consultancy, Honoraria; F. Hoffmann-La Roche/Genentech: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria; Verastem: Consultancy, Honoraria; Lundbeck: Consultancy, Honoraria; Kite Pharma: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Acerta: Consultancy, Honoraria; F. Hoffmann-La Roche/Genentech: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria; Astra Zeneca: Consultancy, Honoraria; Morphosys: Consultancy, Honoraria; TEVA Pharmaceuticals Industries: Consultancy, Honoraria; TEVA Pharmaceuticals Industries: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Janssen-Ortho: Honoraria; Celgene: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Lundbeck: Consultancy, Honoraria. Savage:BMS, Merck, Novartis, Verastem, Abbvie, Servier, and Seattle Genetics: Consultancy, Honoraria; Seattle Genetics, Inc.: Consultancy, Honoraria, Research Funding. Song:Celgene: Honoraria, Research Funding; Janssen: Honoraria; Takeda: Honoraria; Amgen: Honoraria. Freeman:Seattle Genetics, Janssen, Amgen, Celgene, Abbvie: Consultancy, Honoraria. Scott:Roche/Genentech: Research Funding; Celgene: Consultancy; Janssen: Consultancy, Research Funding; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoSting [Institution], Research Funding. Gerrie:Lundbeck, Seattle Genetics: Consultancy, Honoraria.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.202
Teacher spread0.197 · 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".

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Citations0
Published2019
Admission routes1
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