Bendamustine and rituximab as induction therapy in both transplant-eligible and -ineligible patients with mantle cell lymphoma
Bibliographic record
Abstract
Rituximab-containing chemotherapy regimens constitute standard first-line therapy for mantle cell lymphoma (MCL). Since June 2013, 190 patients ≥18 years of age with MCL in British Columbia have been treated with bendamustine and rituximab (BR). The overall response rate to BR was 88% (54% complete response). Of these, 61 of 89 patients (69%) aged ≤65 years received autologous stem cell transplantation and 141 of 190 patients (74%) from the entire cohort received maintenance rituximab. Twenty-three patients (12%) had progressive disease, associated with high risk per the Mantle Cell Lymphoma International Prognostic Index (MIPI), Ki-67 ≥50%, and blastoid/pleomorphic histology. Outcomes were compared with a historical cohort of 248 patients treated with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP; January 2003 to May 2013). Treatment with BR was associated with significant improvements in progression-free survival (PFS), but not overall survival (OS), compared with R-CHOP in the whole cohort (3-year PFS, 66% BR vs 51% R-CHOP, P = .003; 3-year OS, 73% BR vs 66% R-CHOP, P = .054) and in those >65 years of age (3-year PFS, 56% BR vs 35% R-CHOP, P = .001; 3-year OS, 64% BR vs 55% R-CHOP, P = .063). Outcomes in transplanted patients were not statistically significantly different compared with R-CHOP (3-year PFS, 85% BR vs 76% R-CHOP, P = .135; 3-year OS, 90% BR vs 88% R-CHOP, P = .305), although in multivariate analyses, treatment with BR was associated with improved PFS (hazard ratio, 0.40 [95% confidence interval, 0.17-0.94]; P = .036) but not OS. BR is an effective first-line option for most patients with MCL, however, outcomes are suboptimal for those with high-risk features and further studies integrating novel agents are warranted.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".