Secondary efficacy subanalysis by histology from the phase III BRIGHT study: First-line bendamustine-rituximab (BR) compared with standard R-CHOP/R-CVP for patients with advanced indolent non-Hodgkin lymphoma (NHL) or mantle cell lymphoma (MCL).
Bibliographic record
Abstract
8537 Background: BR was previously reported to be statistically noninferior to R-CVP/R-CHOP for complete response rate in the treatment of patients with indolent NHL or MCL. Evaluation of time-to-event outcomes is immature. This subanalysis reports response by histology. Methods: Indolent NHL or MCL was histologically confirmed <6 months before study enrollment in patients who were therapy-naïve. Patients were stratified according to predetermined standard treatment (R-CHOP or RECVP) and lymphoma type, then assigned to receive BR (28-day cycles: bendamustine 90 mg/m2 on days 1 and 2, rituximab 375 mg/m2on day 1) or standard treatment (21-day cycles at standard doses) for 6-8 cycles. Responses were assessed by a blinded independent review committee. The primary efficacy measure was noninferiority of BR complete response (CR) rate for evaluable patients with ≥1 postbaseline efficacy assessment. If the noninferiority threshold was met, superiority was assessed. Secondary measures included tolerability. Results: Of 447 patients enrolled in the study, 213 receiving BR and 206 receiving R-CHOP/R-CVP were evaluable with postbaseline data (Table). BR achieved a statistically noninferior CR rate compared with R-CHOP/R-CVP in patients with indolent NHL and MCL. Conclusions: In patients with treatment-naïve indolent NHL and MCL, BR achieved the primary endpoint of noninferior CR rate. Most CR rates were numerically, but not significantly, higher with BR. Small subgroup results should be interpreted with caution. Support: Teva BPP R&D, Inc. Clinical trial information: NCT00877006. [Table: see text]
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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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".