Venetoclax plus bendamustine-rituximab or bendamustine-obinutuzumab in chronic lymphocytic leukemia: final results of a phase Ib study (GO28440)
Bibliographic record
Abstract
Venetoclax (Ven), an orally administered, potent BCL-2 inhibitor, has demonstrated efficacy in chronic lymphocytic leukaemia (CLL) in combination with rituximab (R) or obinutuzumab (G). Our aim was to investigate the addition of bendamustine (B) to these Ven-containing regimens in relapsed/refractory (R/R) or first-line (1L) CLL. This multi-arm, non-randomized, open-label, phase 1b study was designed to evaluate the maximum tolerated dose (MTD) and safety/tolerability of Ven with BR/BG, with 3+3 dose-escalation followed by safety expansion. Patients received Ven (schedule A) or BR/BG first (schedule B) to compare safety and determine dose/schedule for expansion. Six Ven-BR/-BG cycles were to be administered, then Ven monotherapy until disease progression (R/R) or fixed-duration 1-year treatment (1L). Overall, 33 R/R and 50 1L patients were enrolled. No dose-limiting toxicities were observed (doses 100-400-mg), and the MTD was not reached. Safety was similar between schedules; no tumour lysis syndrome (TLS) occurred during dose-finding. Schedule B and Ven 400-mg were chosen for expansion. The most frequent grade 3-4 toxicity was neutropenia: R/R 64%, 1L Ven-BR 85%, 1L Ven-BG 55%. Grade 3-4 infection rate was: R/R 27%, 1L Ven-BR 0%, 1L Ven-BG 27%. During expansion, one clinical and two laboratory TLS cases occurred. Fewer than half the patients completed six combination therapy cycles with all study drugs; rates of bendamustine discontinuation were high. Overall response rate was 91% in R/R and 100% in 1L patients (16/49 1L patients received Ven for >1 year). In conclusion, addition of bendamustine to Ven-R/-G increased toxicity without apparent efficacy benefit.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".