Venetoclax in Combination with Obinutuzumab in Previously Untreated Fit Patients with Chronic Lymphocytic Leukemia: A Canadian Cost-Utility Analysis
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: Chronic lymphocytic leukemia (CLL) is the most common lymphoproliferative disorder diagnosed in Canada and is associated with a significant economic burden. This study evaluates the cost effectiveness of fixed-treatment duration venetoclax plus obinutuzumab (VEN + O) for previously untreated, fit CLL patients in Canada, for whom this therapy is not universally reimbursed provincially. METHODS: A three-state partitioned survival model was developed using data from the CLL13 trial and a Bayesian network meta-analysis. Health states included progression-free, progressed disease, and death. A lifetime horizon (40-year) was used and a 1.5% discount rate was applied to costs and effects. Costs included drug acquisition, administration, monitoring, adverse events, subsequent treatment, and terminal care. Utility values were derived from previous NICE technology appraisals in CLL. Extensive sensitivity and scenario analyses were conducted. RESULTS: VEN + O was associated with lower total costs and higher quality-adjusted life years and thus dominant compared with ibrutinib, zanubrutinib, and fludarabine plus cyclophosphamide plus rituximab. Compared with acalabrutinib and venetoclax plus ibrutinib, the incremental cost-utility ratios (ICURs) were in the south-west quadrant and substantially above a CA$50,000/QALY willingness-to-pay threshold, meaning VEN + O was cost effective versus these comparators. VEN + O was cost effective versus bendamustine plus rituximab. Extensive sensitivity and scenario analyses confirmed the robustness of these results. CONCLUSIONS: This analysis demonstrates that VEN + O, a 12-month fixed duration treatment, is a cost-effective option for previously untreated fit CLL patients in Canada. VEN + O offers potential health benefits and cost savings when compared with relevant comparator treatments.
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".