Cost-Effectiveness of Brexucabtagene Autoleucel versus Best Supportive Care for the Treatment of Relapsed/Refractory Mantle Cell Lymphoma following Treatment with a Bruton’s Tyrosine Kinase Inhibitor in Canada
Bibliographic record
Abstract
For patients with Mantle Cell Lymphoma (MCL), there is no recognized standard of care for relapsed/refractory (R/R) disease after treatment with a Bruton's tyrosine kinase inhibitor (BTKi). Brexucabtagene autoleucel (brexu-cel) represents a promising new treatment modality in MCL. We explored whether brexu-cel was cost-effective for the treatment of R/R MCL. We developed a partitioned survival mixture cure approach to model the costs and outcomes over a lifetime horizon. The clinical data were derived from the ZUMA-2 clinical trial. The costs were estimated from the publicly available Canadian databases, published oncology literature, and pan-Canadian Oncology Drug Review economic guidance reports. The health state utilities were sourced from the ibrutinib submission to the National Institute for Health and Care Excellence for R/R MCL and supplemented with values from the published oncology literature. In the base case over a lifetime horizon, brexu-cel generated an incremental 9.56 life-years and an additional 7.03 quality-adjusted life-years compared to BSC, while associated with CAD 621,933 in additional costs. The resultant incremental cost-utility ratio was CAD 88,503 per QALY gained compared with BSC. Based on this analysis, we found brexu-cel to be a cost-effective use of healthcare resources relative to BSC for treatment of adult patients with R/R MCL previously treated with a BTKi in Canada, though additional research is needed to confirm these results using longer follow-up data.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".