The Economic Impact of Treatment Sequencing in the Management of Chronic Lymphocytic Leukemia in Canada Using Venetoclax Plus Obinutuzumab
Bibliographic record
Abstract
Introduction: In the management of patients with chronic lymphocytic leukemia (CLL), oral targeted therapies (OTT) represent a significant advancement. However, for most Canadian public and private payers, their high cost raises concerns about financial impact & affordability. In part, this burden is associated with new expensive OTT that are used on a continuous basis until disease progression or unacceptable toxicity. The introduction of venetoclax-based combinations administered for a fixed duration offers new options for CLL patients with the potential to achieve long remission with manageable side effects for a limited period, and most importantly time off therapy. From a Canadian healthcare system perspective, fixed treatment duration would have the potential to offer better budget predictability and reduced costs. Venetoclax in combination with obinutuzumab (VO) is a fixed duration treatment (12 months) recently approved in Canada, with the potential to reduce the cost burden of treating CLL. The primary objective of this project was to estimate the total cumulative cost per patient of different treatment sequences for adults with CLL, considering first line (1L) and subsequent treatments, over a 10-year time horizon, from a Canadian healthcare system perspective. A secondary objective was to evaluate the economic impact of introducing sequences of treatment with VO in 1L, compared to other sequences of treatment without VO. Methods: A 10-year partitioned survival model was developed to assess the economic impact of different treatment sequences in CLL. Five health states were included: 1L, second line (2L), third line (3L), supportive care and death. The total number of treatment sequences considered was limited to 100. Key clinical parameters, including progression-free survival and overall survival data, were extracted from pivotal clinical trials of each selected treatment. Analyses were conducted from a Canadian health-care system perspective; accordingly, only direct medical costs were considered, including treatment acquisition costs, administration costs, follow-up and monitoring costs, cost of tumour lysis syndrome prophylaxis, cost of adverse events as well as cost of supportive care. All results were stratified by TP53 aberration. Results: Total 10-year cumulative costs of treatment sequences starting with each 1L treatment are summarized in Table 1. Overall, treatment sequences starting with VO had lower 10-year cumulative costs compared to sequences starting with other novel agents (i.e., ibrutinib [IBRU] or acalabrutinib [ACAL]). Among patients without TP53 aberration, cumulative costs per patient of sequences starting with VO ranged from $327,574 to $418,213, whereas sequences starting with IBRU or ACAL monotherapy ranged from $772,127 to $930,700 [Figure 1]. Similarly, in adults with TP53 aberration, cumulative costs per patient of sequences starting with VO ranged from $500,639 to $536,507, and sequences starting with IBRU or ACAL monotherapy ranged from $770,737 to $862,554. Cumulative costs for treatment sequences were largely determined by the first two lines of treatment. When comparing treatment sequences with the same 1L therapy, sequences with continuous novel therapies in 2L (e.g., ACAL monotherapy) resulted in higher costs compared to sequences with fixed duration (e.g., venetoclax in combination with rituximab). For patients without TP53 aberration, the economic impact of treating all patients with VO led to savings of $169,341 per patient, over 10 years compared to any other 1L treatment, for the Canadian healthcare system. Savings over 10 years were even higher ($293,731) for patients with TP53 aberration. Although TP53 patients are preferably treated with expensive continuous OTT, VO, a fixed duration OTT, also demonstrates a clear and indisputable therapeutic value in this patient population, with a progression-free survival of 40.6% at 60 months; therefore, making VO available to all patients considerably increases cost savings. Conclusions: Treatment sequences starting with VO regimen in 1L resulted in lower costs compared to sequences starting with other novel agents administered until disease progression. These savings are mainly due to substantial reductions in treatment costs associated with a fixed treatment duration. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".