Cost-Effectiveness of Deferasirox (Exjade®) Versus No Chelation In Patients with Lower Risk Myelodysplastic Syndromes (MDS): A Canadian Perspective
Bibliographic record
Abstract
Abstract Abstract 4962 Introduction: Guidelines for the treatment of MDS recommend iron chelation therapy (ICT) in iron-overloaded lower-risk patients with MDS and candidates for stem cell transplantation. In particular, recent reports indicate that ICT may improve overall survival (OS) in transfusion-dependent patients with low or intermediate-1 (int-1) MDS as per international prognostic scoring system (IPSS) criteria. Deferasirox is a once-daily oral chelator, with easy administration and potentially better compliance. The goal of this study is to evaluate the cost-effectiveness of deferasirox compared to receiving no chelation therapy in transfusion-dependent patients with lower-risk MDS from a Canadian healthcare system perspective. Methods: A Markov model was developed to evaluate the cost-effectiveness of deferasirox compared to receiving no chelation therapy in transfusion-dependent patients with lower-risk (eg, IPSS low or int-1) MDS. The data used in the model were obtained from published or presented studies. Model outcomes, including life years (LY) gained, quality-adjusted life years (QALYs) gained, developing complications of iron overload, progressing to acute myeloid leukemia (AML), death, and direct medical costs of ICT, transfusion, complications and AML, were estimated for each treatment group based on a simulation of 1000 patient lives. Finally, incremental cost-effectiveness ratios (ICER) were calculated as the ratio of total medical costs to LY and QALY gains. Extensive one-way sensitivity analyses were performed to examine the effects of changes in key model parameters. Probabilistic sensitivity analyses were also performed. The outcomes of the model were evaluated over a 20-year time frame and discounted annually at the rate of 5%. Costs are reported in 2009 Canadian dollars (CAD$). Results: Under base case assumptions, patients receiving deferasirox were less likely to progress to cardiac disease, AML, and death compared to patients receiving no chelation therapy. Adding deferasirox was projected to increase OS by 4.46 years (undiscounted); discounting for time, OS was projected to be increased by 2.93 years. Furthermore, undiscounted QALYs were increased by 4.20 years and discounted QALYs, by 2.99 years. The clinical benefits of deferasirox are obtained at an additional expected discounted total lifetime cost of CAD$185,429. The incremental cost-effectiveness ratios were therefore estimated to be CAD$62,001/QALY gained and CAD$63,286/LY saved. Deterministic sensitivity analyses showed the base case results to be robust with respect to variations in assumptions and estimates. The cost-effectiveness acceptability curve shows that deferasirox was preferred to no treatment in 96% of simulations when the willingness to pay for a QALY was CAD$100,000. Conclusion: The results of our analysis indicate that deferasirox offers a cost-effective treatment option for patients with lower-risk MDS as the ICER is within the thresholds that are considered acceptable (ie, $50,000 to $100,000 per QALY gained), from a Canadian healthcare system perspective. Additional clinical studies are ongoing to evaluate event-free survival with deferasirox in patients with lower-risk MDS and transfusional iron overload. Disclosures: El Ouagari: Novartis: Employment. Migliaccio-Walle: Novartis: Research Funding. Lau: Novartis: Employment. Bozkaya: Novartis: Research Funding.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| 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) | 0.005 | 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".