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Cost-effectiveness analysis of axitinib through a probabilistic decision model
1Open University of Cyprus, Health Care Management Programme , Cyprus , Europe.
Expert Opinion on Pharmacotherapy
|May 12, 2015
Summary
Axitinib is a cost-effective option for second-line renal cell carcinoma treatment compared to sorafenib. Despite higher costs, it offers improved outcomes, with a 69.9% probability of cost-effectiveness at a 100,000 euro threshold.
Area of Science:
- Oncology
- Health Economics
- Pharmacoeconomics
Background:
- The oncology field faces rising demand and expensive new treatments.
- Cost-effectiveness analysis (CEA) is crucial for efficient healthcare decisions.
- CEA guides optimal resource allocation for unmet medical needs.
Purpose of the Study:
- To estimate the cost-effectiveness of axitinib versus sorafenib.
- To evaluate axitinib as a second-line treatment for renal cell carcinoma (RCC).
- To assess the Value of Information (VOI) for decision-making.
Main Methods:
- A comprehensive literature review for evidence synthesis.
- A probabilistic Markov model to simulate disease progression.
- Analysis of incremental cost-effectiveness ratio (ICER) and cost-effectiveness acceptability curves (CEACs).
Main Results:
- Axitinib demonstrated an incremental cost of €87,936 per Quality-Adjusted Life Year (QALY) compared to sorafenib.
- The probability of axitinib being cost-effective was 13% at a €60,000 willingness-to-pay (WTP) threshold.
- At a €100,000 WTP threshold, axitinib's cost-effectiveness probability rose to 69.9%.
Conclusions:
- Uncertainty in CEA results stemmed primarily from product price, utility values, and progression-free survival.
- Axitinib presents a potentially cost-effective therapeutic option for second-line RCC treatment.
- The study highlights the importance of CEA in guiding optimal treatment choices in oncology.
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