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. 2015 Nov 10;33(32):3727-32.
doi: 10.1200/JCO.2015.61.9569. Epub 2015 Aug 24.

Cost-Effectiveness Analysis of Regorafenib for Metastatic Colorectal Cancer

Affiliations

Cost-Effectiveness Analysis of Regorafenib for Metastatic Colorectal Cancer

Daniel A Goldstein et al. J Clin Oncol. .

Abstract

Purpose: Regorafenib is a standard-care option for treatment-refractory metastatic colorectal cancer that increases median overall survival by 6 weeks compared with placebo. Given this small incremental clinical benefit, we evaluated the cost-effectiveness of regorafenib in the third-line setting for patients with metastatic colorectal cancer from the US payer perspective.

Methods: We developed a Markov model to compare the cost and effectiveness of regorafenib with those of placebo in the third-line treatment of metastatic colorectal cancer. Health outcomes were measured in life-years and quality-adjusted life-years (QALYs). Drug costs were based on Medicare reimbursement rates in 2014. Model robustness was addressed in univariable and probabilistic sensitivity analyses.

Results: Regorafenib provided an additional 0.04 QALYs (0.13 life-years) at a cost of $40,000, resulting in an incremental cost-effectiveness ratio of $900,000 per QALY. The incremental cost-effectiveness ratio for regorafenib was > $550,000 per QALY in all of our univariable and probabilistic sensitivity analyses.

Conclusion: Regorafenib provides minimal incremental benefit at high incremental cost per QALY in the third-line management of metastatic colorectal cancer. The cost-effectiveness of regorafenib could be improved by the use of value-based pricing.

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Conflict of interest statement

Authors' disclosures of potential conflicts of interest are found in the article online at www.jco.org. Author contributions are found at the end of this article.

Figures

Fig 1.
Fig 1.
Markov model. mCRC, metastatic colorectal cancer.
Fig 2.
Fig 2.
Univariable sensitivity analyses. QALY, quality-adjusted life-year.
Fig 3.
Fig 3.
Cost-effectiveness acceptability curves. QALY, quality-adjusted life-year.
Fig A1.
Fig A1.
Internal validation of overall survival model.

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