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ABSTRACT
Background: A randomized phase III trial of sorafenib vs. placebo in hepatocellular carcinoma (HCC) demonstrated that sorafenib significantly prolonged overall survival (OS) compared to placebo.
Research design and methods: A Markov model was developed to evaluate the cost-effectiveness of sorafenib vs. best supportive care (BSC) in HCC from the perspective of the Canadian provincial Ministry of Health. The model followed survival and time to progression (TTP) in monthly cycles based on the extrapolation of patient level trial data. Health effects were expressed as life-years gained (LYG). Resource use included drugs, physician visits, laboratory tests, scans, and hospitalizations. Unit costs were gathered from public sources and were expressed in 2007 Canadian Dollars. Costs and effects were evaluated over a lifetime and discounted at 5%. Results were presented as mean ± standard deviation. Deterministic and probabilistic sensitivity analyses were conducted.
Results: LYG was longer for sorafenib (1.52 ± 0.16 vs. 1.03 ± 0.09 LYG/patient for sorafenib and BSC, respectively). The lifetime total costs were $47 511 ± 3 656 for sorafenib and $10 376 ± 1 649 for BSC, resulting in an incremental cost–effectiveness ratio (ICER) of $75 821/LYG, and deterministic ICER of $75 759/LYG. The results were most sensitive to OS, TTP and BSC costs after progression. Sensitivity analyses results showed that the model was robust.
Conclusions: The economic evaluation indicates that sorafenib is cost-effective as compared to BSC in HCC. Limitations include multiple data sources, use of expert opinion for resource use, and the lack of utility data.
Acknowledgements
Declaration of interest: This study was supported by a grant from Bayer HealthCare Pharmaceuticals. S. S. and H. M. are directly employed by Bayer Healthcare Pharmaceuticals. J. K. and J. M. have received unrestricted research grants from Bayer Healthcare; however, neither has received an honorarium to author this manuscript. N. M., S. C. and P. D. are employees of United BioSource Corporation. As a research organization, United BioSource constructed the original model upon which this article is based. United BioSource Corporation has undertaken similar projects for other pharmaceutical companies.
The authors would like to acknowledge the help of Edit Remak, Noemi Kreif and Agnes Benedict from United BioSource Corporation in developing the model and in the statistical analysis.