Background and objective: A key reason of high mortality of cancers is attributed to the metastasized cancer, whereas, the medical expense for the treatment of cancer metastases generates heavily financial burden. The population size of metastases cases is small and comprehensive inferencing and prognosis is hard to conduct.
Methods: Because metastases and finance state can develop dynamic transitions over time, this study proposes a semi-Markov model to perform risk and economic evaluation associated to major cancer metastasis (i.e., lung, brain, liver and lymphoma cancer) against rare cases. A nationwide medical database in Taiwan was employed to derive a baseline study population and costs data. The time until development of metastasis and survivability from metastasis, as well as the medical costs were estimated through a semi-Markov based Monte Carlo simulation.
Results: In terms of the survivability and risk associated to metastatic cancer patients, 80% lung and liver cancer cases are tended to metastasize to other part of the body. The highest cost is generated by brain cancer-liver metastasis patients. The survivors group generated approximately 5 times more costs, in average, than the non-survivors group.
Conclusions: The proposed model provides a healthcare decision-support tool to evaluate the survivability and expenditure of major cancer metastases.
Keywords: Cancer metastasis; Monte Carlo simulation; Risk and economic evaluation; Semi-Markov process.
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