Abstract
We summarize results of our research studies on models of combined anticancer radio- and chemotherapy and their comparison with real clinical data. We use two mathematical techniques, which, to our knowledge, have not been applied simultaneously: optimal control theory and survival analysis. We recall results of analytical optimization of combined chemo-radio-therapy for a simple model of tumor growth with respect to the order, in which these two modes of treatment should be applied. Then we study both structural and parametric sensitivity of this model and related optimal control problem. Afterwards, we present results of survival analysis based on the Kaplan-Meier curves for different protocols of chemo-radio-therapy and compare them with real clinical data and results of optimal treatment protocols.
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Acknowledgment
The Authors would like to thank for financial support of their research. The study is partially supported by National Science Committee, Poland, Grant no. 2016/21/B/ST7/02241 and partially by Silesian University of Technology Grant no. 02/010/BK18/0102.
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Świerniak, A., Śmieja, J., Fujarewicz, K., Suwiński, R. (2020). Towards Personalized Radio-Chemotherapy – Learning from Clinical Data vs. Model Optimization. In: Nguyen, N., Jearanaitanakij, K., Selamat, A., Trawiński, B., Chittayasothorn, S. (eds) Intelligent Information and Database Systems. ACIIDS 2020. Lecture Notes in Computer Science(), vol 12033. Springer, Cham. https://doi.org/10.1007/978-3-030-41964-6_32
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DOI: https://doi.org/10.1007/978-3-030-41964-6_32
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