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A Markovian decision model of adaptive cancer treatment and quality of life

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  • Brown, Joel
  • Dubbeldam, Johan
  • Broom, Mark
  • Bayer, Péter

Abstract

This paper develops and analyzes a Markov chain model for the treatment of cancer. Cancer therapy is modeled as the patient's Markov Decision Problem, with the objective of maximizing the patient's discounted expected quality of life years. Patients make decisions on the duration of therapy based on the progression of the disease as well as their own preferences. We obtain a powerful analytic decision tool through which patients may select their preferred treatment strategy. We illustrate the tradeoffs patients in a numerical example and calculate the value lost to a cohort in suboptimal strategies. In a second model patients may make choices to include drug holidays. By delaying therapy, the patient temporarily forgoes the gains of therapy in order to delay its side effects. We obtain an analytic tool that allows numerical approximations of the optimal times of delay.
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Suggested Citation

  • Brown, Joel & Dubbeldam, Johan & Broom, Mark & Bayer, Péter, 2022. "A Markovian decision model of adaptive cancer treatment and quality of life," TSE Working Papers 22-1291, Toulouse School of Economics (TSE).
  • Handle: RePEc:tse:wpaper:126508
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    2. K. Le Lay & E. Myon & S. Hill & L. Riou-Franca & D. Scott & M. Sidhu & D. Dunlop & R. Launois, 2007. "Comparative cost-minimisation of oral and intravenous chemotherapy for first-line treatment of non-small cell lung cancer in the UK NHS system," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 8(2), pages 145-151, June.
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    4. Gilbar, Ora, 1991. "The quality of life of cancer patients who refuse chemotherapy," Social Science & Medicine, Elsevier, vol. 32(12), pages 1337-1340, January.
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