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Finding Optimal Cancer Treatment using Markov Decision Process to Improve Overall Health and Quality of Life

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  • Navonil Deb
  • Abhinandan Dalal
  • Gopal Krishna Basak

Abstract

Markov Decision Processes and Dynamic Treatment Regimes have grown increasingly popular in the treatment of diseases, including cancer. However, cancer treatment often impacts quality of life drastically, and people often fail to take treatments that are sustainable, affordable and can be adhered to. In this paper, we emphasize the usage of ambient factors like profession, radioactive exposure, food habits on the treatment choice, keeping in mind that the aim is not just to relieve the patient of his disease, but rather to maximize his overall physical, social and mental well being. We delineate a general framework which can directly incorporate a net benefit function from a physician as well as patient's utility, and can incorporate the varying probabilities of exposure and survival of patients of varying medical profiles. We also show by simulations that the optimal choice of actions often is sensitive to extraneous factors, like the financial status of a person (as a proxy for the affordability of treatment), and that these actions should be welcome keeping in mind the overall quality of life.

Suggested Citation

  • Navonil Deb & Abhinandan Dalal & Gopal Krishna Basak, 2020. "Finding Optimal Cancer Treatment using Markov Decision Process to Improve Overall Health and Quality of Life," Papers 2011.13960, arXiv.org.
    • Handle: RePEc:arx:papers:2011.13960
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    3. Allison, R. Andrew & Foster, James E., 2004. "Measuring health inequality using qualitative data," Journal of Health Economics, Elsevier, vol. 23(3), pages 505-524, May.
    4. Bercedis Peterson & Frank E. Harrell, 1990. "Partial Proportional Odds Models for Ordinal Response Variables," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 39(2), pages 205-217, June.
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