Strategic cancer therapy planning: optimizing treatment and quality of life with Markov decision processes
Year: 2025
Type: article
Abstract: Background: In managing the progression of diseases, particularly cancer, Markov decision processes (MDP) and dynamic therapy regimes are gaining prominence. Despite this, cancer treatments often negatively impact patients' quality of life, leading many to abandon effective, accessible, and affordable therapies. Materials and methods: This paper introduces a novel MDP-based mathematical framework for optimizing multi-therapy treatment schedules in malignancy therapy. Through practical illustrations, we demonstrate the utility and applicability of the proposed framework. Our approach integrates both patient utility and the physician's net benefit function, accounting for treatment options and survival probabilities across diverse clinical profiles. The system state in our MDP model is defined by tumor progression and normal tissue side effects, while the response field encompasses treatment outcomes categorized into recurrence, tumor regression, and healthy tissue safety. At each decision stage, the physician assesses the patient's condition and selects the optimal treatment strategy to maximize the final reward, determined by the patient's health at the end state. Results/Conclusions: This framework offers a holistic approach to improving overall treatment outcomes while recognizing the importance of preserving patients' quality of life.
DOI: 10.5603/rpor.108580
Authors: Seema Singh, Chandrahas Sahu, Pushpendra Singh, Alka Mishra, Santosh Kumar Mishra, Pawan Kumar Patnaik
Institution: Hemchand Yadav Vishwavidyalaya
Language: English
Subfield: Modeling and Simulation
Field: Mathematics
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,713
OpenAlex ID: W7102687780