An Economic Prevention Plan for Alzheimer's Disease Based on Blood Biomarkers

Document Type : Research Article

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Department of Industrial Engineering & Management Systems, Amirkabir University of Technology (Tehran Polytechnic), Iran

Abstract

This work presents a practical and cost-effective dynamic plan for preventing Alzheimer's disease. The plan involves periodic monitoring of an individual's blood biomarkers, personal characteristics, and budget constraints. The primary goal is to provide a feasible and realistic plan for each individual, with the highest likelihood of being followed. A Markov decision process model is proposed and solved using two algorithms: policy iteration and value iteration. In contrast to cerebrospinal fluid biomarkers, this plan relies on blood-based biomarkers, specifically Tau181 and APOE4, which are more cost-efficient and accessible for periodic testing. The interventions or actions within the model encompass choices between light or intense physical activity and adopting a less or more stringent diet. The decision model seeks to maximize the individual's quality of life while considering associated expenses. The proposed plan is tested on an modified dataset derived from clinical records, and it reveals insightful findings. Notably, our experimental study indicates that younger individuals at risk of the disease are more inclined to invest in preventive measures than those over 65. However, this trend does not apply to individuals lacking the APOE4 gene and those with higher tau181 concentration. The proposed plan can assist physicians in making appropriate recommendations.

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AUT Journal of Modeling and Simulation
Volume 55, Issue 2
December 2023
Pages 2-2

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