New Decision Models of Quality of Life Measures for Interventions Evaluation for Prostate Cancer Patients

Session
Student Paper Presentations

Author
Yung-wen Liu
University of Washington

Description
This paper focuses on the development of new quantitative dynamic models that can be used to measure prostate cancer patients' total quality of life, and hence be used jointly by the physician and the patient to evaluate different interventions and make decision. A general stochastic model (the nonhomogeneous continuous time Markov process) is first developed to capture the process of the stage change for the patient. The probability that a patient stays in each stage at some point in time, and the expected time for a patient to be in each stage can be estimated using the developed stochastic model. A disutility function which is commonly given in economics is incorporated with the stochastic model for estimating the total patient's experience with his illness and medical treatments along with time.

Abstract
This paper focuses on the development of new quantitative dynamic models that can be used to measure prostate cancer patients' total quality of life, and hence be used jointly by the physician and the patient to evaluate different interventions and make decision. A general stochastic model (the nonhomogeneous continuous time Markov process) is first developed to capture the process of the stage change for the patient. The probability that a patient stays in each stage at some point in time, and the expected time for a patient to be in each stage can be estimated using the developed stochastic model. A disutility function which is commonly given in economics is incorporated with the stochastic model for estimating the total patient's experience with his illness and medical treatments along with time.