@inbook{b7649942c90c4603b7aa2b36da07ae98,
title = "Stratified breast cancer follow-up using a partially observable Markov decision process",
abstract = "Frequency and duration of follow-up for patients with breast cancer is still under discussion. Current follow-up consists of annual mammography for the first five years after treatment and does not depend on the personal risk of developing a locoregional recurrence (LRR) or second primary tumor. Aim of this study is to gain insight in how to allocate resources for optimal and personal follow-up. We formulate a discrete-time Partially Observable Markov Decision Process (POMDP) with a finite horzion in which we aim to maximize the total expected number of quality-adjusted life years (QALYs). Transition probabilities were obtained from data from the Netherlands Cancer Registry (NCR). Twice a year the decision is made whether or not a mammography will be performed. Recurrent disease can be detected by both mammography or women themselves (self-detection). The optimal policies were determined for three risk categories based on differentiation of the primary tumor. Our results suggest a slightly more intensive follow-up for patients with a high risk and poorly differentiated tumor, and a less intensive schedule for the other risk groups.",
keywords = "Partially observable Markov decision process (POMDP), Breast cancer, Optimal policies, Stratified follow-up, Markov decision process (MDP)",
author = "J.W.M. Otten and A. Witteveen and I.M.H. Vliegen and S. Siesling and J.B. Timmer and M.J. IJzerman",
year = "2017",
month = mar,
doi = "10.1007/978-3-319-47766-4_7",
language = "English",
isbn = "978-3-319-47764-0",
series = "International Series in Operations Research & Management Science",
publisher = "Springer",
pages = "223--244",
editor = "Boucherie, {Richard J.} and {van Dijk}, {Nico M.}",
booktitle = "Markov Decision Processes in Practice",
}