@inbook{b7649942c90c4603b7aa2b36da07ae98,
title = "Stratified breast cancer follow-up using a partially observable MDP",
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), 2023 OA procedure",
author = "Otten, \{J. W.M.\} and A. Witteveen and Vliegen, \{I. M.H.\} and S. Siesling and Timmer, \{J. B.\} and Maarten 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",
address = "Germany",
}