Stratified breast cancer follow-up using a partially observable MDP

J. W.M. Otten, A. Witteveen*, I. M.H. Vliegen, S. Siesling, J. B. Timmer, M. J. IJzerman

*Corresponding author for this work

Research output: Chapter/Conference proceedingChapterAcademic

6 Citations (Scopus)


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 horizon 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.

Original languageEnglish
Title of host publicationInternational Series in Operations Research and Management Science
PublisherSpringer New York
Number of pages22
Publication statusPublished - 11 Mar 2017
Externally publishedYes

Publication series

SeriesInternational Series in Operations Research and Management Science

Bibliographical note

Publisher Copyright:
© Springer International Publishing AG 2017.


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