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Stratified Breast Cancer Follow-Up Using a Partially Observable MDP

In: Markov Decision Processes in Practice

Author

Listed:
  • J. W. M. Otten

    (University of Twente)

  • A. Witteveen

    (University of Twente)

  • I. M. H. Vliegen

    (University of Twente)

  • S. Siesling

    (University of Twente
    Comprehensive Cancer Organisation)

  • J. B. Timmer

    (University of Twente)

  • M. J. IJzerman

    (University of Twente)

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 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.

Suggested Citation

  • J. W. M. Otten & A. Witteveen & I. M. H. Vliegen & S. Siesling & J. B. Timmer & M. J. IJzerman, 2017. "Stratified Breast Cancer Follow-Up Using a Partially Observable MDP," International Series in Operations Research & Management Science, in: Richard J. Boucherie & Nico M. van Dijk (ed.), Markov Decision Processes in Practice, chapter 0, pages 223-244, Springer.
    • Handle: RePEc:spr:isochp:978-3-319-47766-4_7
    DOI: 10.1007/978-3-319-47766-4_7
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    Cited by:

    1. Malek Ebadi & Raha Akhavan-Tabatabaei, 2021. "Personalized Cotesting Policies for Cervical Cancer Screening: A POMDP Approach," Mathematics, MDPI, vol. 9(6), pages 1-20, March.

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