Risk-based breast cancer follow-up stratified by age

Annemieke Witteveen, Jan W.M. Otten, Ingrid M.H. Vliegen, Sabine Siesling, Judith B. Timmer, Maarten J. IJzerman

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    9 Citations (Scopus)
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    Although personalization of cancer care is recommended, current follow-up after the curative treatment of breast cancer is consensus-based and not differentiated for base-line risk. Every patient receives annual follow-up for 5 years without taking into account the individual risk of recurrence. The aim of this study was to introduce personalized follow-up schemes by stratifying for age. Using data from the Netherlands Cancer Registry of 37 230 patients with early breast cancer between 2003 and 2006, the risk of recurrence was determined for four age groups (<50, 50-59, 60-69, >70). Follow-up was modeled with a discrete-time partially observable Markov decision process. The decision to test for recurrences was made two times per year. Recurrences could be detected by mammography as well as by self-detection. For all age groups, it was optimal to have more intensive follow-up around the peak in recurrence risk in the second year after diagnosis. For the first age group (<50) with the highest risk, a slightly more intensive follow-up with one extra visit was proposed compared to the current guideline recommendation. The other age groups were recommended less visits: four for ages 50-59, three for 60-69, and three for ≥70. With this model for risk-based follow-up, clinicians can make informed decisions and focus resources on patients with higher risk, while avoiding unnecessary and potentially harmful follow-up visits for women with very low risks. The model can easily be extended to take into account more risk factors and provide even more personalized follow-up schedules.

    Original languageEnglish
    Pages (from-to)5291-5298
    Number of pages8
    JournalCancer Medicine
    Issue number10
    Publication statusPublished - 1 Oct 2018


    • breast cancer
    • follow-up
    • locoregional recurrence
    • partially observable Markov decision process
    • second primary
    • Markov Chains
    • Age Distribution
    • Office Visits
    • Risk Assessment
    • Early Detection of Cancer
    • Humans
    • Middle Aged
    • Breast Neoplasms/diagnosis
    • Netherlands
    • Aftercare
    • Life Expectancy
    • Adult
    • Female
    • Registries
    • Aged
    • Neoplasm Recurrence, Local/diagnosis
    • Practice Guidelines as Topic


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