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Using Decision Analysis to Model Cancer Surveillance

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Patient Surveillance After Cancer Treatment

Part of the book series: Current Clinical Oncology ((CCO))

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Abstract

Cancer management includes surveillance of patients after treatment. Such programs become increasingly important since chances of survival after cancer treatment and, thus, disease-free survival rates are continuing to increase. Surveillance programs are also time-consuming and, in addition, a very expensive component of clinical activity since frequent testing is often involved. The choice of a surveillance program is complex and should ideally consider aspects of survival, quality of life, the burden of surveillance tests, and financial costs. As for all clinical decisions, the choice involves a condition of uncertainty. This uncertainty originates from relationships between diagnostic information and the presence of disease, uncertainty about the effects of early treatment, and ambiguity in clinical information [1].

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Author information

Authors and Affiliations

  1. Department of Public Health, Erasmus University, 2040, 3000 CA, Rotterdam, The Netherlands

    Kim E. M. van Kessel & Ewout W. Steyerberg

  2. Department of Epidemiology, Biostatistics and HTA, Radboud University Nijmegen Medical Centre, 9101, 6500HB, Nijmegen, The Netherlands

    Sandra M. E. Geurts & André L. M. Verbeek

Authors
  1. Kim E. M. van Kessel
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  2. Sandra M. E. Geurts
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  3. André L. M. Verbeek
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  4. Ewout W. Steyerberg
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Corresponding author

Correspondence to Ewout W. Steyerberg .

Editor information

Editors and Affiliations

  1. Department of Surgery, Saint Louis University, Vista Avenue 3635, St. Louis, 63110-0050, Missouri, USA

    Frank E. Johnson

  2. Fac. Medicine, Dept. Surgery II, Kyushu University, Fukuoka, 812-8582, Japan

    Yoshihiko Maehara

  3. BC Cancer Agency, West 10th Avenue 600, Vancouver, V5Z 4E6, British Columbia, Canada

    George P. Browman

  4. School of Medicine, Washington University, S. Euclid Ave. 660, St. Louis, 63110, Missouri, USA

    Julie A. Margenthaler

  5. St Helens Teaching Hospital, University of Liverpool, Marshalls Cross Road, St Helens, WA9 3DA, United Kingdom

    Riccardo A. Audisio

  6. Sydney Cancer Centre, Sydney Melanoma Unit, Royal Prince Alfred Hospital, Missenden Road, Camperdown, 2050, New South Wales, Australia

    John F. Thompson

  7. Saint Louis University Medical Center, Saint Louis, 63103, Missouri, USA

    David Y. Johnson

  8. Dana-Farber Cancer Institute, Harvard Medical School, Binney St. 44, Boston, 02115, Massachusetts, USA

    Craig C. Earle

  9. International Atlantic Economic Society, Peachtree Center 299, NEInternatio, Atlanta, 30303, Georgia, USA

    Katherine S. Virgo

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© 2013 Humana Press

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van Kessel, K.E.M., Geurts, S.M.E., Verbeek, A.L.M., Steyerberg, E.W. (2013). Using Decision Analysis to Model Cancer Surveillance. In: Johnson, F., et al. Patient Surveillance After Cancer Treatment. Current Clinical Oncology. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60327-969-7_3

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  • DOI: https://doi.org/10.1007/978-1-60327-969-7_3

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  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-60327-968-0

  • Online ISBN: 978-1-60327-969-7

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