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The Influence of Disease Risk on the Optimal Time Interval between Screens for the Early Detection of Cancer

Author

Listed:
  • James F. O’Mahony
  • Joost van Rosmalen
  • Nino A. Mushkudiani
  • Frans-Willem Goudsmit
  • Marinus J. C. Eijkemans
  • Eveline A. M. Heijnsdijk
  • Ewout W. Steyerberg
  • J. Dik F. Habbema

Abstract

The intervals between screens for the early detection of diseases such as breast and colon cancer suggested by screening guidelines are typically based on the average population risk of disease. With the emergence of ever more biomarkers for cancer risk prediction and the development of personalized medicine, there is a need for risk-specific screening intervals. The interval between successive screens should be shorter with increasing cancer risk. A risk-dependent optimal interval is ideally derived from a cost-effectiveness analysis using a validated simulation model. However, this is time-consuming and costly. We propose a simplified mathematical approach for the exploratory analysis of the implications of risk level on optimal screening interval. We develop a mathematical model of the optimal screening interval for breast cancer screening. We verified the results by programming the simplified model in the MISCAN-Breast microsimulation model and comparing the results. We validated the results by comparing them with the results of a full, published MISCAN-Breast cost-effectiveness model for a number of different risk levels. The results of both the verification and validation were satisfactory. We conclude that the mathematical approach can indicate the impact of disease risk on the optimal screening interval.

Suggested Citation

  • James F. O’Mahony & Joost van Rosmalen & Nino A. Mushkudiani & Frans-Willem Goudsmit & Marinus J. C. Eijkemans & Eveline A. M. Heijnsdijk & Ewout W. Steyerberg & J. Dik F. Habbema, 2015. "The Influence of Disease Risk on the Optimal Time Interval between Screens for the Early Detection of Cancer," Medical Decision Making, , vol. 35(2), pages 183-195, February.
    • Handle: RePEc:sae:medema:v:35:y:2015:i:2:p:183-195
    DOI: 10.1177/0272989X14528380
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    References listed on IDEAS

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    1. Rose Baker, 1998. "Use of a mathematical model to evaluate breast cancer screening policy," Health Care Management Science, Springer, vol. 1(2), pages 103-113, October.
    2. Lisa M. Maillart & Julie Simmons Ivy & Scott Ransom & Kathleen Diehl, 2008. "Assessing Dynamic Breast Cancer Screening Policies," Operations Research, INFORMS, vol. 56(6), pages 1411-1427, December.
    3. Julie Simmons Ivy, 2009. "Can we Do Better? Optimization Models for Breast Cancer Screening," Springer Optimization and Its Applications, in: H. Edwin Romeijn & Panos M. Pardalos (ed.), Handbook of Optimization in Medicine, chapter 2, pages 25-52, Springer.
    4. Michael Shwartz, 1978. "A Mathematical Model Used to Analyze Breast Cancer Screening Strategies," Operations Research, INFORMS, vol. 26(6), pages 937-955, December.
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    Cited by:

    1. Nikolai Mühlberger & Gaby Sroczynski & Artemisa Gogollari & Beate Jahn & Nora Pashayan & Ewout Steyerberg & Martin Widschwendter & Uwe Siebert, 2021. "Cost effectiveness of breast cancer screening and prevention: a systematic review with a focus on risk-adapted strategies," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(8), pages 1311-1344, November.

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