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Optimization of Breast Cancer Screening Modalities

In: Probability, Statistics and Modelling in Public Health

Author

Listed:
  • Yu Shen

    (University of Texas, Department of Biostatistics and Applied Mathematics M. D. Anderson Cancer Center)

  • Giovanni Parmigiani

    (Johns Hopkins University, Departments of Oncology, Biostatistics and Pathology)

Abstract

Mathematical models and decision analyses based on microsimulations have been shown to be useful in evaluating relative merits of various screening strategies in terms of cost and mortality reduction. Most investigations regarding the balance between mortality reduction and costs have focused on a single modality, mammography. A systematic evaluation of the relative expenses and projected benefit of combining clinical breast examination and mammograpphy is not at present available. The purpose of this report is to provide methodologic details including assumptions and data used in the process of modeling for complex decision analyses, when searching for optimal breast cancer screening strategies with the multiple screening modalities. To systematic evaluate the relative expenses and projected bene- fit of screening programmes that combine the two modalities, we build a simulation model incorporating age-specific incidence of the disease, age-specific pre-clinical duration of the disease, age-specific sensitivities of the two screening modalities, and competing causes of mortality. Using decision models, we can integrate information from different sources into the modeling processes, and assess the cost-effectiveness of a variety of screening strategies while incorporating uncertainties.

Suggested Citation

  • Yu Shen & Giovanni Parmigiani, 2006. "Optimization of Breast Cancer Screening Modalities," Springer Books, in: Mikhail Nikulin & Daniel Commenges & Catherine Huber (ed.), Probability, Statistics and Modelling in Public Health, pages 405-420, Springer.
  • Handle: RePEc:spr:sprchp:978-0-387-26023-5_27
    DOI: 10.1007/0-387-26023-4_27
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