Abstract
The optimal schedules for breast cancer screening in terms of examination frequency and ages at examination are of practical interest. A decision-theoretic approach is explored to search for optimal cancer screening programs which should achieve maximum survival benefit while balancing the associated cost to the health care system. We propose a class of utility functions that account for costs associated with screening examinations and value of survival benefit under a non-stable disease model. We consider two different optimization criteria: optimize the number of screening examinations with equal screening intervals between exams but without a prefixed total cost; and optimize the ages at which screening should be given for a fixed total cost. We show that an optimal solution exists under each of the two frameworks. The proposed methods may consider women at different levels of risk for breast cancer so that the optimal screening strategies will be tailored according to a woman’s risk of developing the disease. Results of a numerical study are presented and the proposed models are illustrated with various data inputs. We also use the data inputs from the Health Insurance Plan of New York (HIP) and Canadian National Breast Screening Study (CNBSS) to illustrate the proposed models and to compare the utility values between the optimal schedules and the actual schedules in the HIP and CNBSS trials. Here, the utility is defined as the difference in cure rates between cases found at screening examinations and cases found between screening examinations while accounting for the cost of examinations, under a given screening schedule.
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References
American Cancer Society (2006) Detailed guide: breast cancer. Can breast cancer be found early? http://www.cancer.org/. Accessed Dec 2008
American Society (2010) Breast cancer facts and figures 2009–2010. http://www.cancer.org/Research/CancerFactsFigures/BreastCancerFactsFigures/. Accessed Aug 2010
Boer R, Plevritis S, Clarke L (2004) Diversity of model approaches for breast cancer screening: a review of model assumptions by the Cancer Intervention and Surveillance Network (CISNET) Breast Cancer Groups. Stat Methods Med Res 13:525–538
Day NE, Walter SD (1984) Simplified models of screening for chronic disease: estimation procedures from mass screening programmes. Biometrics 40:1–14
Knudsen AB, McMahon PM, Gazelle GS (2007) Use of modeling to evaluate the cost-effectiveness of cancer screening programs. J Clin Oncol 25:203–208
Lee SJ, Zelen M (1998) Scheduling periodic examinations for the early detection of disease: applications to breast cancer. J Am Stat Assoc 93:1271–1281
Mandelblatt JS, Cronin KA, Bailey S, Berry DA, deKonig HJ, Draisma G, Huang H, Lee SJ, Munsell M, Plevritis SK, Ravdin P, Schechter CB, Sigal B, Stoto MA, Stout NK, van Ravesteyn NT, Venier J, Zelen M, Feuer EJ (2009) Effects of mammography screening under different screening schedules: model estimates of potential benefits and harms. Ann Intern Med 151:738–747
Mandelblatt JS, Schechter CB, Yabroff KR, Lawrence W, Dignam J, Muennig P, Chavez Y, Cullen J, Fahs M (2004) Benefits and costs of interventions to improve breast cancer outcomes in African American women. J Clin Oncol 22:2554–2566
National Cancer Institute (2007) Breast cancer: screening and testing. http://www.cancer.gov/cancertopics/screening/breast/. Accessed Dec 2008
NHS Cancer Screening Programmes (2008) NHS breast screening programme. http://cancerscreening.org.uk/breastscreen/. Accessed Dec 2008
Parmigiani G (1993) On optimal screening ages. J Am Stat Assoc 88:622–628
Rosen PR, Groshen S, Saigo PE, Kinne DW, Hellman S (1989) A long-term follow-up study of survival in stage I (T1N0M0) and stage II (T1N1M0) breast carcinoma. J Clin Oncol 7:355–366
Rudin W (1976) Principles of mathematical analysis, 3rd edn. McGraw-Hill Science, New York
Shen Y, Parmigiani G (2005) A model-based comparison of breast cancer screening strategies: mammograms and clinical breast examination. Cancer Epidemiol Biomarkers Prev 14:529–532
Shen Y, Zelen M (2001) Screening sensitivity and sojourn time from breast cancer early detection trials: mammograms and physical examinations. J Clin Oncol 9:3490–3499
Shen Y, Zelen M (1999) Parametric estimation procedures for screening programmes: stable and nonstable disease models for multimodality case finding. Biometrika 86:503–515
Stout NK, Rosenberg MA, Trentham-Dietz A, Smith MA, Robinson SM, Fryback DG (2006) Retrospective cost-effectiveness analysis of screening mammography. J Natl Cancer Inst 98:774–782
Tsodikov AD, Yakovlev AY (1991) On the optimal policies of breast cancer screening. Math Biosci 107:21–45
US Preventive Services Task Force (2009) Screening for breast cancer: US Preventive Services Task Force recommendation statement. Ann Intern Med 151:716–726
Zelen M (1993) Optimal scheduling of examinations for the early detection of disease. Biometrika 80:279–293
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Ahern, C.H., Cheng, Y. & Shen, Y. Risk-Specific Optimal Cancer Screening Schedules: An Application to Breast Cancer Early Detection. Stat Biosci 3, 169–186 (2011). https://doi.org/10.1007/s12561-011-9032-7
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DOI: https://doi.org/10.1007/s12561-011-9032-7