Using simulation-optimization to construct screening strategies for cervical cancer
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Cervical cancer is the second most common cancer in women worldwide. Cervical screening is critical for preventing this type of cancer. Traditionally, screening strategies are evaluated from an economic point of view through cost-effectiveness analysis. However, cost-effectiveness analysis is typically performed on a limited number of de facto or predetermined screening policies. We develop a simulation-optimization model to determine the ages at which screening should be performed, resulting in dynamic, age-based screening policies. We consider three performance measures: cervical cancer incidence, the number of cervical cancer deaths, and the number of life years lost due to cervical cancer death. Using each performance measure, we compare our optimal, dynamic screening strategies to standard policies considered in the health screening literature that are static and predetermined. We also evaluate the anticipated impact of vaccinations for preventing cervical cancer. The strategies that are developed are compared to those used in practice or considered in the literature. The Centers for Disease Control and Prevention recommends one screening every 3 years, resulting in 14 scheduled lifetime screenings. Our dynamic screening strategies provide approximately the same health benefits as this but with four to six fewer scheduled screenings, depending on the performance measure considered. Our dynamic strategies also provide approximately the same health benefits as screening every 2 years, but with six to nine fewer scheduled screenings. The results suggest that dynamic, age-based cervical cancer screening policies offer substantial economic savings in order to offer the same health benefits as equally spaced screening strategies.
KeywordsSimulation-optimization Health care policy Preventive medicine Women’s health Vaccination
This research was supported by Institutional Research Grant IRG-73-001-31 from the American Cancer Society. The authors wish to thank the associate editor and three referees for their superb comments and feedback on an earlier version of the paper.
- 1.National Cancer Institute (NCI) (2007) Available on-line via http://www.cancer.gov/. Accessed in 2007.
- 2.U.S. Center for Disease Control and Prevention (2004) Genital HPV Infection — CDC Fact Sheet (Available at http://www.cdc.gov/std/HPV/STDFact-HPV.htm, accessed on November 12, 2007).
- 5.U.S. Center for Disease Control and Prevention (2006). CDC’s Advisory Committee Recommends Human Papillomavirus Virus Vaccination. Press Release, Atlanta, GA, June 29, 2006 (Available at http://www.cdc.gov/od/oc/media/pressrel/r060629.htm)
- 6.Goldie S (2003) Chapter 15: Public Health Policy and Cost Effective Analysis. J Natl Cancer Inst Monogr 31:102–110Google Scholar
- 8.Myers E, McCrory D, Nanda K, Bastian L, Matchar D (2000) Mathematical model for the natural history of human papillomavirus infection and cervical carcinogenesis. Am J Epidemiol 151:1158–1171Google Scholar
- 13.Siebert U, Sroczynski G, Hillemanns P, Engel J, Stabenow R, Stegmaier C, Voigt K, Gibis B, Holzel D, Goldie S (2006) The German cervical cancer screening model: development and validation of a decision-analytic model for cervical cancer screening in Germany. Eur J Public Health 16:185–192CrossRefGoogle Scholar
- 18.Faissol DM, Griffin PM, Swann JL (2007) Timing of testing and treatment of hepatitis C and other diseases. Technical report, Georgia Institute of Technology, Atlanta, GeorgiaGoogle Scholar
- 25.Goldie SJ, Kim JJ, Myers E (2006) Chapter 19: cost-effectiveness of cervical cancer screening. Vaccine 24S3:S3/164–S3/170Google Scholar
- 27.Karjane NW (2007) Latest developments in HPV-related diseases and cervical cancer, how to treat a women series, Virginia Commonwealth University, 27 February 2007Google Scholar
- 28.Natarajan N, Mettlin C, Beart RW, Murphy GP (1985) Design and analysis of national patterns of care surveys of the American College of Surgeons. Neoplasia 2:5–10Google Scholar
- 30.Hoyert DL, Heron MP, Murphy SL, Kung H (2006) Deaths: final data for 2003. National vital statistics reports 54 (13), Hyattsville, MD, National Center for Health StatisticsGoogle Scholar
- 31.Mandelblatt J, Lawrence W, Gaffikin L, Limpahayom K, Lumbiganon P, Warakamin S, King J, Yi B, Ringers P, Blumenthal PS (2002) Costs and benefits of different strategies to screen for cervical cancer in less-developed countries. J Natl Cancer Inst 94:1469–1483Google Scholar
- 35.Keeney RL (1992) Value focused thinking. Harvard University Press, CambridgeGoogle Scholar
- 36.Sigurdur O, Jumi K (2002) Simulation optimization. Proceedings 1463 of the 2002 Winter Simulation Conference, San Diego, CA, available at http://www.informs-sim.org/wsc02papers/011.pdf
- 38.Kulasingam SL, Myers ER, Lawson HW, McConnell KJ, Kerlikowske K, Melnikow J, Washington AE, Sawaya GF (2006) Cost-effectiveness of extending cervical cancer screening intervals among women with prior normal Pap tests. Obstet Gynecol 107(2):321–328Google Scholar