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Using simulation-optimization to construct screening strategies for cervical cancer

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Abstract

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.

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Acknowledgements

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.

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Authors and Affiliations

  1. Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, P.O. Box 843083, 1015 Floyd Avenue, Richmond, VA, 23284, USA

    Laura A. McLay, Christodoulos Foufoulides & Jason R. W. Merrick

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  1. Laura A. McLay
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  2. Christodoulos Foufoulides
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  3. Jason R. W. Merrick
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Correspondence to Laura A. McLay.

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McLay, L.A., Foufoulides, C. & Merrick, J.R.W. Using simulation-optimization to construct screening strategies for cervical cancer. Health Care Manag Sci 13, 294–318 (2010). https://doi.org/10.1007/s10729-010-9131-x

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  • DOI: https://doi.org/10.1007/s10729-010-9131-x

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