Objectives: Quality-controlled mammography screening programs (MSP) have led to a reduction in breast cancer mortality. The purpose of this economic analysis was to assess the cost-effectiveness of MSP compared with an established opportunistic screening strategy (OS) in Switzerland, to identify the major factors influencing the economic outcome. Methods: Using cancer registries and clinical data, a Markov-based decision model was designed to compare MSP with OS in the Swiss female population, considering the main screening-specific performance parameters. Results: The discounted incremental life expectancy amounted to 0.022 life-years gained in favor of MSP when screening started at age 40 years and decreased to 0.008 years at the age of 70 years (number needed to screen to avoid one death over 10 years ranged from 10,000 to 2439 women depending on the baseline age). The total discounted life-time cost for screening, treatment at the baseline age of 40 years amounted in MSP to $4366 (OS: $2802) and decreased with the baseline age of 70 years to $2412 (OS: $1446). The discounted incremental cost-effectiveness ratio comparing MSP versus OS ranged from $73,018 (age 40 years) to $118,193 (age 70 years) per life-year gained. Testing all model variables confirmed that both incidence and mortality of breast cancer play the most important role in the health economic outcome, whereas cost and performances (sensitivity, specificity) of screening had a minor impact on the efficiency. Conclusion: This analysis, performed under conservative assumptions, supports that MSP in Switzerland enables a relevant reduction of breast cancer mortality, at moderate additional cost, compared with OS. © 2007, International Society for Pharmacoeconomics and Outcomes Research (ISPOR).
CITATION STYLE
Neeser, K., Szucs, T., Bulliard, J. L., Bachmann, G., & Schramm, W. (2007). Cost-effectiveness analysis of a quality-controlled mammography screening program from the swiss statutory health-care perspective: Quantitative assessment of the most influential factors. Value in Health, 10(1), 42–53. https://doi.org/10.1111/j.1524-4733.2006.00143.x
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