Probabilistic cost-effectiveness modeling of different breast cancer screening policies in Slovenia.

OBJECTIVES: To determine the most cost-effective screening policy for population-based mammography breast cancer screening in Slovenia using probabilistic sensitivity analysis.
METHODS: A time-dependent Markov model for breast cancer was constructed. General principles of cost-effectiveness analysis with multiple strategies were used to compare the costs and effects of 36 different screening policies. Using probability distributions for model parameters, the true effect of uncertainty across model input parameters on expected costs and effects was explored. The results from probabilistic simulation analysis are presented in a form of cost-effectiveness acceptability curves with cost-effectiveness acceptability frontier.
RESULTS: With the presented analysis, it was shown that a 1-year screening interval in population breast cancer screening would produce less benefits at higher costs than less intensive screening and that a 2-year interval would be cost-effective only at high values of society's willingness to pay per quality-adjusted life-year (QALY). Therefore, the optimal screening policy should be chosen among 3-year-interval policies.
CONCLUSIONS: Based on commonly quoted thresholds of society's willingness to pay per QALY of $50,000, the optimal approach in the Slovenian population would be screening women aged from 40 to 80 years every 3 years.