Background: Reducing the false-positive risk in breast cancer screening is important. We examined how the screening-protocol and women's characteristics affect the cumulative false-positive risk.Methods: This is a retrospective cohort study of 1 565 364 women aged 45–69 years who underwent 4 739 498 screening mammograms from 1990 to 2006. Multilevel discrete hazard models were used to estimate the cumulative false-positive risk over 10 sequential mammograms under different risk scenarios.Results: The factors affecting the false-positive risk for any procedure and for invasive procedures were double mammogram reading [odds ratio (OR) = 2.06 and 4.44, respectively], two mammographic views (OR = 0.77 and 1.56, respectively), digital mammography (OR = 0.83 for invasive procedures), premenopausal status (OR = 1.31 and 1.22, respectively), use of hormone replacement therapy (OR = 1.03 and 0.84, respectively), previous invasive procedures (OR = 1.52 and 2.00, respectively), and a familial history of breast cancer (OR = 1.18 and 1.21, respectively). The cumulative false-positive risk for women who started screening at age 50–51 was 20.39% [95% confidence interval (CI) 20.02–20.76], ranging from 51.43% to 7.47% in the highest and lowest risk profiles, respectively. The cumulative risk for invasive procedures was 1.76% (95% CI 1.66–1.87), ranging from 12.02% to 1.58%.Conclusions: The cumulative false-positive risk varied widely depending on the factors studied. These findings are relevant to provide women with accurate information and to improve the effectiveness of screening programs.

Discrete-event simulation is useful in decision-making when assessing health services. Introducing a waiting list prioritization system produced greater benefit than allocating surgery by waiting time only. Use of the simulation model would allow the impact of proposed policies to reduce waiting lists or assign resources more efficiently to be tested.

BackgroundBreast cancer (BC) causes more deaths than any other cancer among women in Catalonia. Early detection has contributed to the observed decline in BC mortality. However, there is debate on the optimal screening strategy. We performed an economic evaluation of 20 screening strategies taking into account the cost over time of screening and subsequent medical costs, including diagnostic confirmation, initial treatment, follow-up and advanced care.MethodsWe used a probabilistic model to estimate the effect and costs over time of each scenario. The effect was measured as years of life (YL), quality-adjusted life years (QALY), and lives extended (LE). Costs of screening and treatment were obtained from the Early Detection Program and hospital databases of the IMAS-Hospital del Mar in Barcelona. The incremental cost-effectiveness ratio (ICER) was used to compare the relative costs and outcomes of different scenarios.ResultsStrategies that start at ages 40 or 45 and end at 69 predominate when the effect is measured as YL or QALYs. Biennial strategies 50-69, 45-69 or annual 45-69, 40-69 and 40-74 were selected as cost-effective for both effect measures (YL or QALYs). The ICER increases considerably when moving from biennial to annual scenarios. Moving from no screening to biennial 50-69 years represented an ICER of 4,469€ per QALY.ConclusionsA reduced number of screening strategies have been selected for consideration by researchers, decision makers and policy planners. Mathematical models are useful to assess the impact and costs of BC screening in a specific geographical area.