Background Despite trials of mammography and widespread use, optimal screening policy is controversial. Design and Objective Six models use common data elements to evaluate US screening strategies. Data Sources The models use national data on age-specific incidence, competing mortality, mammography characteristics and treatment effects. Target Population and Time Horizon A contemporary population cohort followed over their lifetimes. Perspective We use a societal perspective for analysis. Interventions We evaluate 20 screening strategies with varying initiation and cessation ages applied annually or biennially. Outcome Measures Number of mammograms, breast cancer mortality reduction or life years gained [LYG] (vs. no screening), false positives, unnecessary biopsies and over-diagnosis. Results of Base Case The 6 models produce consistent rankings of screening strategies. Screening biennially maintains an average of 81% (range across strategies and models 67–99%) of the benefit of annual screening with almost half the number of false positives. Screening biennially from ages 50 to 69 achieves a median 16.5% (range 15%–23%) breast cancer mortality reduction vs. no screening. Initiating biennial screening at age 40 (vs. 50) reduces mortality by an additional 3% (range 1%–6%), consumes more resources and yields more false positives. Biennial screening after age 69 yields some additional mortality reduction in all models but over-diagnosis increases most substantially at older ages. Sensitivity Analysis Results Varying test sensitivity or treatment patterns do not change conclusions. Limitations Results do not include morbidity from false positives, knowledge of earlier diagnosis or under-going unnecessary treatment. Conclusion Biennial screening achieves most of the benefit of annual screening with less harm. Decisions about the best strategy depend on program and individual objectives and the weight placed on benefits, harms and resource considerations.

Background Controversy persists about optimal mammography screening strategies. Objective To evaluate mammography strategies considering screening and treatment advances. Design Collaboration of six simulation models. Data Sources National data on incidence, risk, breast density, digital mammography performance, treatment effects, and other-cause mortality. Target Population An average-risk cohort. Time Horizon Lifetime. Perspective Societal. Interventions Mammograms from age 40, 45 or 50 to 74 at annual or biennial intervals, or annually from 40 or 45 to 49 then biennially to 74, assuming 100% screening and treatment adherence. Outcome Measures Screening benefits (vs. no screening) include percent breast cancer mortality reduction, deaths averted, and life-years gained. Harms include number of mammograms, false-positives, benign biopsies, and overdiagnosis. Results for Average-Risk Women Biennial strategies maintain 79.8%-81.3% (range across strategies and models: 68.3–98.9%) of annual screening benefits with almost half the false-positives and fewer overdiagnoses. Screening biennially from ages 50–74 achieves a median 25.8% (range: 24.1%-31.8%) breast cancer mortality reduction; annual screening from ages 40–74 years reduces mortality an additional 12.0% (range: 5.7%-17.2%) vs. no screening, but yields 1988 more false-positives and 7 more overdiagnoses per 1000 women screened. Annual screening from ages 50–74 had similar benefits as other strategies but more harms, so would not be recommended. Sub-population Results Annual screening starting at age 40 for women who have a two- to four-fold increase in risk has a similar balance of harms and benefits as biennial screening of average-risk women from 50–74. Limitations We do not consider other imaging technologies, polygenic risk, or non-adherence. Conclusion These results suggest that biennial screening is efficient for average-risk groups, but decisions on strategies depend on the weight given to the balance of harms and benefits. Primary Funding Source National Institutes of Health