Effects of Mammography Screening Under Different Screening Schedules: Model Estimates of Potential Benefits and Harms

Background: Despite trials of mammography and widespread use, optimal screening policy is controversial. Objective: To evaluate U. S. breast cancer screening strategies. Design: 6 models using common data elements. Data Sources: National data on age-specific incidence, competing mortality, mammography characteristics, and treatment effects. Target Population: A contemporary population cohort. Time Horizon: Lifetime. Perspective: Societal. Interventions: 20 screening strategies with varying initiation and cessation ages applied annually or biennially. Outcome Measures: Number of mammograms, reduction in deaths from breast cancer or life-years gained (vs. no screening), false-positive results, unnecessary biopsies, and overdiagnosis. Results of Base-Case Analysis: The 6 models produced consistent rankings of screening strategies. Screening biennially maintained an average of 81% (range across strategies and models, 67% to 99%) of the benefit of annual screening with almost half the number of false-positive results. Screening biennially from ages 50 to 69 years achieved a median 16.5% (range, 15% to 23%) reduction in breast cancer deaths versus no screening. Initiating biennial screening at age 40 years (vs. 50 years) reduced mortality by an additional 3% (range, 1% to 6%), consumed more resources, and yielded more false-positive results. Biennial screening after age 69 years yielded some additional mortality reduction in all models, but overdiagnosis increased most substantially at older ages. Results of Sensitivity Analysis: Varying test sensitivity or treatment patterns did not change conclusions. Limitation: Results do not include morbidity from false-positive results, patient knowledge of earlier diagnosis, or 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.