Collaborative Modeling of the Benefits and Harms Associated With Different U.S. Breast Cancer Screening Strategies

Abstract

Background: Controversy persists about optimal mammography screening strategies.

Objective: To evaluate screening outcomes, taking into account advances in mammography and treatment of breast cancer.

Design: Collaboration of 6 simulation models using national data on incidence, digital mammography performance, treatment effects, and other-cause mortality.

Setting: United States.

Patients: Average-risk U.S. female population and subgroups with varying risk, breast density, or comorbidity.

Intervention: Eight strategies differing by age at which screening starts (40, 45, or 50 years) and screening interval (annual, biennial, and hybrid [annual for women in their 40s and biennial thereafter]). All strategies assumed 100% adherence and stopped at age 74 years.

Measurements: Benefits (breast cancer-specific mortality reduction, breast cancer deaths averted, life-years, and quality-adjusted life-years); number of mammograms used; harms (false-positive results, benign biopsies, and overdiagnosis); and ratios of harms (or use) and benefits (efficiency) per 1000 screens.

Results: Biennial strategies were consistently the most efficient for average-risk women. Biennial screening from age 50 to 74 years avoided a median of 7 breast cancer deaths versus no screening; annual screening from age 40 to 74 years avoided an additional 3 deaths, but yielded 1988 more false-positive results and 11 more overdiagnoses per 1000 women screened. Annual screening from age 50 to 74 years was inefficient (similar benefits, but more harms than other strategies). For groups with a 2- to 4-fold increased risk, annual screening from age 40 years had similar harms and benefits as screening average-risk women biennially from 50 to 74 years. For groups with moderate or severe comorbidity, screening could stop at age 66 to 68 years.

Limitation: Other imaging technologies, polygenic risk, and nonadherence were not considered.

Conclusion: Biennial screening for breast cancer is efficient for average-risk populations. Decisions about starting ages and intervals will depend on population characteristics and the decision makers' weight given to the harms and benefits of screening.

Primary funding source: National Institutes of Health.

Figure 1. Efficiency Frontier for Harms (Average Number of Screening Examinations) and Benefits (Life Years Gained) for Exemplar Model by Screening Strategy

The panel shows an efficiency frontier graph for an exemplar model (model D); comparable graphs are included on Appendix Figure 2 for all 6 models. The graph plots the average number of mammograms per 1,000 women against the life-years gained for each screening strategy (vs. no screening). We plot efficient strategies (i.e., those in which increases in mammography use results in greater life-years gained than the next least-intensive strategy). The line between strategies represents the “efficiency frontier.” Strategies on this line would be considered efficient because they achieve the greatest gain per mammography used compared with the point (or strategy) immediately below it. Points that fall below the line are not as efficient as those on the line. When the slope in the efficiency frontier plot levels off, the additional life-years gained per increase in mammography are small relative to the previous strategies and could indicate a point at which additional screening might be considered as having a low return (benefit). Black strategies are efficient; dark grey strategies are close to the efficiency frontier; and light grey strategies are dominated (inefficient). Biennial strategies are indicated with a square; hybrid strategies (annual in the 40’s, followed by biennial from 50–74) are represented by a triangle, and annual strategies with a circle. Efficiency frontiers for other harm and benefit metrics can be found at: (34)