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 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

Persuasive Interventions for Controversial Cancer Screening Recommendations: Testing a Novel Approach to Help Patients Make Evidence-Based Decisions

“…If such a decision were durable and acted upon, it would substantially reduce the harms and costs of mammography with a minimal decrease in benefit. 45 We found similarly substantial reductions in decisional conflict with our narrated, persuasive video interventions and the print decision-aid interventions, whereas only our video interventions had any effect on preferences. For mammography, we had hypothesized that a greater understanding of the issues might lead to greater decisional conflict, but we did not observe this outcome.…”

Tailoring Breast Cancer Screening Intervals by Breast Density and Risk for Women Aged 50 Years or Older: Collaborative Modeling of Screening Outcomes

“…Biennial screening is supported by clinical trials (5, 6), observational studies (5, 7), and modeling results (8). Present recommendations also acknowledge that implementing screening in clinical practice should involve shared decision-making to consider preferences, risk-levels, and breast density (3, 4).…”

“…However, past empirical research on alternative screening intervals did not include mortality outcomes (12). Moreover, most prior modeling studies have relied on single models (10, 11), data on film-screen mammography and older treatment regimens (10, 11, 13), did not consider changes in breast density as women age (10), and/or did not consider triennial intervals (8). …”

Cost-Effectiveness of Breast Cancer Screening in Turkey, a Developing Country: Results from Bahçeşehir Mammography Screening Project

“…Therefore, this assumption may have caused our study to underestimate the benefits of screening. Ideally, one would use an established microsimulation model such as those used as part of NCI's Cancer Intervention Surveillance Network (CISNET) project to estimate the life expectancies for women undergoing screening more accurately (38)(39)(40). However, there is no such validated model that uses primary data of Turkish female population; therefore, we leave this for future research.…”