Personalizing Breast Cancer Screening Based on Polygenic Risk and Family History

_Background:_ We assessed the clinical utility of a first-degree breast cancer family history and polygenic risk score (PRS) to inform screening decisions among women aged 30-50 years. _Methods:_ Two established breast cancer models evaluated digital mammography screening strategies in the 1985 US birth cohort by risk groups defined by family history and PRS based on 313 single nucleotide polymorphisms. Strategies varied in initiation age and interval. The benefits and harms were compared with those seen with 3 established screening guidelines. _Results:_ Women with a breast cancer family history who initiated biennial screening at age 40 years had a 36% increase in life-years gained and 20% more breast cancer deaths averted, but 21% more overdiagnoses and 63% more false positives. Screening tailored to PRS vs biennial screening from50 to 74 years had smaller positive effects on life-years gained and breast cancer deaths averted but also smaller increases in overdiagnoses and false positives. Combined use of family history and PRS vs biennial screening from 50 to 74 years had the greatest increase in life-years gained and breast cancer deaths averted. _Conclusions:_ Our results suggest that breast cancer family history and PRS could guide screening decisions before age 50 years among women at increased risk for breast cancer but expected increases in overdiagnoses and false positives should be expected

Modeling Ductal Carcinoma In Situ (DCIS): An Overview of CISNET Model Approaches

Background. Ductal carcinoma in situ (DCIS) can be a precursor to invasive breast cancer. Since the advent of screening mammography in the 1980’s, the incidence of DCIS has increased dramatically. The value of screen detection and treatment of DCIS, however, is a matter of controversy, as it is unclear the extent to which detection and treatment of DCIS prevents invasive disease and reduces breast cancer mortality. The aim of this paper is to provide an overview of existing Cancer Intervention and Surveillance Modelling Network (CISNET) modeling approaches for the natural history of DCIS, and to compare these to other modeling approaches reported in the literature. Design. Five of the 6 CISNET models currently include DCIS. Most models assume that some, but not all, lesions progress to invasive cancer. The natural history of DCIS cannot be directly observed and the CISNET models differ in their assumptions and in the data sources used to estimate the DCIS model parameters. Results. These model differences translate into variation in outcomes, such as the amount of overdiagnosis of DCIS, with estimates ranging from 34% to 72% for biennial screening from ages 50 to 74 y. The other models described in the literature also report a large range in outcomes, with progression rates varying from 20% to 91%. Limitations. DCIS grade was not yet included in the CISNET models. Conclusion. In the future, DCIS data by grade from active surveillance trials, the development of predictive markers of progression probability, and evidence from other screening modalities, such as tomosynthesis, may be used to inform and improve the models’ representation of DCIS, and might lead to convergence of the model estimates. Until then, the CISNET model results consistently show a considerable amount of overdiagnosis of DCIS, supporting the safety and value of observational trials for low-risk DCIS

Transition from film to digital mammography: Impact for breast cancer screening through the national breast and cervical cancer early detection program

Introduction The National Breast and Cervical Cancer Early Detection Program (NBCCEDP) provides mammograms and diagnostic services for low-income, uninsured women aged 40-64 years. Mammography facilities within the NBCCEDP gradually shifted from plain-film to digital mammography. The purpose of this study is to assess the impact of replacing film with digital mammography on health effects (deaths averted, life-years gained [LYG]); costs (for screening and diagnostics); and number of women reached. Methods NBCCEDP 2010 data and data representative of the program's target population were used in two established microsimulation models. Models simulated observed screening behavior including different screening intervals (annual, biennial, irregular) and starting ages (40, 50 years) for white, black, and Hispanic women. Model runs were performed in 2012. Results The models predicted 8.0-8.3 LYG per 1,000 film screens for black women, 5.9-7.5 for white women, and 4.0-4.5 for Hispanic women. For all race/ethnicity groups, digital mammography had more LYG than film mammography (2%-4%), but had higher costs (34%-35%). Assuming a fixed budget, 25%-26% fewer women could be served, resulting in 22%-24% fewer LYG if all mammograms were converted to digital. The loss in LYG could be reversed to an 8%-13% increase by only including biennial screening. Conclusions Digital could result in slightly more LYG than film mammography. However, with a fixed budget, fewer women may be served with fewer LYG. Changes in the program, such as only including biennial screening, will increase LYG/screen and could offset the potential decrease in LYG when shifting to digital mammography

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. Primary Funding Source: National Cancer Institute

Benefits, harms, and costs for breast cancer screening after US implementation of digital mammography

Background Compared with film, digital mammography has superior sensitivity but lower specificity for women aged 40 to 49 years and women with dense breasts. Digital has replaced film in virtually all US facilities, but overall population health and cost from use of this technology are unclear. Methods Using five independent models, we compared digital screening strategies starting at age 40 or 50 years applied annually, biennially, or based on density with biennial film screening from ages 50 to 74 years and with no screening. Common data elements included cancer incidence and test performance, both modified by breast density. Lifetime outcomes included mortality, quality-adjusted life-years, and screening and treatment costs. Results For every 1000 women screened biennially from age 50 to 74 years, switching to digital from film yielded a median within-model improvement of 2 life-years, 0.27 additional deaths averted, 220 additional false-positive results, and $0.35 million more in costs. For an individual woman, this translates to a health gain of 0.73 days. Extending biennial digital screening to women ages 40 to 49 years was cost-effective, although results were sensitive to quality-of-life decrements related to screening and false positives. Targeting annual screening by density yielded similar outcomes to targeting by age. Annual screening approaches could increase costs to$5.26 million per 1000 women, in part because of higher numbers of screens and false positives, and were not efficient or cost-effective. Conclusions The transition to digital breast cancer screening in the United States increased total costs for small added health benefits. The value of digital mammography screening among women aged 40 to 49 years depends on women's preferences regarding false positives

Tailoring breast cancer screening intervals by breast density and risk for women aged 50 years or older: Collaborative modeling of screening outcomes

Background: Biennial screening is generally recommended for average-risk women aged 50 to 74 years, but tailored screening may provide greater benefits. Objective: To estimate outcomes for various screening intervals after age 50 year

Collaborative modeling of the benefits and harms associated with different U.S. Breast cancer screening strategies

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 qualityadjusted 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 bene-fits, 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