Harms of Restrictive Risk-Based Mammographic Breast Cancer Screening

Breast Cancer Screening in Women With Dense Breasts: Current Status and Future Directions for Appropriate Risk Stratification and Imaging Utilization

Breast density continues to be a prevailing topic in the field of breast imaging, with continued complexities contributing to overall confusion and controversy among patients and the medical community. In this article, we explore the current status of breast cancer screening in women with dense breasts including breast density legislation. Risk-based approaches to supplemental screening may be more financially cost-effective. While all advanced imaging modalities detect additional primarily invasive, node-negative cancers, the degree to which this occurs can vary by density category. Future directions include expanding the use of density-inclusive risk models with appropriate risk stratification and imaging utilization. Further research is needed, however, to better understand how to optimize population-based screening programs with knowledge of patients' individualized risk, including breast density assessment, to improve the benefit-to-harm ratio of breast cancer screening.

Evidence from a BreastScreen cohort does not support a longer inter-screen interval in women who have no conventional risk factors for breast cancer

Objectives

To determine screening outcomes in women who have no recorded risk factors for breast cancer.

Methods

A retrospective population-based cohort study included all 1,026,137 mammography screening episodes in 323,082 women attending the BreastScreen Western Australia (part of national biennial screening) program between July 2007 and June 2017. Cancer detection rates (CDR) and interval cancer rates (ICR) were calculated in screening episodes with no recorded risk factors for breast cancer versus at least one risk factor stratified by age. CDR was further stratified by timeliness of screening (<27 versus ≥27 months); ICR was stratified by breast density.

Results

Amongst 566,948 screens (55.3%) that had no recorded risk factors, 2347 (40.9%) screen-detected cancers were observed. In screens with no risk factors, CDR was 50 (95%CI 48–52) per 10,000 screens and ICR was 7.9 (95%CI 7.4–8.4) per 10,000 women-years, estimates that were lower than screens with at least one risk factor (CDR 83 (95%CI 80–86) per 10,000 screens, ICR 12.2 (95%CI 11.5–13.0) per 10,000 women-years). Compared to timely screens with risk factors, delayed screens with no risk factors had similar CDR across all age groups and a higher proportion of node positive cancers (26.1% vs 20.7%). ICR was lowest in screens that had no risk factors nor dense breasts in all age groups.

Conclusions

Majority of screens had no recorded breast cancer risk factors, hence a substantial proportion of screen-detected cancers occur in these screening episodes. Our findings may not justify less frequent screening in women with no risk factors.

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40.9% of screen-detected breast cancers occurred in women with no risk factors.

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Cancer detection rate was 50/10,000 in screens with no risk factors.

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Cancer size and nodal status were no more favourable in screens with no risk factors.

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Interval cancer rate was lowest in screens with no risk factors nor dense breasts.

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Our findings may not justify less frequent screening in women with no risk factors.

The current status of risk-stratified breast screening

Apart from high-risk scenarios such as the presence of highly penetrant genetic mutations, breast screening typically comprises mammography or tomosynthesis strategies defined by age. However, age-based screening ignores the range of breast cancer risks that individual women may possess and is antithetical to the ambitions of personalised early detection. Whilst screening mammography reduces breast cancer mortality, this is at the risk of potentially significant harms including overdiagnosis with overtreatment, and psychological morbidity associated with false positives. In risk-stratified screening, individualised risk assessment may inform screening intensity/interval, starting age, imaging modality used, or even decisions not to screen. However, clear evidence for its benefits and harms needs to be established. In this scoping review, the authors summarise the established and emerging evidence regarding several critical dependencies for successful risk-stratified breast screening: risk prediction model performance, epidemiological studies, retrospective clinical evaluations, health economic evaluations and qualitative research on feasibility and acceptability. Family history, breast density or reproductive factors are not on their own suitable for precisely estimating risk and risk prediction models increasingly incorporate combinations of demographic, clinical, genetic and imaging-related parameters. Clinical evaluations of risk-stratified screening are currently limited. Epidemiological evidence is sparse, and randomised trials only began in recent years.

A framework for personalized mammogram screening

Breast cancer screening guidelines serve as crucial evidence-based recommendations in deciding when to begin regular screenings. However, due to developments in breast cancer research and differences in research interpretation, screening guidelines can vary between organizations and within organizations over time. This leads to significant lapses in adopting updated guidelines, variable decision making between physicians, and unnecessary screening for low to moderate risk patients (Jacobson and Kadiyala, 2017; Corbelli et al., 2014). For analysis, risk factors were assessed for patient screening behaviors and results. The outcome variable for the first analysis was whether the patient had undergone screening. The risk factors considered were age, marital status, education level, rural versus urban residence, and family history of breast cancer. The outcome variable for the second analysis was whether patients who had undergone breast cancer screening presented abnormal results. The risk factors considered were age, Body Mass Index, family history, smoking and alcohol status, hormonal contraceptive use, Hormone Replacement Therapy use, age of first pregnancy, number of pregnancies (parity), age of first menses, rural versus urban residence, and whether or not patients had at least one child. Logistic regression analysis displayed strong associations for both outcome variables. Risk of screening nonattendance was negatively associated with age as a continuous variable, age as a dichotomous variable, being married, any college education, and family history. Risk of one or more abnormal mammogram findings was positively associated with family history, and hormonal contraceptive use. This procedure will be further developed to incorporate additional risk factors and refine the analysis of currently implemented risk factors.

Breast Cancer Screening in Inner City and County Populations: A Tale of Two Centers

BACKGROUND

New York's statewide "Get Screened, No Excuses" campaign has been one of the nation's most aggressive actions to improve access to breast cancer screening. Inner city and suburban county medical centers' initiatives were studied to compare outcomes of breast cancer screening and factors that influence access to care.

METHODS

Women delinquent in breast cancer screening one year or greater were offered patient navigator services to aid in timely breast cancer screening. Time-to-event completion rates among different stages of breast cancer screening stages in City and County women were compared. Time-to-event completion rates among different stages of breast cancer screening stages.

RESULTS

2505 women aged ≥40 years accepted PN services. Mean (SD) age of patients was 56.2 (10) years. The mean (SD) age of those who completed breast screening vs. those who did not was 56.8 (10) and 52.5 (.9) years, respectively (P < .01). The rates of screening completion during physical examination, mammography and biopsy stages were 74%, 78% and 100% in City vs. 98%, 85% and 100% in County, respectively (P < .001). Screening phase was the significant predictor of time to completion for breast cancer screening in Cox regression analysis. Over 85% of women completed the breast cancer screening, 74% in City and 97.6% in County (P < .001).

DISCUSSION

Screening phase is an important predictor of time-to complete breast cancer screening. Center location served as the effect modifier of the relationship. The rate of completing the screening was significantly higher and faster among Suburban County compared to Inner City women.

Risk Stratification for Screening Mammography: Benefits and Harms

OBJECTIVE

The purpose of this article is to compare commonly used breast cancer risk assessment models, describe the machine learning approach and big data in risk prediction, and summarize the potential benefits and harms of restrictive risk-based screening.

CONCLUSION

The commonly used risk assessment models for breast cancer can be complex and cumbersome to use. Each model incorporates different sets of risk factors, which are weighted differently and can produce different results for the same patient. No model is appropriate for all subgroups of the general population and only one model incorporates mammographic breast density. Future development of risk prediction tools that are generalizable and simpler to use are needed in guiding clinical decisions.