Collaborative Modeling to Compare Different Breast Cancer Screening Strategies: A Decision Analysis for the US Preventive Services Task Force.

Importance: The effects of breast cancer incidence changes and advances in screening and treatment on outcomes of different screening strategies are not well known. Objective: To estimate outcomes of various mammography screening strategies. Design, Setting, and Population: Comparison of outcomes using 6 Cancer Intervention and Surveillance Modeling Network (CISNET) models and national data on breast cancer incidence, mammography performance, treatment effects, and other-cause mortality in US women without previous cancer diagnoses. Exposures: Thirty-six screening strategies with varying start ages (40, 45, 50 years) and stop ages (74, 79 years) with digital mammography or digital breast tomosynthesis (DBT) annually, biennially, or a combination of intervals. Strategies were evaluated for all women and for Black women, assuming 100% screening adherence and "real-world" treatment. Main Outcomes and Measures: Estimated lifetime benefits (breast cancer deaths averted, percent reduction in breast cancer mortality, life-years gained), harms (false-positive recalls, benign biopsies, overdiagnosis), and number of mammograms per 1000 women. Results: Biennial screening with DBT starting at age 40, 45, or 50 years until age 74 years averted a median of 8.2, 7.5, or 6.7 breast cancer deaths per 1000 women screened, respectively, vs no screening. Biennial DBT screening at age 40 to 74 years (vs no screening) was associated with a 30.0% breast cancer mortality reduction, 1376 false-positive recalls, and 14 overdiagnosed cases per 1000 women screened. Digital mammography screening benefits were similar to those for DBT but had more false-positive recalls. Annual screening increased benefits but resulted in more false-positive recalls and overdiagnosed cases. Benefit-to-harm ratios of continuing screening until age 79 years were similar or superior to stopping at age 74. In all strategies, women with higher-than-average breast cancer risk, higher breast density, and lower comorbidity level experienced greater screening benefits than other groups. Annual screening of Black women from age 40 to 49 years with biennial screening thereafter reduced breast cancer mortality disparities while maintaining similar benefit-to-harm trade-offs as for all women. Conclusions: This modeling analysis suggests that biennial mammography screening starting at age 40 years reduces breast cancer mortality and increases life-years gained per mammogram. More intensive screening for women with greater risk of breast cancer diagnosis or death can maintain similar benefit-to-harm trade-offs and reduce mortality disparities.

Supplemental magnetic resonance imaging plus mammography compared with magnetic resonance imaging or mammography by extent of breast density.

BACKGROUND: Examining screening outcomes by breast density for breast magnetic resonance imaging (MRI) with or without mammography could inform discussions about supplemental MRI in women with dense breasts. METHODS: We evaluated 52 237 women aged 40-79 years who underwent 2611 screening MRIs alone and 6518 supplemental MRI plus mammography pairs propensity score-matched to 65 810 screening mammograms. Rates per 1000 examinations of interval, advanced, and screen-detected early stage invasive cancers and false-positive recall and biopsy recommendation were estimated by breast density (nondense = almost entirely fatty or scattered fibroglandular densities; dense = heterogeneously/extremely dense) adjusting for registry, examination year, age, race and ethnicity, family history of breast cancer, and prior breast biopsy. RESULTS: Screen-detected early stage cancer rates were statistically higher for MRI plus mammography vs mammography for nondense (9.3 vs 2.9; difference = 6.4, 95% confidence interval [CI] = 2.5 to 10.3) and dense (7.5 vs 3.5; difference = 4.0, 95% CI = 1.4 to 6.7) breasts and for MRI vs MRI plus mammography for dense breasts (19.2 vs 7.5; difference = 11.7, 95% CI = 4.6 to 18.8). Interval rates were not statistically different for MRI plus mammography vs mammography for nondense (0.8 vs 0.5; difference = 0.4, 95% CI = -0.8 to 1.6) or dense breasts (1.5 vs 1.4; difference = 0.0, 95% CI = -1.2 to 1.3), nor were advanced cancer rates. Interval rates were not statistically different for MRI vs MRI plus mammography for nondense (2.6 vs 0.8; difference = 1.8 (95% CI = -2.0 to 5.5) or dense breasts (0.6 vs 1.5; difference = -0.9, 95% CI = -2.5 to 0.7), nor were advanced cancer rates. False-positive recall and biopsy recommendation rates were statistically higher for MRI groups than mammography alone. CONCLUSION: MRI screening with or without mammography increased rates of screen-detected early stage cancer and false-positives for women with dense breasts without a concomitant decrease in advanced or interval cancers.

Benefits and Harms of Mammography Screening in 75 + Women to Inform Shared Decision-making: a Simulation Modeling Study.

BACKGROUND: Guidelines recommend shared decision-making (SDM) around mammography screening for women ≥ 75 years old. OBJECTIVE: To use microsimulation modeling to estimate the lifetime benefits and harms of screening women aged 75, 80, and 85 years based on their individual risk factors (family history, breast density, prior biopsy) and comorbidity level to support SDM in clinical practice. DESIGN, SETTING, AND PARTICIPANTS: We adapted two established Cancer Intervention and Surveillance Modeling Network (CISNET) models to evaluate the remaining lifetime benefits and harms of screening U.S. women born in 1940, at decision ages 75, 80, and 85 years considering their individual risk factors and comorbidity levels. Results were summarized for average- and higher-risk women (defined as having breast cancer family history, heterogeneously dense breasts, and no prior biopsy, 5% of the population). MAIN OUTCOMES AND MEASURES: Remaining lifetime breast cancers detected, deaths (breast cancer/other causes), false positives, and overdiagnoses for average- and higher-risk women by age and comorbidity level for screening (one or five screens) vs. no screening per 1000 women. RESULTS: Compared to stopping, one additional screen at 75 years old resulted in six and eight more breast cancers detected (10% overdiagnoses), one and two fewer breast cancer deaths, and 52 and 59 false positives per 1000 average- and higher-risk women without comorbidities, respectively. Five additional screens over 10 years led to 23 and 31 additional breast cancer cases (29-31% overdiagnoses), four and 15 breast cancer deaths avoided, and 238 and 268 false positives per 1000 average- and higher-risk screened women without comorbidities, respectively. Screening women at older ages (80 and 85 years old) and high comorbidity levels led to fewer breast cancer deaths and a higher percentage of overdiagnoses. CONCLUSIONS: Simulation models show that continuing screening in women ≥ 75 years old results in fewer breast cancer deaths but more false positive tests and overdiagnoses. Together, clinicians and 75 + women may use model output to weigh the benefits and harms of continued screening.

Population simulation modeling of disparities in US breast cancer mortality.

BACKGROUND: Populations of African American or Black women have persistently higher breast cancer mortality than the overall US population, despite having slightly lower age-adjusted incidence. METHODS: Three Cancer Intervention and Surveillance Modeling Network simulation teams modeled cancer mortality disparities between Black female populations and the overall US population. Model inputs used racial group-specific data from clinical trials, national registries, nationally representative surveys, and observational studies. Analyses began with cancer mortality in the overall population and sequentially replaced parameters for Black populations to quantify the percentage of modeled breast cancer morality disparities attributable to differences in demographics, incidence, access to screening and treatment, and variation in tumor biology and response to therapy. RESULTS: Results were similar across the 3 models. In 2019, racial differences in incidence and competing mortality accounted for a net ‒1% of mortality disparities, while tumor subtype and stage distributions accounted for a mean of 20% (range across models = 13%-24%), and screening accounted for a mean of 3% (range = 3%-4%) of the modeled mortality disparities. Treatment parameters accounted for the majority of modeled mortality disparities: mean = 17% (range = 16%-19%) for treatment initiation and mean = 61% (range = 57%-63%) for real-world effectiveness. CONCLUSION: Our model results suggest that changes in policies that target improvements in treatment access could increase breast cancer equity. The findings also highlight that efforts must extend beyond policies targeting equity in treatment initiation to include high-quality treatment completion. This research will facilitate future modeling to test the effects of different specific policy changes on mortality disparities.

Challenges and Opportunities of Epidemiological Studies to Reduce the Burden of Cancers in Young Adults.

There are >1.9 million survivors of adolescent and young adult cancers (AYA, diagnosed at ages 15-39) living in the U.S. today. Epidemiologic studies to address the cancer burden in this group have been a relatively recent focus of the research community. In this article, we discuss approaches and data resources for cancer epidemiology and health services research in the AYA population. We consider research that uses data from cancer registries, vital records, healthcare utilization, and surveys, and the accompanying challenges and opportunities of each. To illustrate the strengths of each data source, we present example research questions or areas that are aligned with these data sources and salient to AYAs. Integrating the respective strengths of cancer registry, vital records, healthcare data, and survey-based studies sets the foundation for innovative and impactful research on AYA cancer treatment and survivorship to inform a comprehensive understanding of diverse AYA needs and experiences.

Risk of cancer versus risk of cancer diagnosis? Accounting for diagnostic bias in predictions of breast cancer risk by race and ethnicity.

OBJECTIVES: Cancer risk prediction may be subject to detection bias if utilization of screening is related to cancer risk factors. We examine detection bias when predicting breast cancer risk by race/ethnicity. METHODS: We used screening and diagnosis histories from the Breast Cancer Surveillance Consortium to estimate risk of breast cancer onset and calculated relative risk of onset and diagnosis for each racial/ethnic group compared with non-Hispanic White women. RESULTS: Of 104,073 women aged 40-54 receiving their first screening mammogram at a Breast Cancer Surveillance Consortium facility between 2000 and 2018, 10.2% (n = 10,634) identified as Asian, 10.9% (n = 11,292) as Hispanic, and 8.4% (n = 8719) as non-Hispanic Black. Hispanic and non-Hispanic Black women had slightly lower screening frequencies but biopsy rates following a positive mammogram were similar across groups. Risk of cancer diagnosis was similar for non-Hispanic Black and White women (relative risk vs non-Hispanic White = 0.90, 95% CI 0.65 to 1.14) but was lower for Asian (relative risk = 0.70, 95% CI 0.56 to 0.97) and Hispanic women (relative risk = 0.82, 95% CI 0.62 to 1.08). Relative risks of disease onset were 0.78 (95% CI 0.68 to 0.88), 0.70 (95% CI 0.59 to 0.83), and 0.95 (95% CI 0.84 to 1.09) for Asian, Hispanic, and non-Hispanic Black women, respectively. CONCLUSIONS: Racial/ethnic differences in mammography and biopsy utilization did not induce substantial detection bias; relative risks of disease onset were similar to or modestly different than relative risks of diagnosis. Asian and Hispanic women have lower risks of developing breast cancer than non-Hispanic Black and White women, who have similar risks.

Breast cancer risk characteristics of women undergoing whole-breast ultrasound screening versus mammography alone.

BACKGROUND: There are no consensus guidelines for supplemental breast cancer screening with whole-breast ultrasound. However, criteria for women at high risk of mammography screening failures (interval invasive cancer or advanced cancer) have been identified. Mammography screening failure risk was evaluated among women undergoing supplemental ultrasound screening in clinical practice compared with women undergoing mammography alone. METHODS: A total of 38,166 screening ultrasounds and 825,360 screening mammograms without supplemental screening were identified during 2014-2020 within three Breast Cancer Surveillance Consortium (BCSC) registries. Risk of interval invasive cancer and advanced cancer were determined using BCSC prediction models. High interval invasive breast cancer risk was defined as heterogeneously dense breasts and BCSC 5-year breast cancer risk ≥2.5% or extremely dense breasts and BCSC 5-year breast cancer risk ≥1.67%. Intermediate/high advanced cancer risk was defined as BCSC 6-year advanced breast cancer risk ≥0.38%. RESULTS: A total of 95.3% of 38,166 ultrasounds were among women with heterogeneously or extremely dense breasts, compared with 41.8% of 825,360 screening mammograms without supplemental screening (p < .0001). Among women with dense breasts, high interval invasive breast cancer risk was prevalent in 23.7% of screening ultrasounds compared with 18.5% of screening mammograms without supplemental imaging (adjusted odds ratio, 1.35; 95% CI, 1.30-1.39); intermediate/high advanced cancer risk was prevalent in 32.0% of screening ultrasounds versus 30.5% of screening mammograms without supplemental screening (adjusted odds ratio, 0.91; 95% CI, 0.89-0.94). CONCLUSIONS: Ultrasound screening was highly targeted to women with dense breasts, but only a modest proportion were at high mammography screening failure risk. A clinically significant proportion of women undergoing mammography screening alone were at high mammography screening failure risk.

Association of Screening With Digital Breast Tomosynthesis vs Digital Mammography With Risk of Interval Invasive and Advanced Breast Cancer.

Importance: Digital breast tomosynthesis (DBT) was developed with the expectation of improving cancer detection in women with dense breasts. Studies are needed to evaluate interval invasive and advanced breast cancer rates, intermediary outcomes related to breast cancer mortality, by breast density and breast cancer risk. Objective: To evaluate whether DBT screening is associated with a lower likelihood of interval invasive cancer and advanced breast cancer compared with digital mammography by extent of breast density and breast cancer risk. Design, Setting, and Participants: Cohort study of 504 427 women aged 40 to 79 years who underwent 1 003 900 screening digital mammography and 375 189 screening DBT examinations from 2011 through 2018 at 44 US Breast Cancer Surveillance Consortium (BCSC) facilities with follow-up for cancer diagnoses through 2019 by linkage to state or regional cancer registries. Exposures: Breast Imaging Reporting and Data System (BI-RADS) breast density; BCSC 5-year breast cancer risk. Main Outcomes and Measures: Rates per 1000 examinations of interval invasive cancer within 12 months of screening mammography and advanced breast cancer (prognostic pathologic stage II or higher) within 12 months of screening mammography, both estimated with inverse probability weighting. Results: Among 504 427 women in the study population, the median age at time of mammography was 58 years (IQR, 50-65 years). Interval invasive cancer rates per 1000 examinations were not significantly different for DBT vs digital mammography (overall, 0.57 vs 0.61, respectively; difference, -0.04; 95% CI, -0.14 to 0.06; P = .43) or among all the 836 250 examinations with BCSC 5-year risk less than 1.67% (low to average-risk) or all the 413 061 examinations with BCSC 5-year risk of 1.67% or higher (high risk) across breast density categories. Advanced cancer rates were not significantly different for DBT vs digital mammography among women at low to average risk or at high risk with almost entirely fatty, scattered fibroglandular densities, or heterogeneously dense breasts. Advanced cancer rates per 1000 examinations were significantly lower for DBT vs digital mammography for the 3.6% of women with extremely dense breasts and at high risk of breast cancer (13 291 examinations in the DBT group and 31 300 in the digital mammography group; 0.27 vs 0.80 per 1000 examinations; difference, -0.53; 95% CI, -0.97 to -0.10) but not for women at low to average risk (10 611 examinations in the DBT group and 37 796 in the digital mammography group; 0.54 vs 0.42 per 1000 examinations; difference, 0.12; 95% CI, -0.09 to 0.32). Conclusions and Relevance: Screening with DBT vs digital mammography was not associated with a significant difference in risk of interval invasive cancer and was associated with a significantly lower risk of advanced breast cancer among the 3.6% of women with extremely dense breasts and at high risk of breast cancer. No significant difference was observed in the 96.4% of women with nondense breasts, heterogeneously dense breasts, or with extremely dense breasts not at high risk.

Estimation of Breast Cancer Overdiagnosis in a U.S. Breast Screening Cohort.

BACKGROUND: Mammography screening can lead to overdiagnosis-that is, screen-detected breast cancer that would not have caused symptoms or signs in the remaining lifetime. There is no consensus about the frequency of breast cancer overdiagnosis. OBJECTIVE: To estimate the rate of breast cancer overdiagnosis in contemporary mammography practice accounting for the detection of nonprogressive cancer. DESIGN: Bayesian inference of the natural history of breast cancer using individual screening and diagnosis records, allowing for nonprogressive preclinical cancer. Combination of fitted natural history model with life-table data to predict the rate of overdiagnosis among screen-detected cancer under biennial screening. SETTING: Breast Cancer Surveillance Consortium (BCSC) facilities. PARTICIPANTS: Women aged 50 to 74 years at first mammography screen between 2000 and 2018. MEASUREMENTS: Screening mammograms and screen-detected or interval breast cancer. RESULTS: The cohort included 35 986 women, 82 677 mammograms, and 718 breast cancer diagnoses. Among all preclinical cancer cases, 4.5% (95% uncertainty interval [UI], 0.1% to 14.8%) were estimated to be nonprogressive. In a program of biennial screening from age 50 to 74 years, 15.4% (UI, 9.4% to 26.5%) of screen-detected cancer cases were estimated to be overdiagnosed, with 6.1% (UI, 0.2% to 20.1%) due to detecting indolent preclinical cancer and 9.3% (UI, 5.5% to 13.5%) due to detecting progressive preclinical cancer in women who would have died of an unrelated cause before clinical diagnosis. LIMITATIONS: Exclusion of women with first mammography screen outside BCSC. CONCLUSION: On the basis of an authoritative U.S. population data set, the analysis projected that among biennially screened women aged 50 to 74 years, about 1 in 7 cases of screen-detected cancer is overdiagnosed. This information clarifies the risk for breast cancer overdiagnosis in contemporary screening practice and should facilitate shared and informed decision making about mammography screening. PRIMARY FUNDING SOURCE: National Cancer Institute.

Mammography adherence in relation to function-related indicators in older women.

Prior studies of screening mammography patterns by functional status in older women show inconsistent results. We used Breast Cancer Surveillance Consortium-Medicare linked data (1999-2014) to investigate the association of functional limitations with adherence to screening mammography in 145,478 women aged 66-74 years. Functional limitation was represented by a claims-based function-related indicator (FRI) score which incorporated 16 items reflecting functional status. Baseline adherence was defined as mammography utilization 9-30 months after the index screening mammography. Longitudinal adherence was examined among women adherent at baseline and defined as time from the index mammography to end of the first 30-month gap in mammography. Multivariable logistic regression and Cox proportional hazards models were used to investigate baseline and longitudinal adherence, respectively. Subgroup analyses were conducted by age (66-70 vs. 71-74 years). Overall, 69.6% of participants had no substantial functional limitation (FRI score 0), 23.5% had some substantial limitations (FRI score 1), and 6.8% had serious limitations (FRI score ≥ 2). Mean age at baseline was 68.5 years (SD = 2.6), 85.3% of participants were white, and 77.1% were adherent to screening mammography at baseline. Women with a higher FRI score were more likely to be non-adherent at baseline (FRI ≥ 2 vs. 0: aOR = 1.13, 95% CI = 1.06, 1.20, p-trend < 0.01). Similarly, a higher FRI score was associated with longitudinal non-adherence (FRI ≥ 2 vs. 0: aHR = 1.16, 95% CI = 1.11, 1.22, p-trend < 0.01). Effect measures of FRI did not differ substantially by age categories. Older women with a higher burden of functional limitations are less likely to be adherent to screening mammography recommendations.

Cost-Effectiveness of Screening Mammography Beyond Age 75 Years : A Cost-Effectiveness Analysis.

BACKGROUND: The cost-effectiveness of screening mammography beyond age 75 years remains unclear. OBJECTIVE: To estimate benefits, harms, and cost-effectiveness of extending mammography to age 80, 85, or 90 years according to comorbidity burden. DESIGN: Markov microsimulation model. DATA SOURCES: SEER (Surveillance, Epidemiology, and End Results) program and Breast Cancer Surveillance Consortium. TARGET POPULATION: U.S. women aged 65 to 90 years in groups defined by Charlson comorbidity score (CCS). TIME HORIZON: Lifetime. PERSPECTIVE: National health payer. INTERVENTION: Screening mammography to age 75, 80, 85, or 90 years. OUTCOME MEASURES: Breast cancer death, survival, and costs. RESULTS OF BASE-CASE ANALYSIS: Extending biennial mammography from age 75 to 80 years averted 1.7, 1.4, and 1.0 breast cancer deaths and increased days of life gained by 5.8, 4.2, and 2.7 days per 1000 women for comorbidity scores of 0, 1, and 2, respectively. Annual mammography beyond age 75 years was not cost-effective, but extending biennial mammography to age 80 years was ($54 000, $65 000, and $85 000 per quality-adjusted life-year [QALY] gained for women with CCSs of 0, 1, and ≥2, respectively). Overdiagnosis cases were double the number of deaths averted from breast cancer. RESULTS OF SENSITIVITY ANALYSIS: Costs per QALY gained were sensitive to changes in invasive cancer incidence and shift of breast cancer stage with screening mammography. LIMITATION: No randomized controlled trials of screening mammography beyond age 75 years are available to provide model parameter inputs. CONCLUSION: Although annual mammography is not cost-effective, biennial screening mammography to age 80 years is; however, the absolute number of deaths averted is small, especially for women with comorbidities. Women considering screening beyond age 75 years should weigh the potential harms of overdiagnosis versus the potential benefit of averting death from breast cancer. PRIMARY FUNDING SOURCE: National Cancer Institute and National Institutes of Health.

Breast biopsy patterns and findings among older women undergoing screening mammography: The role of age and comorbidity.

INTRODUCTION: Limited evidence exists on the impact of age and comorbidity on biopsy rates and findings among older women. MATERIALS AND METHODS: We used data from 170,657 women ages 66-94 enrolled in the United States Breast Cancer Surveillance Consortium (BCSC). We estimated one-year rates of biopsy by type (any, fine-needle aspiration (FNA), core or surgical) and yield of the most invasive biopsy finding (benign, ductal carcinoma in situ (DCIS) and invasive breast cancer) by age and comorbidity. Statistical significance was assessed using Wald statistics comparing coefficients estimated from logistic regression models adjusted for age, comorbidity, BCSC registry, and interaction between age and comorbidity. RESULTS: Of 524,860 screening mammograms, 9830 biopsies were performed following 7930 exams (1.5%) within one year, specifically 5589 core biopsies (1.1%), 3422 (0.7%) surgical biopsies and 819 FNAs (0.2%). Biopsy rates per 1000 screens decreased with age (66-74:15.7, 95%CI:14.8-16.8), 75-84:14.5(13.5-15.6), 85-94:13.2(11.3,15.4), ptrend < 0.001) and increased with Charlson Comorbidity Score (CCS = 0:14.4 (13.5-15.3), CCS = 1:16.6 (15.2-18.1), CCS ≥2:19.0 (16.9-21.5), ptrend < 0.001).Biopsy rates increased with CCS at ages 66-74 and 75-84 but not 85-94. Core and surgical biopsy rates increased with CCS at ages 66-74 only. For each biopsy type, the yield of invasive breast cancer increased with age irrespective of comorbidity. DISCUSSION: Women aged 66-84 with significant comorbidity in a breast cancer screening population had higher breast biopsy rates and similar rates of invasive breast cancer diagnosis than their counterparts with lower comorbidity. A considerable proportion of these diagnoses may represent overdiagnoses, given the high competing risk of death from non-breast-cancer causes among older women.

Prioritizing breast imaging services during the COVID pandemic: A survey of breast imaging facilities within the Breast Cancer Surveillance Consortium.

The COVID-19 pandemic disrupted breast cancer screening and diagnostic imaging in the United States. We sought to evaluate how medical facilities prioritized breast imaging services during periods of reduced capacity or upon re-opening after closures. In fall 2020, we surveyed 77 breast imaging facilities within the Breast Cancer Surveillance Consortium in the United States. The survey ascertained the pandemic's impact on clinical practices during March-September 2020. Nearly all facilities (97%) reported closing or operating at reduced capacity at some point during this period. All facilities were open by August 2020, though 14% were still operating at reduced capacity in September 2020. During periods of re-opening or reduced capacity, 93% of facilities reported prioritizing diagnostic breast imaging over breast cancer screening. For diagnostic imaging, facilities prioritized based on rescheduling canceled appointments (89%), specific indication for diagnostic imaging (89%), patient demand (84%), individual characteristics and risk factors (77%), and time since last imaging examination (72%). For screening mammography, facilities prioritized based on rescheduled cancelations (96%), patient demand (83%), individual characteristics and risk factors (73%), and time since last mammogram (71%). For biopsy services, more than 90% of facilities reported prioritization based on rescheduling of canceled exams, patient demand, patient characteristics and risk factors and level of suspicion on imaging. The observed patterns from this large and geographically diverse sample of facilities in the United States indicate that multiple factors were commonly used to prioritize breast imaging services during periods of reduced capacity.

Function-related Indicators and Outcomes of Screening Mammography in Older Women: Evidence from the Breast Cancer Surveillance Consortium Cohort.

BACKGROUND: Previous reports suggested risk of death and breast cancer varied by comorbidity and age in older women undergoing mammography. However, impacts of functional limitations remain unclear. METHODS: We used data from 238,849 women in the Breast Cancer Surveillance Consortium-Medicare linked database (1999-2015) who had screening mammogram at ages 66-94 years. We estimated risk of breast cancer, breast cancer death, and non-breast cancer death by function-related indicator (FRI) which incorporated 16 claims-based items and was categorized as an ordinal variable (0, 1, and 2+). Fine and Gray proportional sub-distribution hazards models were applied with breast cancer and death treated as competing events. Risk estimates by FRI scores were adjusted by age and NCI comorbidity index separately and stratified by these factors. RESULTS: Overall, 9,252 women were diagnosed with breast cancer, 406 died of breast cancer, and 41,640 died from non-breast cancer causes. The 10-year age-adjusted invasive breast cancer risk slightly decreased with FRI score [FRI = 0: 4.0%, 95% confidence interval (CI) = 3.8-4.1; FRI = 1: 3.9%, 95% CI = 3.7-4.2; FRI ≥ 2: 3.5%, 95% CI = 3.1-3.9). Risk of non-breast cancer death increased with FRI score (FRI = 0: 18.8%, 95% CI = 18.5-19.1; FRI = 1: 24.4%, 95% CI = 23.9-25.0; FRI ≥ 2: 39.8%, 95% CI = 38.8-40.9]. Risk of breast cancer death was low with minimal differences across FRI scores. NCI comorbidity index-adjusted models and stratified analyses yielded similar patterns. CONCLUSIONS: Risk of non-breast cancer death substantially increases with FRI score, whereas risk of breast cancer death is low regardless of functional status. IMPACT: Older women with functional limitations should be informed that they may not benefit from screening mammography.

Assessment of a Risk-Based Approach for Triaging Mammography Examinations During Periods of Reduced Capacity.

Importance: Breast cancer screening, surveillance, and diagnostic imaging services were profoundly limited during the initial phase of the coronavirus disease 2019 (COVID-19) pandemic. Objective: To develop a risk-based strategy for triaging mammograms during periods of decreased capacity. Design, Setting, and Participants: This population-based cohort study used data collected prospectively from mammography examinations performed in 2014 to 2019 at 92 radiology facilities in the Breast Cancer Surveillance Consortium. Participants included individuals undergoing mammography. Data were analyzed from August 10 to November 3, 2020. Exposures: Clinical indication for screening, breast symptoms, personal history of breast cancer, age, time since last mammogram/screening interval, family history of breast cancer, breast density, and history of high-risk breast lesion. Main Outcomes and Measures: Combinations of clinical indication, clinical history, and breast cancer risk factors that subdivided mammograms into risk groups according to their cancer detection rate were identified using classification and regression trees. Results: The cohort included 898 415 individuals contributing 1 878 924 mammograms (mean [SD] age at mammogram, 58.6 [11.2] years) interpreted by 448 radiologists, with 1 722 820 mammograms in individuals without a personal history of breast cancer and 156 104 mammograms in individuals with a history of breast cancer. Most individuals were aged 50 to 69 years at imaging (1 113 174 mammograms [59.2%]), and 204 305 (11.2%) were Black, 206 087 (11.3%) were Asian or Pacific Islander, 126 677 (7.0%) were Hispanic or Latina, and 40 021 (2.2%) were another race/ethnicity or mixed race/ethnicity. Cancer detection rates varied widely based on clinical indication, breast symptoms, personal history of breast cancer, and age. The 12% of mammograms with very high (89.6 [95% CI, 82.3-97.5] to 122.3 [95% CI, 108.1-138.0] cancers detected per 1000 mammograms) or high (36.1 [95% CI, 33.1-39.3] to 47.5 [95% CI, 42.4-53.3] cancers detected per 1000 mammograms) cancer detection rates accounted for 55% of all detected cancers and included mammograms to evaluate an abnormal mammogram or breast lump in individuals of all ages regardless of breast cancer history, to evaluate breast symptoms other than lump in individuals with a breast cancer history or without a history but aged 60 years or older, and for short-interval follow-up in individuals aged 60 years or older without a breast cancer history. The 44.2% of mammograms with very low cancer detection rates accounted for 13.1% of detected cancers and included annual screening mammograms in individuals aged 50 to 69 years (3.8 [95% CI, 3.5-4.1] cancers detected per 1000 mammograms) and all screening mammograms in individuals younger than 50 years regardless of screening interval (2.8 [95% CI, 2.6-3.1] cancers detected per 1000 mammograms). Conclusions and Relevance: In this population-based cohort study, clinical indication and individual risk factors were associated with cancer detection and may be useful for prioritizing mammography in times and settings of decreased capacity.

Comparative Access to and Use of Digital Breast Tomosynthesis Screening by Women's Race/Ethnicity and Socioeconomic Status.

Importance: Digital breast tomosynthesis (DBT) has reduced recall and increased cancer detection compared with digital mammography (DM), depending on women's age and breast density. Whether DBT screening access and use are equitable across groups of women based on race/ethnicity and socioeconomic characteristics is uncertain. Objective: To determine women's access to and use of DBT screening based on race/ethnicity, educational attainment, and income. Design, Setting, and Participants: This cross-sectional study included 92 geographically diverse imaging facilities across 5 US states, at which a total of 2 313 118 screening examinations were performed among women aged 40 to 89 years from January 1, 2011, to December 31, 2017. Data were analyzed from June 13, 2019, to August 18, 2020. Exposures: Women's race/ethnicity, educational level, and community-level household income. Main Outcomes and Measures: Access to DBT (on-site access) at time of screening by examination year and actual use of DBT vs DM screening by years since facility-level DBT adoption (≤5 years). Results: Among the 2 313 118 screening examinations included in the analysis, the proportion of women who had DBT access at the time of their screening appointment increased from 11 558 of 354 107 (3.3%) in 2011 to 194 842 of 235 972 (82.6%) in 2017. In 2012, compared with White women, Black (relative risk [RR], 0.05; 95% CI, 0.03-0.11), Asian American (RR, 0.28; 95% CI, 0.11-0.75), and Hispanic (RR, 0.38; 95% CI, 0.18-0.80) women had significantly less DBT access, and women with less than a high school education had lower DBT access compared with college graduates (RR, 0.18; 95% CI, 0.10-0.32). Among women attending facilities with both DM and DBT available at the time of screening, Black women experienced lower DBT use compared with White women attending the same facility (RRs, 0.83 [95% CI, 0.82-0.85] to 0.98 [95% CI, 0.97-0.99]); women with lower educational level experienced lower DBT use (RRs, 0.79 [95% CI, 0.74-0.84] to 0.88 [95% CI, 0.85-0.91] for non-high school graduates and 0.90 [95% CI, 0.89-0.92] to 0.96 [95% CI, 0.93-0.99] for high school graduates vs college graduates); and women within the lowest income quartile experienced lower DBT use vs women in the highest income quartile (RRs, 0.89 [95% CI, 0.87-0.91] to 0.99 [95% CI, 0.98-1.00]) regardless of the number of years after facility-level DBT adoption. Conclusions and Relevance: In this cross-sectional study, women of minority race/ethnicity and lower socioeconomic status experienced lower DBT access during the early adoption period and persistently lower DBT use when available over time. Future efforts should address racial/ethnic, educational, and financial barriers to DBT screening.

Barriers to Implementing Cardiovascular Risk Calculation in Primary Care: Alignment With the Consolidated Framework for Implementation Research.

INTRODUCTION: Cardiovascular disease risk calculators can inform and guide preventive strategies and treatment decisions by clinicians and patients. However, their uptake in primary care has been slow despite the recommendation in national cardiovascular disease prevention guidelines. Identifying the barriers to the implementation of cardiovascular disease risk calculators is essential for promoting their adoption. METHODS: The authors qualitatively analyzed structured physician educator notes written during an outreach education intervention with 44 small- and medium-sized primary care clinics that participated in the Agency for Healthcare Research and Quality‒funded EvidenceNOW Healthy Hearts Northwest trial. The authors coded barriers to the implementation of cardiovascular disease risk calculation and aligned them to the Consolidated Framework for Implementation Research. RESULTS: The authors identified 13 barriers from the physician educators' notes. The majority (n=8, 62%) mapped to the framework's Inner Setting domain. The 5 most commonly noted barriers were (1) time constraints to use a calculator (N=23 clinics), (2) limitations to accessing a calculator or the necessary information to use a calculator (N=22 clinics), (3) no or minimal buy-in from clinicians or staff to use a calculator (N=19 clinics), (4) reported patient fear of side effects from statin medications or patient dislike of taking medications per the guidelines (N=17 clinics), and (5) lack of documented clinic workflow for using a calculator (N=16 clinics). CONCLUSIONS: To improve the uptake of cardiovascular disease risk calculation in primary care, future cardiovascular disease prevention and implementation research should consider tailoring interventions to the common barriers to implementing cardiovascular disease risk calculation. TRIAL REGISTRATION: This study is registered at www.clinicaltrials.gov NCT02839382.

The Role of Social Determinants of Health in Self-Reported Access to Health Care Among Women Undergoing Screening Mammography.

Background: Social determinants of health (SDOH) contribute to health care disparities, with social and economic barriers often leading to difficulties in obtaining necessary care. We evaluated barriers to receiving health care, focusing on caretaker responsibilities, health insurance and cost, and transportation. Materials and Methods: We included women ages ≥40 years receiving screening mammography across three Breast Cancer Surveillance Consortium registries from 2012 to 2017. Women self-reported social and financial barriers to receiving health care in the 12 months before their screening mammogram. We evaluated woman- and census-based community-level factors associated with reporting a barrier using multivariate logistic regression. We assessed interaction with urban versus nonurban residence using Wald tests. Results: Among 393,430 women, 3.6% reported a barrier with a higher proportion in urban versus nonurban settings (3.9% [n = 11,977] vs. 2.2% [n = 1,655], respectively; p < 0.001). Among women reporting a barrier, health care cost and/or no insurance was the most common (49.3%), and no transportation was the least common (7.8%). Compared with white women, odds of reporting barriers were higher among black (adjusted odds ratio [aOR] = 1.30, 95% confidence interval [CI]: 1.16-1.44), Hispanic (aOR = 1.66, 95% CI: 1.53-1.80), and other race (aOR = 1.84, 95% CI: 1.65-2.04) women. Barriers were less likely in women with higher median household income (aOR = 0.69, 95% CI: 0.61-0.79) or higher average health insurance costs (aOR = 0.85, 95% CI: 0.74-0.98), but were more likely in high diversity index areas (aOR = 1.28, 95% CI: 1.11-1.48). Conclusions: Social and financial barriers exist based on race/ethnicity and SDOH related to income, insurance costs, and place of residence among women undergoing screening mammography. Breast imaging facilities could utilize information on these barriers to improve biennial screening adherence or ensure that women with abnormal findings obtain appropriate follow-up care through targeted interventions.

Screening Mammography Outcomes: Risk of Breast Cancer and Mortality by Comorbidity Score and Age.

BACKGROUND: Potential benefits of screening mammography among women ages 75 years and older remain unclear. METHODS: We evaluated 10-year cumulative incidence of breast cancer and death from breast cancer and other causes by Charlson Comorbidity Index (CCI) and age in the Medicare-linked Breast Cancer Surveillance Consortium (1999-2010) cohort of 222 088 women with no less than 1 screening mammogram between ages 66 and 94 years. RESULTS: During median follow-up of 107 months, 7583 were diagnosed with invasive breast cancer and 1742 with ductal carcinoma in situ; 471 died from breast cancer and 42 229 from other causes. The 10-year cumulative incidence of invasive breast cancer did not change with increasing CCI but decreased slightly with age: ages 66-74 years (CCI0 = 4.0% [95% CI = 3.9% to 4.2%] vs CCI ≥ 2 = 3.9% [95% CI = 3.5% to 4.3%]); ages 75-84 years (CCI0 = 3.7% [95% CI = 3.5% to 3.9%] vs CCI ≥ 2 = 3.4% [95% CI = 2.9% to 3.9%]); and ages 85-94 years (CCI0 = 2.7% [95% CI = 2.3% to 3.1%] vs CCI ≥ 2 = 2.1% [95% CI = 1.3% to 3.0%]). The 10-year cumulative incidence of other-cause death increased with increasing CCI and age: ages 66-74 years (CCI0 = 10.4% [95% CI = 10.3 to 10.7%] vs CCI ≥ 2 = 43.4% [95% CI = 42.2% to 44.4%]), ages 75-84 years (CCI0 = 29.8% [95% CI = 29.3% to 30.2%] vs CCI ≥ 2 = 61.7% [95% CI = 60.2% to 63.3%]), and ages 85 to 94 years (CCI0 = 60.3% [95% CI = 59.1% to 61.5%] vs CCI ≥ 2 = 84.8% [95% CI = 82.5% to 86.9%]). The 10-year cumulative incidence of breast cancer death was small and did not vary by age: ages 66-74 years = 0.2% (95% CI = 0.2% to 0.3%), ages 75-84 years = 0.29% (95% CI = 0.25% to 0.34%), and ages 85 to 94 years = 0.3% (95% CI = 0.2% to 0.4%). CONCLUSIONS: Cumulative incidence of other-cause death was many times higher than breast cancer incidence and death, depending on comorbidity and age. Hence, older women with increased comorbidity may experience diminished benefit from continued screening.