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Annual surveillance mammography is recommended for breast cancer survivors on the basis of observational studies and meta-analyses showing reduced breast cancer mortality and improved quality of life. However, breast cancer survivors are at higher risk of subsequent breast cancer and have a fourfold increased risk of interval breast cancers compared with individuals without a personal history of breast cancer. Supplemental surveillance modalities offer increased cancer detection compared with mammography alone, but utilization is variable, and benefits must be balanced with possible harms of false-positive findings. In this review, we describe the current state of mammographic surveillance, summarize evidence for supplemental surveillance in breast cancer survivors, and explore a risk-based approach to selecting surveillance imaging strategies. Further research identifying predictors associated with increased risk of interval second breast cancers and development of validated risk prediction tools may help physicians and patients weigh the benefits and harms of surveillance breast imaging and decide on a personalized approach to surveillance for improved breast cancer outcomes.

PurposeThe aim of this study was to develop a prioritization strategy for scheduling immediate screening mammographic interpretation and possible diagnostic evaluation.MethodsA population-based cohort with screening mammograms performed from 2012 to 2020 at 126 radiology facilities from 7Breast Cancer Surveillance Consortium registries was identified. Classification trees identified combinations of clinical history (age, BI-RADS® density, time since prior mammogram, history of false-positive recall or biopsy result), screening modality (digital mammography, digital breast tomosynthesis), and facility characteristics (profit status, location, screening volume, practice type, academic affiliation) that grouped screening mammograms by recall rate, with ≥12/100 considered high and ≥16/100 very high. An efficiency ratio was estimated as the percentage of recalls divided by the percentage of mammograms.ResultsThe study cohort included 2,674,051 screening mammograms in 925,777 women, with 235,569 recalls. The most important predictor of recall was time since prior mammogram, followed by age, history of false-positive recall, breast density, history of benign biopsy, and screening modality. Recall rates were very high for baseline mammograms (21.3/100; 95% confidence interval, 19.7-23.0) and high for women with ≥5 years since prior mammogram (15.1/100; 95% confidence interval, 14.3-16.1). The 9.2% of mammograms in subgroups with very high and high recall rates accounted for 19.2% of recalls, an efficiency ratio of 2.1 compared with a random approach. Adding women

Data describing outcomes for patients with early stage lung cancer who undergo expectant management is lacking, despite evidence of a sub-population with indolent malignancies. We used the National Cancer Data Base (NCDB) to identify factors associated with active surveillance for early stage lung cancer. Additionally, we sought to describe outcomes of three different care plans: active surveillance, no treatment, and Stereotactic Body Radiation Therapy (SBRT).Patients diagnosed in 2010 to 2017 with early stage lung cancer who underwent active surveillance, no treatment, and SBRT were retrospectively identified in the NCDB. Multinomial logistic regression was used to assess care plan selection. Kaplan Meier analysis was used to assess overall survival (OS).We identified 30,107 patients that met our inclusion criteria: 838 (3%) underwent active surveillance, 6388 patients (21%) received no treatment, and 22,881 (76%) underwent SBRT. Black race (relative risk ratio (RRR): 1.66) and older age (RRR: 1.02) were significant positive predictors of active surveillance selection. Conversely, higher tumor stage (RRR: 0.26) and squamous cell carcinoma (RRR: 0.35) were significant negative predictors of active surveillance selection. Kaplan Meier analysis revealed a longer median OS associated with active surveillance compared to no treatment at 49.3 months versus 26.5 months, respectively. SBRT OS was 43.1 months.We identified a population of lung cancer patients who underwent expectant management with favorable outcomes. Additionally, we identified factors associated with active surveillance selection. The selection of active surveillance over no treatment was associated with significantly longer OS.

Background Minimally invasive breast biopsy (MIBB) is the standard of care for the diagnosis of breast cancer, with consensus guidelines suggesting MIBB goals of 90% of total biopsies. In a previous study of patients in the rural state of Vermont, USA (population size of 640,000), rural breast cancer patients had open biopsies 42% of the time compared to 29% of urban breast cancer patients. The aim of this study was to assess overall population‐based biopsy trends in Vermont. Methods The Vermont Breast Cancer Surveillance System (VBCSS) was used to identify women receiving MIBB and excisional breast biopsies in Vermont. Patient zip code at the time of initial biopsy was used to determine the patient residence rurality by rural–urban commuting area codes (RUCA 2.0™). Results There were 9122 diagnostic episodes from 1999 to 2018. MIBB was the initial biopsy method in 7524 (82.5%) cases, while surgical excision was the initial biopsy method in 1598 (17.5%) cases. A linear trend fit estimated an increase of 1.3% per year (p, Minimally invasive needle biopsy has been the standard of care for breast cancer diagnosis since the early 2000’s. However, a number of studies through 2010, including our prior report from Vermont, showed persistently high rates of open surgical biopsies in rural populations. In this manuscript, we report updated results from a state‐wide retrospective study of breast biopsies, stratified by rurality of patient residence; we evaluated the trend of minimally invasive breast biopsies from 1999 to 2018 and show for the first time that the state as a whole has reached the standard of care of over 90% breast biopsies performed as minimally invasive.

Background Elevated mammographic breast density is a strong breast cancer risk factor with poorly understood etiology. Increased deposition of collagen, one of the main fibrous proteins present in breast stroma, has been associated with increased mammographic density. Collagen fiber architecture has been linked to poor outcomes in breast cancer. However, relationships of quantitative collagen fiber features assessed in diagnostic biopsies with mammographic density and lesion severity are not well-established. Methods Clinically indicated breast biopsies from 65 in situ or invasive breast cancer cases and 73 frequency matched-controls with a benign biopsy result were used to measure collagen fiber features (length, straightness, width, alignment, orientation and density (fibers/µm2)) using second harmonic generation microscopy in up to three regions of interest (ROIs) per biopsy: normal, benign breast disease, and cancer. Local and global mammographic density volumes were quantified in the ipsilateral breast in pre-biopsy full-field digital mammograms. Associations of fibrillar collagen features with mammographic density and severity of biopsy diagnosis were evaluated using generalized estimating equation models with an independent correlation structure to account for multiple ROIs within each biopsy section. Results Collagen fiber density was positively associated with the proportion of stroma on the biopsy slide (p p = 0.035) and within a 2 mm perilesional ring (p = 0.02), but not with global mammographic density measures. As severity of the breast biopsy diagnosis increased at the ROI level, collagen fibers tended to be less dense, shorter, straighter, thinner, and more aligned with one another (p Conclusions Collagen fiber density was positively associated with local, but not global, mammographic density, suggesting that collagen microarchitecture may not translate into macroscopic mammographic features. However, collagen fiber features may be markers of cancer risk and/or progression among women referred for biopsy based on abnormal breast imaging.

Background A paucity of research addresses breast cancer screening strategies for women at lower-than-average breast cancer risk. The aim of this study was to examine screening harms and benefits among women aged 50-74 years at lower-than-average breast cancer risk by breast density. Methods Three well-established, validated Cancer Intervention and Surveillance Network models were used to estimate the lifetime benefits and harms of different screening scenarios, varying by screening interval (biennial, triennial). Breast cancer deaths averted, life-years and quality-adjusted life-years gained, false-positives, benign biopsies, and overdiagnosis were assessed by relative risk (RR) level (0.6, 0.7, 0.85, 1 [average risk]) and breast density category, for US women born in 1970. Results Screening benefits decreased proportionally with decreasing risk and with lower breast density. False-positives, unnecessary biopsies, and the percentage overdiagnosis also varied substantially by breast density category; false-positives and unnecessary biopsies were highest in the heterogeneously dense category. For women with fatty or scattered fibroglandular breast density and a relative risk of no more than 0.85, the additional deaths averted and life-years gained were small with biennial vs triennial screening. For these groups, undergoing 4 additional screens (screening biennially [13 screens] vs triennially [9 screens]) averted no more than 1 additional breast cancer death and gained no more than 16 life-years and no more than 10 quality-adjusted life-years per 1000 women but resulted in up to 232 more false-positives per 1000 women. Conclusion Triennial screening from age 50 to 74 years may be a reasonable screening strategy for women with lower-than-average breast cancer risk and fatty or scattered fibroglandular breast density.

Background: Women at high risk for breast cancer due to genetics or risk factor profiles are counseled to adopt lifestyle, behavioral, and dietary changes to help reduce their risk. These recommendations are based on studies of women at average risk, so their effectiveness in high-risk women is unclear. Methods: We evaluated the impact of physical activity, smoking, alcohol consumption, and intake of folate and carotenoids on mammographic breast density—a proxy for breast cancer risk—among 387 high-risk women. Exposures were self-reported on questionnaires. Breast dense area, nondense area, and percent dense area were measured from screening mammograms with Library for Breast Radiodensity Assessment software. Cross-sectional associations were estimated with multivariable quantile regression models. Results: After adjusting for age, adiposity, reproductive history, and use of postmenopausal hormones, no breast density measure was associated with physical activity level, smoking status, alcohol consumption, or estimated intake of folate, alpha-carotene, beta-carotene, lutein/zeaxanthin, and beta-cryptoxanthin. Lycopene intake was associated with lower dense area when comparing the highest and lowest intake categories (adjusted difference in median = −14 cm2, 95% confidence interval: −29 to 1.3 cm2). This association may be explained by incomplete adjustment for adiposity. Conclusions: Recommended lifestyle, behavioral, and dietary changes to mitigate personal risk of breast cancer do not substantially impact mammographic breast density measures. Impact: Alternative strategies, such as increased uptake of chemoprevention, may better serve risk reduction efforts in women at high risk for breast cancer.

Core facilities have a ubiquitous and increasingly valuable presence at research institutions. Although many shared cores were originally created to provide routine services and access to complex and expensive instrumentation for the research community, they are frequently called upon by investigators to design protocols and procedures to help answer complex research questions. For instance, shared microscopy resources are evolving from providing access to and training on complex imaging instruments to developing detailed innovative protocols and experimental strategies, including sample preparation techniques, staining, complex imaging parameters, and high-level image analyses. These approaches require close intellectual collaboration between core staff and research investigators to formulate and coordinate plans for protocol development suited to the research question. Herein, we provide an example of such coordinated collaboration between a shared microscopy facility and a team of scientists and clinician–investigators to approach a complex multiprobe immunostaining, imaging, and image analysis project investigating the tumor microenvironment from human breast cancer samples. Our hope is that this example may be used to convey to institute administrators the critical importance of the intellectual contributions of the scientific staff in core facilities to research endeavors.

Background Estimating advanced breast cancer risk in women undergoing annual or biennial mammography could identify women who may benefit from less or more intensive screening. We developed an actionable model to predict cumulative 6-year advanced cancer (prognostic pathologic stage II or higher) risk according to screening interval. Methods We included 931 186 women aged 40-74 years in the Breast Cancer Surveillance Consortium undergoing 2 542 382 annual (prior mammogram within 11-18 months) or 752 049 biennial (prior within 19-30 months) screening mammograms. The prediction model includes age, race and ethnicity, body mass index, breast density, family history of breast cancer, and prior breast biopsy subdivided by menopausal status and screening interval. We used fivefold cross-validation to internally validate model performance. We defined higher than 95th percentile as high risk (>0.658%), higher than 75th percentile to 95th or less percentile as intermediate risk (0.380%-0.658%), and 75th or less percentile as low to average risk ( Results Obesity, high breast density, and proliferative disease with atypia were strongly associated with advanced cancer. The model is well calibrated and has an area under the receiver operating characteristics curve of 0.682 (95% confidence interval = 0.670 to 0.694). Based on women’s predicted advanced cancer risk under annual and biennial screening, 69.1% had low or average risk regardless of screening interval, 12.4% intermediate risk with biennial screening and average risk with annual screening, and 17.4% intermediate or high risk regardless of screening interval. Conclusion Most women have low or average advanced cancer risk and can undergo biennial screening. Intermediate-risk women may consider annual screening, and high-risk women may consider supplemental imaging in addition to annual screening.

Background: There is widespread interest in discriminating indolent from aggressive ductal carcinoma in situ (DCIS). We sought to evaluate collagen organization in the DCIS tumor microenvironment in relation to pathologic characteristics and patient outcomes. Methods: We retrieved fixed tissue specimens for 90 DCIS cases within the population-based Vermont DCIS Cohort. We imaged collagen fibers within 75 μm of the tumor/stromal boundary on hematoxylin and eosin–stained slides using multiphoton microscopy with second-harmonic generation. Automated software quantified collagen fiber length, width, straightness, density, alignment, and angle to the tumor/stroma boundary. Factor analysis identified linear combinations of collagen fiber features representing composite attributes of collagen organization. Results: Multiple collagen features were associated with DCIS grade, necrosis pattern, or periductal fibrosis (P < 0.05). After adjusting for treatments and nuclear grade, risk of recurrence (defined as any second breast cancer diagnosis) was lower among cases with greater collagen fiber width [hazard ratio (HR), 0.57 per one standard deviation increase; 95% confidence interval (CI), 0.39–0.84] and fiber density (HR, 0.60; 95% CI, 0.42–0.85), whereas risk was elevated among DCIS cases with higher fiber straightness (HR, 1.47; 95% CI, 1.05–2.06) and distance to the nearest two fibers (HR, 1.47; 95% CI, 1.06–2.02). Fiber length, alignment, and fiber angle were not associated with recurrence (P > 0.05). Five composite factors were identified, accounting for 72.4% of the total variability among fibers; three were inversely associated with recurrence (HRs ranging from 0.60 to 0.67; P ≤ 0.01). Conclusions: Multiple aspects of collagen organization around DCIS lesions are associated with recurrence risk. Impact: Collagen organization should be considered in the development of prognostic DCIS biomarker signatures.

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

Background Established mammography screening performance metrics use the initial screening mammography assessment because they were developed for radiologist performance auditing, yet these metrics are frequently used to inform health policy and screening decision making. The authors have developed new performance metrics based on the final assessment that consider the entire screening episode, including diagnostic workup. Methods The authors used data from 2,512,577 screening episodes during 2005-2017 at 146 facilities in the United States participating in the Breast Cancer Surveillance Consortium. Screening performance metrics based on the final assessment of the screening episode were compared with conventional metrics defined with the initial assessment. Results were also stratified by breast density and breast cancer risk. Results The cancer detection rates were similar for the final assessment (4.1 per 1000; 95% confidence interval [CI], 3.8-4.3 per 1000) and the initial assessment (4.1 per 1000; 95% CI, 3.9-4.3 per 1000). The interval cancer rate was 12% higher when it was based on the final assessment (0.77 per 1000; 95% CI, 0.71-0.83 per 1000) versus the initial assessment (0.69 per 1000; 95% CI, 0.64-0.74 per 1000), and this resulted in a modest difference in sensitivity (84.1% [95% CI, 83.0%-85.1%] vs 85.7% [95% CI, 84.8%-86.6%], respectively). Absolute differences in the interval cancer rate between final and initial assessments increased with breast density and breast cancer risk (eg, a difference of 0.29 per 1000 for women with extremely dense breasts and a 5-year risk >2.49%). Conclusions Established screening performance metrics underestimate the interval cancer rate of a mammography screening episode, particularly for women with dense breasts or an elevated breast cancer risk. Women, clinicians, policymakers, and researchers should use final-assessment performance metrics to support informed screening decisions.

Breast cancer screening with digital breast tomosynthesis may decrease false-positive results compared with digital mammography.To estimate the probability of receiving at least 1 false-positive result after 10 years of screening with digital breast tomosynthesis vs digital mammography in the US.An observational comparative effectiveness study with data collected prospectively for screening examinations was performed between January 1, 2005, and December 31, 2018, at 126 radiology facilities in the Breast Cancer Surveillance Consortium. Analysis included 903 495 individuals aged 40 to 79 years. Data analysis was conducted from February 9 to September 7, 2021.Screening modality, screening interval, age, and Breast Imaging Reporting and Data System breast density.Cumulative risk of at least 1 false-positive recall for further imaging, short-interval follow-up recommendation, and biopsy recommendation after 10 years of annual or biennial screening with digital breast tomosynthesis vs digital mammography, accounting for competing risks of breast cancer diagnosis and death.In this study of 903 495 women, 2 969 055 nonbaseline screening examinations were performed with interpretation by 699 radiologists. Mean (SD) age of the women at the time of the screening examinations was 57.6 (9.9) years, and 58% of the examinations were in individuals younger than 60 years and 46% were performed in women with dense breasts. A total of 15% of examinations used tomosynthesis. For annual screening, the 10-year cumulative probability of at least 1 false-positive result was significantly lower with tomosynthesis vs digital mammography for all outcomes: 49.6% vs 56.3% (difference, -6.7; 95% CI, -7.4 to -6.1) for recall, 16.6% vs 17.8% (difference, -1.1; 95% CI, -1.7 to -0.6) for short-interval follow-up recommendation, and 11.2% vs 11.7% (difference, -0.5; 95% CI, -1.0 to -0.1) for biopsy recommendation. For biennial screening, the cumulative probability of a false-positive recall was significantly lower for tomosynthesis vs digital mammography (35.7% vs 38.1%; difference, -2.4; 95% CI, -3.4 to -1.5), but cumulative probabilities did not differ significantly by modality for short-interval follow-up recommendation (10.3% vs 10.5%; difference, -0.1; 95% CI, -0.7 to 0.5) or biopsy recommendation (6.6% vs 6.7%; difference, -0.1; 95% CI, -0.5 to 0.4). Decreases in cumulative probabilities of false-positive results with tomosynthesis vs digital mammography were largest for annual screening in women with nondense breasts (differences for recall, -6.5 to -12.8; short-interval follow-up, 0.1 to -5.2; and biopsy recommendation, -0.5 to -3.1). Regardless of modality, cumulative probabilities of false-positive results were substantially lower for biennial vs annual screening (overall recall, 35.7 to 38.1 vs 49.6 to 56.3; short-interval follow-up, 10.3 to 10.5 vs 16.6 to 17.8; and biopsy recommendation, 6.6 to 6.7 vs 11.2 to 11.7); older vs younger age groups (eg, among annual screening in women ages 70-79 vs 40-49, recall, 39.8 to 47.0 vs 60.8 to 68.0; short-interval follow-up, 13.3 to 14.2 vs 20.7 to 20.9; and biopsy recommendation, 9.1 to 9.3 vs 13.2 to 13.4); and women with entirely fatty vs extremely dense breasts (eg, among annual screening in women aged 50-59 years, recall, 29.1 to 36.3 vs 58.8 to 60.4; short-interval follow-up, 8.9 to 11.6 vs 19.5 to 19.8; and biopsy recommendation, 4.9 to 8.0 vs 15.1 to 15.3).In this comparative effectiveness study, 10-year cumulative probabilities of false-positive results were lower on digital breast tomosynthesis vs digital mammography. Biennial screening interval, older age, and nondense breasts were associated with larger reductions in false-positive probabilities than screening modality.

We evaluated self-report of decision quality and regret with breast cancer surgical treatment by pre-operative breast MRI use in women recently diagnosed with breast cancer.We conducted a survey with 957 women aged 18 + with stage 0-III breast cancer identified in the Breast Cancer Surveillance Consortium. Participants self-reported receipt of pre-operative breast MRI. Primary outcomes were process measures in the Breast Cancer Surgery Decision Quality Instrument (BCS-DQI) (continuous outcome) and Decision Regret Scale (dichotomized outcome as any/none). Generalized estimating equations with linear and logit link were used to estimate adjusted associations between breast MRI and primary outcomes. All analyses were also stratified by breast density.Survey participation rate was 27.9% (957/3430). Study population was primarily 60 years, White, college educated, and diagnosed with early-stage breast cancer. Pre-operative breast MRI was reported in 46% of women. A higher proportion of women who were younger age ( 50 years), commercially insured, and self-detected their breast cancer reported pre-operative breast MRI use. In adjusted analysis, pre-operative breast MRI use compared with no use was associated with a small but statistically significantly higher decision quality scores (69.5 vs 64.7, p-value = 0.043). Decision regret did not significantly differ in women who reported pre-operative breast MRI use compared with no use (54.2% v. 48.7%, respectively, p-value = 0.11). Study results did not vary when stratified by breast density for either primary outcome.Breast MRI use in the diagnostic work-up of breast cancer does not negatively alter women's perceptions of surgical treatment decisions in early survivorship.NCT03029286.

BACKGROUND: Consistency in reporting Breast Imaging Reporting and Data System (BI-RADS) breast density on mammograms is important because breast density is used for breast cancer risk assessment and is reported directly to women and clinicians to inform decisions about supplemental screening. PURPOSE: To assess the consistency of BI-RADS density reporting between digital breast tomosynthesis (DBT) and digital mammography (DM) and evaluate density as a breast cancer risk factor when assessed using DM versus DBT. MATERIALS AND METHODS: The Breast Cancer Surveillance Consortium is a prospective cohort study of women undergoing mammography with DM or DBT. This secondary analysis included women aged 40–79 years who underwent at least two screening mammography examinations less than 36 months apart. Percentage agreement and κ statistic were estimated for pairs of BI-RADS density assessments. Cox proportional hazards regression was used to calculate hazard ratios (HRs) of breast density as a risk factor for invasive breast cancer. RESULTS: A total of 403 326 pairs of mammograms from 342 149 women were evaluated. There were no significant differences in breast density assessment in pairs consisting of one DM and one DBT examination (57 516 of 74 729 [77%]; κ = 0.64), two DM examinations (238 678 of 301 743 [79%]; κ = 0.67), and two DBT examinations (20 763 of 26 854 [77%]; κ = 0.65). Results were similar when restricting the analyses to pairs read by the same radiologist. The breast cancer HRs for breast density were similar for DM and DBT (P = .45 for interaction). The HRs for density acquired using DM and DBT, respectively, were 0.55 (95% CI: 0.49, 0.63) and 0.37 (95% CI: 0.21, 0.66) for almost entirely fat, 1.47 (95% CI: 1.37, 1.58) and 1.36 (95% CI: 1.02, 1.82) for heterogeneously dense, and 1.72 (95% CI: 1.54, 1.93) and 2.05 (95% CI: 1.25, 3.36) for extremely dense breasts. CONCLUSION: Radiologist reporting of Breast Imaging Reporting and Data System density obtained with digital breast tomosynthesis did not differ from that obtained with digital mammography. © RSNA, 2021 Online supplemental material is available for this article.

Background: We evaluated differences in diagnostic mammography performance based on women's race/ethnicity. Methods: This cohort study included 267,868 diagnostic mammograms performed to evaluate screening mammogram findings at 98 facilities in the Breast Cancer Surveillance Consortium between 2005 and 2017. Mammogram assessments were recorded prospectively and breast cancers occurring within one year were ascertained. Performance statistics were calculated with 95% confidence intervals (CI) for each racial/ethnic group. Multivariable regression was used to control for personal characteristics and imaging facility. Results: Among non-Hispanic White (70%), non-Hispanic Black (13%), Asian/Pacific Islander (10%), and Hispanic (7%) women, the invasive cancer detection rate (iCDR, per 1,000 mammograms) and positive predictive value (PPV2) were highest among non-Hispanic White women (iCDR, 35.8; 95% CI, 35.0–36.7; PPV2, 27.8; 95% CI, 27.3–28.3) and lowest among Hispanic women (iCDR, 22.3; 95% CI, 20.2–24.6; PPV2, 19.4; 95% CI, 18.0–20.9). Short interval follow-up recommendations were most common among non-Hispanic Black women [(31.0%; 95% CI, 30.6%–31.5%) vs. other groups, range, 16.6%–23.6%]. False-positive biopsy recommendations were most common among Asian/Pacific Islander women [per 1,000 mammograms: 169.2; 95% CI, 164.8–173.7) vs. other groups, range, 126.5–136.1]. Some differences were explained by adjusting for receipt of diagnostic ultrasound or MRI for iCDR and imaging facility for short-interval follow-up. Other differences changed little after adjustment. Conclusions: Diagnostic mammography performance varied across racial/ethnic groups. Addressing characteristics related to imaging facility and access, rather than personal characteristics, may help reduce some of these disparities. Impact: Diagnostic mammography performance studies should include racially and ethnically diverse populations to provide an accurate view of the population-level effects.

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.

Background The COVID-19 pandemic reduced mammography use, potentially delaying breast cancer diagnoses. Purpose To examine breast biopsy recommendations and breast cancers diagnosed before and during the COVID-19 pandemic by mode of detection (screen detected vs symptomatic) and women's characteristics. Materials and Methods In this secondary analysis of prospectively collected data, monthly breast biopsy recommendations after mammography, US, or both with subsequent biopsy performed were examined from 66 facilities of the Breast Cancer Surveillance Consortium between January 2019 and September 2020. The number of monthly and cumulative biopsies recommended and performed and the number of subsequent cancers diagnosed during the pandemic period (March 2020 to September 2020) were compared with data from the prepandemic period using Wald χ2 tests. Analyses were stratified by mode of detection and race or ethnicity. Results From January 2019 to September 2020, 17 728 biopsies were recommended and performed, with 6009 cancers diagnosed. From March to September 2020, there were substantially fewer breast biopsy recommendations with cancer diagnoses when compared with the same period in 2019 (1650 recommendations in 2020 vs 2171 recommendations in 2019 [24% fewer], P < .001), predominantly due to fewer screen-detected cancers (722 cancers in 2020 vs 1169 cancers in 2019 [38% fewer], P < .001) versus symptomatic cancers (895 cancers in 2020 vs 965 cancers in 2019 [7% fewer], P = .27). The decrease in cancer diagnoses was largest in Asian (67 diagnoses in 2020 vs 142 diagnoses in 2019 [53% fewer], P = .06) and Hispanic (82 diagnoses in 2020 vs 145 diagnoses in 2019 [43% fewer], P = .13) women, followed by Black women (210 diagnoses in 2020 vs 287 diagnoses in 2019 [27% fewer], P = .21). The decrease was smallest in non-Hispanic White women (1128 diagnoses in 2020 vs 1357 diagnoses in 2019 [17% fewer], P = .09). Conclusion There were substantially fewer breast biopsies with cancer diagnoses during the COVID-19 pandemic from March to September 2020 compared with the same period in 2019, with Asian and Hispanic women experiencing the largest declines, followed by Black women. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Heller in this issue.

Breast and thyroid cancers are two malignancies with highest incidence in women. These cancers often occur metachronously. Women with thyroid cancer are at increased risk for subsequent breast cancer; women with breast cancer have an increased incidence of later development of thyroid cancer, suggesting a common etiology. This bidirectional relationship is reported worldwide; however, the underlying reasons for this co-occurrence are unknown. In this review, we summarize the current epidemiologic evidence and putative mechanisms of these metachronous or synchronous cancers. Key potential causative factors are chemotherapy and radiotherapy of the primary tumor, genetic variants linking the two diseases, hormonal signaling both from the thyroid gland and from estrogens, and lifestyle and environmental factors. There is a critical need for additional epidemiologic studies focused on gender and regional incidence together with molecular investigations on common tumorigenic pathways in these endocrine cancers. Understanding the putative mechanisms will aid in the diagnosis and clinical management of both diseases.

ImportanceDiagnostic delays in breast cancer detection may be associated with later-stage disease and higher anxiety, but data on multilevel factors associated with diagnostic delay are limited.ObjectiveTo evaluate individual-, neighborhood-, and health care–level factors associated with differences in time from abnormal screening to biopsy among racial and ethnic groups.Design, Setting, and ParticipantsThis prospective cohort study used data from women aged 40 to 79 years who had abnormal results in screening mammograms conducted in 109 imaging facilities across 6 US states between 2009 and 2019. Data were analyzed from February 21 to November 4, 2021.ExposuresIndividual-level factors included self-reported race and ethnicity, age, family history of breast cancer, breast density, previous breast biopsy, and time since last mammogram; neighborhood-level factors included geocoded education and income based on residential zip codes and rurality; and health care–level factors included mammogram modality, screening facility academic affiliation, and facility onsite biopsy service availability. Data were also assessed by examination year.Main Outcome and MeasuresThe main outcome was unadjusted and adjusted relative risk (RR) of no biopsy within 30, 60, and 90 days using sequential log-binomial regression models. A secondary outcome was unadjusted and adjusted median time to biopsy using accelerated failure time models.ResultsA total of 45 186 women (median [IQR] age at screening, 56 [48-65] years) with 46 185 screening mammograms with abnormal results were included. Of screening mammograms with abnormal results recommended for biopsy, 15 969 (34.6%) were not resolved within 30 days, 7493 (16.2%) were not resolved within 60 days, and 5634 (12.2%) were not resolved within 90 days. Compared with White women, there was increased risk of no biopsy within 30 and 60 days for Asian (30 days: RR, 1.66; 95% CI, 1.31-2.10; 60 days: RR, 1.58; 95% CI, 1.15-2.18), Black (30 days: RR, 1.52; 95% CI, 1.30-1.78; 60 days: 1.39; 95% CI, 1.22-1.60), and Hispanic (30 days: RR, 1.50; 95% CI, 1.24-1.81; 60 days: 1.38; 95% CI, 1.11-1.71) women; however, the unadjusted risk of no biopsy within 90 days only persisted significantly for Black women (RR, 1.28; 95% CI, 1.11-1.47). Sequential adjustment for selected individual-, neighborhood-, and health care–level factors, exclusive of screening facility, did not substantially change the risk of no biopsy within 90 days for Black women (RR, 1.27; 95% CI, 1.12-1.44). After additionally adjusting for screening facility, the increased risk for Black women persisted but showed a modest decrease (RR, 1.20; 95% CI, 1.08-1.34).Conclusions and RelevanceIn this cohort study involving a diverse cohort of US women recommended for biopsy after abnormal results on screening mammography, Black women were the most likely to experience delays to diagnostic resolution after adjusting for multilevel factors. These results suggest that adjustment for multilevel factors did not entirely account for differences in time to breast biopsy, but unmeasured factors, such as systemic racism and other health care system factors, may impact timely diagnosis.

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), p(trend)=2:19.0 (16.9–21.5), p(trend)

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.

Background The coronavirus disease 2019 (COVID-19) pandemic led to a near-total cessation of mammography services in the United States in mid-March 2020. It is unclear if screening and diagnostic mammography volumes have recovered to prepandemic levels and whether use has varied by women’s characteristics. Methods We collected data on 461 083 screening mammograms and 112 207 diagnostic mammograms conducted during January 2019 through July 2020 at 62 radiology facilities in the Breast Cancer Surveillance Consortium. We compared monthly screening and diagnostic mammography volumes before and during the pandemic stratified by age, race and ethnicity, breast density, and family history of breast cancer. Results Screening and diagnostic mammography volumes in April 2020 were 1.1% (95% confidence interval [CI] = 0.5% to 2.4%) and 21.4% (95% CI = 18.7% to 24.4%) of the April 2019 prepandemic volumes, respectively, but by July 2020 had rebounded to 89.7% (95% CI = 79.6% to 101.1%) and 101.6% (95% CI = 93.8% to 110.1%) of the July 2019 prepandemic volumes, respectively. The year-to-date cumulative volume of screening and diagnostic mammograms performed through July 2020 was 66.2% (95% CI = 60.3% to 72.6%) and 79.9% (95% CI = 75.4% to 84.6%), respectively, of year-to-date volume through July 2019. Screening mammography rebound was similar across age groups and by family history of breast cancer. Monthly screening mammography volume in July 2020 for Black, White, Hispanic, and Asian women reached 96.7% (95% CI = 88.1% to 106.1%), 92.9% (95% CI = 82.9% to 104.0%), 72.7% (95% CI = 56.5% to 93.6%), and 51.3% (95% CI = 39.7% to 66.2%) of the July 2019 prepandemic volume, respectively. Conclusions Despite a strong overall rebound in mammography volume by July 2020, the rebound lagged among Asian and Hispanic women, and a substantial cumulative deficit in missed mammograms accumulated, which may have important health consequences.

Key Points Question How can imaging facilities optimize the number of breast cancers detected during periods of reduced capacity using clinical indication and individual characteristics? Findings In this cohort study including 898 415 individuals with 1 878 924 mammograms, 12% of mammograms with very high and high cancer detection rates accounted for 55% of detected cancers, while 44% of mammograms with very low cancer detection rate accounted for 13% of detected cancers. Meaning These findings suggest that triaging individuals most likely to have cancer detected during periods of reduced capacity could result in detecting the most cancers while performing the fewest examinations compared with a non–risk-based approach., This cohort study assesses strategies to triage patients for mammogram cancer screening during times 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.

The COVID-19 pandemic resulted in numerous changes in delivery of healthcare services, including breast cancer screening and surveillance. Although facilities have implemented a number of strategies to provide services, women's thoughts and experiences related to breast cancer screening and surveillance during a pandemic are not well known. This focus group study with women across seven states recruited through the Breast Cancer Surveillance Consortium aims to remedy this gap in information. Thirty women ranging in age from 31 to 69 participated in five virtual focus groups, eight of whom had prior breast cancer. The first three focus groups covered a range of topics related to screening and surveillance during the pandemic while the last two groups covered experiences and then a review of sample communications to women about screening and surveillance during the pandemic to obtain reactions and recommendations. More than half of the women had screening or surveillance during the pandemic. Coding and analyses resulted in nine themes in three topic areas: decision factors, screening experiences, and preferred communications. Themes included weighing the risks of COVID-19 versus cancer; feelings that screening and surveillance were mostly safe but barriers may be heightened; feeling safe when undergoing screening but receiving a range of pandemic-specific communications from none to a lot; and wanting communications that are personalized, clear and concise. Based on these findings, providers and facilities should assure women of pandemic safety measures, review methods and content of communications, and assess for barriers to screening that may be amplified during the pandemic, including anxiety and access.

Breast cancer is the most common cancer and the second most common cause of cancer mortality among women in the United States. Efforts to promote breast cancer control in rural settings face specific challenges. Access to breast cancer screening, diagnosis, and treatment services is impaired by shortages of primary care and specialist providers, and geographic distance from medical facilities. Women in rural areas have comparable breast cancer mortality rates compared to women in urban settings, but this is due in large part to lower incidence rates and masks a substantial rural/urban disparity in breast cancer survival among women diagnosed with breast cancer. Mammography screening utilization rates are slightly lower among rural women than their urban counterparts, with a corresponding increase in late stage breast cancer. Differences in breast cancer survival persist after controlling for stage at diagnosis, largely due to disparities in access to treatment. Travel distance to treatment centers is the most substantial barrier to improved breast cancer outcomes in rural areas. While numerous interventions have been demonstrated in controlled studies to be effective in promoting treatment access and adherence, widespread dissemination in public health and clinical practice remains lacking. Efforts to improve breast cancer control in rural areas should focus on implementation strategies for improving access to breast cancer treatments.

BACKGROUND: Digital breast tomosynthesis (DBT) combined with digital mammography (DM) is increasingly used in the United States instead of DM alone for breast cancer screening. Early screening outcomes incorporating synthetic mammography (SM) with DBT have suggested that SM is an acceptable non–radiation dose alternative to DM. PURPOSE: To compare multicenter outcomes from breast cancer screening with SM/DBT versus DM/DBT. MATERIALS AND METHODS: This was a retrospective study of consecutive screening mammograms obtained at two institutions. Eligible studies consisted of 34 106 DM/DBT examinations between October 3, 2011, and October 31, 2014, and 34 180 SM/DBT examinations between January 7, 2015, and February 2, 2018, at the University of Pennsylvania and 51 148 DM/DBT examinations between January 1, 2012, and May 31, 2016, and 31 929 SM/DBT examinations between June 1, 2016, and March 30, 2018, at the University of Vermont. Demographics of women who attended screening and results from screening were recorded. Recall rate, biopsy rate, false-negative rate, cancer detection rate, positive predictive value, sensitivity, and specificity were calculated according to modality and institution. Descriptive statistics, χ(2) tests, and logistic regression were used in analysis. RESULTS: The study included 151 363 screening examinations among 151 363 women (mean age, 58.1 years ± 10.9 [standard deviation]). The unadjusted recall rate was lower with SM/DBT than with DM/DBT (7.0% [4630 of 66 109 examinations] for SM/DBT vs 7.9% [6742 of 85 254 examinations] for DM/DBT; P < .01). However, after multivariable adjustment, SM/DBT was associated with a slightly higher recall rate compared with DM/DBT (adjusted odds ratio [OR], 1.06; adjusted 95% CI: 1.01, 1.11; P = .02). Similarly, after multivariable adjustment, SM/DBT was associated with slightly lower specificity compared with DM/DBT (adjusted OR, 0.95; adjusted 95% CI: 0.90, 0.99; P = .02). There was no statistically significant difference in biopsy rate (P = .54), false-negative rate (P = .38), cancer detection rate (P = .55), invasive or in situ cancer detection rate (P = .52 and P = .98, respectively), positive predictive value (P = .78), or sensitivity (P = .33) for SM/DBT versus DM/DBT overall or within either institution (P > .05 for all). CONCLUSION: Breast cancer screening performance is maintained within benchmarks when synthetic mammography replaces digital mammography in digital breast tomosynthesis imaging. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Lång in this issue.

Background: Overweight/obesity and dense breasts are strong breast cancer risk factors whose prevalences vary by race/ethnicity. The breast cancer population attributable risk proportions (PARP) explained by these factors across racial/ethnic groups are unknown. Methods: We analyzed data collected from 3,786,802 mammography examinations (1,071,653 women) in the Breast Cancer Surveillance Consortium, associated with 21,253 invasive breast cancers during a median of 5.2 years follow-up. HRs for body mass index (BMI) and breast density, adjusted for age and registry were estimated using separate Cox regression models by race/ethnicity (White, Black, Hispanic, Asian) and menopausal status. HRs were combined with observed risk-factor proportions to calculate PARPs for shifting overweight/obese to normal BMI and shifting heterogeneously/extremely dense to scattered fibroglandular densities. Results: The prevalences and HRs for overweight/obesity and heterogeneously/extremely dense breasts varied across races/ethnicities and menopausal status. BMI PARPs were larger for postmenopausal versus premenopausal women (12.0%–28.3% vs. 1.0%–9.9%) and nearly double among postmenopausal Black women (28.3%) than other races/ethnicities (12.0%–15.4%). Breast density PARPs were larger for premenopausal versus postmenopausal women (23.9%–35.0% vs. 13.0%–16.7%) and lower among premenopausal Black women (23.9%) than other races/ethnicities (30.4%–35.0%). Postmenopausal density PARPs were similar across races/ethnicities (13.0%–16.7%). Conclusions: Overweight/obesity and dense breasts account for large proportions of breast cancers in White, Black, Hispanic, and Asian women despite large differences in risk-factor distributions. Impact: Risk prediction models should consider how race/ethnicity interacts with BMI and breast density. Efforts to reduce BMI could have a large impact on breast cancer risk reduction, particularly among postmenopausal Black women.

Importance Many US radiologists have screening mammography recall rates above the expert-recommended threshold of 12%. The influence of digital breast tomosynthesis (DBT) on the distribution of radiologist recall rates is uncertain. Objective To evaluate radiologists’ recall and cancer detection rates before and after beginning interpretation of DBT examinations. Design, Setting, and Participants This cohort study included 198 radiologists from 104 radiology facilities in the Breast Cancer Surveillance Consortium who interpreted 251 384 DBT and 2 000 681 digital mammography (DM) screening examinations from 2009 to 2017, including 126 radiologists (63.6%) who interpreted DBT examinations during the study period and 72 (36.4%) who exclusively interpreted DM examinations (to adjust for secular trends). Data were analyzed from April 2018 to July 2019. Exposures Digital breast tomosynthesis and DM screening examinations. Main Outcomes and Measures Recall rate and cancer detection rate. Results A total of 198 radiologists interpreted 2 252 065 DM and DBT examinations (2 000 681 [88.8%] DM examinations; 251 384 [11.2%] DBT examinations; 710 934 patients [31.6%] aged 50-59 years; 1 448 981 [64.3%] non-Hispanic white). Among the 126 radiologists (63.6%) who interpreted DBT examinations, 83 (65.9%) had unadjusted DM recall rates of no more than 12% before using DBT, with a median (interquartile range) recall rate of 10.0% (7.5%-13.0%). On DBT examinations, 96 (76.2%) had an unadjusted recall rate of no more than 12%, with a median (interquartile range) recall rate of 8.8% (6.3%-11.3%). A secular trend in recall rate was observed, with the multivariable-adjusted risk of recall on screening examinations declining by 1.2% (95% CI, 0.9%-1.5%) per year. After adjusting for examination characteristics and secular trends, recall rates were 15% lower on DBT examinations compared with DM examinations interpreted before DBT use (relative risk, 0.85; 95% CI, 0.83-0.87). Adjusted recall rates were significantly lower on DBT examinations compared with DM examinations interpreted before DBT use for 45 radiologists (35.7%) and significantly higher for 18 (14.3%); 63 (50.0%) had no statistically significant change. The unadjusted cancer detection rate on DBT was 5.3 per 1000 examinations (95% CI, 5.0-5.7 per 1000 examinations) compared with 4.7 per 1000 examinations (95% CI, 4.6-4.8 per 1000 examinations) on DM examinations interpreted before DM use (multivariable-adjusted risk ratio, 1.21; 95% CI, 1.11-1.33). Conclusions and Relevance In this study, DBT was associated with an overall decrease in recall rate and an increase in cancer detection rate. However, our results indicated that there is wide variability among radiologists, including a subset of radiologists who experienced increased recall rates on DBT examinations. Radiology practices should audit radiologist DBT screening performance and consider additional DBT training for radiologists whose performance does not improve as expected.

Objective. Breast cancer simulation models must take changing mortality rates into account to evaluate the potential impact of cancer control interventions. We estimated mortality rates due to breast cancer and all other causes combined to determine their impact on overall mortality by year, age, and birth cohort. Methods. Based on mortality rates from publicly available datasets, an age-period-cohort model was used to estimate the proportion of deaths due to breast cancer for US women aged 0 to 119 years, with birth years 1900 to 2000. Breast cancer mortality was calculated as all-cause mortality multiplied by the proportion of deaths due to breast cancer; other-cause mortality was the difference between all-cause and breast cancer mortality. Results. Breast cancer and other-cause mortality rates were higher for older ages and birth cohorts. The percent of deaths due to breast cancer increased across birth cohorts from 1900 to 1940 then decreased. Among 50-year-old women, in the 1920 birth cohort, 52 (9.9%) of 100,000 deaths (95% CI, 9.8% to 10.1%) were attributed to breast cancer whereas 476 of 100,000 were due to other causes; in the 1960 birth cohort, 22 (8.5%) of 100,000 deaths (95% CI, 8.3% to 8.7%) were attributed to breast cancer with 242 of 100,000 deaths due to other causes. The percentage of all deaths due to breast cancer was highest (4.1% to 12.9%) for women in their 40s and 50s for all birth cohorts. Conclusions. This study offers evidence that advances in breast cancer screening and treatment have reduced breast cancer mortality for women across the age spectrum, and provides estimates of age-, year- and birth cohort-specific competing mortality rates for simulation models. Other-cause mortality estimates are important in these models because most women die from causes other than breast cancer.

The University of Wisconsin Breast Cancer Epidemiology Simulation Model (UWBCS), also referred to as Model W, is a discrete-event microsimulation model that uses a systems engineering approach to replicate breast cancer epidemiology in the US over time. This population-based model simulates the lifetimes of individual women through 4 main model components: breast cancer natural history, detection, treatment, and mortality. A key feature of the UWBCS is that, in addition to specifying a population distribution in tumor growth rates, the model allows for heterogeneity in tumor behavior, with some tumors having limited malignant potential (i.e., would never become fatal in a woman’s lifetime if left untreated) and some tumors being very aggressive based on metastatic spread early in their onset. The model is calibrated to Surveillance, Epidemiology, and End Results (SEER) breast cancer incidence and mortality data from 1975 to 2010, and cross-validated against data from the Wisconsin cancer reporting system. The UWBCS model generates detailed outputs including underlying disease states and observed clinical outcomes by age and calendar year, as well as costs, resource usage, and quality of life associated with screening and treatment. The UWBCS has been recently updated to account for differences in breast cancer detection, treatment, and survival by molecular subtypes (defined by ER/HER2 status), to reflect the recent advances in screening and treatment, and to consider a range of breast cancer risk factors, including breast density, race, body-mass-index, and the use of postmenopausal hormone therapy. Therefore, the model can evaluate novel screening strategies, such as risk-based screening, and can assess breast cancer outcomes by breast cancer molecular subtype. In this article, we describe the most up-to-date version of the UWBCS.

Background: Patients who receive an abnormal cancer screening result require follow-up for diagnostic testing, but the time to follow-up varies across patients and practices. Methods: We used a simulation study to estimate the change in lifetime screening benefits when time to follow-up for breast, cervical, and colorectal cancers was increased. Estimates were based on four independently developed microsimulation models that each simulated the life course of adults eligible for breast (women ages 50–74 years), cervical (women ages 21–65 years), or colorectal (adults ages 50–75 years) cancer screening. We assumed screening based on biennial mammography for breast cancer, triennial Papanicolaou testing for cervical cancer, and annual fecal immunochemical testing for colorectal cancer. For each cancer type, we simulated diagnostic testing immediately and at 3, 6, and 12 months after an abnormal screening exam. Results: We found declines in screening benefit with longer times to diagnostic testing, particularly for breast cancer screening. Compared to immediate diagnostic testing, testing at 3 months resulted in reduced screening benefit, with fewer undiscounted life years gained per 1,000 screened (breast: 17.3%, cervical: 0.8%, colorectal: 2.0% and 2.7%, from two colorectal cancer models), fewer cancers prevented (cervical: 1.4% fewer, colorectal: 0.5% and 1.7% fewer, respectively), and, for breast and colorectal cancer, a less favorable stage distribution. Conclusions: Longer times to diagnostic testing after an abnormal screening test can decrease screening effectiveness, but the impact varies substantially by cancer type. Impact: Understanding the impact of time to diagnostic testing on screening effectiveness can help inform quality improvement efforts. Cancer Epidemiol Biomarkers Prev; 27(2); 158–64. ©2017 AACR.

County-level analyses demonstrate that overall cancer incidence is generally lower in rural areas, though incidence and mortality from tobacco-associated cancers are higher than in non-rural areas and have experienced slower declines over time. The goal of our study was to examine state-level rurality and smoking-related cancer outcomes. We used publicly-available national data to quantify rurality, cigarette smoking prevalence, and smoking-attributable cancer incidence and mortality at the state level and to estimate the population-attributable fraction of cancer deaths attributable to smoking for each state, overall and by gender, for 12 smoking-associated cancers. Accounting for a 15-year lag between smoking exposure and cancer diagnosis, the median proportion of smoking-attributable cancer deaths was 28.2% in Virginia (24.6% rural) and ranged from 19.9% in Utah (9.4% rural) to 35.1% in Kentucky (41.6% rural). By gender, the highest proportion of smoking-attributable cancer deaths for women (29.5%) was in a largely urban state (Nevada, 5.8% rural) and for men (38.0%) in a largely rural state (Kentucky). Regression analyses categorizing state-level rurality into low (0–13.9%), moderate (15.3–29.9%) and high (33.6–61.3%) levels showed that high rurality was associated with 5.8% higher cigarette smoking prevalence, higher age-adjusted smoking-associated cancer incidence (44.3 more cases per 100,000 population), higher smoking-associated cancer mortality (29.8 more deaths per 100,000 population), and 3.4% higher proportion of smoking-attributable cancer deaths compared with low rurality. Our findings highlight the magnitude of the relationship between state-level rurality and smoking-attributable cancer outcomes and the importance of tobacco control in reducing cancer disparities in rural populations.

Importance Breast density is associated with breast cancer risk in women aged 40 to 65 years, but there is limited evidence of its association with risk of breast cancer among women aged 65 years or older. Objective To compare the association between breast density and risk of invasive breast cancer among women aged 65 to 74 years vs women aged 75 years or older and to evaluate whether the association is modified by body mass index (BMI). Design, setting, and participants This prospective cohort study used data from the Breast Cancer Surveillance Consortium from January 1, 1996, to December 31, 2012, for US women aged 65 years or older who underwent screening mammography. Data were analyzed from January 1, 2018, to December 31, 2020. Exposures Breast Imaging Reporting and Data System breast density category, age, and BMI. Main outcomes and measures The 5-year cumulative incidence of invasive breast cancer by level of breast density (almost entirely fat, scattered fibroglandular densities, or heterogeneous or extreme density) and age (65-74 vs ≥75 years) was calculated using weighted means. Cox proportional hazards models were fit to estimate the association of breast density with invasive breast cancer risk. The likelihood ratio test was used to test the interaction between BMI and breast density. Results A total of 221 714 screening mammograms from 193 787 women were included in the study; a total of 38% of the study population was aged 75 years or older. Of the mammograms, most were from women aged 65 to 74 years (64.6%) and non-Hispanic White individuals (81.4%). The 5-year cumulative incidence of invasive breast cancer increased in association with increasing breast density among women aged 65 to 74 years (almost entirely fatty breasts: 11.3 per 1000 women [95% CI, 10.4-12.5 per 1000 women]; scattered fibroglandular densities: 17.2 per 1000 women [95% CI, 16.1-17.9 per 1000 women]; extremely or heterogeneously dense breasts: 23.7 per 1000 women [95% CI, 22.4-25.3 per 1000 women]) and among those aged 75 years or older (fatty breasts: 13.5 per 1000 women [95% CI, 11.6-15.5]; scattered fibroglandular densities: 18.4 per 1000 women [95% CI, 17.0-19.5 per 1000 women]; extremely or heterogeneously dense breasts: 22.5 per 1000 women [95% CI, 20.2-24.2 per 1000 women]). Extreme or heterogeneous breast density was associated with increased risk of breast cancer compared with scattered fibroglandular breast density in both age categories (65-74 years: hazard ratio [HR], 1.39 [95% CI, 1.28-1.50]; ≥75 years: HR, 1.23 [95% CI, 1.10-1.37]). Women with almost entirely fatty breasts had a decrease of approximately 30% (range, 27%-34%) in the risk of invasive breast cancer compared with women with scattered fibroglandular breast density (65-74 years: HR, 0.66 [95% CI, 0.58-0.75]; ≥75 years: HR, 0.73; 95% CI, 0.62-0.86). Associations between breast density and breast cancer risk were not significantly modified by BMI (for age 65-74 years: likelihood ratio test, 2.67; df, 2; P = .26; for age ≥75 years, 2.06; df, 2; P = .36). Conclusions and relevance The findings suggest that breast density is associated with increased risk of invasive breast cancer among women aged 65 years or older. Breast density and life expectancy should be considered together when discussing the potential benefits vs harms of continued screening mammography in this population.

Background: Increase in breast cancer incidence associated with mammography screening diffusion may have attenuated risk associations between family history and breast cancer. Methods: The proportions of women ages 40 to 74 years reporting a first-degree family history of breast cancer were estimated in the Breast Cancer Surveillance Consortium cohort (BCSC: N = 1,170,900; 1996–2012) and the Collaborative Breast Cancer Study (CBCS: cases N = 23,400; controls N = 26,460; 1987–2007). Breast cancer (ductal carcinoma in situ and invasive) relative risk estimates and 95% confidence intervals (CI) associated with family history were calculated using multivariable Cox proportional hazard and logistic regression models. Results: The proportion of women reporting a first-degree family history increased from 11% in the 1980s to 16% in 2010 to 2013. Family history was associated with a >60% increased risk of breast cancer in the BCSC (HR, 1.61; 95% CI, 1.55–1.66) and CBCS (OR, 1.64; 95% CI, 1.57–1.72). Relative risks decreased slightly with age. Consistent trends in relative risks were not observed over time or across stage of disease at diagnosis in both studies, except among older women (ages 60–74) where estimates were attenuated from about 1.7 to 1.3 over the last 20 years (P trend = 0.08 for both studies). Conclusions: Although the proportion of women with a first-degree family history of breast cancer increased over time and by age, breast cancer risk associations with family history were nonetheless fairly constant over time for women under age 60. Impact: First-degree family history of breast cancer remains an important breast cancer risk factor, especially for younger women, despite its increasing prevalence in the mammography screening era. Cancer Epidemiol Biomarkers Prev; 26(12); 1753–60. ©2017 AACR.

Due to limitations in the ability to identify non-progressive disease, ductal carcinoma in situ (DCIS) is usually managed similarly to localized invasive breast cancer. We used simulation modeling to evaluate the potential impact of a hypothetical test that identifies non-progressive DCIS. A discrete-event model simulated a cohort of U.S. women undergoing digital screening mammography. All women diagnosed with DCIS underwent the hypothetical DCIS prognostic test. Women with test results indicating progressive DCIS received standard breast cancer treatment and a decrement to quality of life corresponding to the treatment. If the DCIS test indicated non-progressive DCIS, no treatment was received and women continued routine annual surveillance mammography. A range of test performance characteristics and prevalence of non-progressive disease were simulated. Analysis compared discounted quality-adjusted life years (QALYs) and costs for test scenarios to base-case scenarios without the test. Compared to the base case, a perfect prognostic test resulted in a 40% decrease in treatment costs, from $13,321 to $8005 USD per DCIS case. A perfect test produced 0.04 additional QALYs (16 days) for women diagnosed with DCIS, added to the base case of 5.88 QALYs per DCIS case. The results were sensitive to the performance characteristics of the prognostic test, the proportion of DCIS cases that were non-progressive in the model, and the frequency of mammography screening in the population. A prognostic test that identifies non-progressive DCIS would substantially reduce treatment costs but result in only modest improvements in quality of life when averaged over all DCIS cases.

Purpose To compare screening magnetic resonance (MR) imaging performance in the Breast Cancer Surveillance Consortium (BCSC) with Breast Imaging Reporting and Data System (BI-RADS) benchmarks. Materials and Methods This study was approved by the institutional review board and compliant with HIPAA and included BCSC screening MR examinations collected between 2005 and 2013 from 5343 women (8387 MR examinations) linked to regional Surveillance, Epidemiology, and End Results program registries, state tumor registries, and pathologic information databases that identified breast cancer cases and tumor characteristics. Clinical, demographic, and imaging characteristics were assessed. Performance measures were calculated according to BI-RADS fifth edition and included cancer detection rate (CDR), positive predictive value of biopsy recommendation (PPV2), sensitivity, and specificity. Results The median patient age was 52 years; 52% of MR examinations were performed in women with a first-degree family history of breast cancer, 46% in women with a personal history of breast cancer, and 15% in women with both risk factors. Screening MR imaging depicted 146 cancers, and 35 interval cancers were identified (181 total-54 in situ, 125 invasive, and two status unknown). The CDR was 17 per 1000 screening examinations (95% confidence interval [CI]: 15, 20 per 1000 screening examinations; BI-RADS benchmark, 20-30 per 1000 screening examinations). PPV2 was 19% (95% CI: 16%, 22%; benchmark, 15%). Sensitivity was 81% (95% CI: 75%, 86%; benchmark, >80%), and specificity was 83% (95% CI: 82%, 84%; benchmark, 85%-90%). The median tumor size of invasive cancers was 10 mm; 88% were node negative. Conclusion The interpretative performance of screening MR imaging in the BCSC meets most BI-RADS benchmarks and approaches benchmark levels for remaining measures. Clinical practice performance data can inform ongoing benchmark development and help identify areas for quality improvement. © RSNA, 2017.

In 2009, the U.S. Preventive Services Task Force (USPSTF) recommended biennial mammography for women aged 50-74 years and shared decision-making for women aged 40-49 years for breast cancer screening. We evaluated changes in mammography screening interval after the 2009 recommendations.We conducted a prospective cohort study of women aged 40-74 years who received 821,052 screening mammograms between 2006 and 2012 using data from the Breast Cancer Surveillance Consortium. We compared changes in screening intervals and stratified intervals based on whether the mammogram at the end of the interval occurred before or after the 2009 recommendation. Differences in mean interval length by woman-level characteristics were compared using linear regression.The mean interval (in months) minimally decreased after the 2009 USPSTF recommendations. Among women aged 40-49 years, the mean interval decreased from 17.2 months to 17.1 months (difference -0.16%, 95% confidence interval [CI] -0.30 to -0.01). Similar small reductions were seen for most age groups. The largest change in interval length in the post-USPSTF period was declines among women with a first-degree family history of breast cancer (difference -0.68%, 95% CI -0.82 to -0.54) or a 5-year breast cancer risk ≥2.5% (difference -0.58%, 95% CI -0.73 to -0.44).The 2009 USPSTF recommendation did not lengthen the average mammography interval among women routinely participating in mammography screening. Future studies should evaluate whether breast cancer screening intervals lengthen toward biennial intervals following new national 2016 breast cancer screening recommendations, particularly among women less than 50 years of age.

ObjectiveWe sought to identify and characterize examinations in women with a personal history of breast cancer likely performed for asymptomatic surveillance.MethodsWe included surveillance mammograms (1997-2017) in asymptomatic women with a personal history of breast cancer diagnosed at age ≥18 years (1996-2016) from 103 Breast Cancer Surveillance Consortium facilities. We examined facility-level variability in examination indication. We modeled the relative risk (RR) and 95% confidence intervals (CIs) at the examination level of a (1) nonscreening indication and (2) surveillance interval ≤9 months using Poisson regression with fixed effects for facility, stage, diagnosis age, surgery, examination year, and time since diagnosis.ResultsAmong 244,855 surveillance mammograms, 69.5% were coded with a screening indication, 12.7% short-interval follow-up, and 15.3% as evaluation of a breast problem. Within a facility, the proportion of examinations with a screening indication ranged from 6% to 100% (median 86%, interquartile range 79%-92%). Facilities varied the most for examinations in the first 5 years after diagnosis, with 39.4% of surveillance mammograms having a nonscreening indication. Within a facility, breast conserving surgery compared with mastectomy (RR= 1.64; 95% CI= 1.60-1.68) and less time since diagnosis (1 year versus 5 years; RR= 1.69; 95% CI= 1.66-1.72; 3 years versus 5 years= 1.20; 95% CI= 1.18-1.23) were strongly associated with a nonscreening indication with similar results for ≤9-month surveillance interval. Screening indication and >9-month surveillance intervals were more common in more recent years.ConclusionVariability in surveillance indications across facilities in the United States supports including indications beyond screening in studies evaluating surveillance mammography effectiveness and demonstrates the need for standardization.

BACKGROUND: Breast tumor stratification by recurrence-risk is a critical for deciding patient treatment. Here an approach combining cancer pathways microarray data complemented by RNA in situ hybridization (ISH) was investigated as a means for recurrence marker discovery and visualization in pathology specimens. METHODS: LncRNA and mRNA expressions in breast carcinomas with low (n=8) versus intermediate/high (n=10) recurrence-scores as estimated by 21-gene assay and pathology review were compared by microarray assay. Tissue microarrays were prepared from breast carcinomas (n=20) and ductal carcinoma in situ (DCIS) specimens (n=84 patients) with known outcomes. Thirteen RNA ISH assays were performed: lncRNAs (BBC3–1, FER3, RAD21-AS1, ZEB1–2) and mRNAs (GLO1, GLTSCR2, TGFB1, TLR2) [implicated by the microarray data]; MKI67; a pooled panel of recurrence-associated proliferation markers (BIRC5, Cyclin B1, MKI67, MYBL2, STK15); a pooled panel of non-proliferation recurrence-associated markers (CEACAM5, HTF9C, NDRG1, TP53, SLC7A5); and lncRNAs H19 and HOTAIR. RESULTS: Seven lncRNAs and 10 mRNAs showed significantly (P

Background There is lack of consensus regarding the use of breast MRI for routine surveillance for second breast cancer events in women with a personal history of breast cancer. Purpose To compare performance of surveillance mammography with breast MRI. Materials and Methods This observational cohort study used prospectively collected data and included 13 266 women age 18 years and older (mean age, 60 years ± 13) with stage 0-III breast cancer who underwent 33 938 mammographic examinations and 2506 breast MRI examinations from 2005 to 2012 in the Breast Cancer Surveillance Consortium. Women were categorized into two groups: mammography alone (n = 11 745) or breast MRI (n = 1521). Performance measures were calculated by using end-of-day assessment and occurrence of second breast cancer events within 1 year of imaging. Logistic regression was used to compare performance for breast MRI versus mammography alone, adjusting for women, examination, and primary breast cancer characteristics. Analysis was conducted on a per-examination basis. Results Breast MRI was associated with younger age at diagnosis, chemotherapy, and higher education and income. Raw performance measures for breast MRI versus mammography were as follows, respectively: cancer detection rates, 10.8 (95% confidence interval [CI]: 6.7, 14.8) versus 8.2 (95% CI: 7.3, 9.2) per 1000 examinations; sensitivity, 61.4% (27 of 44; 95% CI: 46.5%, 76.2%) versus 70.3% (279 of 397; 95% CI: 65.8%, 74.8%); and biopsy rate, 10.1% (253 of 2506; 95% CI: 8.9%, 11.3%) versus 4.0% (1343 of 33 938; 95% CI: 3.7%, 4.2%). In multivariable models, breast MRI was associated with higher biopsy rate (odds ratio [OR], 2.2; 95% CI: 1.9, 2.7; P < .001) and cancer detection rate (OR, 1.7; 95% CI: 1.1, 2.7; P = .03) than mammography alone. However, there were no differences in sensitivity (OR, 1.1; 95% CI: 0.4, 2.9; P = .84) or interval cancer rate (OR, 1.1; 95% CI: 0.6, 2.2; P = .70). Conclusion Comparison of the performance of surveillance breast MRI with mammography must account for patient characteristics. Whereas breast MRI leads to higher biopsy and cancer detection rates, there were no significant differences in sensitivity or interval cancers compared with mammography. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Newell in this issue.

Background: U.S. women of ages 50–74 years are recommended to receive screening mammography at least biennially. Our objective was to evaluate multilevel predictors of nonadherence among screened women, as these are not well known. Materials and Methods: A cohort study was conducted among women of ages 50–74 years with a screening mammogram in 2011 with a negative finding (Breast Imaging-Reporting and Data System 1 or 2) within Population-based Research Optimizing Screening through Personalized Regimens (PROSPR) consortium research centers. We evaluated the association between woman-level factors, radiology facility, and PROSPR research center, and nonadherence to breast cancer screening guidelines, defined as not receiving breast imaging within 27 months of an index screening mammogram. Multilevel mixed-effects logistic regression was used to calculate odds ratios and 95% confidence intervals. Results: Nonadherence to guideline-recommended screening interval was 15.5% among 51,241 women with a screening mammogram. Non-Hispanic Asian/Pacific Islander women, women of other races, heavier women, and women of ages 50–59 years had a greater odds of nonadherence. There was no association with ZIP code median income. Nonadherence varied by research center and radiology facility (variance = 0.10, standard error = 0.03). Adjusted radiology facility nonadherence rates ranged from 10.0% to 26.5%. One research center evaluated radiology facility communication practices for screening reminders and scheduling, but these were not associated with nonadherence. Conclusions: Breast cancer screening interval nonadherence rates in screened women varied across radiology facilities even after adjustment for woman-level characteristics and research center. Future studies should investigate other characteristics of facilities, practices, and health systems to determine factors integral to increasing continued adherence to breast cancer screening.

IMPORTANCE: Federal legislation proposes requiring that screening mammography reports to practitioners and women incorporate breast density information and that women with dense breasts discuss supplemental imaging with their practitioner given their increased risk of interval breast cancer. Instead of discussing supplemental imaging with all women with dense breasts, it may be more efficient to identify women at high risk of advanced breast cancer who may benefit most from supplemental imaging. OBJECTIVE: To identify women at high risk of advanced breast cancer to target woman-practitioner discussions about the need for supplemental imaging. DESIGN, SETTING, AND PARTICIPANTS: This prospective cohort study assessed 638 856 women aged 40 to 74 years who had 1 693 163 screening digital mammograms taken at Breast Cancer Surveillance Consortium (BCSC) imaging facilities from January 3, 2005, to December 31, 2014. Data analysis was performed from October 10, 2018, to March 20, 2019. EXPOSURES: Breast Imaging Reporting and Data System (BI-RADS) breast density and BCSC 5-year breast cancer risk. MAIN OUTCOMES AND MEASURES: Advanced breast cancer (stage IIB or higher) within 12 months of screening mammography; high advanced cancer rates (≥0.61 cases per 1000 mammograms) defined as the top 25th percentile of advanced cancer rates, and discussions per potential advanced cancer prevented. RESULTS: A total of 638 856 women (mean [SD] age, 56.5 [8.9] years) were included in the study. Women with dense breasts (heterogeneously or extremely dense) accounted for 47.0% of screened women and 60.0% of advanced cancers. Low advanced cancer rates (

Changes to mammography practice, including revised Breast Imaging Reporting and Data System (BI-RADS) density classification guidelines and implementation of digital breast tomosynthesis (DBT), may impact clinical breast density assessment. We investigated temporal trends in clinical breast density assessment among 2 990 291 digital mammography (DM) screens and 221 063 DBT screens interpreted by 722 radiologists from 144 facilities in the Breast Cancer Surveillance Consortium. After age-standardization, 46.3% (95% CI = 44.1% to 48.6%) of DM screens were assessed as dense (heterogeneously/extremely dense) during the BI-RADS 4th edition era (2005-2013), compared to 46.5% (95% CI = 43.8% to 49.1%) during the 5th edition era (2014-2016) (P = .93 from two-sided generalized score test). Among DBT screens in the BI-RADS 5th edition era, 45.8% (95% CI = 42.0% to 49.7%) were assessed as dense (P = .77 from two-sided generalized score test) compared to 46.5% (95% CI = 43.8% to 49.1%) dense on DM in BI-RADS 5th edition era. Results were similar when examining all four density categories and age subgroups. Clinicians, researchers, and policymakers may reasonably expect stable density distributions across screened populations despite changes to the BI-RADS guidelines and implementation of DBT.

BACKGROUND: There is growing evidence that digital breast tomosynthesis (DBT) results in lower recall rates and higher cancer detection rates when compared with digital mammography. However, whether DBT interpretative performance changes with experience (learning curve effect) is unknown. PURPOSE: To evaluate screening DBT performance by cumulative DBT volume within 2 years after adoption relative to digital mammography (DM) performance 1 year before DBT adoption. MATERIALS AND METHODS: This prospective study included 106 126 DBT and 221 248 DM examinations in 271 362 women (mean age, 57.5 years) from 2010 to 2017 that were interpreted by 104 radiologists from 53 facilities in the Breast Cancer Surveillance Consortium. Conditional logistic regression was used to estimate within-radiologist effects of increasing cumulative DBT volume on recall and cancer detection rates relative to DM and was adjusted for examination-level characteristics. Changes were also evaluated by subspecialty and breast density. RESULTS: Before DBT adoption, DM recall rate was 10.4% (95% confidence interval [CI]: 9.5%, 11.4%) and cancer detection rate was 4.0 per 1000 screenings (95% CI: 3.6 per 1000 screenings, 4.5 per 1000 screenings); after DBT adoption, DBT recall rate was lower (9.4%; 95% CI: 8.2%, 10.6%; P = .02) and cancer detection rate was similar (4.6 per 1000 screenings; 95% CI: 4.0 per 1000 screenings, 5.2 per 1000 screenings; P = .12). Relative to DM, DBT recall rate decreased for a cumulative DBT volume of fewer than 400 studies (odds ratio [OR] = 0.83; 95% CI: 0.78, 0.89) and remained lower as volume increased (400–799 studies, OR = 0.8 [95% CI: 0.75, 0.85]; 800–1199 studies, OR = 0.81 [95% CI: 0.76, 0.87]; 1200–1599 studies, OR = 0.78 [95% CI: 0.73, 0.84]; 1600–2000 studies, OR = 0.81 [95% CI: 0.75, 0.88]; P < .001). Improvements were sustained for breast imaging subspecialists (OR range, 0.67–0.85; P < .02) and readers who were not breast imaging specialists (OR range, 0.80–0.85; P < .001). Recall rates decreased more in women with nondense breasts (OR range, 0.68–0.76; P < .001) than in those with dense breasts (OR range, 0.86–0.90; P ≤ .05; P interaction < .001). Cancer detection rates for DM and DBT were similar, regardless of DBT volume (P ≥ .10). CONCLUSION: Early performance improvements after digital breast tomosynthesis (DBT) adoption were sustained regardless of DBT volume, radiologist subspecialty, or breast density. © RSNA, 2019 See also the editorial by Hooley in this issue.

Background Breast density is strongly related to breast cancer. Identifying associations between environmental exposures and density may elucidate relationships with breast cancer. Metals and polycyclic aromatic hydrocarbons (PAHs) may influence breast density via oxidative stress or endocrine disruption. Methods Study participants (n = 222,581) underwent a screening mammogram in 2011 at a radiology facility in the Breast Cancer Surveillance Consortium. Zip code residential levels of airborne PAHs and metals (arsenic, cadmium, chromium, cobalt, lead, manganese, mercury, nickel, and selenium) were assessed using the 2011 EPA National Air Toxics Assessment. Breast density was measured using the Breast Imaging–Reporting and Data System (BI-RADS) lexicon. Logistic regression was used to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CI) for the individual air toxics and dense breasts (BI-RADS 3 or 4). Weighted quantile sum (WQS) regression was used to model the association between the air toxic mixture and density. Results Higher residential levels of arsenic, cobalt, lead, manganese, nickel, or PAHs were individually associated with breast density. Comparing the highest to the lowest quartile, higher odds of having dense breasts were observed for cobalt (OR = 1.60, 95% CI 1.56–1.64) and lead (OR = 1.56, 95% CI 1.52–1.64). Associations were stronger for premenopausal women. The WQS index was associated with density overall (OR = 1.22, 95% CI 1.20–1.24); the most heavily weighted air toxics were lead and cobalt. Conclusions In this first study to evaluate the association between air toxics and breast density, women living in areas with higher concentrations of lead and cobalt were more likely to have dense breasts. Electronic supplementary material The online version of this article (10.1186/s13058-019-1110-7) contains supplementary material, which is available to authorized users.

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.

Few studies have attempted to characterize how co-occurring risk factors for substance use disorders intersect. A recent study examined this question regarding cigarette smoking and demonstrated that co-occurring risk factors generally act independently. The present study examines whether that same pattern of independent intersection of risk factors extends to illicit drug abuse/dependence using a U.S. nationally representative sample (National Survey on Drug Use and Health, 2011–2013). Logistic regression and classification and regression tree (CART) modeling were used to examine risk of past-year drug abuse/dependence associated with a well-established set of risk factors for substance use (age, gender, race/ethnicity, education, poverty, smoking status, alcohol abuse/dependence, mental illness). Each of these risk factors was associated with significant increases in the odds of drug abuse/dependence in univariate logistic regressions. Each remained significant in a multivariate model examining all eight risk factors simultaneously. CART modeling of these 8 risk factors identified subpopulation risk profiles wherein drug abuse/dependence prevalence varied from < 1% to > 80% corresponding to differing combinations of risk factors present. Alcohol abuse/dependence and cigarette smoking had the strongest associations with drug abuse/dependence risk. These results demonstrate that co-occurring risk factors for illicit drug/abuse dependence generally intersect in the same independent manner as risk factors for cigarette smoking, underscoring further fundamental commonalities across these different types of substance use disorders. These results also underscore the fundamental importance of differences in the presence of co-occurring risk factors when considering the often strikingly different prevalence rates of illicit drug abuse/dependence in U.S. population subgroups.

Relatively little has been reported characterizing cumulative risk associated with co-occurring risk factors for cigarette smoking. The purpose of the present study was to address that knowledge gap in a U.S. nationally representative sample.Data were obtained from 114,426 adults (≥18years) in the U.S. National Survey on Drug Use and Health (years 2011-13). Multiple logistic regression and classification and regression tree (CART) modeling were used to examine risk of current smoking associated with eight co-occurring risk factors (age, gender, race/ethnicity, educational attainment, poverty, drug abuse/dependence, alcohol abuse/dependence, mental illness).Each of these eight risk factors was independently associated with significant increases in the odds of smoking when concurrently present in a multiple logistic regression model. Effects of risk-factor combinations were typically summative. Exceptions to that pattern were in the direction of less-than-summative effects when one of the combined risk factors was associated with generally high or low rates of smoking (e.g., drug abuse/dependence, age ≥65). CART modeling identified subpopulation risk profiles wherein smoking prevalence varied from a low of 11% to a high of 74% depending on particular risk factor combinations. Being a college graduate was the strongest independent predictor of smoking status, classifying 30% of the adult population.These results offer strong evidence that the effects associated with common risk factors for cigarette smoking are independent, cumulative, and generally summative. The results also offer potentially useful insights into national population risk profiles around which U.S. tobacco policies can be developed or refined.

In the U.S., guidelines recommend that women continue mammography screening until at least age 74, but recent evidence suggests declining screening rates in older women. We estimated adherence to screening mammography and multilevel factors associated with adherence in a longitudinal cohort of older women. Women aged 66–75 years receiving screening mammography within the Breast Cancer Surveillance Consortium were linked to Medicare claims (2005–2010). Claims data identified baseline adherence, defined as receiving subsequent mammography within approximately 2 years, and length of time adherent to guidelines. Characteristics associated with adherence were investigated using logistic and Cox proportional hazards regression models. Analyses were stratified by age to investigate variation in relationships between patient factors and adherence. Among 49,775 women, 89% were adherent at baseline. Among women 66–70 years, those with less than a high school education were more likely to be non-adherent at baseline (odds ratio [OR] 1.96; 95% confidence interval [CI] 1.65–2.33) and remain adherent for less time (hazard ratio [HR] 1.41; 95% CI 1.11–1.80) compared to women with a college degree. Women with ≥ 1 versus no Charlson co-morbidities were more likely to be non-adherent at baseline (OR 1.46; 95% CI 1.31–1.62) and remain adherent for less time (HR 1.44; 95% CI 1.24–1.66). Women aged 71–75 had lower adherence overall, but factors associated with non-adherence were similar. In summary, adherence to guidelines is high among Medicare-enrolled women in the U.S. receiving screening mammography. Efforts are needed to ensure that vulnerable populations attain these same high levels of adherence.