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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 7 Breast 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

BackgroundWe evaluated differences in diagnostic mammography performance based on women's race/ethnicity.MethodsThis 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.ResultsAmong 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.ConclusionsDiagnostic 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.ImpactDiagnostic mammography performance studies should include racially and ethnically diverse populations to provide an accurate view of the population-level effects.

IntroductionLimited evidence exists on the impact of age and comorbidity on biopsy rates and findings among older women.Materials and methodsWe 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.ResultsOf 524,860 screening mammograms, 9830 biopsies were performed following 7930 exams (1.5%) within one year, specifically 5589 core biopsies (1.1%), 3422 (0.7%) surgical biopsies and 819 FNAs (0.2%). Biopsy rates per 1000 screens decreased with age (66-74:15.7, 95%CI:14.8-16.8), 75-84:14.5(13.5-15.6), 85-94:13.2(11.3,15.4), ptrend

PurposePreoperative breast MRI is used to evaluate for additional cancer and extent of disease for newly diagnosed breast cancer, yet benefits and harms of preoperative MRI are not well-documented. We examined whether preoperative MRI yields additional biopsy and cancer detection by extent of breast density.MethodsWe followed women in the Breast Cancer Surveillance Consortium with an incident breast cancer diagnosed from 2005 to 2017. We quantified breast biopsies and cancers detected within 6 months of diagnosis by preoperative breast MRI receipt, overall and by breast density, accounting for MRI selection bias using inverse probability weighted logistic regression.ResultsAmong 19,324 women with newly diagnosed breast cancer, 28% had preoperative MRI, 11% additional biopsy, and 5% additional cancer detected. Four times as many women with preoperative MRI underwent additional biopsy compared to women without MRI (22.6% v. 5.1%). Additional biopsy rates with preoperative MRI increased with increasing breast density (27.4% for extremely dense compared to 16.2% for almost entirely fatty breasts). Rates of additional cancer detection were almost four times higher for women with v. without MRI (9.9% v. 2.6%). Conditional on additional biopsy, age-adjusted rates of additional cancer detection were lowest among women with extremely dense breasts, regardless of imaging modality (with MRI: 35.0%; 95% CI 27.0-43.0%; without MRI: 45.1%; 95% CI 32.6-57.5%).ConclusionFor women with dense breasts, preoperative MRI was associated with much higher biopsy rates, without concomitant higher cancer detection. Preoperative MRI may be considered for some women, but selecting women based on breast density is not supported by evidence.Trial registrationClinicalTrials.gov: NCT02980848; registered 2017.

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.

As more artificial intelligence (AI)-enhanced mammography screening tools enter the clinical market, greater focus will be placed on external validation in diverse patient populations. In this viewpoint, we outline lessons learned from prior efforts in this field, the need to validate algorithms on newer screening technologies and diverse patient populations, and conclude by discussing the need for a framework for continuous monitoring and recalibration of these AI tools. Sufficient validation and continuous monitoring of emerging AI tools for breast cancer screening will require greater stakeholder engagement and the creation of shared policies and guidelines.

BackgroundEstablished 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.MethodsThe 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.ResultsThe 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%).ConclusionsEstablished 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.

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.

ImportanceMany 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.ObjectiveTo evaluate radiologists' recall and cancer detection rates before and after beginning interpretation of DBT examinations.Design, setting, and participantsThis 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.ExposuresDigital breast tomosynthesis and DM screening examinations.Main outcomes and measuresRecall rate and cancer detection rate.ResultsA 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 relevanceIn 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.

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.

ObjectiveThe purpose of this study was to determine whether digital breast tomosynthesis (DBT) adoption was associated with a decrease in screening mammography capacity across Breast Cancer Screening Consortium facilities, given concerns about increasing imaging and interpretation times associated with DBT.Subjects and methodsFacility characteristics and examination volume data were collected prospectively from Breast Cancer Screening Consortium facilities that adopted DBT between 2011 and 2014. Interrupted time series analyses using Poisson regression models in which facility was considered a random effect were used to evaluate differences between monthly screening volumes during the 12-month preadoption period and the 12-month postadoption period (with the two periods separated by a 3-month lag) and to test for changes in month-to-month facility-level screening volume during the preadoption and postadoption periods.ResultsAcross five regional breast imaging registries, 15 of 83 facilities (18.1%) adopted DBT for screening between 2011 and 2014. Most had no academic affiliation (73.3% [11/15]), were nonprofit (80.0% [12/15]), and were general radiology practices (66.7% [10/15]). Facility-level monthly screening volumes were slightly higher during the postadoption versus preadoption periods (relative risk [RR], 1.09; 95% CI, 1.06-1.11). Monthly screening volumes remained relatively stable within the preadoption period (RR, 1.00 per month; 95% CI 1.00-1.01 per month) and the postadoption period (RR, 1.00; 95% CI, 1.00-1.01 per month).ConclusionIn a cohort of facilities with varied characteristics, monthly screening examination volumes did not decrease after DBT adoption.

PurposeThis study aims to determine whether radiologists who perform well in screening also perform well in interpreting diagnostic mammography.Materials and methodsWe evaluated the accuracy of 468 radiologists interpreting 2,234,947 screening and 196,164 diagnostic mammograms. Adjusting for site, radiologist, and patient characteristics, we identified radiologists with performance in the highest tertile and compared to those with lower performance.ResultsA moderate correlation was noted for radiologists' accuracy when interpreting screening versus their accuracy on diagnostic examinations: sensitivity (rspearman=0.51, 95% CI: 0.22, 0.80; P=.0006) and specificity (rspearman=0.40, 95% CI: 0.30, 0.49; P

ObjectiveAmong vulnerable women, unequal access to advanced breast imaging modalities beyond screening mammography may lead to delays in cancer diagnosis and unfavourable outcomes. We aimed to compare on-site availability of advanced breast imaging services (ultrasound, magnetic resonance imaging [MRI], and image-guided biopsy) between imaging facilities serving vulnerable patient populations and those serving non-vulnerable populations.Setting73 imaging facilities across five Breast Cancer Surveillance Consortium regional registries in the United States during 2011 and 2012.MethodsWe examined facility and patient characteristics across a large, national sample of imaging facilities and patients served. We characterized facilities as serving vulnerable populations based on the proportion of mammograms performed on women with lower educational attainment, lower median income, racial/ethnic minority status, and rural residence.We performed multivariable logistic regression to determine relative risks of on-site availability of advanced imaging at facilities serving vulnerable women versus facilities serving non-vulnerable women.ResultsFacilities serving vulnerable populations were as likely (Relative risk [RR] for MRI = 0.71, 95% Confidence Interval [CI] 0.42, 1.19; RR for MRI-guided biopsy = 1.07 [0.61, 1.90]; RR for stereotactic biopsy = 1.18 [0.75, 1.85]) or more likely (RR for ultrasound = 1.38 [95% CI 1.09, 1.74]; RR for ultrasound-guided biopsy = 1.67 [1.30, 2.14]) to offer advanced breast imaging services as those serving non-vulnerable populations.ConclusionsAdvanced breast imaging services are physically available on-site for vulnerable women in the United States, but it is unknown whether factors such as insurance coverage or out-of-pocket costs might limit their use.

BackgroundEstimates of risk for radiation-induced breast cancer from mammography screening have not considered variation in dose exposure or diagnostic work-up after abnormal screening results.ObjectiveTo estimate distributions of radiation-induced breast cancer incidence and mortality from digital mammography screening while considering exposure from screening and diagnostic mammography and dose variation among women.Design2 simulation-modeling approaches.SettingU.S. population.PatientsWomen aged 40 to 74 years.InterventionAnnual or biennial digital mammography screening from age 40, 45, or 50 years until age 74 years.MeasurementsLifetime breast cancer deaths averted (benefits) and radiation-induced breast cancer incidence and mortality (harms) per 100,000 women screened.ResultsAnnual screening of 100,000 women aged 40 to 74 years was projected to induce 125 breast cancer cases (95% CI, 88 to 178) leading to 16 deaths (CI, 11 to 23), relative to 968 breast cancer deaths averted by early detection from screening. Women exposed at the 95th percentile were projected to develop 246 cases of radiation-induced breast cancer leading to 32 deaths per 100,000 women. Women with large breasts requiring extra views for complete examination (8% of population) were projected to have greater radiation-induced breast cancer risk (266 cancer cases and 35 deaths per 100,000 women) than other women (113 cancer cases and 15 deaths per 100,000 women). Biennial screening starting at age 50 years reduced risk for radiation-induced cancer 5-fold.LimitationLife-years lost from radiation-induced breast cancer could not be estimated.ConclusionRadiation-induced breast cancer incidence and mortality from digital mammography screening are affected by dose variability from screening, resultant diagnostic work-up, initiation age, and screening frequency. Women with large breasts may have a greater risk for radiation-induced breast cancer.Primary funding sourceAgency for Healthcare Research and Quality, U.S. Preventive Services Task Force, National Cancer Institute.

ObjectiveThe purpose of this study was to evaluate concordance between BI-RADS assessments and management recommendations for breast MRI in community practice.Materials and methodsBreast MRI data were collected from four regional Breast Cancer Surveillance Consortium registries from 2005 to 2011 for women who were 18-79 years old. Assessments and recommendations were compared to determine concordance according to BI-RADS guidelines. Concordance was compared by assessment category as well as by year of examination and clinical indication.ResultsIn all, 8283 MRI examinations were included in the analysis. Concordance was highest (93% [2475/2657]) in examinations with a BI-RADS category 2 (benign) assessment. Concordance was also high in examinations with category 1 (negative) (87% [1669/1909]), category 0 (incomplete) (83% [348/417]), category 5 (highly suggestive of malignancy) (83% [208/252]), and category 4 (suspicious) (74% [734/993]) assessments. Examinations with categories 3 (probably benign) and 6 (known biopsy-proven malignancy) assessments had the lowest concordance rates (36% [302/837] and 56% [676/1218], respectively). The most frequent discordant recommendation for a category 3 assessment was routine follow-up. The most frequent discordant recommendation for a category 6 assessment was biopsy. Concordance of assessments and management recommendations differed across clinical indications (p < 0.0001), with the lowest concordance in examinations to assess disease extent.ConclusionBreast MRI BI-RADS management recommendations were most concordant for assessments of negative, incomplete, suspicious, and highly suggestive of malignancy. Lower concordance for assessments of probably benign and known biopsy-proven malignancy and for examinations performed to assess disease extent highlight areas for interventions to improve breast MRI reporting.

PurposeTo evaluate the effectiveness of combined biennial digital mammography and tomosynthesis screening, compared with biennial digital mammography screening alone, among women with dense breasts.Materials and methodsAn established, discrete-event breast cancer simulation model was used to estimate the comparative clinical effectiveness and cost-effectiveness of biennial screening with both digital mammography and tomosynthesis versus digital mammography alone among U.S. women aged 50-74 years with dense breasts from a federal payer perspective and a lifetime horizon. Input values were estimated for test performance, costs, and health state utilities from the National Cancer Institute Breast Cancer Surveillance Consortium, Medicare reimbursement rates, and medical literature. Sensitivity analyses were performed to determine the implications of varying key model parameters, including combined screening sensitivity and specificity, transient utility decrement of diagnostic work-up, and additional cost of tomosynthesis.ResultsFor the base-case analysis, the incremental cost per quality-adjusted life year gained by adding tomosynthesis to digital mammography screening was $53 893. An additional 0.5 deaths were averted and 405 false-positive findings avoided per 1000 women after 12 rounds of screening. Combined screening remained cost-effective (less than $100 000 per quality-adjusted life year gained) over a wide range of incremental improvements in test performance. Overall, cost-effectiveness was most sensitive to the additional cost of tomosynthesis.ConclusionBiennial combined digital mammography and tomosynthesis screening for U.S. women aged 50-74 years with dense breasts is likely to be cost-effective if priced appropriately (up to $226 for combined examinations vs $139 for digital mammography alone) and if reported interpretive performance metrics of improved specificity with tomosynthesis are met in routine practice.

BackgroundMany states have laws requiring mammography facilities to tell women with dense breasts and negative results on screening mammography to discuss supplemental screening tests with their providers. The most readily available supplemental screening method is ultrasonography, but little is known about its effectiveness.ObjectiveTo evaluate the benefits, harms, and cost-effectiveness of supplemental ultrasonography screening for women with dense breasts.DesignComparative modeling with 3 validated simulation models.Data sourcesSurveillance, Epidemiology, and End Results Program; Breast Cancer Surveillance Consortium; and medical literature.Target populationContemporary cohort of women eligible for routine screening.Time horizonLifetime.PerspectivePayer.InterventionSupplemental ultrasonography screening for women with dense breasts after a negative screening mammography result.Outcome measuresBreast cancer deaths averted, quality-adjusted life-years (QALYs) gained, biopsies recommended after a false-positive ultrasonography result, and costs.Results of base-case analysisSupplemental ultrasonography screening after a negative mammography result for women aged 50 to 74 years with heterogeneously or extremely dense breasts averted 0.36 additional breast cancer deaths (range across models, 0.14 to 0.75), gained 1.7 QALYs (range, 0.9 to 4.7), and resulted in 354 biopsy recommendations after a false-positive ultrasonography result (range, 345 to 421) per 1000 women with dense breasts compared with biennial screening by mammography alone. The cost-effectiveness ratio was $325,000 per QALY gained (range, $112,000 to $766,000). Supplemental ultrasonography screening for only women with extremely dense breasts cost $246,000 per QALY gained (range, $74,000 to $535,000).Results of sensitivity analysisThe conclusions were not sensitive to ultrasonography performance characteristics, screening frequency, or starting age.LimitationProvider costs for coordinating supplemental ultrasonography were not considered.ConclusionSupplemental ultrasonography screening for women with dense breasts would substantially increase costs while producing relatively small benefits.Primary funding sourceNational Cancer Institute.

PurposeThe breast imaging modalities of mammography, ultrasound, and MRI are widely used for screening, diagnosis, treatment, and surveillance of breast cancer. Geographic access to breast imaging services in various modalities is not known at a national level overall or for population subgroups.MethodsA retrospective study of 2004-2008 Medicare claims data was conducted to identify ZIP codes in which breast imaging occurred, and data were mapped. Estimated travel times were made for each modality for 215,798 census block groups in the contiguous United States. Using Census 2010 data, travel times were characterized by sociodemographic factors for 92,788,909 women aged ≥30 years, overall, and by subgroups of age, race/ethnicity, rurality, education, and median income.ResultsOverall, 85% of women had travel times of ≤20 minutes to nearest mammography or ultrasound services, and 70% had travel times of ≤20 minutes for MRI with little variation by age. Native American women had median travel times 2-3 times longer for all 3 modalities, compared to women of other racial/ethnic groups. For rural women, median travel times to breast imaging services were 4-8-fold longer than they were for urban women. Black and Asian women had the shortest median travel times to services for all 3 modalities.ConclusionsTravel times to mammography and ultrasound breast imaging facilities are short for most women, but for breast MRI, travel times are notably longer. Native American and rural women are disadvantaged in geographic access based on travel times to breast imaging services. This work informs potential interventions to reduce inequities in access and utilization.

To characterize patients' willingness to donate a biospecimen for future research as part of a breast cancer-related biobank involving a general screening population. We performed a prospective cross-sectional study of 4,217 women aged 21-89 years presenting to our facilities for screening mammogram between December 2010 and October 2011. This HIPAA-compliant study was approved by our institutional review board. We collected data on patients' interest in and actual donation of a biospecimen, motivators and barriers to donating, demographic information, and personal breast cancer risk factors. A multivariate logistic regression analysis was performed to identify patient-level characteristics associated with an increased likelihood to donate. Mean patient age was 57.8 years (SD 11.1 years). While 66.0 % (2,785/4,217) of patients were willing to donate blood or saliva during their visit, only 56.4 % (2,378/4,217) actually donated. Women with a college education (OR = 1.27, p = 0.003), older age (OR = 1.02, p < 0.001), previous breast biopsy (OR = 1.23, p = 0.012), family history of breast cancer (OR = 1.23, p = 0.004), or a comorbidity (OR = 1.22, p = 0.014) were more likely to donate. Asian-American women were significantly less likely to donate (OR = 0.74, p = 0.005). The major reason for donating was to help all future patients (42.3 %) and the major reason for declining donation was privacy concerns (22.3 %). A large proportion of women participating in a breast cancer screening registry are willing to donate blood or saliva to a biobank. Among minority participants, Asian-American women are less likely to donate and further qualitative research is required to identify novel active recruitment strategies to insure their involvement.