Breast Cancer Surveillance Consortium Registries Research Articles

Variation in second breast cancer risk after primary invasive cancer by time since primary cancer diagnosis and estrogen receptor status.

In women with previously treated breast cancer, occurrence and timing of second breast cancers have implications for surveillance. The authors examined the timing of second breast cancers by primary cancer estrogen receptor (ER) status in the Breast Cancer Surveillance Consortium. Women who were diagnosed with American Joint Commission on Cancer stage I-III breast cancer were identified within six Breast Cancer Surveillance Consortium registries from 2000 to 2017. Characteristics collected at primary breast cancer diagnosis included demographics, ER status, and treatment. Second breast cancer events included subsequent ipsilateral or contralateral breast cancers diagnosed >6months after primary diagnosis. The authors examined cumulative incidence and second breast cancer rates by primary cancer ER status during 1-5 versus 6-10years after diagnosis. At 10years, the cumulative second breast cancer incidence was 11.8% (95% confidence interval [CI], 10.7%-13.1%) for women with ER-negative disease and 7.5% (95% CI, 7.0%-8.0%) for those with ER-positive disease. Women with ER-negative cancer had higher second breast cancer rates than those with ER-positive cancer during the first 5 years of follow-up (16.0 per 1000 person-years [PY]; 95% CI, 14.2-17.9 per 1000 PY; vs. 7.8 per 1000 PY; 95% CI, 7.3-8.4 per 1000 PY, respectively). After 5 years, second breast cancer rates were similar for women with ER-negative versus ER-positive breast cancer (12.1 per 1000 PY; 95% CI, 9.9-14.7; vs. 9.3 per 1000 PY; 95% CI, 8.4-10.3 per 1000 PY, respectively). ER-negative primary breast cancers are associated with a higher risk of second breast cancers than ER-positive cancers during the first 5 years after diagnosis. Further study is needed to examine the potential benefit of more intensive surveillance targeting these women in the early postdiagnosis period.

Prioritizing Screening Mammograms for Immediate Interpretation and Diagnostic Evaluation on the Basis of Risk for Recall

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 <50 years of age with dense breasts accounted for 20.3% of mammograms and 33.9% of recalls (efficiency ratio = 1.7). Results including facility-level characteristics were similar. ConclusionsPrioritizing women with baseline mammograms or ≥5 years since prior mammogram for immediate interpretation and possible diagnostic evaluation could considerably reduce the number of women needing to return for diagnostic imaging at another visit.

Breast Density Knowledge in a Screening Mammography Population Exposed to Density Notification.

Women are increasingly informed about their breast density due to state density reporting laws. However, accuracy of personal breast density knowledge remains unclear. We compared self-reported with clinically assessed breast density and assessed knowledge of density implications and feelings about future screening. From December 2017 to January 2020, we surveyed women aged 40 to 74 years without prior breast cancer, with a normal screening mammogram in the prior year, and ≥1 recorded breast density measures in four Breast Cancer Surveillance Consortium registries with density reporting laws. We measured agreement between self-reported and BI-RADS breast density categorized as "ever-dense" if heterogeneously or extremely dense within the past 5 years or "never-dense" otherwise, knowledge of dense breast implications, and feelings about future screening. Survey participation was 28% (1,528 of 5,408), and 59% (896 of 1,528) of participants had ever-dense breasts. Concordance between self-report versus clinical density was 76% (677 of 896) among women with ever-dense breasts and 14% (89 of 632) among women with never-dense breasts, and 34% (217 of 632) with never-dense breasts reported being told they had dense breasts. Desire for supplemental screening was more frequent among those who reported having dense breasts 29% (256 of 893) or asked to imagine having dense breasts 30% (152 of 513) versus those reporting nondense breasts 15% (15 of 102) (P= .003, P= .002, respectively). Women with never-dense breasts had 6.3-fold higher odds (95% confidence interval:3.39-11.80) of accurate knowledge in states reporting density to all compared to states reporting only to women with dense breasts. Standardized communications of breast density results to all women may increase density knowledge and are needed to support informed screening decisions.

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

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 < 0.001) and increased with Charlson Comorbidity Score (CCS = 0:14.4 (13.5–15.3), CCS = 1:16.6 (15.2–18.1), CCS ≥2:19.0 (16.9–21.5), ptrend < 0.001).Biopsy rates increased with CCS at ages 66–74 and 75–84 but not 85–94. Core and surgical biopsy rates increased with CCS at ages 66–74 only. For each biopsy type, the yield of invasive breast cancer increased with age irrespective of comorbidity. DiscussionWomen aged 66–84 with significant comorbidity in a breast cancer screening population had higher breast biopsy rates and similar rates of invasive breast cancer diagnosis than their counterparts with lower comorbidity. A considerable proportion of these diagnoses may represent overdiagnoses, given the high competing risk of death from non-breast-cancer causes among older women.

Digital Mammography and Breast Tomosynthesis Performance in Women with a Personal History of Breast Cancer, 2007-2016.

Background Since 2007, digital mammography and digital breast tomosynthesis (DBT) replaced screen-film mammography. Whether these technologic advances have improved diagnostic performance has, to the knowledge of the authors, not yet been established. Purpose To evaluate the performance and outcomes of surveillance mammography (digital mammography and DBT) performed from 2007 to 2016 in women with a personal history of breast cancer and compare with data from 1996 to 2007 and the performance of digital mammography screening benchmarks. Materials and Methods In this observational cohort study, five Breast Cancer Surveillance Consortium registries provided prospectively collected mammography data linked with tumor registry and pathologic outcomes. This study identified asymptomatic women with American Joint Committee on Cancer anatomic stages 0-III primary breast cancer who underwent surveillance mammography from 2007 to 2016. The primary outcome was a second breast cancer diagnosis within 1 year of mammography. Performance measures included the recall rate, cancer detection rate, interval cancer rate, positive predictive value of biopsy recommendation, sensitivity, and specificity. Results Among 32 331 women who underwent 117 971 surveillance mammographic examinations (112 269 digital mammographic examinations and 5702 DBT examinations), the mean age at initial diagnosis was 59 years ± 12 (standard deviation). Of 1418 second breast cancers diagnosed, 998 were surveillance-detected cancers and 420 were interval cancers. The recall rate was 8.8% (10 365 of 117 971; 95% CI: 8.6%, 9.0%), the cancer detection rate was 8.5 per 1000 examinations (998 of 117 971; 95% CI: 8.0, 9.0), the interval cancer rate was 3.6 per 1000 examinations (420 of 117 971; 95% CI: 3.2, 3.9), the positive predictive value of biopsy recommendation was 31.0% (998 of 3220; 95% CI: 29.4%, 32.7%), the sensitivity was 70.4% (998 of 1418; 95% CI: 67.9%, 72.7%), and the specificity was 98.1% (114 331 of 116 553; 95% CI: 98.0%, 98.2%). Compared with previously published studies, interval cancer rate was comparable with rates from 1996 to 2007 in women with a personal history of breast cancer and was higher than the published digital mammography screening benchmarks. Conclusion In transitioning from screen-film to digital mammography and digital breast tomosynthesis, surveillance mammography performance demonstrated minimal improvement over time and remained inferior to the performance of screening mammography benchmarks. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Moy and Gao in this issue.

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

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

Assessment of Machine Learning of Breast Pathology Structures for Automated Differentiation of Breast Cancer and High-Risk Proliferative Lesions

Following recent US Food and Drug Administration approval, adoption of whole slide imaging in clinical settings may be imminent, and diagnostic accuracy, particularly among challenging breast biopsy specimens, may benefit from computerized diagnostic support tools. To develop and evaluate computer vision methods to assist pathologists in diagnosing the full spectrum of breast biopsy samples, from benign to invasive cancer. In this diagnostic study, 240 breast biopsies from Breast Cancer Surveillance Consortium registries that varied by breast density, diagnosis, patient age, and biopsy type were selected, reviewed, and categorized by 3 expert pathologists as benign, atypia, ductal carcinoma in situ (DCIS), and invasive cancer. The atypia and DCIS cases were oversampled to increase statistical power. High-resolution digital slide images were obtained, and 2 automated image features (tissue distribution feature and structure feature) were developed and evaluated according to the consensus diagnosis of the expert panel. The performance of the automated image analysis methods was compared with independent interpretations from 87 practicing US pathologists. Data analysis was performed between February 2017 and February 2019. Diagnostic accuracy defined by consensus reference standard of 3 experienced breast pathologists. The accuracy of machine learning tissue distribution features, structure features, and pathologists for classification of invasive cancer vs noninvasive cancer was 0.94, 0.91, and 0.98, respectively; the accuracy of classification of atypia and DCIS vs benign tissue was 0.70, 0.70, and 0.81, respectively; and the accuracy of classification of DCIS vs atypia was 0.83, 0.85, and 0.80, respectively. The sensitivity of both machine learning features was lower than that of the pathologists for the invasive vs noninvasive classification (tissue distribution feature, 0.70; structure feature, 0.49; pathologists, 0.84) but higher for the classification of atypia and DCIS vs benign cases (tissue distribution feature, 0.79; structure feature, 0.85; pathologists, 0.72) and the classification of DCIS vs atypia (tissue distribution feature, 0.88; structure feature, 0.89; pathologists, 0.70). For the DCIS vs atypia classification, the specificity of the machine learning feature classification was similar to that of the pathologists (tissue distribution feature, 0.78; structure feature, 0.80; pathologists, 0.82). The computer-based automated approach to interpreting breast pathology showed promise, especially as a diagnostic aid in differentiating DCIS from atypical hyperplasia.

Performance of Screening Ultrasonography as an Adjunct to Screening Mammography in Women Across the Spectrum of Breast Cancer Risk

Whole-breast ultrasonography has been advocated to supplement screening mammography to improve outcomes in women with dense breasts. To determine the performance of screening mammography plus screening ultrasonography compared with screening mammography alone in community practice. Observational cohort study. Two Breast Cancer Surveillance Consortium registries provided prospectively collected data on screening mammography with vs without same-day breast ultrasonography from January 1, 2000, to December 31, 2013. The dates of analysis were March 2014 to December 2018. A total of 6081 screening mammography plus same-day screening ultrasonography examinations in 3386 women were propensity score matched 1:5 to 30 062 screening mammograms without screening ultrasonography in 15 176 women from a sample of 113 293 mammograms. Exclusion criteria included a personal history of breast cancer and self-reported breast symptoms. Screening mammography with vs without screening ultrasonography. Cancer detection rate and rates of interval cancer, false-positive biopsy recommendation, short-interval follow-up, and positive predictive value of biopsy recommendation were estimated and compared using log binomial regression. Screening mammography with vs without ultrasonography examinations was performed more often in women with dense breasts (74.3% [n = 4317 of 5810] vs 35.9% [n = 39 928 of 111 306] in the overall sample), in women who were younger than 50 years (49.7% [n = 3022 of 6081] vs 31.7% [n = 16 897 of 112 462]), and in women with a family history of breast cancer (42.9% [n = 2595 of 6055] vs 15.0% [n = 16 897 of 112 462]). While 21.4% (n = 1154 of 5392) of screening ultrasonography examinations were performed in women with high or very high (≥2.50%) Breast Cancer Surveillance Consortium 5-year risk scores, 53.6% (n = 2889 of 5392) had low or average (<1.67%) risk. Comparing mammography plus ultrasonography with mammography alone, the cancer detection rate was similar at 5.4 vs 5.5 per 1000 screens (adjusted relative risk [RR], 1.14; 95% CI, 0.76-1.68), as were interval cancer rates at 1.5 vs 1.9 per 1000 screens (RR, 0.67; 95% CI, 0.33-1.37). The false-positive biopsy rates were significantly higher at 52.0 vs 22.2 per 1000 screens (RR, 2.23; 95% CI, 1.93-2.58), as was short-interval follow-up at 3.9% vs 1.1% (RR, 3.10; 95% CI, 2.60-3.70). The positive predictive value of biopsy recommendation was significantly lower at 9.5% vs 21.4% (RR, 0.50; 95% CI, 0.35-0.71). In a relatively young population of women at low, intermediate, and high breast cancer risk, these results suggest that the benefits of supplemental ultrasonography screening may not outweigh associated harms.

Breast Density and Risk of Invasive Breast Cancer among Older Women Undergoing Mammography: The Breast Cancer Surveillance Consortium Cohort Study

Abstract This study examined whether breast density is associated with risk of breast cancer in women age ≥65 years undergoing screening mammography in community practice. Methods: We used prospective cohort data between 1996 and 2012 from the Breast Cancer Surveillance Consortium (BCSC). We calculated separate cumulative incidence models for breast cancer incidence according to Breast Imaging Reporting and Data System (BI-RADS) breast density for women ages 65–74 and ages ≥75. Multivariable Cox proportional hazards regression models were fitted to determine the risk of invasive breast cancer adjusted for BCSC registry, race/ethnicity, BMI, hormone therapy use and benign breast disease. Results: Among the 403,268 women included in the study, approximately 40% were ages ≥75. The annual incidence rate of invasive breast cancer increased with increasing breast density among women ages 65–74 [BI- RADS fatty breasts: 2.2% (95% CI, 2.1%–2.4%) vs. heterogeneously or extremely dense breasts: 4.7% (95% CI, 4.6%–4.9%)] and women ages 75+ [BI-RADS fatty breasts: 2.3% (95% CI, 2.1%–2.5%) vs. heterogeneously or extremely dense: 4.3% (95% CI, 4.1%–4.5%)]. Women with BI-RADS fatty breasts had a decreased risk of breast cancer among women ages 65–74 [HR: 0.66 (95% CI: 0.58%–0.78%) and women ages ≥75 [HR: 0.73 (95% CI: 0.62%–0.87%). Women with BI-RADS heterogeneously or extremely dense breasts were found to have increased risk of breast cancer among women ages 65–74 [HR: 1.39 (95% CI: 1.28%–1.51%)] and women ages ≥75 [HR: 1.23 (95% CI: 1.10%–1.37%)]. Conclusions: Older women with higher BI-RADS density had a significantly increased risk of breast cancer. These findings add further evidence that breast density continues to be associated with an increased risk of breast cancer, even among women age ≥75 years.

Family History and Breast Cancer Risk Among Older Women in the Breast Cancer Surveillance Consortium Cohort

First-degree family history is a strong risk factor for breast cancer, but controversy exists about the magnitude of the association among older women. To determine whether first-degree family history is associated with increased risk of breast cancer among older women, and identify whether the association varies by breast density. Prospective cohort study between 1996 and 2012 from 7 Breast Cancer Surveillance Consortium (BCSC) registries located in New Hampshire, North Carolina, San Francisco Bay area, western Washington state, New Mexico, Colorado, and Vermont. During a mean (SD) follow-up of 6.3 (3.2) years, 10 929 invasive breast cancers were diagnosed in a cohort of 403 268 women 65 years and older with data from 472 220 mammography examinations. We estimated the 5-year cumulative incidence of invasive breast cancer by first-degree family history, breast density, and age groups. Cox proportional hazards models were fit to estimate the association of first-degree family history with risk of invasive breast cancer (after adjustment for breast density, BCSC registry, race/ethnicity, body mass index, postmenopausal hormone therapy use, and benign breast disease for age groups 65 to 74 years and 75 years and older, separately). Data analyses were performed between June 2016 and June 2017. First-degree family history of breast cancer. Incident breast cancer. In 403 268 women 65 years and older, first-degree family history was associated with an increased risk of breast cancer among women ages 65 to 74 years (hazard ratio [HR], 1.48; 95% CI, 1.35-1.61) and 75 years and older (HR, 1.44; 95% CI, 1.28-1.62). Estimates were similar for women 65 to 74 years with first-degree relative's diagnosis age younger than 50 years (HR, 1.47; 95% CI, 1.25-1.73) vs 50 years and older (HR, 1.33; 95% CI, 1.17-1.51) and for women ages 75 years and older with the relative's diagnosis age younger than 50 years (HR, 1.31; 95% CI, 1.05-1.63) vs 50 years and older (HR, 1.55; 95% CI, 1.33-1.81). Among women ages 65 to 74 years, the risk associated with first-degree family history was highest among those with fatty breasts (HR, 1.67; 95% CI, 1.27-2.21), whereas in women 75 years and older the risk associated with family history was highest among those with dense breasts (HR, 1.55; 95% CI, 1.29-1.87). First-degree family history was associated with increased risk of invasive breast cancer in all subgroups of older women irrespective of a relative's age at diagnosis.

Relationship between preoperative breast MRI and surgical treatment of non-metastatic breast cancer.

More extensive surgical treatments for early stage breast cancer are increasing. The patterns of preoperative MRI overall and by stage for this trend has not been well established. Using Breast Cancer Surveillance Consortium registry data from 2010 through 2014, we identified women with an incident non-metastatic breast cancer and determined use of preoperative MRI and initial surgical treatment (mastectomy, with or without contralateral prophylactic mastectomy (CPM), reconstruction, and breast conserving surgery ± radiation). Clinical and sociodemographic covariates were included in multivariable logistic regression models to estimate adjusted odds ratios and 95% confidence intervals. Of the 13 097 women, 2217 (16.9%) had a preoperative MRI. Among the women with MRI, results indicated 32% higher odds of unilateral mastectomy compared to breast conserving surgery and of mastectomy with CPM compared to unilateral mastectomy. Women with preoperative MRI also had 56% higher odds of reconstruction. Preoperative MRI in women with DCIS and early stage invasive breast cancer is associated with more frequent mastectomy, CPM, and reconstruction surgical treatment. Use of more extensive surgical treatment and reconstruction among women with DCIS and early stage invasive cancer whom undergo MRI warrants further investigation.

Correlation Between Screening Mammography Interpretive Performance on a Test Set and Performance in Clinical Practice

Evidence is inconsistent about whether radiologists' interpretive performance on a screening mammography test set reflects their performance in clinical practice. This study aimed to estimate the correlation between test set and clinical performance and determine if the correlation is influenced by cancer prevalence or lesion difficulty in the test set. This institutional review board-approved study randomized 83 radiologists from six Breast Cancer Surveillance Consortium registries to assess one of four test sets of 109 screening mammograms each; 48 radiologists completed a fifth test set of 110 mammograms 2 years later. Test sets differed in number of cancer cases and difficulty of lesion detection. Test set sensitivity and specificity were estimated using woman-level and breast-level recall with cancer status and expert opinion as gold standards. Clinical performance was estimated using women-level recall with cancer status as the gold standard. Spearman rank correlations between test set and clinical performance with 95% confidence intervals (CI) were estimated. For test sets with fewer cancers (N = 15) that were more difficult to detect, correlations were weak to moderate for sensitivity (woman level = 0.46, 95% CI = 0.16, 0.69; breast level = 0.35, 95% CI = 0.03, 0.61) and weak for specificity (0.24, 95% CI = 0.01, 0.45) relative to expert recall. Correlations for test sets with more cancers (N = 30) were close to 0 and not statistically significant. Correlations between screening performance on a test set and performance in clinical practice are not strong. Test set performance more accurately reflects performance in clinical practice if cancer prevalence is low and lesions are challenging to detect.

National Performance Benchmarks for Modern Diagnostic Digital Mammography: Update from the Breast Cancer Surveillance Consortium

Purpose To establish contemporary performance benchmarks for diagnostic digital mammography with use of recent data from the Breast Cancer Surveillance Consortium (BCSC). Materials and Methods Institutional review board approval was obtained for active or passive consenting processes or to obtain a waiver of consent to enroll participants, link data, and perform analyses. Data were obtained from six BCSC registries (418 radiologists, 92 radiology facilities). Mammogram indication and assessments were prospectively collected for women undergoing diagnostic digital mammography and linked with cancer diagnoses from state cancer registries. The study included 401 548 examinations conducted from 2007 to 2013 in 265 360 women. Results Overall diagnostic performance measures were as follows: cancer detection rate, 34.7 per 1000 (95% confidence interval [CI]: 34.1, 35.2); abnormal interpretation rate, 12.6% (95% CI: 12.5%, 12.7%); positive predictive value (PPV) of a biopsy recommendation (PPV2), 27.5% (95% CI: 27.1%, 27.9%); PPV of biopsies performed (PPV3), 30.4% (95% CI: 29.9%, 30.9%); false-negative rate, 4.8 per 1000 (95% CI: 4.6, 5.0); sensitivity, 87.8% (95% CI: 87.3%, 88.4%); and specificity, 90.5% (95% CI: 90.4%, 90.6%). Among cancers detected, 63.4% were stage 0 or 1 cancers, 45.6% were minimal cancers, the mean size of invasive cancers was 21.2 mm, and 69.6% of invasive cancers were node negative. Performance metrics varied widely across diagnostic indications, with cancer detection rate (64.5 per 1000) and abnormal interpretation rate (18.7%) highest for diagnostic mammograms obtained to evaluate a breast problem with a lump. Compared with performance during the screen-film mammography era, diagnostic digital performance showed increased abnormal interpretation and cancer detection rates and decreasing PPVs, with less than 70% of radiologists within acceptable ranges for PPV2 and PPV3. Conclusion These performance measures can serve as national benchmarks that may help transform the marked variation in radiologists' diagnostic performance into targeted quality improvement efforts. © RSNA, 2017 Online supplemental material is available for this article.

Relationship of Predicted Risk of Developing Invasive Breast Cancer, as Assessed with Three Models, and Breast Cancer Mortality among Breast Cancer Patients.

PurposeBreast cancer risk prediction models are used to plan clinical trials and counsel women; however, relationships of predicted risks of breast cancer incidence and prognosis after breast cancer diagnosis are unknown.MethodsUsing largely pre-diagnostic information from the Breast Cancer Surveillance Consortium (BCSC) for 37,939 invasive breast cancers (1996–2007), we estimated 5-year breast cancer risk (<1%; 1–1.66%; ≥1.67%) with three models: BCSC 1-year risk model (BCSC-1; adapted to 5-year predictions); Breast Cancer Risk Assessment Tool (BCRAT); and BCSC 5-year risk model (BCSC-5). Breast cancer-specific mortality post-diagnosis (range: 1–13 years; median: 5.4–5.6 years) was related to predicted risk of developing breast cancer using unadjusted Cox proportional hazards models, and in age-stratified (35–44; 45–54; 55–69; 70–89 years) models adjusted for continuous age, BCSC registry, calendar period, income, mode of presentation, stage and treatment. Mean age at diagnosis was 60 years.ResultsOf 6,021 deaths, 2,993 (49.7%) were ascribed to breast cancer. In unadjusted case-only analyses, predicted breast cancer risk ≥1.67% versus <1.0% was associated with lower risk of breast cancer death; BCSC-1: hazard ratio (HR) = 0.82 (95% CI = 0.75–0.90); BCRAT: HR = 0.72 (95% CI = 0.65–0.81) and BCSC-5: HR = 0.84 (95% CI = 0.75–0.94). Age-stratified, adjusted models showed similar, although mostly non-significant HRs. Among women ages 55–69 years, HRs approximated 1.0. Generally, higher predicted risk was inversely related to percentages of cancers with unfavorable prognostic characteristics, especially among women 35–44 years.ConclusionsAmong cases assessed with three models, higher predicted risk of developing breast cancer was not associated with greater risk of breast cancer death; thus, these models would have limited utility in planning studies to evaluate breast cancer mortality reduction strategies. Further, when offering women counseling, it may be useful to note that high predicted risk of developing breast cancer does not imply that if cancer develops it will behave aggressively.

Validation of a Medicare Claims-based Algorithm for Identifying Breast Cancers Detected at Screening Mammography

The breast cancer detection rate is a benchmark measure of screening mammography quality, but its computation requires linkage of mammography interpretive performance information with cancer incidence data. A Medicare claims-based measure of detected breast cancers could simplify measurement of this benchmark and facilitate mammography quality assessment and research. To validate a claims-based algorithm that can identify with high positive predictive value (PPV) incident breast cancers that were detected at screening mammography. Development of a claims-derived algorithm using classification and regression tree analyses within a random half-sample of Medicare screening mammography claims followed by validation of the algorithm in the remaining half-sample using clinical data on mammography results and cancer incidence from the Breast Cancer Surveillance Consortium (BCSC). Female fee-for-service Medicare enrollees aged 68 years and older who underwent screening mammography from 2001 to 2005 within BCSC registries in 4 states (CA, NC, NH, and VT), enabling linkage of claims and BCSC mammography data (N=233,044 mammograms obtained by 104,997 women). Sensitivity, specificity, and PPV of algorithmic identification of incident breast cancers that were detected by radiologists relative to a reference standard based on BCSC mammography and cancer incidence data. An algorithm based on subsequent codes for breast cancer diagnoses and treatments and follow-up mammography identified incident screen-detected breast cancers with 92.9% sensitivity [95% confidence interval (CI), 91.0%-94.8%], 99.9% specificity (95% CI, 99.9%-99.9%), and a PPV of 88.0% (95% CI, 85.7%-90.4%). A simple claims-based algorithm can accurately identify incident breast cancers detected at screening mammography among Medicare enrollees. The algorithm may enable mammography quality assessment using Medicare claims alone.

Concordance of BI-RADS Assessments and Management Recommendations for Breast MRI in Community Practice.

The purpose of this study was to evaluate concordance between BI-RADS assessments and management recommendations for breast MRI in community practice. Breast 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. In 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. Breast 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.

Disparities in the use of screening magnetic resonance imaging of the breast in community practice by race, ethnicity, and socioeconomic status.

Uptake of breast magnetic resonance imaging (MRI) coupled with breast cancer risk assessment offers the opportunity to tailor the benefits and harms of screening strategies for women with differing cancer risks. Despite the potential benefits, there is also concern for worsening population-based health disparities. Among 316,172 women aged 35 to 69 years from 5 Breast Cancer Surveillance Consortium registries (2007-2012), the authors examined 617,723 negative screening mammograms and 1047 screening MRIs. They examined the relative risks (RRs) of MRI use by women with a <20% lifetime breast cancer risk and RR in the absence of MRI use by women with a ≥20% lifetime risk. Among women with a <20% lifetime risk of breast cancer, non-Hispanic white women were found to be 62% more likely than nonwhite women to undergo an MRI (95% confidence interval, 1.32-1.98). Of these women, those with an educational level of some college or technical school were 43% more likely and those who had at least a college degree were 132% more likely to receive an MRI compared with those with a high school education or less. Among women with a ≥20% lifetime risk, there was no statistically significant difference noted with regard to the use of screening MRI by race or ethnicity, but high-risk women with a high school education or less were less likely to undergo screening MRI than women who had graduated from college (RR, 0.40; 95% confidence interval, 0.25-0.63). Uptake of screening MRI of the breast into clinical practice has the potential to worsen population-based health disparities. Policies beyond health insurance coverage should ensure that the use of this screening modality reflects evidence-based guidelines.

Facility Mammography Volume in Relation to Breast Cancer Screening Outcomes.

To clarify the relationship between facility-level mammography interpretive volume and breast cancer screening outcomes. We calculated annual mammography interpretive volumes from 2000-2009 for 116 facilities participating in the U.S. Breast Cancer Surveillance Consortium (BCSC). Radiology, pathology, cancer registry, and women's self-report information were used to determine the indication for each exam, cancer characteristics, and patient characteristics. We examined the effect of annual total volume and percentage of mammograms that were screening on cancer detection rates using multinomial logistic regression adjusting for age, race/ethnicity, time since last mammogram, and BCSC registries. "Good prognosis" tumours were defined as screen-detected invasive cancers that were <15 mm, early stage, and lymph node negative at diagnosis. From 3,098,481 screening mammograms, 9,899 cancers were screen-detected within one year of the exam. Approximately 80% of facilities had annual total interpretive volumes of >2,000 mammograms, and 42% had >5,000. Higher total volume facilities were significantly more likely to diagnose invasive tumours with good prognoses (odds ratio [OR] 1.32; 95% confidence interval [CI] 1.10-1.60, for total volume of 5,000-10,000/year v. 1,000-2,000/year; p-for-trend <0.001). A concomitant decrease in tumours with poor prognosis was seen (OR 0.78; 95%CI 0.63-0.98 for total volume of 5,000-10,000/year v. 1,000-2,000/year). Mammography facilities with higher total interpretive volumes detected more good prognosis invasive tumours and fewer poor prognosis invasive tumours, suggesting that women attending these facilities may be more likely to benefit from screening.

Patterns of Breast Magnetic Resonance Imaging Use in Community Practice

Breast magnetic resonance imaging (MRI) is increasingly used for breast cancer screening, diagnostic evaluation, and surveillance. However, we lack data on national patterns of breast MRI use in community practice. To describe patterns of breast MRI use in US community practice during the period 2005 through 2009. Observational cohort study using data collected from 2005 through 2009 on breast MRI and mammography from 5 national Breast Cancer Surveillance Consortium registries. Data included 8931 breast MRI examinations and 1,288,924 screening mammograms from women aged 18 to 79 years. We calculated the rate of breast MRI examinations per 1000 women with breast imaging within the same year and described the clinical indications for the breast MRI examinations by year and age. We compared women screened with breast MRI to women screened with mammography alone for patient characteristics and lifetime breast cancer risk. The overall rate of breast MRI from 2005 through 2009 nearly tripled from 4.2 to 11.5 examinations per 1000 women, with the most rapid increase from 2005 to 2007 (P = .02). The most common clinical indication was diagnostic evaluation (40.3%), followed by screening (31.7%). Compared with women who received screening mammography alone, women who underwent screening breast MRI were more likely to be younger than 50 years, white non-Hispanic, and nulliparous and to have a personal history of breast cancer, a family history of breast cancer, and extremely dense breast tissue (all P < .001). The proportion of women screened using breast MRI at high lifetime risk for breast cancer (>20%) increased during the study period from 9% in 2005 to 29% in 2009. Use of breast MRI for screening in high-risk women is increasing. However, our findings suggest that there is a need to improve appropriate use, including among women who may benefit from screening breast MRI.

Upgrade of high-risk breast lesions detected on mammography in the Breast Cancer Surveillance Consortium

BackgroundUpgrade rates of high-risk breast lesions after screening mammography were examined. MethodsThe Breast Cancer Surveillance Consortium registry was used to identify all Breast Imaging Reporting and Data System category 4 assessments followed by needle biopsies with high-risk lesions. Follow-up was performed for all women. ResultsHigh-risk lesions were found in 957 needle biopsies, with excision documented in 53%. Most (n = 685) were atypical ductal hyperplasia (ADH), 173 were lobular neoplasia, and 99 were papillary lesions. Upgrade to cancer varied with type of lesion (18% in ADH, 10% in lobular neoplasia, and 2% in papillary lesions). In premenopausal women with ADH, upgrade was associated with family history. Cancers associated with ADH were mostly (82%) ductal carcinoma in situ, and those associated with lobular neoplasia were mostly (56%) invasive. During a further 2 years of follow-up, cancer was documented in 1% of women with follow-up surgery and in 3% with no surgery. ConclusionsDespite low rates of surgery, low rates of cancer were documented during follow-up. Benign papillary lesions diagnosed on Breast Imaging Reporting and Data System category 4 mammograms among asymptomatic women do not justify surgical excision.