The Importance of Outcomes Ascertainment for Accurate Assessment of the Mammography Screening Cancer Detection Rate: A Simulation Study.

PURPOSE: Cancer detection rate (CDR), an important metric in the mammography screening audit, is designed to ensure adequate sensitivity. Most practices use biopsy results as the reference standard; however, commonly ascertainment of biopsy results is incomplete. We used simulation to determine the relationship between the cancer ascertainment rate of biopsy (AR-biopsy), CDR estimation, and associated error rates in classifying whether practices and radiologists meet the established ACR benchmark of 2.5 per 1,000. MATERIALS AND METHODS: We simulated screening mammography volume, number of cancers detected, and CDR, using negative binomial and beta-binomial distributions, respectively. Simulations were performed at both the practice and radiologist level. Average CDR was based on linearly rescaling a published CDR by the AR-biopsy. CDR distributions were simulated for AR-biopsy between 5% and 100% in steps of five percentage points and were summarized with boxplots and smoothed histograms over the range of AR-biopsy, to quantify the proportion of practices and radiologists meeting the ACR benchmark at each level of AR-biopsy. RESULTS: Decreasing AR-biopsy led to an increasing probability of categorizing CDR performance as being below the ACR benchmark. Our simulation predicts that at the practice level, an AR-biopsy of 65% categorizes 17.6% below the benchmark (compared to 1.6% at an AR-biopsy of 100%), and at the radiologist level, an AR-biopsy of 65% categorizes 34.7% as being below the benchmark (compared to 11.6% at an AR-biopsy of 100%). CONCLUSIONS: Our simulation demonstrates that decreasing the AR-biopsy (in currently clinically relevant ranges) has the potential to artifactually lower the assessed CDR on both the practice and radiologist levels and may, in turn, increase the chance of erroneous categorization of underperformance per the ACR benchmark.

ENIGMA CHEK2gether Project: A Comprehensive Study Identifies Functionally Impaired CHEK2 Germline Missense Variants Associated with Increased Breast Cancer Risk.

PURPOSE: Germline pathogenic variants in CHEK2 confer moderately elevated breast cancer risk (odds ratio, OR ∼ 2.5), qualifying carriers for enhanced breast cancer screening. Besides pathogenic variants, dozens of missense CHEK2 variants of uncertain significance (VUS) have been identified, hampering the clinical utility of germline genetic testing (GGT). EXPERIMENTAL DESIGN: We collected 460 CHEK2 missense VUS identified by the ENIGMA consortium in 15 countries. Their functional characterization was performed using CHEK2-complementation assays quantifying KAP1 phosphorylation and CHK2 autophosphorylation in human RPE1-CHEK2-knockout cells. Concordant results in both functional assays were used to categorize CHEK2 VUS from 12 ENIGMA case-control datasets, including 73,048 female patients with breast cancer and 88,658 ethnicity-matched controls. RESULTS: A total of 430/460 VUS were successfully analyzed, of which 340 (79.1%) were concordant in both functional assays and categorized as functionally impaired (N = 102), functionally intermediate (N = 12), or functionally wild-type (WT)-like (N = 226). We then examined their association with breast cancer risk in the case-control analysis. The OR and 95% CI (confidence intervals) for carriers of functionally impaired, intermediate, and WT-like variants were 2.83 (95% CI, 2.35-3.41), 1.57 (95% CI, 1.41-1.75), and 1.19 (95% CI, 1.08-1.31), respectively. The meta-analysis of population-specific datasets showed similar results. CONCLUSIONS: We determined the functional consequences for the majority of CHEK2 missense VUS found in patients with breast cancer (3,660/4,436; 82.5%). Carriers of functionally impaired missense variants accounted for 0.5% of patients with breast cancer and were associated with a moderate risk similar to that of truncating CHEK2 variants. In contrast, 2.2% of all patients with breast cancer carried functionally wild-type/intermediate missense variants with no clinically relevant breast cancer risk in heterozygous carriers.

Team Science Principles Enhance Cancer Care Delivery Quality Improvement: Interdisciplinary Implementation of Breast Cancer Screening Shared Decision Making.

PURPOSE: Implementing shared decision making (SDM), recommended in screening mammography by national guidelines for women age 40-49 years, faces challenges that innovations in quality improvement and team science (TS) are poised to address. We aimed to improve the effectiveness, patient-centeredness, and efficiency of SDM in primary care for breast cancer screening. METHODS: Our interdisciplinary team included primary and specialty care, psychology, epidemiology, communication science, engineering, and stakeholders (patients and clinicians). Over a 6-year period, we executed two iterative cycles of plan-do-study-act (PDSA) to develop, revise, and implement a SDM tool using TS principles. Patient and physician surveys and retrospective analysis of tool performance informed our first PDSA cycle. Patient and physician surveys, toolkit use, and clinical outcomes in the second PDSA cycle supported SDM implementation. We gathered team member assessments on the importance of individual TS activities. RESULTS: Our first PDSA cycle successfully generated a SDM tool called Breast Cancer Risk Estimator, deemed valuable by 87% of patients surveyed. Our second PDSA cycle increased Breast Cancer Risk Estimator utilization, from 2,000 sessions in 2017 to 4,097 sessions in 2019 while maintaining early-stage breast cancer diagnoses. Although TS activities such as culture, trust, and communication needed to be sustained throughout the project, shared goals, research/data infrastructure support, and leadership were more important earlier in the project and persisted in the later stages of the project. CONCLUSION: Combining rigorous quality improvement and TS principles can support the complex, interdependent, and interdisciplinary activities necessary to improve cancer care delivery exemplified by our implementation of a breast cancer screening SDM tool.

A new perspective on breast cancer diagnostic guidelines to reduce overdiagnosis.

Overdiagnosis of breast cancer, defined as diagnosing a cancer that would otherwise not cause symptoms or death in a patient's lifetime, costs U.S. health care system over $1.2 billion annually. Overdiagnosis rates, estimated to be around 10%-40%, may be reduced if indolent breast findings can be identified and followed with noninvasive imaging rather than biopsy. However, there are no validated guidelines for radiologists to decide when to choose imaging options recognizing cancer grades and types. The aim of this study is to optimize breast cancer diagnostic decisions based on cancer types using a large-scale finite-horizon Markov decision process (MDP) model with 4.6 million states to help reduce overdiagnosis. We prove the optimality of a divide-and-search algorithm that relies on tight upper bounds on the optimal decision thresholds to find an exact optimal solution. We project the high-dimensional MDP onto two lower dimensional MDPs and obtain feasible upper bounds on the optimal decision thresholds. We use real data from two private mammography databases and demonstrate our model performance through a previously validated simulation model that has been used by the policy makers to set the national screening guidelines in the United States. We find that a decision-analytical framework optimizing diagnostic decisions while accounting for breast cancer types has a strong potential to improve the quality of life and alleviate the immense costs of overdiagnosis. Our model leads to a 20 % reduction in overdiagnosis on the screening population, which translates into an annual savings of approximately $300 million for the U.S. health care system.

Surveillance Imaging vs Symptomatic Recurrence Detection and Survival in Stage II-III Breast Cancer (AFT-01).

BACKGROUND: Guidelines for follow-up after locoregional breast cancer treatment recommend imaging for distant metastases only in the presence of patient signs and/or symptoms. However, guidelines have not been updated to reflect advances in imaging, systemic therapy, or the understanding of biological subtype. We assessed the association between mode of distant recurrence detection and survival. METHODS: In this observational study, a stage-stratified random sample of women with stage II-III breast cancer in 2006-2007 and followed through 2016 was selected, including up to 10 women from each of 1217 Commission on Cancer facilities (n = 10 076). The explanatory variable was mode of recurrence detection (asymptomatic imaging vs signs and/or symptoms). The outcome was time from initial cancer diagnosis to death. Registrars abstracted scan type, intent (cancer-related vs not, asymptomatic surveillance vs not), and recurrence. Data were merged with each patient's National Cancer Database record. RESULTS: Surveillance imaging detected 23.3% (284 of 1220) of distant recurrences (76.7%, 936 of 1220 by signs and/or symptoms). Based on propensity-weighted multivariable Cox proportional hazards models, patients with asymptomatic imaging compared with sign and/or symptom detected recurrences had a lower risk of death if estrogen receptor (ER) and progesterone receptor (PR) negative, HER2 negative (triple negative; hazard ratio [HR] = 0.73, 95% confidence interval [CI] = 0.54 to 0.99), or HER2 positive (HR = 0.51, 95% CI = 0.33 to 0.80). No association was observed for ER- or PR-positive, HER2-negative (HR = 1.14, 95% CI = 0.91 to 1.44) cancers. CONCLUSIONS: Recurrence detection by asymptomatic imaging compared with signs and/or symptoms was associated with lower risk of death for triple-negative and HER2-positive, but not ER- or PR-positive, HER2-negative cancers. A randomized trial is warranted to evaluate imaging surveillance for metastases results in these subgroups.

Utilization and Cancer Yield of Probably Benign Assessment Category in the National Mammography Database: 2009 to 2018.

PURPOSE: Data on utilization rate and cancer yield of BI-RADS® category 3 in routine clinical practice in diagnostic mammography are sparse. The aim of this study was to determine utilization rate and cancer yield of BI-RADS 3 in diagnostic mammography in the ACR National Mammography Database (NMD). METHODS: Retrospective analysis of NMD mammograms from January 1, 2009, to June 30, 2018, was performed. BI-RADS 3 utilization rate in diagnostic setting was calculated and stratified by patient, facility, and examination-level variables. Patient-level cancer yield was calculated among women with BI-RADS 3 assessment and adequate follow-up (imaging follow-up ≥24 months or biopsy). Logistic regression was performed to assess the odds of utilization of BI-RADS 3, with respect to facility, examination, and patient variables, and the odds of malignancy among patients with probably benign findings. Chi-square and t tests were used to determine significance (P < .05). RESULTS: Data from 19,443,866 mammograms from 500 NMD facilities across 31 states were analyzed, of which 3,039,952 were diagnostic mammograms. Utilization rate of BI-RADS 3 was 15.5% (470,155 of 3,039,952) in the diagnostic setting. There was a statistically significant difference in BI-RADS 3 utilization rate across all collected variables (P < .001). Patient-level cancer yield at 2-year follow-up was 0.91% (2,009 of 220,672; 95% confidence interval [CI], 0.87%-0.95%) in the diagnostic setting. Patient and examination variables associated with significantly higher likelihood of malignancy included calcifications (odds ratio, 4.27; 95% CI, 2.43-7.51), patient age > 70 years (odds ratio, 3.77; 95% CI, 2.49-5.7), and presence of prior comparisons (odds ratio, 1.23; 95% CI, 1.07-1.42). CONCLUSIONS: In the NMD, BI-RADS 3 assessment was common in diagnostic mammography (15.5%), with an overall cancer yield of 0.91%, less than the benchmark of 2%. Utilization trends in diagnostic mammography warrant further research for optimization of use.

Patient and Clinician Characteristics That Predict Breast Cancer Screening Behavior in 40-49-Year-Old Women.

Guidelines recommend that clinicians practice shared decision-making (SDM) with women in their 40s to discuss breast cancer screening. Traditionally, SDM includes discussion of values and preferences to help determine a decision that is congruent with what the patient desires. We analyzed 54 women's breast cancer screening decisions after a SDM conversation with their clinician. We looked at both patient and clinician characteristics that predicted whether or not a woman would get a screening mammogram. Women with a family history of breast cancer or who had a previous abnormal mammogram had higher rates of screening. Screening rates also varied widely between clinicians, raising the question of whether clinician attitudes impacted the SDM conversation.

Risk of Late-Onset Breast Cancer in Genetically Predisposed Women.

PURPOSE: The prevalence of germline pathogenic variants (PVs) in established breast cancer predisposition genes in women in the general population over age 65 years is not well-defined. However, testing guidelines suggest that women diagnosed with breast cancer over age 65 years might have < 2.5% likelihood of a PV in a high-penetrance gene. This study aimed to establish the frequency of PVs and remaining risks of breast cancer for each gene in women over age 65 years. METHODS: A total of 26,707 women over age 65 years from population-based studies (51.5% with breast cancer and 48.5% unaffected) were tested for PVs in germline predisposition gene. Frequencies of PVs and associations between PVs in each gene and breast cancer were assessed, and remaining lifetime breast cancer risks were estimated for non-Hispanic White women with PVs. RESULTS: The frequency of PVs in predisposition genes was 3.18% for women with breast cancer and 1.48% for unaffected women over age 65 years. PVs in BRCA1, BRCA2, and PALB2 were found in 3.42% of women diagnosed with estrogen receptor (ER)-negative, 1.0% with ER-positive, and 3.01% with triple-negative breast cancer. Frequencies of PVs were lower among women with no first-degree relatives with breast cancer. PVs in CHEK2, PALB2, BRCA2, and BRCA1 were associated with increased risks (odds ratio = 2.9-4.0) of breast cancer. Remaining lifetime risks of breast cancer were ≥ 15% for those with PVs in BRCA1, BRCA2, and PALB2. CONCLUSION: This study suggests that all women diagnosed with triple-negative breast cancer or ER-negative breast cancer should receive genetic testing and that women over age 65 years with BRCA1 and BRCA2 PVs and perhaps with PALB2 and CHEK2 PVs should be considered for magnetic resonance imaging screening.

Risk of Breast Cancer Among Carriers of Pathogenic Variants in Breast Cancer Predisposition Genes Varies by Polygenic Risk Score.

PURPOSE: This study assessed the joint association of pathogenic variants (PVs) in breast cancer (BC) predisposition genes and polygenic risk scores (PRS) with BC in the general population. METHODS: A total of 26,798 non-Hispanic white BC cases and 26,127 controls from predominately population-based studies in the Cancer Risk Estimates Related to Susceptibility consortium were evaluated for PVs in BRCA1, BRCA2, ATM, CHEK2, PALB2, BARD1, BRIP1, CDH1, and NF1. PRS based on 105 common variants were created using effect estimates from BC genome-wide association studies; the performance of an overall BC PRS and estrogen receptor-specific PRS were evaluated. The odds of BC based on the PVs and PRS were estimated using penalized logistic regression. The results were combined with age-specific incidence rates to estimate 5-year and lifetime absolute risks of BC across percentiles of PRS by PV status and first-degree family history of BC. RESULTS: The estimated lifetime risks of BC among general-population noncarriers, based on 10th and 90th percentiles of PRS, were 9.1%-23.9% and 6.7%-18.2% for women with or without first-degree relatives with BC, respectively. Taking PRS into account, more than 95% of BRCA1, BRCA2, and PALB2 carriers had > 20% lifetime risks of BC, whereas, respectively, 52.5% and 69.7% of ATM and CHEK2 carriers without first-degree relatives with BC, and 78.8% and 89.9% of those with a first-degree relative with BC had > 20% risk. CONCLUSION: PRS facilitates personalization of BC risk among carriers of PVs in predisposition genes. Incorporating PRS into BC risk estimation may help identify > 30% of CHEK2 and nearly half of ATM carriers below the 20% lifetime risk threshold, suggesting the addition of PRS may prevent overscreening and enable more personalized risk management approaches.

Quantitative breast density analysis to predict interval and node-positive cancers in pursuit of improved screening protocols: a case-control study.

BACKGROUND: This study investigates whether quantitative breast density (BD) serves as an imaging biomarker for more intensive breast cancer screening by predicting interval, and node-positive cancers. METHODS: This case-control study of 1204 women aged 47-73 includes 599 cancer cases (302 screen-detected, 297 interval; 239 node-positive, 360 node-negative) and 605 controls. Automated BD software calculated fibroglandular volume (FGV), volumetric breast density (VBD) and density grade (DG). A radiologist assessed BD using a visual analogue scale (VAS) from 0 to 100. Logistic regression and area under the receiver operating characteristic curves (AUC) determined whether BD could predict mode of detection (screen-detected or interval); node-negative cancers; node-positive cancers, and all cancers vs. controls. RESULTS: FGV, VBD, VAS, and DG all discriminated interval cancers (all p < 0.01) from controls. Only FGV-quartile discriminated screen-detected cancers (p < 0.01). Based on AUC, FGV discriminated all cancer types better than VBD or VAS. FGV showed a significantly greater discrimination of interval cancers, AUC = 0.65, than of screen-detected cancers, AUC = 0.61 (p < 0.01) as did VBD (0.63 and 0.53, respectively, p < 0.001). CONCLUSION: FGV, VBD, VAS and DG discriminate interval cancers from controls, reflecting some masking risk. Only FGV discriminates screen-detected cancers perhaps adding a unique component of breast cancer risk.

A Population-Based Study of Genes Previously Implicated in Breast Cancer.

BACKGROUND: Population-based estimates of the risk of breast cancer associated with germline pathogenic variants in cancer-predisposition genes are critically needed for risk assessment and management in women with inherited pathogenic variants. METHODS: In a population-based case-control study, we performed sequencing using a custom multigene amplicon-based panel to identify germline pathogenic variants in 28 cancer-predisposition genes among 32,247 women with breast cancer (case patients) and 32,544 unaffected women (controls) from population-based studies in the Cancer Risk Estimates Related to Susceptibility (CARRIERS) consortium. Associations between pathogenic variants in each gene and the risk of breast cancer were assessed. RESULTS: Pathogenic variants in 12 established breast cancer-predisposition genes were detected in 5.03% of case patients and in 1.63% of controls. Pathogenic variants in BRCA1 and BRCA2 were associated with a high risk of breast cancer, with odds ratios of 7.62 (95% confidence interval [CI], 5.33 to 11.27) and 5.23 (95% CI, 4.09 to 6.77), respectively. Pathogenic variants in PALB2 were associated with a moderate risk (odds ratio, 3.83; 95% CI, 2.68 to 5.63). Pathogenic variants in BARD1, RAD51C, and RAD51D were associated with increased risks of estrogen receptor-negative breast cancer and triple-negative breast cancer, whereas pathogenic variants in ATM, CDH1, and CHEK2 were associated with an increased risk of estrogen receptor-positive breast cancer. Pathogenic variants in 16 candidate breast cancer-predisposition genes, including the c.657_661del5 founder pathogenic variant in NBN, were not associated with an increased risk of breast cancer. CONCLUSIONS: This study provides estimates of the prevalence and risk of breast cancer associated with pathogenic variants in known breast cancer-predisposition genes in the U.S. population. These estimates can inform cancer testing and screening and improve clinical management strategies for women in the general population with inherited pathogenic variants in these genes. (Funded by the National Institutes of Health and the Breast Cancer Research Foundation.).

Framing the Clinical Encounter: Shared Decision-Making, Mammography Screening, and Decision Satisfaction.

The study examines whether physicians' framing of clinical interactions is related to patient shared decision-making (SDM) satisfaction when using a clinical decision support tool (CDST) concerning mammographic screening. To answer this question, we combined (a) system log data from a CDST, (b) content coding of the physicians' message framing while using the CDST, and (c) a post-visit patient survey to assess SDM satisfaction concerning screening mammography. Results suggest that two types of message frames - consequence frames and numerical frames - moderated the relationship of the CDST on SDM satisfaction. When the CDST displayed low risk of breast cancer for a patient, physicians were able to improve the cognitive aspects of SDM satisfaction by framing the consequences of mammography screening in positive terms. However, when the physician delivered the numerical information in relative, rather than absolute terms, the patient's SDM satisfaction was reduced. Our study advances previous message framing effect research in health communication from experimental settings to clinical encounters. It also discusses the importance of delivering risk-congruent frames in clinical settings.

Cancer Yield and Patterns of Follow-up for BI-RADS Category 3 after Screening Mammography Recall in the National Mammography Database.

Background The literature supports the use of short-interval follow-up as an alternative to biopsy for lesions assessed as probably benign, Breast Imaging Reporting and Data System (BI-RADS) category 3, with an expected malignancy rate of less than 2%. Purpose To assess outcomes from 6-, 12-, and 24-month follow-up of probably benign findings first identified at recall from screening mammography in the National Mammography Database (NMD). Materials and Methods This retrospective study included women recalled from screening mammography with BI-RADS category 3 assessment at additional evaluation from January 2009 through March 2018 from 471 NMD facilities. Only the first BI-RADS category 3 occurrence for women aged 25 years or older with no personal history of breast cancer was analyzed, with biopsy or 2-year imaging follow-up. Cancer yield and positive predictive value of biopsies performed (PPV3) were determined at each follow-up. Results Among 45 202 women (median age, 55 years; range, 25-90 years) with a BI-RADS category 3 lesion, 1574 (3.5%) underwent biopsy at the time of lesion detection, yielding 72 cancers (cancer yield, 4.6%; 72 of 1574 women). For the remaining 43 628 women who accepted surveillance, 922 were seen within 90 days (with 78 lesions biopsied and 12 [15%] classified as malignant). The women still in surveillance (31 465 of 43 381 women [72.5%]) underwent follow-up mammography at 6 months. Of 3001 (9.5%) lesions biopsied, 456 (15.2%) were malignant (cancer yield, 1.5%; 456 of 31 465 women; 95% confidence interval [CI]: 1.3%, 1.6%). Among 18 748 of 25 997 women (72.1%) in surveillance who underwent follow-up at 12 months, 1219 (6.5%) underwent biopsy with 230 (18.9%) malignant lesions found (cancer yield, 1.2%; 230 of 18 748 women; 95% CI: 1.1%, 1.4%). Through 2-year follow-up, the biopsy rate was 11.2% (4894 of 43 628 women) with a cancer yield of 1.86% (810 malignancies found among 43 628 women; 95% CI: 1.73%, 1.98%) and a PPV3 of 16.6% (810 malignancies found among 4894 women). Conclusion In the National Mammography Database, Breast Imaging Reporting and Data System (BI-RADS) category 3 use is appropriate, with 1.86% cumulative cancer yield through 2-year follow-up. Of 810 malignancies, 468 (57.8%) were diagnosed at or before 6 months, validating necessity of short-interval follow-up of mammographic BI-RADS category 3 findings. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Moy in this issue.

Modeling the natural history of ductal carcinoma in situ based on population data.

BACKGROUND: The incidence of ductal carcinoma in situ (DCIS) has increased substantially since the introduction of mammography screening. Nevertheless, little is known about the natural history of preclinical DCIS in the absence of biopsy or complete excision. METHODS: Two well-established population models evaluated six possible DCIS natural history submodels. The submodels assumed 30%, 50%, or 80% of breast lesions progress from undetectable DCIS to preclinical screen-detectable DCIS; each model additionally allowed or prohibited DCIS regression. Preclinical screen-detectable DCIS could also progress to clinical DCIS or invasive breast cancer (IBC). Applying US population screening dissemination patterns, the models projected age-specific DCIS and IBC incidence that were compared to Surveillance, Epidemiology, and End Results data. Models estimated mean sojourn time (MST) in the preclinical screen-detectable DCIS state, overdiagnosis, and the risk of progression from preclinical screen-detectable DCIS. RESULTS: Without biopsy and surgical excision, the majority of DCIS (64-100%) in the preclinical screen-detectable state progressed to IBC in submodels assuming no DCIS regression (36-100% in submodels allowing for DCIS regression). DCIS overdiagnosis differed substantially between models and submodels, 3.1-65.8%. IBC overdiagnosis ranged 1.3-2.4%. Submodels assuming DCIS regression resulted in a higher DCIS overdiagnosis than submodels without DCIS regression. MST for progressive DCIS varied between 0.2 and 2.5 years. CONCLUSIONS: Our findings suggest that the majority of screen-detectable but unbiopsied preclinical DCIS lesions progress to IBC and that the MST is relatively short. Nevertheless, due to the heterogeneity of DCIS, more research is needed to understand the progression of DCIS by grades and molecular subtypes.

Core Elements of Shared Decision-making for Women Considering Breast Cancer Screening: Results of a Modified Delphi Survey.

BACKGROUND: The United States Preventive Services Task Force recommends individualized breast cancer screening for average-risk women before age 50, advised by risk assessment and shared decision-making (SDM). However, the foundational principles of this recommendation that would inform decision support tools for patients and primary care physicians at the point of care have not been codified. Determining the core elements of SDM for breast cancer screening as valued by patients and primary care providers (PCPs) is necessary for implementing effective SDM tools. The aim of this study is to affirm core elements of SDM in the context of clinical interactions, through a Delphi consensus process. METHODS: A Delphi was conducted with 30 participants (10 women aged 40-49, 10 PCPs, and 10 healthcare decision scientists), to codify core elements of breast cancer screening SDM. The criterion for establishing consensus was a threshold of 80% agreement. The Delphi concluded with an 83% response rate. RESULTS: Of 48 items fielded, 44 met the threshold on the high-importance end of the response scale and were accepted as core elements. Core elements across three thematic categories-information delivery and patient education, interpersonal clinician-patient communication, and framework of the decision-received panelists' support in nearly equal measure. Panelists unanimously agreed that SDM should include provision of clearly understandable information, including that of personal breast cancer risk factors, and benefits and harms of mammography screening, and that PCPs should convey they are listening, knowledgeable, and demonstrate cultural sensitivity. DISCUSSION: This research codifies the core elements of SDM for mammography in women 40-49, augmenting the evidence to inform discussions between patients and physicians. These core elements of SDM have the potential to operationalize SDM for breast cancer screening in an effort to improve public health outcomes.

Long-Term Outcomes and Cost-Effectiveness of Breast Cancer Screening With Digital Breast Tomosynthesis in the United States.

BACKGROUND: Digital breast tomosynthesis (DBT) is increasingly being used for routine breast cancer screening. We projected the long-term impact and cost-effectiveness of DBT compared to conventional digital mammography (DM) for breast cancer screening in the United States. METHODS: Three Cancer Intervention and Surveillance Modeling Network breast cancer models simulated US women ages 40 years and older undergoing breast cancer screening with either DBT or DM starting in 2011 and continuing for the lifetime of the cohort. Screening performance estimates were based on observational data; in an alternative scenario, we assumed 4% higher sensitivity for DBT. Analyses used federal payer perspective; costs and utilities were discounted at 3% annually. Outcomes included breast cancer deaths, quality-adjusted life-years (QALYs), false-positive examinations, costs, and incremental cost-effectiveness ratios (ICERs). RESULTS: Compared to DM, DBT screening resulted in a slight reduction in breast cancer deaths (range across models 0-0.21 per 1000 women), small increase in QALYs (1.97-3.27 per 1000 women), and a 24-28% reduction in false-positive exams (237-268 per 1000 women) relative to DM. ICERs ranged from $195 026 to $270 135 per QALY for DBT relative to DM. When assuming 4% higher DBT sensitivity, ICERs decreased to $130 533-$156 624 per QALY. ICERs were sensitive to DBT costs, decreasing to $78 731 to $168 883 and $52 918 to $118 048 when the additional cost of DBT was reduced to $36 and $26 (from baseline of $56), respectively. CONCLUSION: DBT reduces false-positive exams while achieving similar or slightly improved health benefits. At current reimbursement rates, the additional costs of DBT screening are likely high relative to the benefits gained; however, DBT could be cost-effective at lower screening costs.

Image-based screening for men at high risk for breast cancer: Benefits and drawbacks.

Male breast cancer is a rare malignancy. Due to low prevalence and limited data to support male breast cancer screening, there are currently no recommendations for image-based screening in asymptomatic men and few recommendations for men at high risk for breast cancer. However, symptomatically diagnosed cancers in men are typically advanced, suggesting that earlier detection may improve outcomes. In this article we briefly review the risk factors for male breast cancer, and discuss the potential benefits and possible drawbacks of routine image-based screening for men at high risk for breast cancer.

Age-based versus Risk-based Mammography Screening in Women 40-49 Years Old: A Cross-sectional Study.

Background Risk-based screening in women 40-49 years old has not been evaluated in routine screening mammography practice. Purpose To use a cross-sectional study design to compare the trade-offs of risk-based and age-based screening for women 45 years of age or older to determine short-term outcomes. Materials and Methods A retrospective cross-sectional study was performed by using a database of 20 539 prospectively interpreted consecutive digital screening mammograms in 10 280 average-risk women aged 40-49 years who were screened at an academic medical center between January 1, 2006, and December 31, 2013. Two hypothetical screening scenarios were compared: an age-based (≥45 years) scenario versus a risk-based (a 5-year risk of breast cancer greater than that of an average 50-year-old) scenario. Risk factors for risk-based screening included family history, race, age, prior breast biopsy, and breast density. Outcomes included breast cancers detected at mammography, false-positive mammograms, and benign biopsy findings. Short-term outcomes were compared by using the χ2 test. Results The screening population included 71 148 screening mammograms in 24 928 women with a mean age of 55.5 years ± 8.9 (standard deviation) (age range, 40-74 years). In women 40-49 years old, usual care included 50 screening-detected cancers, 1787 false-positive mammograms, and 384 benign biopsy results. The age-based (≥45 years) screening strategy revealed more cancers than did the risk-based strategy (34 [68%] vs 13 [26%] of 50; P < .001), while prompting more false-positive mammograms (899 [50.3%] vs 216 [12.1%] of 1787; P < .001) and benign biopsy results (175 [45.6%] vs 49 [12.8%] of 384; P < .001). The risk-based strategy demonstrated low levels of eligibility (few screenings) in the 40-44-year age group. Differences in outcomes in the 45-49-year age group explained the overall hypothetical screening strategy differences. Conclusion Risk-based screening for women 40-49 years old includes few women in the 40-44-year age range. Significant trade-offs in the 45-49-year age group explain the overall difference between hypothetical screening scenarios, both of which reduce the benefits as well as the harms of mammography for women 40-49 years old. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Joe and Hayward in this issue.

A Probabilistic Model to Support Radiologists' Classification Decisions in Mammography Practice.

We developed a probabilistic model to support the classification decisions made by radiologists in mammography practice. Using the feature observations and Breast Imaging Reporting and Data System (BI-RADS) classifications from radiologists examining diagnostic and screening mammograms, we modeled their decisions to understand their judgments. Our model could help improve the decisions made by radiologists using their own feature observations and classifications while maintaining their observed sensitivities. Based on 112,433 mammographic cases from 36,111 patients and 13 radiologists at 2 separate institutions with a 1.1% prevalence of malignancy, we trained a probabilistic Bayesian network (BN) to estimate the malignancy probabilities of lesions. For each radiologist, we learned an observed probabilistic threshold within the model. We compared the sensitivity and specificity of each radiologist against the BN model using either their observed threshold or the standard 2% threshold recommended by BI-RADS. We found significant variability among the radiologists' observed thresholds. By applying the observed thresholds, the BN model showed a 0.01% (1 case) increase in false negatives and a 28.9% (3612 cases) reduction in false positives. When using the standard 2% BI-RADS-recommended threshold, there was a 26.7% (47 cases) increase in false negatives and a 47.3% (5911 cases) reduction in false positives. Our results show that we can significantly reduce screening mammography false positives with a minimal increase in false negatives. We find that learning radiologists' observed thresholds provides valuable information regarding the conservativeness of clinical practice and allows us to quantify the variability in sensitivity across and within institutions. Our model could provide support to radiologists to improve their performance and consistency within mammography practice.

Relationships Between Human-Extracted MRI Tumor Phenotypes of Breast Cancer and Clinical Prognostic Indicators Including Receptor Status and Molecular Subtype.

PURPOSE: The purpose of this study was to investigate if human-extracted MRI tumor phenotypes of breast cancer could predict receptor status and tumor molecular subtype using MRIs from The Cancer Genome Atlas project. MATERIALS AND METHODS: Our retrospective interpretation study utilized the analysis of HIPAA-compliant breast MRI data from The Cancer Imaging Archive. One hundred and seven preoperative breast MRIs of biopsy proven invasive breast cancers were analyzed by 3 fellowship-trained breast-imaging radiologists. Each study was scored according to the Breast Imaging Reporting and Data System lexicon for mass and nonmass features. The Spearman rank correlation was used for association analysis of continuous variables; the Kruskal-Wallis test was used for associating continuous outcomes with categorical variables. The Fisher-exact test was used to assess correlations between categorical image-derived features and receptor status. Prediction of estrogen receptor (ER), progesterone receptor, human epidermal growth factor receptor, and molecular subtype were performed using random forest classifiers. RESULTS: ER+ tumors were associated with the absence of rim enhancement (P = 0.019, odds ratio [OR] 5.5), heterogeneous internal enhancement (P = 0.02, OR 6.5), peritumoral edema (P = 0.0001, OR 10.0), and axillary adenopathy (P = 0.04, OR 4.4). ER+ tumors were smaller than ER- tumors (23.7 mm vs 29.2 mm, P = 0.02, OR 8.2). All of these variables except the lack of axillary adenopathy were also associated with progesterone receptor+ status. Luminal A tumors (n = 57) were smaller compared to nonLuminal A (21.8 mm vs 27.5 mm, P = 0.035, OR 7.3) and lacked peritumoral edema (P = 0.001, OR 6.8). Basal like tumors were associated with heterogeneous internal enhancement (P = 0.05, OR 10.1), rim enhancement (P = 0.05, OR6.9), and perituomral edema (P = 0.0001, OR 13.8). CONCLUSIONS: Human extracted MRI tumor phenotypes may be able to differentiate those tumors with a more favorable clinical prognosis from their more aggressive counterparts.