Breast Cancer Surveillance Research Articles

Extending the Breast Cancer Surveillance Consortium Model of Invasive Breast Cancer.

We extended the Breast Cancer Surveillance Consortium (BCSC) version 2 (v2) model of invasive breast cancer risk to include BMI, extended family history of breast cancer, and age at first live birth (version 3 [v3]) to better inform appropriate breast cancer prevention therapies and risk-based screening. We used Cox proportional hazards regression to estimate the age- and race- and ethnicity-specific relative hazards for family history of breast cancer, breast density, history of benign breast biopsy, BMI, and age at first live birth for invasive breast cancer in the BCSC cohort. We evaluated calibration using the ratio of expected-to-observed (E/O) invasive breast cancers in the cohort and discrimination using the area under the receiver operating characteristic curve (AUROC). We analyzed data from 1,455,493 women age 35-79 years without a history of breast cancer. During a mean follow-up of 7.3 years, 30,266 women were diagnosed with invasive breast cancer. The BCSC v3 model had an E/O of 1.03 (95% CI, 1.01 to 1.04) and an AUROC of 0.646 for 5-year risk. Compared with the v2 model, discrimination of the v3 model improved most in Asian, White, and Black women. Among women with a BMI of 30.0-34.9 kg/m2, the true-positive rate in women with an estimated 5-year risk of 3% or higher increased from 10.0% (v2) to 19.8% (v3) and the improvement was greater among women with a BMI of ≥35 kg/m2 (7.6%-19.8%). The BCSC v3 model updates an already well-calibrated and validated breast cancer risk assessment tool to include additional important risk factors. The inclusion of BMI was associated with the largest improvement in estimated risk for individual women.

Personalized surveillance and aftercare for non-metastasized breast cancer: the NABOR study protocol of a multiple interrupted time series design

BackgroundFollow-up of curatively treated primary breast cancer patients consists of surveillance and aftercare and is currently mostly the same for all patients. A more personalized approach, based on patients’ individual risk of recurrence and personal needs and preferences, may reduce patient burden and reduce (healthcare) costs. The NABOR study will examine the (cost-)effectiveness of personalized surveillance (PSP) and personalized aftercare plans (PAP) on patient-reported cancer worry, self-rated and overall quality of life and (cost-)effectiveness.MethodsA prospective multicenter multiple interrupted time series (MITs) design is being used. In this design, 10 participating hospitals will be observed for a period of eighteen months, while they -stepwise- will transit from care as usual to PSPs and PAPs. The PSP contains decisions on the surveillance trajectory based on individual risks and needs, assessed with the ‘Breast Cancer Surveillance Decision Aid’ including the INFLUENCE prediction tool. The PAP contains decisions on the aftercare trajectory based on individual needs and preferences and available care resources, which decision-making is supported by a patient decision aid. Patients are non-metastasized female primary breast cancer patients (N = 1040) who are curatively treated and start follow-up care. Patient reported outcomes will be measured at five points in time during two years of follow-up care (starting about one year after treatment and every six months thereafter). In addition, data on diagnostics and hospital visits from patients’ Electronical Health Records (EHR) will be gathered. Primary outcomes are patient-reported cancer worry (Cancer Worry Scale) and overall quality of life (as assessed with EQ-VAS score). Secondary outcomes include health care costs and resource use, health-related quality of life (as measured with EQ5D-5L/SF-12/EORTC-QLQ-C30), risk perception, shared decision-making, patient satisfaction, societal participation, and cost-effectiveness. Next, the uptake and appreciation of personalized plans and patients’ experiences of their decision-making process will be evaluated.DiscussionThis study will contribute to insight in the (cost-)effectiveness of personalized follow-up care and contributes to development of uniform evidence-based guidelines, stimulating sustainable implementation of personalized surveillance and aftercare plans.Trial registrationStudy sponsor: ZonMw. Retrospectively registered at ClinicalTrials.gov (2023), ID: NCT05975437.

Simultaneous bilateral mastectomy and RRSO for BRCA2-positive non-invasive breast cancer in Japan: a case report and analysis of initial experience.

In Japan, genetic testing, surveillance, and risk-reducing surgery for hereditary breast and ovarian cancer (HBOC) syndrome have been covered by the Japanese national insurance system since April 2020. On the other hand, the current situation is that medical care, including surveillance of undiagnosed (cancer-free) patients, is self-funded even for individuals with HBOC. We report a case in which breast cancer was diagnosed at an early stage during surveillance for cancer-free HBOC at the patient's own expense, and risk-reducing surgery was performed at the same time as treatment for breast cancer. The patient was a 63-year-old woman. Her sister had a history of breast cancer in her 30s and was found to be a BRCA2 pathogenic variant carrier by genetic testing. The patient therefore presented to the genetic department of our hospital and underwent genetic testing (out-of-pocket). A pathogenic variant was found at the same site. During annual breast and ovarian surveillance at the patient's own expense, a physician with sufficient expertise in contrast-enhanced breast magnetic resonance imaging (MRI) noticed a change in the contrast enhancement pattern on breast MRI and performed needle biopsy, revealing ductal carcinoma in situ. At the request of the patient, she underwent concurrent contralateral risk-reducing mastectomy and risk-reducing salpingo-oophorectomy in addition to breast cancer treatment. We encountered a case in which cancer treatment and risk-reducing surgery were performed at the same time for a pathogenic variant carrier who was very anxious about developing cancer. Surveillance of cancer-free BRCA1/2 mutation carriers and expansion of insurance coverage for surgery are important future issues.

Enzyme-catalyzed electrochemical aptasensor for ultrasensitive detection of soluble PD-L1 in breast cancer based on decorated covalent organic frameworks and carbon nanotubes

BackgroundSoluble programmed death-ligand 1 (sPD-L1) is critically involved in breast cancer recurrence and metastasis. However, the clinical application of highly sensitive sPD-L1 assays remains a challenge due to its low abundance in peripheral blood. To address this issue, for the first time, an enzyme-catalyzed electrochemical aptasensing platform was devised, incorporating covalent organic frameworks-gold nanoparticles-antibody-horseradish peroxidase (COFs-AuNPs-Ab-HRP) and polyethyleneimine-functionalized multiwalled carbon nanotubes (MWCNTs-PEI-AuNPs) for the highly specific and ultrasensitive detection of sPD-L1. ResultsMWCNTs-PEI-AuNPs possessed an extensive specific surface area and exhibited excellent electrical conductivity, facilitating the immobilization of aptamer and amplifying the signal. COFs modified with AuNPs not only amplified the electrical signal but also proffered a loading platform for the Ab and HRP. The favorable biocompatibility of COFs contributed to the preservation of enzyme activity and stability. HRP acted in synergy with hydrogen peroxide (H2O2) to catalyze the oxidation of hydroquinone (HQ) to benzoquinone (BQ). Subsequently, BQ underwent electrochemical reduction to HQ, inducing an enzymatic redox cycle that amplified the electrochemical signal and enhanced the sensitivity and selectivity of the detection method. The developed aptasensor displayed a liner range for sPD-L1 identification from 1 pg mL−1 to 100 ng mL−1 and the detection limit reached 0.143 pg mL−1 (S/N = 3). SignificancePaving the way for clinical application, this strategy detected differences in sPD-L1 in cell supernatants and peripheral blood of breast cancer patients with higher sensitivity compared to commercial sPD-L1 ELISA kit. This work demonstrates significant potential in offering reference information for early diagnosis and disease surveillance of breast cancer.

Digital mammography and digital breast tomosynthesis for detecting invasive lobular and ductal carcinoma.

Invasive lobular carcinoma (ILC) is a distinct histological subtype of breast cancer that can make early detection with mammography challenging. We compared imaging performance of digital breast tomosynthesis (DBT) to digital mammography (DM) for diagnoses of ILC, invasive ductal carcinoma (IDC), and invasive mixed carcinoma (IMC) in a screening population. We included screening exams (DM; n = 1,715,249 or DBT; n = 414,793) from 2011 to 2018 among 839,801 women in the Breast Cancer Surveillance Consortium. Examinations were followed for one year to ascertain incident ILC, IDC, or IMC. We measured cancer detection rate (CDR) and interval invasive cancer rate/1000 screening examinations for each histological subtype and stratified by breast density and modality. We calculated relative risk (RR) for DM vs. DBT using log-binomial models to adjust for the propensity of receiving DBT vs. DM. Unadjusted CDR per 1000 mammograms of ILC overall was 0.33 (95%CI: 0.30-0.36) for DM; 0.45 (95%CI: 0.39-0.52) for DBT, and for women with dense breasts- 0.33 (95%CI: 0.29-0.37) for DM and 0.54 (95%CI: 0.43-0.66) for DBT. Similar results were noted for IDC and IMC. Adjusted models showed a significantly increased RR for cancer detection with DBT compared to DM among women with dense breasts for all three histologies (RR; 95%CI: ILC 1.53; 1.09-2.14, IDC 1.21; 1.02-1.44, IMC 1.76; 1.30-2.38), but no significant increase among women with non-dense breasts. DBT was associated with higher CDR for ILC, IDC, and IMC for women with dense breasts. Early detection of ILC with DBT may improve outcomes for this distinct clinical entity.

“I don’t need any more unknowns hanging over my head”: Views of patients with cancer on variants of uncertain significance and low/moderate risk results from genomic sequencing

PurposeWe sought to explore patient-reported utility of all types of cancer results from genomic sequencing (GS). MethodsQualitative study, using semi-structured interviews with patients who underwent GS within a trial. Thematic analysis employing constant comparison was used. Two coders coded transcripts, with use of a third coder to resolve conflicts. Results25 patients participated: female (22), >50 years (18), European (12), Ashkenazi Jewish (5), Middle Eastern (3), or other ethnicity (5), with breast cancer history (20).Patients’ perceptions of the utility of cancer GS results hinged on whether they triggered clinical action. For example, when patients were enrolled into high-risk breast cancer surveillance programs for low/moderate risk breast cancer genes, they perceived the results to be very “useful” and of moderate-high utility. In contrast, patients receiving low/moderate risk or primary variants of uncertain significance results without clinical action perceived results as “concerning,” leading to harms, such as hypervigilance about cancer symptoms.Overall, having supportive relatives or providers enhanced perceptions of utility. ConclusionPatients’ perceptions of cancer GS results hinged on whether they triggered clinical management. Consequently, patients who received results without clinical action became hypervigilant, experiencing harms. Our findings call for a need to develop practice interventions to support patients with cancer undergoing GS.

Assessing Mode of Recurrence in Breast Cancer to Identify an Optimised Follow-Up Pathway: 10-Year Institutional Review.

Breast cancer surveillance programmes ensure early identification of recurrence which maximises overall survival. Programmes include annual clinical examination and radiological assessment. There remains debate around the value of annual clinical exam in diagnosing recurrent disease/second primaries. The aim was to assess diagnostic modalities for recurrent breast cancer with a focus on evaluating the role of annual clinical examination. A prospectively maintained database from a symptomatic breast cancer service between 2010-2020 was reviewed. Patients with biopsy-proven recurrence/second breast primary were included. The primary outcome was the diagnostic modality by which recurrences/secondary breast cancers were observed. Diagnostic modalities included (i) self-detection by the patient, (ii) clinical examination by a breast surgeon or (iii) radiological assessment. A total of 233 patients were identified and, following application of exclusion criteria, a total of 140 patients were included. A total of 65/140 (46%) patients were diagnosed clinically, either by self-detection or clinical examination, while 75/140 (54%) were diagnosed radiologically. A total of 59/65 (91%) of patients clinically diagnosed with recurrence presented to the breast clinic after self-detection of an abnormality. Four (6%) patients had cognitive impairment and recurrence was diagnosed by a carer. Two (3%) patients were diagnosed with recurrence by a breast surgeon at clinical examination. The median time to recurrence in all patients was 48 months (range 2-263 months). Clinical examination provides little value in diagnosing recurrence (<5%) and surveillance programmes may benefit from reduced focus on such a modality. Regular radiological assessment and ensuring patients have urgent/easy access to a breast clinic if they develop new symptoms/signs should be the focus of surveillance programmes.

Longitudinal adherence to breast cancer surveillance following cancer genetic testing in an integrated health care system.

Screening with mammography and breast magnetic resonance imaging (MRI) is an important risk management strategy for individuals with inherited pathogenic variants (PVs) in genes associated with increased breast cancer risk. We describe longitudinal screening adherence in individuals who underwent cancer genetic testing as part of usual care in a vertically integrated health system. We determined the proportion time covered (PTC) by annual mammography and breast MRI for individuals with PVs in TP53, BRCA1, BRCA2, PALB2, NF1, CHEK2, and ATM. We determined time covered by biennial mammography beginning at age 50years for individuals who received negative results, uncertain results, or with PVs in genes without specific breast cancer screening recommendations. One hundred and forty individuals had PVs in TP53, BRCA1, BRCA2, PALB2, NF1, CHEK2, or ATM. Among these individuals, average PTC was 48% (range 0-99%) for annual screening mammography and 34% (range 0-100%) for annual breast MRI. Average PTC was highest for individuals with PVs in CHEK2 (N = 14) and lowest for individuals with PVs in TP53 (N = 3). Average PTC for biennial mammography (N = 1,027) was 49% (0-100%). Longitudinal screening adherence in individuals with PVs in breast cancer associated genes, as measured by the proportion of time covered, is low; adherence to annual breast MRI falls below that of annual mammography. Additional research should examine screening behavior in individuals with PVs in breast cancer associated genes with a goal of developing interventions to improve adherence to recommended risk management.

Racial and Ethnic Variation in Diagnostic Mammography Performance among Women Reporting a Breast Lump.

We evaluated diagnostic mammography among women with a breast lump to determine whether performance varied across racial and ethnic groups. This study included 51,014 diagnostic mammograms performed between 2005 and 2018 in the Breast Cancer Surveillance Consortium among Asian/Pacific Islander (12%), Black (7%), Hispanic/Latina (6%), and White (75%) women reporting a lump. Breast cancers occurring within 1 year were ascertained from cancer registry linkages. Multivariable regression was used to adjust performance statistic comparisons for breast cancer risk factors, mammogram modality, demographics, additional imaging, and imaging facility. Cancer detection rates were highest among Asian/Pacific Islander [per 1,000 exams, 84.2 (95% confidence interval (CI): 72.0-98.2)] and Black women [81.4 (95% CI: 69.4-95.2)] and lowest among Hispanic/Latina women [42.9 (95% CI: 34.2-53.6)]. Positive predictive values (PPV) were higher among Black [37.0% (95% CI: 31.2-43.3)] and White [37.0% (95% CI: 30.0-44.6)] women and lowest among Hispanic/Latina women [22.0% (95% CI: 17.2-27.7)]. False-positive results were most common among Asian/Pacific Islander women [per 1,000 exams, 183.9 (95% CI: 126.7-259.2)] and lowest among White women [112.4 (95% CI: 86.1-145.5)]. After adjustment, false-positive and cancer detection rates remained higher for Asian/Pacific Islander and Black women (vs. Hispanic/Latina and White). Adjusted PPV was highest among Asian/Pacific Islander women. Among women with a lump, Asian/Pacific Islander and Black women were more likely to have cancer detected and more likely to receive a false-positive result compared with White and Hispanic/Latina women. Strategies for optimizing diagnostic mammography among women with a lump may vary by racial/ethnic group, but additional factors that influence performance differences need to be identified. See related In the Spotlight, p. 1479.

Evaluating clinical efficacy of hospital-based surveillance with mammography and ultrasonography for breast cancer

Periodic mammography and/or sonography examinations are conducted across numerous hospitals nationalwidely, especially for antedees with a positive mammography screening. Despite the regular practice, clinical efficacy of hospital-based breast cancer surveillance remains unclear. Specifically, the impact of surveillance interval upon survival and prognostic surrogates stratified by menopausal status, as well as malignant transition rate should be deciphered. We retrieved cancer registry to ascertain 841 breast cancers with surveillance history through administration data. Healthy controls underwent breast surveillance and were concurrently free of cancer. More benign diseases rather than cancers were identified from premenopausal women (age ≤50 years) with sonography alone within one year, as well as older women (age >50) with both mammography and sonography one to two years before a cancer or benign diagnosis. Among breast cancers, mammography alone during the antecedent one to two years had a protective effect for diagnosing carcinoma in situ rather than invasive cancer (age-adjusted odds ratio: 0.048, P=0.016). Three-state time homogeneous Markov model showed that hospital-based breast surveillance within 2 years of disease onset reduced the malignant transition rate by 65.16% (59.79-76.74%). The clinical efficacy of breast cancer surveillance was evidenced.

Sources of Disparities in Surveillance Mammography Performance and Risk-Guided Recommendations for Supplemental Breast Imaging: A Simulation Study.

Surveillance mammography is recommended for all women with a history of breast cancer. Risk-guided surveillance incorporating advanced imaging modalities based on individual risk of a second cancer could improve cancer detection. However, personalized surveillance may also amplify disparities. In simulated populations using inputs from the Breast Cancer Surveillance Consortium (BCSC), we investigated race- and ethnicity-based disparities. Disparities were decomposed into those due to primary breast cancer and treatment characteristics, social determinants of health (SDOH) and differential error in second cancer ascertainment by modeling populations with or without variation across race and ethnicity in the distribution of these characteristics. We estimated effects of disparities on mammography performance and supplemental imaging recommendations stratified by race and ethnicity. In simulated cohorts based on 65,446 BCSC surveillance mammograms, when only cancer characteristics varied by race and ethnicity, mammograms for Black women had lower sensitivity compared with the overall population (64.1% vs. 71.1%). Differences between Black women and the overall population were larger when both cancer characteristics and SDOH varied by race and ethnicity (53.8% vs. 71.1%). Basing supplemental imaging recommendations on high predicted second cancer risk resulted in less frequent recommendations for Hispanic (6.7%) and Asian/Pacific Islander women (6.4%) compared with the overall population (10.0%). Variation in cancer characteristics and SDOH led to disparities in surveillance mammography performance and recommendations for supplemental imaging. Risk-guided surveillance imaging may exacerbate disparities. Decision-makers should consider implications for equity in cancer outcomes resulting from implementing risk-guided screening programs. See related In the Spotlight, p. 1479.

Individualizing Breast Cancer Surveillance According to Tumor Subtype

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

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

Region-of-Interest Optimization for Deep-Learning-Based Breast Cancer Detection in Mammograms

The early detection and diagnosis of breast cancer may increase survival rates and reduce overall treatment costs. The cancer of the breast is a severe and potentially fatal disease that impacts individuals worldwide. Mammography is a widely utilized imaging technique for breast cancer surveillance and diagnosis. However, images produced with mammography frequently contain noise, poor contrast, and other anomalies that hinder radiologists from interpreting the images. This study develops a novel deep-learning technique for breast cancer detection using mammography images. The proposed procedure consists of two primary steps: region-of-interest (ROI) (1) extraction and (2) classification. At the beginning of the procedure, a YOLOX model is utilized to distinguish breast tissue from the background and to identify ROIs that may contain lesions. In the second phase, the EfficientNet or ConvNeXt model is applied to the data to identify benign or malignant ROIs. The proposed technique is validated using a large dataset of mammography images from various institutions and compared to several baseline methods. The pF1 index is used to measure the effectiveness of the technique, which aims to establish a balance between the number of false positives and false negatives, and is a harmonic mean of accuracy and recall. The proposed method outperformed existing methods by an average of 8.0%, obtaining superior levels of precision and sensitivity, and area under the receiver operating characteristics curve (ROC AUC) and the precision–recall curve (PR AUC). In addition, ablation research was conducted to investigate the effects of the procedure’s numerous components. According to the findings, the proposed technique is another choice that could enhance the detection and diagnosis of breast cancer using mammography images.

Impact of BMI on Prevalence of Dense Breasts by Race and Ethnicity.

Density notification laws require notifying women of dense breasts with dense breast prevalence varying by race/ethnicity. We evaluated whether differences in body mass index (BMI) account for differences in dense breasts prevalence by race/ethnicity. Prevalence of dense breasts (heterogeneously or extremely dense) according to Breast Imaging Reporting and Data System and obesity (BMI > 30 kg/m2) were estimated from 2,667,207 mammography examinations among 866,033 women in the Breast Cancer Surveillance Consortium (BCSC) from January 2005 through April 2021. Prevalence ratios (PR) for dense breasts relative to overall prevalence by race/ethnicity were estimated by standardizing race/ethnicity prevalence in the BCSC to the 2020 U.S. population, and adjusting for age, menopausal status, and BMI using logistic regression. Dense breasts were most prevalent among Asian women (66.0%) followed by non-Hispanic/Latina (NH) White (45.5%), Hispanic/Latina (45.3%), and NH Black (37.0%) women. Obesity was most prevalent in Black women (58.4%) followed by Hispanic/Latina (39.3%), NH White (30.6%), and Asian (8.5%) women. The adjusted prevalence of dense breasts was 19% higher [PR = 1.19; 95% confidence interval (CI), 1.19-1.20] in Asian women, 8% higher (PR = 1.08; 95% CI, 1.07-1.08) in Black women, the same in Hispanic/Latina women (PR = 1.00; 95% CI, 0.99-1.01), and 4% lower (PR = 0.96; 95% CI, 0.96-0.97) in NH White women relative to the overall prevalence. Clinically important differences in breast density prevalence are present across racial/ethnic groups after accounting for age, menopausal status, and BMI. If breast density is the sole criterion used to notify women of dense breasts and discuss supplemental screening it may result in implementing inequitable screening strategies across racial/ethnic groups. See related In the Spotlight, p. 1479.

The impact of social determinants of health (SDOH) on use of germline genetic testing for triple-negative breast cancer (TNBC) in the community oncology setting.

1094 Background: TNBC presents at an earlier age of onset and at a more advanced stage, and is associated with a worse outcome in African American women. In a subset of patients, TNBC is associated with germline BRCA1 and/or BRCA2 mutations. Genetic testing improves breast cancer and other surveillance as well as treatment outcomes. Current NCCN Guidelines recommend germline testing for all patients with any stage TNBC. Previous versions recommended testing in patients aged 60 years or younger. This study aimed to identify factors associated with receiving genetic testing among patients with TNBC in the community oncology setting. Methods: This was a retrospective observational cross-sectional study examining patient profiles, demographics, SDOH indicators, and germline genetic testing data. Patients in The US Oncology Network diagnosed with any stage TNBC between 3/31/2017 and 9/30/2021 aged 60 years or younger were identified.Data from the iKnowMed EHR was used for patient identification, baseline characteristics, and social determinants, including area deprivation index (ADI), a validated measure of socioeconomic status (SES) based on address. Mean ADI percentile scores using national and state level benchmarks were calculated as well as stratifications above and below the 80th percentile (where higher scores &gt; 80 are markers of low SES). Evidence of germline genetic testing (yes/no) was compiled from iKM, network genetic databases, and confirmatory chart audits. Only US Oncology Network sites participating in confirmatory audits were included in this analysis. Results: Among participating sites, 1318 patients with TNBC were identified with a mean age of 49 years; 58% were White, 22% Black, 3% Asian, and 16% other/unknown; and evidence for germline genetic testing was found for 981 (74.4%). Statistically significant differences in germline testing rates were found for age (48.4 years for tested, 50.7 years for not tested); race (67% for Black patients, 77% for White); US census region (68% in South, 70% in Midwest, 83% in Northeast, and 87% in West); practice size (mean number of physicians: 32.8 per practice for testing group, 29.2 for untested); and for nationally benchmarked ADI score (mean ADI of 42.3: tested and 47.1 for not tested). No significant difference was seen across the spectrum of ethnicity, with 82% testing among Hispanic or Latino patients compared with 74% for non-Hispanic or Latino, p = 0.074. No significant differences were observed for clinical variables. Conclusions: We report that 75% of patients with TNBC in our community oncology network received genetic testing. However, significantly lower testing rates were observed for patients who were Black, had lower SES, and resided in the South and Midwest geographic regions. Further research should be performed to understand reasons why testing was not done, to address barriers.

The role of ct-DNA in breast cancer surveillance assessing treatment response and recurrence: A community center experience.

e13021 Background: Breast cancer is a heterogeneous disease and primarily classified on immunohistochemistry. Currently treatment is based on biopsy but studies have showed changes in subtype and acquired resistance in the original subtype due to cancer therapies. While biopsy is gold standard, recently liquid biopsy from serum containing circulating tumor DNA (ct-DNA) has emerged as a noninvasive technique of tumor surveillance. Methods: This is a retrospective study approved by the IRB at Monmouth Medical Center. Objectives were to identify use of ct-DNA level and highlight the trends over course of treatment. Subjects were identified by reviewing patient’s charts and included on criteria of age &gt; 18 years and in whom ct-DNA level was followed up. 27 patients were identified and results were obtained by categorizing the patients and calculating the proportions. Results: A total of 27 patients were included. The mean age at diagnosis of cancer was 56.29 years (95% CI 51.19-61.39). Among 27 patients, 11 had left sided and 16 had right sided tumor. The pathology identified was Invasive ductal in 18, adenocarcinoma in 2, lobular in 4, poorly differentiated in 2 and mesenchymal in 1 of the patients. Hormonal subtypes identified were triple negative in 11, ER/PR+ve/Her 2-ve in 8, triple positive in 2, ER/PR-ve/Her 2+ve in 1 and ER+ve in 5 of the patients. Among 27, 8 of the patients had stage I, 15 had stage II, 3 had stage III and 1 had stage IV disease. During the course of treatment, 7 of patients had left, 10 had right and 7 had bilateral mastectomy due to BRCA mutation identified on genetic testing. 3 of the patients did not undergo surgery. ct-DNA levels were elevated 8.05 and 1.31 MTM/ml in 2 patients and subsequently became undetectable and decrease in tumor size was noticed from 6.1 cm to 1.1 cm and 1.8 cm to 9mm. ct-DNA levels remained undetectable the rest of 25 patients and patient’s remained gross tumor free on interval MRI imaging of the breasts. Conclusions: The ct-DNA levels have a great utility in establishing the correlation of treatment effect on tumor volume. All this information is vital for clinical decision making and appropriate management. Therefore, the application of liquid biopsy and ct-DNA analysis in breast cancer opens a window of opportunity that encompasses all possible disease situations: from early diagnosis, through the detection of minimal residual disease, the early detection of relapse, and the monitoring and treatment planning for advanced disease. A limitation of study was low sample size. [Table: see text]

Digital Breast Tomosynthesis versus Digital Mammography Screening Performance on Successive Screening Rounds from the Breast Cancer Surveillance Consortium.

Background Prior cross-sectional studies have observed that breast cancer screening with digital breast tomosynthesis (DBT) has a lower recall rate and higher cancer detection rate compared with digital mammography (DM). Purpose To evaluate breast cancer screening outcomes with DBT versus DM on successive screening rounds. Materials and Methods In this retrospective cohort study, data from 58 breast imaging facilities in the Breast Cancer Surveillance Consortium were collected. Analysis included women aged 40-79 years undergoing DBT or DM screening from 2011 to 2020. Absolute differences in screening outcomes by modality and screening round were estimated during the study period by using generalized estimating equations with marginal standardization to adjust for differences in women's risk characteristics across modality and round. Results A total of 523 485 DBT examinations (mean age of women, 58.7 years ± 9.7 [SD]) and 1 008 123 DM examinations (mean age, 58.4 years ± 9.8) among 504 863 women were evaluated. DBT and DM recall rates decreased with successive screening round, but absolute recall rates in each round were significantly lower with DBT versus DM (round 1 difference, -3.3% [95% CI: -4.6, -2.1] [P < .001]; round 2 difference, -1.8% [95% CI: -2.9, -0.7] [P = .003]; round 3 or above difference, -1.2% [95% CI: -2.4, -0.1] [P = .03]). DBT had significantly higher cancer detection (difference, 0.6 per 1000 examinations [95% CI: 0.2, 1.1]; P = .009) compared with DM only for round 3 and above. There were no significant differences in interval cancer rate (round 1 difference, 0.00 per 1000 examinations [95% CI: -0.24, 0.30] [P = .96]; round 2 or above difference, 0.04 [95% CI: -0.19, 0.31] [P = .76]) or total advanced cancer rate (round 1 difference, 0.00 per 1000 examinations [95% CI: -0.15, 0.19] [P = .94]; round 2 or above difference, -0.06 [95% CI: -0.18, 0.11] [P = .43]). Conclusion DBT had lower recall rates and could help detect more cancers than DM across three screening rounds, with no difference in interval or advanced cancer rates. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Skaane in this issue.

Test sensitivity in a prospective cancer screening program: A critique of a common proxy measure.

The true sensitivity of a cancer screening test, defined as the frequency with which the test returns a positive result if the cancer is present, is a key indicator of diagnostic performance. Given the challenges of directly assessing test sensitivity in a prospective screening program, proxy measures for true sensitivity are frequently reported. We call one such proxy empirical sensitivity, as it is given by the observed ratio of screen-detected cancers to the sum of screen-detected and interval cancers. In the setting of the canonical three-state Markov model for progression from preclinical onset to clinical diagnosis, we formulate a mathematical relationship for how empirical sensitivity varies with the screening interval and the mean preclinical sojourn time and identify conditions under which empirical sensitivity exceeds or falls short of true sensitivity. In particular, when the inter-screening interval is short relative to the mean sojourn time, empirical sensitivity tends to exceed true sensitivity, unless true sensitivity is high. The Breast Cancer Surveillance Consortium (BCSC) has reported an estimate of 0.87 for the empirical sensitivity of digital mammography. We show that this corresponds to a true sensitivity of 0.82 under a mean sojourn time of 3.6 years estimated based on breast cancer screening trials. However, the BCSC estimate of empirical sensitivity corresponds to even lower true sensitivity under more contemporary, longer estimates of mean sojourn time. Consistently applied nomenclature that distinguishes empirical sensitivity from true sensitivity is needed to ensure that published estimates of sensitivity from prospective screening studies are properly interpreted.

Breast cancer risk prediction combining a convolutional neural network-based mammographic evaluation with clinical factors.

Deep learning techniques, including convolutional neural networks (CNN), have the potential to improve breast cancer risk prediction compared to traditional risk models. We assessed whether combining a CNN-based mammographic evaluation with clinical factors in the Breast Cancer Surveillance Consortium (BCSC) model improved risk prediction. We conducted a retrospective cohort study among 23,467 women, age 35-74, undergoing screening mammography (2014-2018). We extracted electronic health record (EHR) data on risk factors. We identified 121 women who subsequently developed invasive breast cancer at least 1year after the baseline mammogram. Mammograms were analyzed with a pixel-wise mammographic evaluation using CNN architecture. We used logistic regression models with breast cancer incidence as the outcome and predictors including clinical factors only (BCSC model) or combined with CNN risk score (hybrid model). We compared model prediction performance via area under the receiver operating characteristics curves (AUCs). Mean age was 55.9years (SD, 9.5) with 9.3% non-Hispanic Black and 36% Hispanic. Our hybrid model did not significantly improve risk prediction compared to the BCSC model (AUC of 0.654 vs 0.624, respectively, p = 0.063). In subgroup analyses, the hybrid model outperformed the BCSC model among non-Hispanic Blacks (AUC 0.845 vs. 0.589; p = 0.026) and Hispanics (AUC 0.650 vs 0.595; p = 0.049). We aimed to develop an efficient breast cancer risk assessment method using CNN risk score and clinical factors from the EHR. With future validation in a larger cohort, our CNN model combined with clinical factors may help predict breast cancer risk in a cohort of racially/ethnically diverse women undergoing screening.