Population Breast Cancer Screening Research Articles

Patient navigation as an effective way to increase breast, cervical, and colorectal cancer screening among immigrants in the US: A systematic review.

e22501 Background: Immigrants undergo recommended cervical, breast, and colorectal cancer screening at a lower frequency than U.S.-born patients and face unique language, educational, and cultural barriers. The delay or lack of screening has known implications in the presentation of breast, cervical, and colorectal malignancies, including worse staging at diagnosis. To address the disparity in cancer screening that immigrants experience, various interventions have been studied, including patient navigation (PN) programs. This systematic review aims to determine whether PN increases cervical, breast, and colorectal cancer screening in immigrant populations. Methods: A systematic literature search was conducted using PubMed, Scopus, and Web of Science to identify English-language articles published from January 2000 to November 2023 examining the role of patient navigators in encouraging routine breast, colorectal, and cervical cancer screening among immigrant populations in the United States. For the articles that met the inclusion criteria, details of patient navigation programs and uptake or change in cancer screening behaviors were extracted. Results: We screened 2196 articles, 53 of which met criteria for review, and 18 articles were ultimately included in the analysis. PN programs increased breast, cervical, or colorectal screening within immigrant populations compared to the control or alternative intervention in all 18 studies. In 7 out of 18 (38.9%) studies, the PN intervention group achieved screening rates similar to or above Non-Hispanic White national average screening rates. Two of those studies occurred in the outpatient setting, which resulted in higher screening rates than community-based settings. Two of those 7 studies that matched the Non-Hispanic White screening rates also had a longer duration of over 4 years. The majority of PN programs included educational sessions or materials and screening appointment scheduling assistance delivered from members of the same cultural group. Other services included identification and assistance with overcoming barriers, insurance assistance, reminders, transportation, and accompaniment to screening appointments. Of the 18 studies included, rural areas were underrepresented, and the training of patient navigators was not always described. Conclusions: Our review suggests that PN programs are effective at increasing cancer screening rates among immigrant populations, and certain aspects of PN programs, including outpatient settings and longer navigation duration, may help to further increase screening rates.

Identifying modifiable risk factors to improve immigrant breast cancer screening in the United States.

1530 Background: Despite marked reductions in breast cancer mortality since 1990, recent data suggest that progress has slowed—owing in part to plateaus in breast cancer screening in underserved populations. Historically low rates of screening coupled with rising breast cancer incidence make immigrants an important population for targeted intervention. Herein, we (1) compare contemporary rates of breast cancer screening among immigrants versus US natives; and (2) identify modifiable risk factors to inform the development of interventions to improve screening among immigrants in the United States. Methods: Using data from the 2019 and 2021 National Health Interview Surveys, screening eligible female participants (ages 40-79 years old) were identified, then classified by immigrant status as defined by nativity (US native vs. foreign-born). Primary outcome was receipt of screening mammogram in the last two years. Logistic regression models examined associations between immigrant status and mammography, with and without adjustments for age, metropolitan residence, overall health status, and survey year. Sequential analysis was then used to assess the degree to which modifiable social risk factors influence the magnitude of the association between immigrant status and mammography. Results: Of 20,090 female participants included in the study, 20% were immigrants. Compared to US natives, immigrants were less likely to have received a mammogram in the last two years (67% vs. 72%, aOR [95%CI], 0.87 [0.78-0.96], p=0.006)—an effect that was most pronounced among immigrant noncitizens (57%; 0.55 [0.47-0.64], p<0.001) but reversed among immigrants with US citizenship (74%; 1.14 [1.01-1.29], p=0.03). Of the factors assessed, having a usual source of care (5.73 [4.77-6.87]) or insurance (4.60 [3.74-5.67]) was associated with the greatest odds of biennial mammography, followed by educational attainment (1.38 [1.19-1.60]) and employment (1.19 [1.09-1.30]; all p<0.001). While having a usual source of care or employment attenuated—but did not eliminate—the association between immigrant status and mammography (0.87 [0.78-0.96], p=0.01 and 0.89 [0.80-0.99], p=0.03, respectively), this finding was not observed upon inclusion of insurance status or education in sequential models (0.97 [0.87-1.09], p=0.6 and 1.09 [0.96-1.21], p=0.13, respectively). With respect to insurance type, Medicare Advantage (4.60 [3.74-5.67]) conferred the largest benefit, followed by private insurance (4.54 [4.00-5.26]), Medicaid (2.63 [2.20-3.14]), and Medicare (4.39 [3.53-5.46]; all p<0.001). Conclusions: Breast cancer screening remains low in noncitizen immigrant populations. Targeted interventions to improve access to health insurance coverage and primary care for noncitizens may be most effective for improving rates of screening mammography among immigrants and thus warrant further investigation.

Impact of a risk based breast screening decision aid on understanding, acceptance and decision making

Internationally, population breast cancer screening is moving towards a risk-stratified approach and requires engagement and acceptance from current and future screening clients. A decision aid (www.defineau.org) was developed based on women’s views, values, and knowledge regarding risk-stratified breast cancer screening. This study aims to evaluate the impact of the decision aid on women’s knowledge, risk perception, acceptance of risk assessment and change of screening frequency, and decision-making. Here we report the results of a pre and post-survey in which women who are clients of BreastScreen Victoria were invited to complete an online questionnaire before and after viewing the decision aid. 3200 potential participants were invited, 242 responded with 127 participants completing both surveys. After reviewing the decision aid there was a significant change in knowledge, acceptance of risk-stratified breast cancer screening and of decreased frequency screening for lower risk. High levels of acceptance of risk stratification, genetic testing and broad support for tailored screening persisted pre and post review. The DEFINE decision aid has a positive impact on acceptance of lower frequency screening, a major barrier to the success of a risk-stratified program and may contribute to facilitating change to the population breast screening program in Australia.

The role of polygenic risk scores in breast cancer risk perception and decision-making.

Polygenic risk scores (PRS) have the potential to improve the accuracy of clinical risk assessments, yet questions about their clinical validity and readiness for clinical implementation persist. Understanding how individuals integrate and act on the information provided by PRS is critical for their effective integration into routine clinical care, yet few studies have examined how individuals respond to the receipt of polygenic risk information. We conducted an embedded Ethical, Legal, and Social Implications (ELSI) study to examine if and how unaffected participants in a US population breast cancer screening trial understood and utilized PRS, as part of a multifactorial risk score combining traditional risk factors with a genetic risk assessment, to make screening and risk-reduction decisions. Semi-structured qualitative interviews were conducted with 24 trial participants who were designated at elevated risk for breast cancer due to their combined risk score. Interviews were analyzed using a grounded theory approach. Participants understood PRS conceptually and accepted it as one of many risk factors to consider, yet the value and meaning they ascribed to this risk estimate varied. Most participants reported financial and insurance barriers to enhanced screening with MRI and were not interested in taking risk-reducing medications. These findings contribute to our understanding of how PRS may be best translated from research to clinical care. Furthermore, they illuminate ethical concerns about identifying risk and making recommendations based on polygenic risk in a population screening context where many may have trouble accessing appropriate care.

A modelled evaluation of the impact of COVID-19 on breast, bowel, and cervical cancer screening programmes in Australia.

Australia introduced COVID-19 infection prevention and control measures in early 2020. To help prepare health services, the Australian Government Department of Health commissioned a modelled evaluation of the impact of disruptions to population breast, bowel, and cervical cancer screening programmes on cancer outcomes and cancer services. We used the Policy1 modelling platforms to predict outcomes for potential disruptions to cancer screening participation, covering periods of 3, 6, 9, and 12 mo. We estimated missed screens, clinical outcomes (cancer incidence, tumour staging), and various diagnostic service impacts. We found that a 12-mo screening disruption would reduce breast cancer diagnoses (9.3% population-level reduction over 2020-2021) and colorectal cancer (up to 12.1% reduction over 2020-21), and increase cervical cancer diagnoses (up to 3.6% over 2020-2022), with upstaging expected for these cancer types (2, 1.4, and 6.8% for breast, cervical, and colorectal cancers, respectively). Findings for 6-12-mo disruption scenarios illustrate that maintaining screening participation is critical to preventing an increase in the burden of cancer at a population level. We provide programme-specific insights into which outcomes are expected to change, when changes are likely to become apparent, and likely downstream impacts. This evaluation provided evidence to guide decision-making for screening programmes and emphasises the ongoing benefits of maintaining screening in the face of potential future disruptions.

Expanding the boundaries of previously obtained informed consent in research: Views from participants in the Personalised Risk-based Mammascreening study.

Understanding participants' concerns and information needs regarding broadened consent is crucial to ensure transparency and participant autonomy. Our study qualitatively examined these issues in women participating in the Personalized RISk-based MAmmascreening study (PRISMA). The original PRISMA informed consent was project-specific (i.e., breast cancer research), limiting the scope of secondary research. We explored participants' needs for broadened consent to preserve informed decision-making while maximising the potential re-use of data. Focus groups (FGs) were performed following a semistructured discussion guide. Two independent researchers analysed the data thematically using an inductive approach. Twenty-three asymptomatic women and 13 women diagnosed with breast cancer were randomly divided into six FGs. Four superordinate themes were identified: (1) Normalization, (2) Attitude towards the pharmaceutical industry, (3) Privacy and (4) Knowledge. Our participants viewed data sharing as an important conduit for advancing medical science. Perceived integrity was more often attributed to noncommercial than commercial parties, with a marked mistrust towards the pharmaceutical industry. Most requested information needs related to data protection. Participants' ideal consent process would confer a range of options; for example, they would be able to choose with whom data can be shared, whether data will be de-identified or anonymous, the expiration date of their consent and how, if requested, general and personal study results would be disclosed. Our participants expressed clear information needs and a strong desire to be actively engaged in future data sharing decisions. Given that many researchers collaborate with commercial parties, building public confidence in these institutions would be beneficial. Illustrative examples addressing privacy concerns and clarifying difficult terms would aid consent decision-making. Although our participants displayed great altruism in sharing their data and accepted that broad consent would ultimately facilitate future research, broad consent did not reflect their ideal situation. Dynamic consent may be an option but warrants further feasibility research. Women were recruited from the general breast cancer screening population. Their perceptions and information needs, as reported in this study, will not only inform broadened consent for PRISMA but ideally guide other consent templates and decisions regarding consent processes.

Artificial intelligence (AI) for breast cancer screening: BreastScreen population-based cohort study of cancer detection.

Artificial intelligence (AI) has been proposed to reduce false-positive screens, increase cancer detection rates (CDRs), and address resourcing challenges faced by breast screening programs. We compared the accuracy of AI versus radiologists in real-world population breast cancer screening, and estimated potential impacts on CDR, recall and workload for simulated AI-radiologist reading. External validation of a commercially-available AI algorithm in a retrospective cohort of 108,970 consecutive mammograms from a population-based screening program, with ascertained outcomes (including interval cancers by registry linkage). Area under the ROC curve (AUC), sensitivity and specificity for AI were compared with radiologists who interpreted the screens in practice. CDR and recall were estimated for simulated AI-radiologist reading (with arbitration) and compared with program metrics. The AUC for AI was 0.83 compared with 0.93 for radiologists. At a prospective threshold, sensitivity for AI (0.67; 95% CI: 0.64-0.70) was comparable to radiologists (0.68; 95% CI: 0.66-0.71) with lower specificity (0.81 [95% CI: 0.81-0.81] versus 0.97 [95% CI: 0.97-0.97]). Recall rate for AI-radiologist reading (3.14%) was significantly lower than for the BSWA program (3.38%) (-0.25%; 95% CI:-0.31 to-0.18; P<0.001). CDR was also lower (6.37 versus 6.97 per 1000) (-0.61; 95% CI:-0.77 to-0.44; P<0.001); however, AI detected interval cancers that were not found by radiologists (0.72 per 1000; 95% CI: 0.57-0.90). AI-radiologist reading increased arbitration but decreased overall screen-reading volume by 41.4% (95% CI: 41.2-41.6). Replacement of one radiologist by AI (with arbitration) resulted in lower recall and overall screen-reading volume. There was a small reduction in CDR for AI-radiologist reading. AI detected interval cases that were not identified by radiologists, suggesting potentially higher CDR if radiologists were unblinded to AI findings. These results indicate AI's potential role as a screen-reader of mammograms, but prospective trials are required to determine whether CDR could improve if AI detection was actioned in double-reading with arbitration. National Breast Cancer Foundation (NBCF), National Health and Medical Research Council (NHMRC).

Harnessing artificial intelligence to automate delineation of volumetric breast cancers from magnetic resonance imaging to improve tumor characterization.

597 Background: Automated breast tumor identification and segmentation in magnetic resonance imaging (MRI) is a difficult and crucial area of study in breast cancer research. Artificial intelligence (AI) models are increasingly being developed for automated localization of lesions in imaging studies to facilitate quantitative assessment of features for improved diagnostic, prognostic and predictive performance. Such models have had success in detecting breast cancers in mammography, ultrasound and CT, but few have achieved three-dimensional (3D) volumetric tumor segmentation from breast MRI. The purpose of this study was to apply two state-of-the-art AI – specifically, deep learning (DL) - algorithms to 3D MRI breast cancer data and identify the higher performing algorithm for precise segmentation of breast tumors. Methods: We evaluated pre-treatment, T1 post-gadolinium contrast enhanced breast MRI from 222 patients with known breast cancers (n = 262). Images were split into training (n = 142), validation (n = 36), and hold-out test (n = 44) datasets. Two DL algorithms, U-Net and VAE-UNet, were trained to classify tumors on the training dataset across 1000 epochs. The output for each is a precise localization and segmentation of each tumor at the pixel level from every MRI image. We evaluated the performance of each algorithm using 5-fold cross-validation and testing on the validation and test sets. We calculated a dice accuracy score for each model as the performance comparison metric. Results: The highest dice accuracy score achieved on the validation dataset by generic U-Net was 83.38%, with an average across 1000 epochs of 62.41%. The highest dice accuracy achieved on the validation dataset by VAE-UNet was 82.62%, with an average across epochs of 61.28%. On our test dataset, the highest dice accuracy score achieved by U-Net was 93.09%, with an average across epochs of 66.31%, and the highest accuracy score for VAE-UNet was 90.98%, with average across epochs of 50.47%. Although U-Net appeared to perform slightly better than VAE-Unet for most cases, there were distinct cases where VAE-UNet outperformed U-Net (dice score up to 59% better than U-Net). Subsequent analysis indicated that VAE-UNet preferentially outperforms U-Net for tumors with low sphericity (p = 0.001). Conclusions: Our results suggest that U-Net is well suited for segmenting breast tumors from breast MRI in most cases, but that VAE-UNet outperforms U-Net when the tumor shapes are less spherical. Our findings could inform the choice of DL algorithms in research and clinical endeavors that rely on accurate breast cancer tumor segmentation. In particular, these two tools could be configured to facilitate tumor assessment from breast MRI in the clinical setting for: breast cancer screening in high-risk patient populations, pre-surgical planning, and monitoring of treatment response.

Women’s attitudes towards healthy life awareness and breast cancer screening during the coronavirus disease 2019 pandemic: a cross-sectional descriptive study

In the COVID-19 pandemic, fear of coronavirus infection has caused individuals to hesitate to access medical services and postpone their participation in diagnostic and screening programs. With this research, it was aimed to examine the relationship between women's wellness awareness and attitudes towards breast cancer screening during the COVID-19 pandemic. The descriptive cross-sectional type research was conducted between 30 January 2021 and 30 July 2021. The sample of the study consisted of 396 women between the ages of 40 and 69 who were in the breast cancer screening population under national cancer screening standards and met the criteria for inclusion. The data of the study were collected using a web-based and self-reported questionnaire, Personal Information Form, Healthy Life Awareness Scale and Cancer Screening Attitude Scale. It was determined that more than half of women postponed breast cancer screening during the COVID-19 pandemic, and the reasons for the postponement were often fear of contamination. It was determined that there was a relationship between the participants' awareness of healthy living and their attitudes towards cancer screening (P < 0.05). It was found that approximately two out of every three women in the screening population during the pandemic did not have screening or postponed it due to fear of contamination. It was determined that women who had awareness of healthy living and had breast cancer screening before the pandemic had a positive attitude towards cancer screening during the COVID-19 pandemic period.

Abstract P2-10-05: The estimated impact of COVID-19 on population breast cancer screening outcomes, and options for risk-based recovery

Abstract OBJECTIVES AND RATIONALE Estimating the impact of COVID-19 on cancer screening programs and related outcomes can help health services prepare for potential delays in diagnoses and different demands on treatment services and plan for best approaches to recovery. Simulation modelling enables estimation of outcomes for a range of scenarios. In this study, we estimate the impact of various disruptions and recovery strategies for the Australian biennial mammographic breast screening program (BreastScreen). METHOD Policy1-Breast is a continuous-time, multiple-cohort micro-simulation model that simulates the whole Australian female population, incorporating breast cancer risk and natural history, breast density, menopause, hormone therapy use and breast cancer screening. Firstly, in the early stages of the COVID pandemic we used Policy1-Breast to evaluate how 3, 6, 9 and 12-month pauses to BreastScreen would impact on population-level breast cancer diagnoses, tumour staging, and breast cancer survival, compared to business-as-usual (BAU) outcomes. Secondly, to explore options for recovery after an actual one-month screening pause in April 2020, we evaluated a range of assumed throughput levels following screening resumption (50% or 80% up to December, then 100% to 120% from Jan 2021), comparing various protocols where specific sub-groups of clients were prioritised for screening during the recovery period. Outcomes are reported for the target age range for the BreastScreen program (50-74 years). RESULTS For 3- to 12-month pauses, we estimated a slight reduction in 5-year survival following diagnosis for women directly affected by a pause, but no discernible changes to population-level breast cancer mortality rates up to 2023. We estimated marked fluctuations in population rates of invasive breast cancer diagnoses with a 10% increase in cancer diagnoses between 2020-2021 and 2022-2023. For a 12-month pause to screening we estimate that population-level breast cancers would increase in size (with an additional 4% &amp;gt;15mm at diagnosis) and be more likely to involve the nodes (increasing from 26% to 30% of all cancers). We estimate that median screening intervals during 2020-2021 would increase from 104 weeks under BAU up to 130 weeks with a 12-month pause, and BreastScreen recall rates and false positive recall rates would fluctuate markedly over time. For the second evaluation of a one-month pause followed by various throughput and prioritisation scenarios, we estimated that screen-detected cancer rates would vary markedly with throughput but interval cancer rates would not, leading to fluctuations in program sensitivity of up to 6%. Reflecting the periodic nature of screening participation, we estimated the extent to which longer-term future screening participation rates are expected echo the peaks and troughs in participation due to the impacts of the COVID pandemic in 2020. We estimate that for a given throughput assumption, client prioritisation could lead to different rescreening rates, screening intervals, and time required for prioritisation protocols, with little change to cancer outcomes. CONCLUSION These modelled evaluations estimate short and longer-term effects of COVID-19 on the impact of population breast cancer screening in Australia. The estimated changes in breast cancer rates and characteristics would be expected to have a flow-on effect on the demand for treatment services in terms of throughput and case-mix. Preparing for such outcomes is critical given that treatment services are also directly impacted by the pandemic. The modelled outcomes are likely to be relevant to other high-income settings with established population breast cancer screening programs. Citation Format: Pietro Procopio, Sabine Deij, Louiza S Velentzis, Amanda Tattam, Lara Petelin, Carolyn Nickson. The estimated impact of COVID-19 on population breast cancer screening outcomes, and options for risk-based recovery [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-10-05.

Artificial intelligence (AI) to enhance breast cancer screening: protocol for population-based cohort study of cancer detection

IntroductionArtificial intelligence (AI) algorithms for interpreting mammograms have the potential to improve the effectiveness of population breast cancer screening programmes if they can detect cancers, including interval cancers, without contributing...

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.

Changes in breast cancer screening rates among 32 community health centers during the COVID-19 pandemic.

BackgroundBreast cancer screening utilization steeply dropped at the start of the coronavirus disease 2019 (COVID‐19) pandemic. However, the effects on breast cancer screening in lower income populations are unknown. This study examined changes in breast cancer screening rates (BCSRs) during the pandemic among 32 community health centers (CHCs) that provided health care to lower income populations.MethodsSecondary data from 32 CHCs participating in an American Cancer Society grant program to increase breast cancer screening services were used. BCSRs were defined as the percentage of women aged 50 to 74 years who had a medical visit in the past 12 months (142,207 in 2018, 142,003 in 2019, and 150,630 in 2020) and received a screening mammogram within the last 27 months. BCSRs in July 2020, July 2019, and June 2018 were compared with screening rate ratios (SRRs) and corresponding 95% confidence intervals (CIs).ResultsBCSRs significantly rose by 18% between 2018 and 2019 (from 45.8% to 53.9%; SRR, 1.18; 95% CI, 1.17‐1.18) and then declined by 8% between 2019 and 2020 (from 53.9% to 49.6%; SRR, 0.92; 95% CI, 0.92‐0.93). If the 2018‐2019 BCSR trends had continued through 2020, 63.3% of women would have been screened in 2020 in contrast to the 49.6% who were; this potentially translated into 47,517 fewer mammograms and 242 missed breast cancer diagnoses in this population.ConclusionsIn this study of 32 CHCs, BCSRs declined by 8% from July 2019 to 2020, and this reversed an 18% improvement between July 2018 and 2019. Declining BCSRs among CHCs during the COVID‐19 pandemic call for policies to support and resources to identify women in need of screening.

The psychological impact and experience of breast cancer screening in young women with an increased risk of breast cancer due to neurofibromatosis type 1.

Women with neurofibromatosis type 1 (NF1) have an increased risk of developing early breast cancer with a poorer prognosis compared to the general population. Therefore, international management guidelines recommend regular screening in women with NF1 starting from 30 to 35 years. As the psychological impacts of breast cancer screening in other high-risk populations cannot be extended to women with NF1, due to increased incidence of cognitive and mental health issues, the psychological harms of breast screening in women with NF1 are unknown. Consequently, the aim of this study was to assess the psychological impact of breast cancer screening in women with NF1 attending an established risk management clinic. Twenty-eight women with NF1 (30–50 years) completed psychological well-being and patient experience questionnaires, administered across five time points, before and after their initial and second round annual breast screening visits. Preliminary findings demonstrated the screening regimen was well-tolerated, with most participants reporting high satisfaction with the screening process. Overall, no significant increase in psychological distress related to the breast screening process was identified, with mean cancer worry and anxiety scores decreasing over time. However, some women did experience negative aspects of screening and barriers to re-attendance at annual breast screening appointments. As some women with NF1 exhibited clinical levels of psychological distress prior to screening, efforts to identify those at risk and additional support to address concerns and expectations throughout the breast screening process may be beneficial.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10689-021-00259-9.

Breast cancer mortality gaps in Romanian women compared to the EU after 10 years of accession: Is breast cancer screening a priority for action in Romania? (Review of the Statistics).

Breast cancer remains the most common cause of morbidity and mortality by cancer in females worldwide, even though it is largely preventable through population screening. Despite notable progress in the last years in the EU, breast cancer screening programs still maintain wide variations among countries and socio-economic groups. This statistical review aimed to investigate the breast cancer-related health gaps in Romanian women compared to the average EU female population after 10 years of accession (2007-2016). We evaluated breast cancer-related deaths, age-standardized mortality rates and contribution of breast cancer to life expectancy. Trends and percentage changes were compared between Romania and EU-27 for breast cancer, all cancer and all causes of mortality. We found a higher increase of breast cancer deaths in Romania, an increasing trend of mortality (opposite to EU) and a contribution to life expectancy at birth that increased gradually from 0.45 to 0 48 years. All these health gaps compared to EU are aggravated by the fact that no population screening for breast cancer is organized in the country. The opportunities for organizing such a program are consistent, but they should be increased in the future, in order to control the health gap between Romania and EU.

Identification of Variants (rs11571707, rs144848, and rs11571769) in the BRCA2 Gene Associated with Hereditary Breast Cancer in Indigenous Populations of the Brazilian Amazon.

Estimates show that 5–10% of breast cancer cases are hereditary, caused by genetic variants in autosomal dominant genes; of these, 16% are due to germline mutations in the BRCA1 and BRCA2 genes. The comprehension of the mutation profile of these genes in the Brazilian population, particularly in Amazonian Amerindian groups, is scarce. We investigated fifteen polymorphisms in the BRCA1 and BRCA2 genes in Amazonian Amerindians and compared the results with the findings of global populations publicly available in the 1000 Genomes Project database. Our study shows that three variants (rs11571769, rs144848, and rs11571707) of the BRCA2 gene, commonly associated with hereditary breast cancer, had a significantly higher allele frequency in the Amazonian Amerindian individuals in comparison with the African, American, European, and Asian groups analyzed. These data outline the singular genetic profiles of the indigenous population from the Brazilian Amazon region. The knowledge about BRCA1 and BRCA2 variants is critical to establish public policies for hereditary breast cancer screening in Amerindian groups and populations admixed with them, such as the Brazilian population.

Breast Cancer Screening in Inner City and County Populations: A Tale of Two Centers.

New York's statewide "Get Screened, No Excuses" campaign has been one of the nation's most aggressive actions to improve access to breast cancer screening. Inner city and suburban county medical centers' initiatives were studied to compare outcomes of breast cancer screening and factors that influence access to care. Women delinquent in breast cancer screening one year or greater were offered patient navigator services to aid in timely breast cancer screening. Time-to-event completion rates among different stages of breast cancer screening stages in City and County women were compared. Time-to-event completion rates among different stages of breast cancer screening stages. 2505 women aged ≥40years accepted PN services. Mean (SD) age of patients was 56.2 (10) years. The mean (SD) age of those who completed breast screening vs. those who did not was 56.8 (10) and 52.5 (.9) years, respectively (P < .01). The rates of screening completion during physical examination, mammography and biopsy stages were 74%, 78% and 100% in City vs. 98%, 85% and 100% in County, respectively (P < .001). Screening phase was the significant predictor of time to completion for breast cancer screening in Cox regression analysis. Over 85% of women completed the breast cancer screening, 74% in City and 97.6% in County (P < .001). Screening phase is an important predictor of time-to complete breast cancer screening. Center location served as the effect modifier of the relationship. The rate of completing the screening was significantly higher and faster among Suburban County compared to Inner City women.

The cost-effectiveness of digital breast tomosynthesis in a population breast cancer screening program

ObjectivesTo evaluate at which sensitivity digital breast tomosynthesis (DBT) would become cost-effective compared to digital mammography (DM) in a population breast cancer screening program, given a constant estimate of specificity.MethodsIn a microsimulation model, the cost-effectiveness of biennial screening for women aged 50–75 was simulated for three scenarios: DBT for women with dense breasts and DM for women with fatty breasts (scenario 1), DBT for the whole population (scenario 2) or maintaining DM screening (reference). For DM, sensitivity was varied depending on breast density from 65 to 87%, and for DBT from 65 to 100%. The specificity was set at 96.5% for both DM and DBT. Direct medical costs were considered, including screening, biopsy and treatment costs. Scenarios were considered to be cost-effective if the incremental cost-effectiveness ratio (ICER) was below €20,000 per life year gain (LYG).ResultsFor both scenarios, the ICER was more favourable at increasing DBT sensitivity. Compared with DM screening, 0.8–10.2% more LYGs were found when DBT sensitivity was at least 75% for scenario 1, and 4.7–18.7% when DBT sensitivity was at least 80% for scenario 2. At €96 per DBT, scenario 1 was cost-effective at a DBT sensitivity of at least 90%, and at least 95% for scenario 2. At €80 per DBT, these values decreased to 80% and 90%, respectively.ConclusionDBT is more likely to be a cost-effective alternative to mammography in women with dense breasts. Whether DBT could be cost-effective in a general population highly depends on DBT costs.Key Points• DBT could be a cost-effective screening modality for women with dense breasts when its sensitivity is at least 90% at a maximum cost per screen of €96.• DBT has the potential to be cost-effective for screening all women when sensitivity is at least 90% at a maximum cost per screen of €80.• Whether DBT could be used as an alternative to mammography for screening all women is highly dependent on the cost of DBT per screen.

Reducing indications for radial scar surgical excision in Slovenian breast cancer screening program

PurposeManagement of the radial scar (RS)/complex sclerosing lesion (CSL) diagnosed by core needle biopsy (CNB) in breast cancer screening population (BCSP) is controversial due to its intrinsic malignant potential. We aimed to determine (i) the rate of upgrade of the RS/CSL to malignant lesions and (ii) radiological characteristics and CNB histopathological findings of the lesions related to the upgrade of the RS/CSL to malignant lesions after surgical excision in our BCSP. Patients and methodsDatabase of Slovenian National Breast Cancer Screening Program was checked for terms RS/CSL in all patients who underwent CNB in the period 2008–2018. The ratios of upgrade from CNB RS/SCL to malignant lesions after surgical excision were calculated with specific interest to the radiological characteristics and the CNB patohistologically findings of the lesions. ResultsOf 162 patients with diagnosis of RS/CSL on the CNB, 121/156 (78%) cases underwent surgical excision. 6 of 121 (5%) cases were upgraded to a malignant diagnosis in surgical specimen, 3 cases of invasive carcinoma and 3 cases of DCIS, respectively. Five of the upgraded cases (5/6, 83.3%) showed atypical epithelial proliferative lesions (AEPL) on CNB. In one upgraded case without AEPL the lesion presented as 33 mm architectural distortion with microcalcifications on the mammogram. ConclusionsIn BCSP setting RS/CSL without AEPL/papilloma and those measuring less than 2 cm in the largest diameter can be followed radiologically. Increasing the number of cores and adequate sampling of the periphery and the centre of the RS/CSL improves the pick-up rate of associated atypia/malignancy.

Deep learning modeling using normal mammograms for predicting breast cancer risk.

Toinvestigate two deep learning-based modeling schemes for predicting short-term risk of developing breast cancer using prior normal screening digital mammograms in a case-control setting. We conducted a retrospective Institutional Review Board-approved study on a case-control cohort of 226 patients (including 113 women diagnosed with breast cancer and 113 controls) who underwent general population breast cancer screening. For each patient, a prior normal (i.e., with negative or benign findings) digital mammogram examination [including mediolateral oblique (MLO) view and craniocaudal (CC) view two images] was collected. Thus, a total of 452 normal images (226 MLO view images and 226 CC view images) of this case-control cohort were analyzed to predict the outcome, i.e., developing breast cancer (cancer cases) or remaining breast cancer-free (controls) within the follow-up period. We implemented an end-to-end deep learning model and a GoogLeNet-LDA model and compared their effects in several experimental settings using two mammographic view images and inputting two different subregions of the images to the models. The proposed models were also compared to logistic regression modeling of mammographic breast density. Area under the receiver operating characteristic curve (AUC) was used as the model performance metric. The highest AUC was 0.73 [95% Confidence Interval (CI): 0.68-0.78; GoogLeNet-LDA model on CC view] when using the whole-breast and was 0.72 (95% CI: 0.67-0.76; GoogLeNet-LDA model on MLO+CC view) when using the dense tissue, respectively, as the model input. The GoogleNet-LDA model significantly (all P<0.05) outperformed the end-to-end GoogLeNet model in all experiments. CC view was consistently more predictive than MLO view in both deep learning models, regardless of the input subregions. Both models exhibited superior performance than the percent breast density (AUC=0.54; 95% CI: 0.49-0.59). The proposed deep learning modeling approach can predict short-term breast cancer risk using normal screening mammogram images. Larger studies are needed to further reveal the promise of deep learning in enhancing imaging-based breast cancer risk assessment.