Breast Cancer Screening Research Articles

Female cancer screening in India: Results from the National Family Health Survey (NFHS-5) and the way forward

ABSTRACT The incidence of cancer is increasing in India, reflecting global trends. This study attempts to identify various socioeconomic factors associated with breast and cervical cancer screening in females aged 30-49 years using the National Family Health Survey-5 (NFHS-5) data. Data focused on sociodemographic variables, cancer awareness, and information on breast and cervical cancer screening. Poisson regression was used to identify factors and reported adjusted prevalence ratio (APR) and 95% confidence intervals (CI). The proportion of women who had undergone breast and cervical cancer screening all over India was 0.9% and 1.9%, respectively. Socioeconomic factors seem to play a role as the poor and middle wealth index groups were less likely to undertake breast (APR = 0.60; 95%CI: 0.37, 0.99) and cervical cancer (APR = 0.68; 95%CI: 0.51, 0.92) screening compared to the wealthier groups. Moreover, 43% of participants in the poor wealth index category had not undergone cervical cancer screening (APR = 0.57; 95%CI: 0.33, 0.96). Further, women who watched messages on visual media were more likely to undergo screening for breast (APR = 2.00; 95%CI: 1.12, 3.57) and cervical cancer (APR = 1.46; 95%CI: 1.18, 1.82) within a week. In conclusion, screening for cancer among Indian females is remarkably low, which highlights the need for a uniform protocol for message dissemination on cancer and to collect information based on risk assessment. Furthermore, the negligible community participation in cancer screening points to the potential role of sociodemographic characteristics in taking up cancer screening, which was reflected in less participation among socioeconomically disadvantaged groups.

Status and influencing factors of knowledge, attitudes and practices relating to screening for breast and cervical cancer among rural women aged 40–65 years in China: a cross-sectional study

ObjectivesThe objectives are to investigate the status of knowledge, attitudes and practices (KAP) and to identify factors related to KAP towards breast and cervical cancer screening among rural Chinese women...

Association between mammographic screening history and stage at diagnosis among women with screen-detected breast cancer.

145 Background: Although screening mammography is an effective means of detecting breast cancer at earlier stages, some women are still diagnosed with later stage disease despite screening mammography. We hypothesized that screening history prior to diagnosis may impact stage at diagnosis and breast cancer mortality among women with screen-detected breast cancer. Methods: Retrospective cohort study of women aged 70+ in the SEER-Medicare database, diagnosed with ER+/HER2- breast cancer from 2010-2017, and enrolled in fee-for service Medicare Parts A and B from 5-years prior to diagnosis through 1 year after. We used validated claims-based algorithms to identify cancers that were detected by screening mammogram. We quantified 5-year screening history by number of prior screens. Stage at diagnosis was dichotomized into very early (T1N0) vs. later stage (T2+ or N+) disease. Multivariable logistic regression was used to assess the association between screening history and stage at diagnosis and Cox proportional hazards used to examine breast cancer mortality. Models were adjusted for demographic and clinical covariates associated with later stage disease in bivariate analyses. Results: We included 13,029 women with screen-detected breast cancer; 3,813 (29.27%) women had later stage disease at diagnosis, and 10,095 (77.48%) had at least one prior negative screening mammogram within the past five years. During this time, 2,359 (18.11%) women had only one prior mammogram, 3,132 (24.03%) had two, and 4,604 (35.34%) had three or four. Having at least one prior mammogram was associated with 56% lower odds of being diagnosed with later stage disease (OR: 0.44, 95% CI=0.40-0.48). Sociodemographic factors associated with increased odds of later stage disease included living in an area with greater poverty (20-100% vs. 0-5% of residents, OR: 1.19, 1.00-1.40), non-Hispanic Black race (OR: 1.18, 1.00-1.38), and Medicare/Medicaid dual eligibility (OR: 1.20, 1.06-1.36). Factors associated with later stage disease included living in an area with a more people with a high-school education (30-40% vs. 0-30% of residents, OR: 0.87, 0.77-0.97). At total of 696 deaths from breast cancer were observed, including 273 deaths among 2,935 women with no prior screening (9.3%) and 423 deaths among 10,097 women who had undergone screening within the past five years (4.2%, P < 0.001). Receiving at least one negative screening prior to diagnosis was associated with decreased breast cancer-specific Mortality in adjusted analysis (HR: 0.48, 0.40-0.57). Conclusions: The use of prior routine screening mammography was associated with lower risk of being diagnosed with later stage disease and dying from breast cancer in elderly women with screen-detected breast cancer. Future research is warranted regarding the impact of routine vs. sporadic screening on potential morbidity and mortality in this age group.

Perspectives of international experts and the Danish citizens on the ‘relevant knowledge’ that citizens need for making informed choices about participation in cancer screening: qualitative study.

ObjectivesThis study aimed to investigate the perspectives of international experts and Danish citizens on relevant knowledge about population-based breast, colorectal and cervical cancer screening. MethodsThis was a qualitative interview study with focus group interviews with experts and Danish citizens eligible for breast, colorectal and/or cervical cancer screening. Data were collected using semi-structured interview guides, audio-recorded and transcribed verbatim. A thematic analysis was conducted. ResultsParticipants were nine international experts from Germany, Canada, the USA, Sweden, the Netherlands and Australia, and 54 citizens from Denmark. Most citizens had 'adequate' or 'problematic' levels of health literacy. Themes that experts and citizens agreed on were: knowledge about the disease and symptoms, practical information about screening, benefits of screening, the option of non-participation and the importance of having numeric knowledge of possible screening outcomes. Experts agreed on the importance of knowledge about the harms of screening, but only a minority of citizens considered this important. ConclusionsThe experts and citizens disagreed on the relevance of knowledge about harms of screening and agreed on other relevant knowledge. Practice implicationsWhat experts and citizens find important may not align when making informed decisions. Therefore, experts and citizens needs to be involved when developing questionnaires.

Clinical experience on the limited role of ultrasound for breast cancer screening in BRCA1 and BRCA2 mutations carriers aged 30–39 years

PurposeIn BRCA germline pathogenic sequence variants (PSV) carriers aged 30–39 years imaging is recommended at six-month intervals. The European society for medical oncology recommendation of the use of 6-monthly MRI six-monthly MRI screening is being considered at our institution, particularly for younger carriers under the age of 35, although it is not mandatory. If 6-monthly MRI is unavailable, annual MRI may be supplemented by ultrasound (with or without mammography). The aim of this study was to evaluate the utility of ultrasound screening added to mammography, as a 6-month supplement to annual MRI in BRCA PSV carriers aged 30–39 years. Materials and methodsThis IRB approved retrospective study included BRCA PSV carriers aged 30–39 years, who underwent breast cancer screening at our institution between January 2015 and March 2023. Participants were divided into two groups, those who had supplemental whole-breast US and mammography at six months and underwent screening before March 2019, and those who had only mammography without supplemental US and enrolled in screening after March 2019. Patient characteristics, cancer detection rates and cancer characteristics were compared between the two groups. ResultsOverall, 200 asymptomatic BRCA1/2 PSV carriers undergoing screening in our institution were included in the study. Mean age was 35.7 ± 3.5 years, and mean follow-up time was 37.4 ± 38.0 months. There were 118 (59 %) women screened with supplemental US, and 82 (41 %) women without. Eight cancers were diagnosed during the study period, four in women with supplemental US and four in women without. The sensitivity of whole-breast screening US was 25 % (1/4), specificity 85.7 % (222/259), PPV 2.6 % (1/38), and NPV 98.7 % (222/225). Of the four cancers detected in women screened with supplemental US, one was diagnosed by whole-breast US, two by MRI, and one by mammography. Of eight cancers included in this study, two were not detectable by targeted second-look US. All eight cancers were detectable by MRI. ConclusionThe addition of whole-breast ultrasound to mammography and MRI screening in BRCA PSV carriers aged 30–39 years offered limited incremental benefit. MRI with 6 months supplemental mammography without US detected all cancer cases.

Associations of individual and partner incarceration history and receipt of cancer screening in the US.

50 Background: Incarceration history is linked to limited access to care, including cancer screenings. Adverse consequences may also extend to their partners due to financial burdens and social stigma. This study examined associations of individual and partner incarceration history and receipt of cancer screenings in the United States. Methods: We identified individuals aged ≥ 50 years currently living with a partner who responded to the 2014-2020 Health and Retirement Study. Incarceration history was defined from responses to the question ‘Have you ever been an inmate in a jail, prison, juvenile detention center, or other correctional facility?’ People were categorized into 3 groups: 1) without individual or partner incarceration history, 2) with individual incarceration history only, and 3) with partner incarceration history only. People with both individual and partner incarceration history were excluded due to small sample size. We used multivariate logistic regression models to generate prevalence ratios (PRs) comparing receipt of any breast, cervical, and colorectal cancer screenings ≤2 years among screening-eligible people (defined by the US Preventive Services Taskforce guideline) with individual or partner incarceration history to people without incarceration history, stratifying by sex and controlling for age group, race and ethnicity, educational attainment, and comorbidity. Results: Of the sample, 0.9% and 11.8% of females and males reported individual incarceration history, respectively; 11.1% and 1.0% reported partner incarceration history, respectively. Compared to females without individual or partner incarceration history, women with partner incarceration history were less likely to receive breast cancer screening (PR:0.7, 95CI: 0.5-0.9); women with individual incarceration history were less likely to receive colorectal cancer screening in the past 2 years (PR: 0.7, 95% CI: 0.5-0.9). Compared to males without individual or partner incarceration history, men with partner incarceration history were less likely to receive colorectal cancer screening (PR: 0.5, 95% CI: 0.4-0.7). Conclusions: Individual or partner incarceration history was associated with lower prevalence of cancer screening. Programs to improve access to care and cancer screening among both people with incarcerations history and their partners are warranted. Adjusted association of individual and partner incarceration history and receipt of cancer screening. Female Male No Individual or Partner History With Individual History With Partner History No Individual or Partner History With Individual History With Partner History Cancer screening Breast (n=2556) Ref. 2.0 (0.5 - 8.3) 0.7 (0.5 - 0.9) -- Cervical (n=817) 1.4 (0.4 - 5.6) 0.9 (0.6 - 1.4) Colorectal (n=2682 for female, n=2207 for male) 0.7 (0.5 - 0.9) 0.9 (0.7 - 1.0) Ref. 1.0 (0.9 - 1.2) 0.5 (0.4 - 0.7) Ref: referent group.

The global and regional disease burden of breast cancer from 1980 to 2021: An analysis of GBD study 2021.

146 Background: Breast cancer (BC) is the most common malignancy in women and presents a huge disease burden worldwide. Early detection, via mammographic screening, improves outcomes significantly. We present estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021, delineating the trajectory of BC from 1980 - 2021. This analysis considers the impact of screening practices on the incidence and mortality of patients worldwide, offering comprehensive examination of trends over the past 4 decades. Methods: Data were methodically retrieved from GBD study, which included age-standardized death rates and Disability-Adjusted Life Years (DALY). Dataset was stratified globally and by continent, with further regional analysis of the African continent into Northern, Southern, Eastern, Western, and Central, and by World Bank income classifications of countries. We examined global age-standardized mortality rates (ASMR), followed by an analysis of global disability-adjusted life years (DALY). Finally, we identified which countries, stratified by income levels, demonstrate the highest rates. Analytical processing was conducted using Joinpoint regression to determine average annual percentage changes (AAPC). Results: Globally, Age Adjusted Death Rates (ASDR) continuously declined from 1980-2021. In 1980, the ASDR was 16.33 (95% UI: 15.39-17.22) and it declined continuously to 14.54 (AAPC: -0.28; 95% CI: -0.3, -0.27) in 2021. Globally, DALYs rate was 503.8 (95% UI: 475.9-532.2) per 100,000 people in 1990 and it decreased to 455.5 (AAPC: 3.22; 95% CI: -0.33, -0.30) in 2021. In geographical analysis, America and Europe had uniformly declining ASDRs while Africa and Asia had a steady rise in ASDR. From 1980 to 2021, America had decreasing death rates with an AAPC of -0.78 (95% CI: -0.80, -0.76). Europe also had a declining trend, albeit nonsignificant, with an AAPC of -0.53 (95% CI: -0.55, -0.49). Conversely, the AAPC for Asia was 0.42 (95% CI: 0.41-0.43) showing a continuous incline in deaths related to BC from 1980 to 2021. The highest increase in ASDRs was observed in Africa with an AAPC of 0.90 (95% CI: 0.89-0.91). Upon sub-analysis of Africa, we observed Western and Southern Africa had highest ASDRs compared to other parts of Africa. According to World Bank income levels, high income countries had declining death rates while upper-middle, lower-middle, and low-income countries all had increasing deaths rates with the highest rise in lower middle income countries. Conclusions: Asia and Africa have limited implementation of BC screening protocols and correspondingly exhibit higher BC associated mortality. Enhanced screening programs are imperative for the timely diagnosis and management of BC, ultimately improving survival rate. The enormous discrepancy in mortality rates underscores the critical importance of accessible and comprehensive BC screening initiatives globally.

An approach for classification of breast cancer using lightweight deep convolution neural network

The rapid advancement of deep learning has generated considerable enthusiasm regarding its utilization in addressing medical imaging issues. Machine learning (ML) methods can help radiologists to diagnose breast cancer (BCs) barring invasive measures. Informative hand-crafted features are essential prerequisites for traditional machine learning classifiers to achieve accurate results, which are time-consuming to extract. In this paper, our deep learning algorithm is created to precisely identify breast cancers on screening mammograms, employing a training method that effectively utilizes training datasets with either full clinical annotation or solely the cancer status of the entire image. The proposed approach utilizes Lightweight Convolutional Neural Network (LWCNN) that allows automatic extraction features in an end-to-end manner. We have tested LWCNN model in two experiments. In the first experiment, the model was tested with two cases' original and enhancement datasets 1. It achieved 95 %, 93 %, 99 % and 98 % for training and testing accuracy respectively. In the second experiment, the model has been tested with two cases' original and enhancement datasets 2. It achieved 95 %, 91 %, 99 % and 92 % for training and testing accuracy respectively. Our proposed method, which uses various convolutional network to classify screening mammograms achieved exceptional performance when compared to other methods. The findings from these experiments clearly indicate that automatic deep learning techniques can be trained effectively to attain remarkable accuracy across a wide range of mammography datasets. This holds significant promise for improving clinical tools and reducing both false positive and false negative outcomes in screening mammography.

Ethnic and racialized disparities in the use of screening services for pap smears and mammograms in Canada.

Breast and cervical cancers pose significant health challenges for women globally, emphasizing the critical importance of effective screening programs for early detection. In Canada, despite the implementation of accessible healthcare systems, ethnic and racialized disparities in cancer screening persist. This study aims to assess ethnic and racialized disparities in breast and cervical cancer screening in Canada. Using 2015-2019 data from the Canadian Community Health Survey, we analyzed women aged 18-70 in distinct ethnic and racial groups. The primary outcome was mammography or Papanicolaou test (pap smear). The secondary outcome was time since the last screening. We used weighted multivariable logistic regression to estimate the odds of having a pap smear or mammography across the ethnic and racialized groups, adjusted for relevant covariates. Results were reported as odds ratios (ORs) with 95% confidence intervals (CIs). We included 14,628,067 women of which 72.5% were White, 8.4% Southeast Asian, 4.7% South Asian, 3.4% Indigenous, 2.7% Black, 2.0% West Asian, and 1.6% Latin American. In comparison with the White reference group, a higher odds ratio of not having a pap smear was estimated for the West Asian (5.63; CI 3.85, 8.23), South Asian (5.19; CI 3.79, 7.12), Southeast Asian (4.35; CI 3.46, 5.46), and Black groups (2.62; CI 1.82, 3.78). Disparities in mammography screening were found only for the Southeast Asian group with higher odds of not having screening (1.85; CI 1.15, 2.98) compared to the White reference group. This study reveals significant disparities in pap smear and mammography screenings affecting various ethnic groups, particularly in West Asia, South Asian, and Black communities. These findings underscore the urgent need for targeted interventions, policies, and healthcare strategies to address these gaps and ensure equitable access to essential breast and cervical cancer prevention across all ethnicity.

Optimization and correction of breast dynamic optical imaging projection data based on deep learning

Breast cancer poses a significant health threat to women, necessitating advancements in diagnostic technologies. Breast dynamic optical imaging (DOI) technology, recognized for its non-invasive and radiation-free properties, is extensively utilized for the early screening and quantitative analysis of breast tumors. The integration of deep learning, a robust technology for automatic image feature extraction, with breast DOI has the potential to enhance tumor detection and diagnosis significantly. This paper introduces a deep learning-enhanced image optimization approach to overcome challenges such as poor image quality and distorted projection data commonly encountered in existing DOI methods. The approach utilizes convolutional neural networks (CNNs) to extract features from raw images and employs generative adversarial networks (GANs) to enhance these images, thereby improving their quality and contrast. Additionally, a novel correction algorithm is developed to address projection data distortion, enabling the reconstruction and correction of this data for more accurate and reliable imaging results. Experimental findings confirm that the proposed method markedly enhances both image quality and projection data accuracy in breast DOI, offering a reliable foundation for clinical diagnosis. This study not only provides a new perspective and methodology for the early screening and diagnosis of breast cancer but also holds substantial clinical importance and prospective applications.

USPSTF recommends biennial mammography for breast cancer screening in women aged 40 to 74 y.

US Preventive Services Task Force; Nicholson WK, Silverstein M, Wong JB, et al. Screening for breast cancer: US Preventive Services Task Force recommendation statement. JAMA. 2024;331:1918-1930. 38687503.

Artificial Intelligence Algorithm for Subclinical Breast Cancer Detection

Early breast cancer detection is associated with lower morbidity and mortality. To examine whether a commercial artificial intelligence (AI) algorithm for breast cancer detection could estimate the development of future cancer. This retrospective cohort study of 116 495 women aged 50 to 69 years with no prior history of breast cancer before they underwent at least 3 consecutive biennial screening examinations used scores from an AI algorithm (INSIGHT MMG, version 1.1.7.2; Lunit Inc; used September 28, 2022, to April 5, 2023) for breast cancer detection and screening data from multiple, consecutive rounds of mammography performed from September 13, 2004, to December 21, 2018, at 9 breast centers in Norway. The statistical analyses were performed from September 2023 to August 2024. Artificial intelligence algorithm score indicating suspicion for the presence of breast cancer. The algorithm provided a continuous cancer detection score for each examination ranging from 0 to 100, with increasing values indicating a higher likelihood of cancer being present on the current mammogram. Maximum AI algorithm score for cancer detection and absolute difference in score among breasts of women developing screening-detected cancer, women with interval cancer, and women who screened negative. The mean (SD) age at the first study round was 58.5 (4.5) years for 1265 women with screening-detected cancer in the third round, 57.4 (4.6) years for 342 women with interval cancer after 3 negative screening rounds, and 56.4 (4.9) years for 116 495 women without breast cancer all 3 screening rounds. The mean (SD) absolute differences in AI scores among breasts of women developing screening-detected cancer were 21.3 (28.1) at the first study round, 30.7 (32.5) at the second study round, and 79.0 (28.9) at the third study round. The mean (SD) differences prior to interval cancer were 19.7 (27.0) at the first study round, 21.0 (27.7) at the second study round, and 34.0 (33.6) at the third study round. The mean (SD) differences among women who did not develop breast cancer were 9.9 (17.5) at the first study round, 9.6 (17.4) at the second study round, and 9.3 (17.3) at the third study round. Areas under the receiver operating characteristic curve for the absolute difference were 0.63 (95% CI, 0.61-0.65) at the first study round, 0.72 (95% CI, 0.71-0.74) at the second study round, and 0.96 (95% CI, 0.95-0.96) at the third study round for screening-detected cancer and 0.64 (95% CI, 0.61-0.67) at the first study round, 0.65 (95% CI, 0.62-0.68) at the second study round, and 0.77 (95% CI, 0.74-0.79) at the third study round for interval cancers. In this retrospective cohort study of women undergoing screening mammography, mean absolute AI scores were higher for breasts developing vs not developing cancer 4 to 6 years before their eventual detection. These findings suggest that commercial AI algorithms developed for breast cancer detection may identify women at high risk of a future breast cancer, offering a pathway for personalized screening approaches that can lead to earlier cancer diagnosis.

Deep learning assessment of senescence-associated nuclear morphologies in mammary tissue from healthy female donors to predict future risk of breast cancer: a retrospective cohort study

Cellular senescence has been associated with cancer as either a barrier mechanism restricting autonomous cell proliferation or a tumour-promoting microenvironmental mechanism that secretes proinflammatory paracrine factors. With most work done in non-human models and the heterogeneous nature of senescence, the precise role of senescent cells in the development of cancer in humans is not well understood. Furthermore, more than 1 million non-malignant breast biopsies are taken every year that could be a major resource for risk stratification. We aimed to explore the clinical relevance for breast cancer development of markers of senescence in mammary tissue from healthy female donors. In this retrospective cohort study, we applied single-cell deep learning senescence predictors, based on nuclear morphology, to histological images of haematoxylin and eosin-stained breast biopsy samples from healthy female donors at the Komen Tissue Bank (KTB) at the Indiana University Simon Cancer Center (Indianapolis, IN, USA). All KTB participants (aged ≥18 years) who underwent core biopsies for research purposes between 2009 and 2019 were eligible for the study. Senescence was predicted in the epithelial (terminal duct lobular units [TDLUs] and non-TDLU epithelium), stromal, and adipose tissue compartments using validated models, previously trained on cells induced to senescence by ionising radiation (IR), replicative exhaustion (or replicative senescence; RS), or antimycin A, atazanavir-ritonavir, and doxorubicin (AAD) exposures. To benchmark our senescence-based cancer prediction results, we generated 5-year Gail scores-the current clinical gold standard for breast cancer risk prediction-for participants aged 35 years and older on the basis of characteristics at the time of tissue donation. The primary outcome was estimated odds of breast cancer via logistic modelling for each tissue compartment based on predicted senescence scores in cases (participants who had been diagnosed with breast cancer as of data cutoff, July 31, 2022) and controls (those who had not been diagnosed with breast cancer). 4382 female donors (median age at donation 45 years [IQR 34-57]) were eligible for the study. As of data cutoff (median follow-up of 10 years [7-11]), 86 (2·0%) had developed breast cancer a mean of 4·8 years (SD 2·84) after date of donation and 4296 (98·0%) had not received a breast cancer diagnosis. Among the 86 cases, we found significant differences in adipose-specific IR and AAD senescence prediction scores compared with controls. Risk analysis showed that individuals in the upper half (above the median) of scores for the adipose tissue IR model had higher odds of developing breast cancer (odds ratio [OR] 1·71 [95% CI 1·10-2·68]; p=0·019), whereas the adipose AAD model revealed a reduced odds of developing breast cancer (OR 0·57 [0·36-0·88]; p=0·013). For the other tissue compartments and the RS model, no significant associations were found (except for stromal tissue via the IR model, had higher odds of developing breast cancer [OR 1·59, 1·03-2·49]). Individuals with both of the adipose risk factors had an OR of 3·32 (1·68-7·03; p=0·0009). Participants with 5-year Gail scores above the median had an OR for development of cancer of 2·33 (1·46-3·82; p=0·0012) compared with those with scores below the median. When combining Gail scores with our adipose AAD risk model, we found that individuals with both of these predictors had an OR of 4·70 (2·29-10·90; p<0·0001). When combining the Gail score with our adipose IR model, we found that individuals with both predictors had an OR of 3·45 (1·77-7·24; p=0·0002). Assessment of senescence-associated nuclear morphologies with deep learning allows prediction of future cancer risk from normal breast biopsy samples. The combination of multiple models improved prediction of future breast cancer compared with the current clinical benchmark, the Gail model. Our results suggest an important role for microscope image-based deep learning models in predicting future cancer development. Such models could be incorporated into current breast cancer risk assessment and screening protocols. Novo Nordisk Foundation, Danish Cancer Society, and the US National Institutes of Health.

ID: 332106 How MRI Conditionality of an SCS System Could Impede Screening for Breast Cancer

ID: 332106 How MRI Conditionality of an SCS System Could Impede Screening for Breast Cancer

ASO Author Reflections: The Utility of Clinical Breast Examinations in a High-Risk Patient Population.

ASO Author Reflections: The Utility of Clinical Breast Examinations in a High-Risk Patient Population.

Interventions to reduce racial/ethnic disparities across the breast cancer care continuum.

160 Background: In the United States, racial/ethnic disparities in adoption of breast cancer evidence-based practices (EBPs) persist along the cancer care continuum. This scoping review applied an implementation science lens to describe the current evidence base for interventions to reduce disparities, synthesizing evidence on effective interventions while highlighting gaps in the literature. Methods: A formalized search strategy identified USA-based interventional studies aiming to improve adoption of an EBP along the breast cancer care continuum among racially/ethnically minoritized patients. Relevant articles from 1/2010 - 8/2022 (Medline, Embase, Cochrane, and Scopus) were included. For each article, two reviewers screened and extracted data, with a third resolving discrepancies. The PRISMA-ScR checklist and JBO Manual for Evidence Synthesis framework were followed. Results: Our search strategy yielded 45,215 articles. After applying inclusion/exclusion criteria, 59 articles were retained, targeting screening (85%, 50 of 59), treatment (12%, 7 of 59), and survivorship (5%, 3 of 59) (2 targeted multiple areas). No articles targeted end-of-life care. Of these, 49% (29 of 59) were randomized controlled trials (RCTs). Among 24 screening RCTs, the most common interventions—and fraction with statistically significant improved screening uptake—were patient navigation (100%, 11 of 11) and patient education (80%, 4 of 5). Among 4 treatment RCTs, 3 targeted adjuvant chemotherapy uptake. Of these, 1 had significant improvements and used patient navigation. The 2 studies without significant improvements used a patient tracking tool/alert system or patient education. Among 2 survivorship RCTs, one used email interventions, resulting in significantly improved physical activity and dietary health. A second used a nurse-facilitated internet support group, resulting in significantly improved physical/psychological symptoms. Early to mid-stage implementation outcomes (acceptability, adoption, appropriateness, feasibility, or fidelity) were commonly measured (81%, 48 of 59). No study measured later stage implementation outcomes (sustainability or costs). Conclusions: In multiple studies, patient navigation and education improved breast cancer screening among racially/ethnically minoritized populations. In one study, patient navigation improved completion of adjuvant treatment. Despite these studies, patient navigation is not reimbursed for cancer screening, and adoption has not been widespread. Future studies should focus on evaluating and improving later stage implementation outcomes (sustainability and costs). Based on these results, insurance reimbursement mechanisms for screening-related navigation may be warranted. Future breast cancer care delivery disparities research should also be expanded to include treatment, survivorship, and end-of-life care.

Australian healthcare workers’ views on artificial intelligence in BreastScreen: Results of a mixed method survey study

IntroductionThe evolving role of Artificial Intelligence (AI) in medicine, particularly in radiology and population-based breast cancer screening programs, offers potential accuracy gains and efficiency improvements. However, successful implementation requires understanding of healthcare workers’ views on AI, which this study aims to explore within the Australian BreastScreen program. MethodsAn online survey was distributed to clinical staff involved in breast imaging, collecting responses from November 2022 to April 2023. The survey encompassed demographic information, opinions, and experiences with AI in medical imaging, with questions covering various scenarios of AI integration in BreastScreen ResultsOut of an estimated 350 professionals contacted, 95 responded, with 84.2 % (80/95) being radiologists. Less than half of respondents (44.9 %, 40/89) had worked with artificial intelligence for image classification previously. The majority of radiologists 74.2 % (46/62) thought that the use of AI in reading mammograms for BreastScreen would improve workflow. However, radiologists thought they would behave with increasing caution with scenarios where AI was more autonomous, with the majority of radiologists (63.3 %, 38/60) uncomfortable with holding accountability when the AI was used to triage and remove cases from the workflow. Notably, 60 % of radiologists (36/60) expressed concerns about accountability. DiscussionThe findings suggest an optimistic attitude towards AI among Australian healthcare workers, although when given hypothetical scenarios for the way AI could be integrated into BreastScreen, there was increasing caution with scenarios where AI was more autonomous. This study highlights understanding and concerns of healthcare professionals working in population screening which are important to address when implementing AI into the healthcare system.

Housing-related disparities in receipt of breast cancer screening among Medicaid beneficiaries.

76 Background: People experiencing or at risk of homelessness (PEH) are often diagnosed with advanced breast cancer, suggesting barriers to preventive care and screening. However, there is limited data that examine screening among PEH, undermining efforts to characterize and address potential disparities in screening. To address this gap, we investigated housing-related disparities in receipt of breast cancer screening in Medicaid, which disproportionately serves low-income PEH. Methods: We used a novel linkage of Pennsylvania Medicaid data with encounter-level data on housing-related services (Housing Management Information System; HMIS) from 2011 to 2017. We compared rates of biennial mammography between a cohort of Medicaid women receiving housing-related services in HMIS (i.e., a proxy for experience/risk of homelessness) and randomly sampled comparison beneficiaries without any housing services use. We estimated both unadjusted and adjusted disparities in receipt of biennial mammography (controlled for county and year fixed effects, demographic and Medicaid eligibility characteristics, and baseline healthcare utilization and comorbidities). We also examined heterogeneity in disparities by beneficiaries in the following HMIS subgroups: 1) receiving supportive housing, 2) experiencing chronic homelessness (i.e., 12+ months of homelessness), and 3) unstably housed (housed but receiving homelessness prevention services). Results: We identified 1,792 Medicaid beneficiaries with an HMIS encounter and 71,664 comparison beneficiaries. Those in the HMIS cohort were more likely to be younger, non-Hispanic Black, eligible for Medicaid due to disability, and have a higher number of inpatient visits and comorbidities. The unadjusted proportion receiving mammogram was 44.8% and 50.1% in the HMIS vs. comparison cohort, with an overall disparity of 5.3 percentage-points (pp, P &lt;.001). This disparity estimate remained was robust to adjusting for covariates (-4.3 pp; P &lt; .001). We found the largest adjusted disparity when comparing beneficiaries experiencing chronic homelessness (-8.5 pp; P = .038) relative to the comparison cohort. In contrast, the disparity was smaller among women receiving supportive housing (-3.7 pp; P = .098) and unstably housed women (-3.3 pp; P = .071). Conclusions: There was a significant disparity in the utilization of mammography among women PEH, especially those who experience chronic homelessness, in Pennsylvania Medicaid. Our finding illuminates the health consequences of housing insecurity and underscore a need for programs providing adequate housing, such as supportive housing, to address disparities in screening. In the meantime, greater efforts should be dedicated to improving the uptake of screening among at-risk populations at the point of contact with the healthcare system (e.g. when PEH engage with care).

Association Between Cancer Screening Patterns and Carer Literacy in Individuals With Cognitive Decline: An Observational Study.

The incidence rates of dementia, mild cognitive impairment, and cancer increase with age, posing challenges to affected individuals and their families. However, there are currently no clear cancer screening guidelines for individuals with cognitive impairment. This study analyzed the impact of carer health literacy on screening behaviors in this population. We conducted a postal follow-up survey, associated with the National Center for Geriatrics and Gerontology-Life STORIES of People with Dementia, that targeted primary carers to assess their reports regarding patient attendance at regular cancer screenings recommended by the Japanese Ministry of Health, Labor and Welfare, over the preceding 2 years. Screening rates were compared between the memory clinic cohort and the national average, and the influence of carer health literacy level on screening was analyzed. Among the 826 total individuals analyzed, the memory clinic cohort exhibited lower breast cancer screening rates, at 11% among female patients aged 65-74 years versus the national average of 32%. Higher health literacy among carers was significantly associated with increased screening. For female patients, carers with high levels of communicative health literacy were more likely to ensure that patients attended screenings for gastric (adjusted odds ratio [AOR], 1.77; 95% confidence interval [CI], 1.03-3.04), colorectal (AOR, 1.70, 95% CI 1.08-2.70), and breast cancers (AOR, 3.08; 95% CI, 1.40-6.76). Among the male patients, high communicative health literacy was associated with increased lung cancer screening attendance (AOR, 1.82; 95% CI, 1.11-2.99). Our research highlights a notable gap in cancer screening attendance between individuals with cognitive impairment and the general population, potentially arising from the intricate nature of screening procedures and the extensive burden on carers. More informed decisions and increased screening rates can be achieved through patient-centric communication strategies that accommodate the cognitive abilities of patients, ensuring the comprehensibility and accessibility of health-related information.

Diagnostic Accuracy of Screening Contrast-enhanced Mammography for Women with Extremely Dense Breasts at Increased Risk of Breast Cancer.

Background Mammogram interpretation is challenging in female patients with extremely dense breasts (Breast Imaging Reporting and Data System [BI-RADS] category D), who have a higher breast cancer risk. Contrast-enhanced mammography (CEM) has recently emerged as a potential alternative; however, data regarding CEM utility in this subpopulation are limited. Purpose To evaluate the diagnostic performance of CEM for breast cancer screening in female patients with extremely dense breasts. Materials and Methods This retrospective single-institution study included consecutive CEM examinations in asymptomatic female patients with extremely dense breasts performed from December 2012 to March 2022. From CEM examinations, low-energy (LE) images were the equivalent of a two-dimensional full-field digital mammogram. Recombined images highlighting areas of contrast enhancement were constructed using a postprocessing algorithm. The sensitivity and specificity of LE images and CEM images (ie, including both LE and recombined images) were calculated and compared using the McNemar test. Results This study included 1299 screening CEM examinations (609 female patients; mean age, 50 years ± 9 [SD]). Sixteen screen-detected cancers were diagnosed, and two interval cancers occured. Five cancers were depicted at LE imaging and an additional 11 cancers were depicted at CEM (incremental cancer detection rate, 8.7 cancers per 1000 examinations). CEM sensitivity was 88.9% (16 of 18; 95% CI: 65.3, 98.6), which was higher than the LE examination sensitivity of 27.8% (five of 18; 95% CI: 9.7, 53.5) (P = .003). However, there was decreased CEM specificity (88.9%; 1108 of 1246; 95% CI: 87.0, 90.6) compared with LE imaging (specificity, 96.2%; 1199 of 1246; 95% CI: 95.0, 97.2) (P < .001). Compared with specificity at baseline, CEM specificity at follow-up improved to 90.7% (705 of 777; 95% CI: 88.5, 92.7; P = .01). Conclusion Compared with LE imaging, CEM showed higher sensitivity but lower specificity in female patients with extremely dense breasts, although specificity improved at follow-up. © RSNA, 2024 See also the editorial by Lobbes in this issue.