Breast Cancer Survival Research Articles

Awareness, Knowledge, and Current Practice of Breast Cancer Among Surgeons in Jordan.

Breast cancer (BC) is the most prevalent cancer in Jordan. De-escalation in treatment reflects a paradigm shift in BC treatment. More tailored strategies and the adoption of a multidisciplinary approach are essential to apply recent changes in management. In the era of breast surgery fellowship, adopting well-structured training is essential to apply recent therapeutic guidelines and meet patients' expectations. A cross-sectional study using a customized, self-reported questionnaire was used. Data collection occurred anonymously using a link via WhatsApp in the period between February 2023 and April 2023. A total of 89 surgeons were involved in this study, and only 14 (15.7%) completed a subspecialty in breast surgery. About 58.4% considered the age of 40 years as the starting point for screening, and 84.3% reported that mammogram screening is associated with improved BC survival. Only 10.1% and 28.1% acknowledged the applicability of both tomosynthesis and breast magnetic resonance imaging in screening, respectively. A significant difference in the mean knowledge score about BC is observed between general surgeon and those with subspecialty. Varying levels of awareness concerning different risk factors and their correlation with the likelihood of BC occurrence observed. Although 56.2% of participants could offer breast conserving surgery and consider it oncological safe, only 48.3% defined it correctly. Of the participants, 61.8% and 76.4% stated that sentinel lymph node biopsy can be safely applied in clinically negative or suspicious axillary nodes, respectively, with <50% of surgeon performing it in their practice. More efforts are required to enhance the knowledge and practice of surgeons in the field of breast surgery. Adopting national guidelines can facilitate the acceptance and improvement of current practices among surgeons in Jordan.

Evaluation of sarcopenia-associated survival in breast cancer with computed tomography-based pectoral muscle area measurements

Objective: Breast cancer is the most common and deadly female cancer. In breast cancer cases, survival is closely related to muscle mass, which is one of the components of body composition. Our aim was to investigate the usefulness of computed-tomography (CT)- based pectoral muscle measurements in detecting sarcopenia in patients with non-metastatic breast cancer and the relationship of these measurements with survival. Patients and Methods: Our study included 62 adult female breast cancer cases diagnosed with breast cancer between January 2012 and January 2018 and without metastasis in positron emission tomography/CT (PET/CT) examination obtained for pre-treatment staging. To evaluate sarcopenia, skeletal muscle index (SMI) and pectoral muscle index (PMI) were calculated by measuring pectoral muscle area and skeletal muscle area at L3 vertebra level on PET/CT images. Results: Deceased patients were significantly older (Median=73.90, IQR=27.04) than surviving patients (Median=54.60, IQR=13.37, p=0.025) and were diagnosed with cancer later in life (Median=63.92 IQR=30.16’ vs. Median=47.51 IQR=15.0, p=0.030). When the threshold of 31 cm2/m2 was selected, there was a statistically significant difference in survival between sarcopenic and non-sarcopenic groups (p=0.031). Conclusion: In conclusion, the presence of sarcopenia in female breast cancer cases is a parameter that affects survival and can be measured using radiological imaging methods. In addition to the measurements accepted in the literature regarding sarcopenia, pectoral muscle measurements can be chosen as an alternative method in the diagnosis of sarcopenia.

Does structural racism impact receipt of NCCN guideline-concordant breast cancer treatment?

Disparities in breast cancer survival remain a challenge. We aimed to analyze the effect of structural racism, as measured by the Index of Concentration at the Extremes (ICE), on receipt of National Cancer Center Network (NCCN) guideline-concordant breast cancer treatment. We identified patients treated at two institutions from 2005 to 2017 with stage I-IV breast cancer. Census tracts served as neighborhood proxies. Using 5-year estimates from the American Community Survey, 5 ICE variables were computed to create 5 models, controlling for economic segregation, non-Hispanic Black (NHB) segregation, NHB/economic segregation, Hispanic segregation, and Hispanic/economic segregation. Multi-level logistic regression models were used to determine the association between individual and neighborhood-level characteristics on receipt of NCCN guideline-concordant breast cancer treatment. 5173 patients were included: 55.2% were Hispanic, 27.5% were NHW, and 17.3% were NHB. Regardless of economic or residential segregation, a NHB patient was less likely to receive appropriate treatment [(OR)Model1 0.58 (0.45-0.74); ORModel2 0.59 (0.46-0.78); ORModel3 0.62 (0.47-0.81); ORModel4 0.53 (0.40-0.69); ORModel5 0.59(0.46-0.76); p < 0.05]. To our knowledge, this is the first analysis assessing receipt of NCCN guideline-concordant treatment by ICE, a validated measure for structural racism. While much literature emphasizes neighborhood-level barriers to treatment, our results demonstrate that compared to NHW patients, NHB patients are less likely to receive NCCN guideline-concordant breast cancer treatment, independent of economic or residential segregation. Our study suggests that there are potential unaccounted individual or neighborhood barriers to receipt of appropriate care that go beyond economic or residential segregation.

The role of laboratory indices on treatment response and survival in breast cancer receiving neoadjuvant chemotherapy.

Neoadjuvant chemotherapy (NACT) is the standard treatment for locally advanced, high-risk breast cancer. Pathological complete response (pCR) improves survival. Peripheral blood-derived indices reflecting systemic inflammation and nutritional status have long been used as predictive and prognostic markers in solid malignancies. This retrospective study investigates whether eight commonly used indices in patients receiving NACT affect pCR and survival. This study includes 624 locally advanced breast cancer patients who received NACT. The biomarker indices were calculated from peripheral blood samples taken two weeks before starting chemotherapy. The indices' optimal cut-off values were determined using ROC Curve analysis. During a median follow-up period of 42months, recurrence was detected in 146 patients, and 75 patients died. pCR was observed in 166 patients (26.6%). In univariate analysis, NLR, PLR, SII, PNI, HALP, and HRR were statistically significantly associated (p = 0.00; p = 0.03; p = 0.03; p = 0.02; p = 0.00; p = 0.02 respectively), but in multivariate analysis, only NLR was significantly predictive for pCR(p = 0.04). In multivariate analysis, the HGB/RDW score significantly predicted DFS(p = 0.04). The PNI score was identified as a marker predicting survival for both OS and PFS (p = 0.01, p = 0.01, respectively). In conclusion, peripheral blood-derived indices have prognostic and predictive values on pCR and survival. However, further studies are needed to validate our findings.

Discovering predisposing genes for hereditary breast cancer using deep learning.

Breast cancer (BC) is the most common malignancy affecting Western women today. It is estimated that as many as 10% of BC cases can be attributed to germline variants. However, the genetic basis of the majority of familial BC cases has yet to be identified. Discovering predisposing genes contributing to familial BC is challenging due to their presumed rarity, low penetrance, and complex biological mechanisms. Here, we focused on an analysis of rare missense variants in a cohort of 12 families of Middle Eastern origins characterized by a high incidence of BC cases. We devised a novel, high-throughput, variant analysis pipeline adapted for family studies, which aims to analyze variants at the protein level by employing state-of-the-art machine learning models and three-dimensional protein structural analysis. Using our pipeline, we analyzed 1218 rare missense variants that are shared between affected family members and classified 80 genes as candidate pathogenic. Among these genes, we found significant functional enrichment in peroxisomal and mitochondrial biological pathways which segregated across seven families in the study and covered diverse ethnic groups. We present multiple evidence that peroxisomal and mitochondrial pathways play an important, yet underappreciated, role in both germline BC predisposition and BC survival.

Smart Biosensor for Breast Cancer Survival Prediction Based on Multi-View Multi-Way Graph Learning.

Biosensors play a crucial role in detecting cancer signals by orchestrating a series of intricate biological and physical transduction processes. Among various cancers, breast cancer stands out due to its genetic underpinnings, which trigger uncontrolled cell proliferation, predominantly impacting women, and resulting in significant mortality rates. The utilization of biosensors in predicting survival time becomes paramount in formulating an optimal treatment strategy. However, conventional biosensors employing traditional machine learning methods encounter challenges in preprocessing features for the learning task. Despite the potential of deep learning techniques to automatically extract useful features, they often struggle to effectively leverage the intricate relationships between features and instances. To address this challenge, our study proposes a novel smart biosensor architecture that integrates a multi-view multi-way graph learning (MVMWGL) approach for predicting breast cancer survival time. This innovative approach enables the assimilation of insights from gene interactions and biosensor similarities. By leveraging real-world data, we conducted comprehensive evaluations, and our experimental results unequivocally demonstrate the superiority of the MVMWGL approach over existing methods.

Fbxo45 facilitates the malignant progression of breast cancer by targeting Bim for ubiquitination and degradation

BackgroundBreast cancer is one of the common malignancies in women. Evidence has demonstrated that FBXO45 plays a pivotal role in oncogenesis and progression. However, the role of FBXO45 in breast tumorigenesis remains elusive. Exploration of the regulatory mechanisms of FBXO45 in breast cancer development is pivotal for potential therapeutic interventions in patients with breast cancer.MethodsHence, we used numerous approaches to explore the functions of FBXO45 and its underlaying mechanisms in breast cancer pathogenesis, including CCK-8 assay, EdU assay, colony formation analysis, apoptosis assay, RT-PCR, Western blotting, immunoprecipitation, ubiquitination assay, and cycloheximide chase assay.ResultsWe found that downregulation of FBXO45 inhibited cell proliferation, while upregulation of FBXO45 elevated cell proliferation in breast cancer. Silencing of FBXO45 induced cell apoptosis, whereas overexpression of FBXO45 inhibited cell apoptosis in breast cancer. Moreover, FBXO45 interacted with BIM and regulated its ubiquitination and degradation. Furthermore, knockdown of FBXO45 inhibited cell proliferation via regulation of BIM pathway. Notably, overexpression of FBXO45 facilitated tumor growth in mice. Strikingly, FBXO45 expression was associated with poor survival of breast cancer patients.ConclusionOur study could provide the rational for targeting FBXO45 to obtain benefit for breast cancer patients. Altogether, modulating FBXO45/Bim axis could be a promising strategy for breast cancer therapy.

Geospatial disparities in survival of patients with breast cancer in sub-Saharan Africa from the African Breast Cancer-Disparities in Outcomes cohort (ABC-DO): a prospective cohort study

There is an urgent need to improve breast cancer survival in sub-Saharan Africa. Geospatial barriers delay diagnosis and treatment, but their effect on survival in these settings is not well understood. We examined geospatial disparities in 4-year survival in the African Breast Cancer-Disparities in Outcomes cohort. In this prospective cohort study, women (aged ≥18 years) newly diagnosed with breast cancer were recruited from eight hospitals in Namibia, Nigeria, South Africa, Uganda, and Zambia. They reported sociodemographic information in interviewer-administered questionnaires, and their clinical and treatment data were collected from medical records. Vital status was ascertained by contacting participants or their next of kin every 3 months. The primary outcome was all-cause mortality in relation to rural versus urban residence, straight-line distance, and modelled travel time to hospital, analysed using restricted mean survival time, Cox proportional hazards, and flexible parametric survival models. 2228 women with breast cancer were recruited between Sept 8, 2014, and Dec 31, 2017. 127 were excluded from analysis (58 had potentially recurrent cancer, had previously received treatment, or had no follow-up; 14 from minority ethnic groups with small sample sizes; and 55 with missing geocoded home addresses). Among the 2101 women included in analysis, 928 (44%) lived in a rural area. 1042 patients had died within 4 years of diagnosis; 4-year survival was 39% (95% CI 36-42) in women in rural areas versus 49% (46-52) in urban areas (unadjusted hazard ratio [HR] 1·24 [95% CI 1·09-1·40]). Among the 734 women living more than 1 h from the hospital, the crude 4-year survival was 37% (95% CI 32-42) in women in rural areas versus 54% (46-62) in women in urban areas (HR 1·35 [95% CI 1·07-1·71] after adjustment for age, stage, and treatment status). Among women in rural areas, mortality rates increased with distance (adjusted HR per 50 km 1·04, 1·01-1·07) and travel time (adjusted HR per h 1·06, 1·02-1·10). Among women with early-stage breast cancer receiving treatment, women in rural areas had a strong survival disadvantage (overall HR 1·54, 1·14-2·07 adjusted for age and stage; >1 h distance adjusted HR 2·14, 1·21-3·78). Geospatial barriers reduce survival of patients with breast cancer in sub-Saharan Africa. Specific attention is needed to support patients with early-stage breast cancer living in rural areas far from cancer treatment facilities. US National Institutes of Health (National Cancer Institute), Susan G Komen for the Cure, and the International Agency for Research on Cancer.

Prognostic factors and overall survival of breast cancer in Benin: a hospital-based study

BackgroundIn Benin, a country in West Africa, breast cancer is the leading cancer in women, both in terms of incidence and mortality. However, evidence on the mortality of breast cancer and its associated factors is lacking in this country. Our aim was to describe and analyze the clinical, histopathological, and prognostic aspects of breast cancer in Benin.MethodsA descriptive and analytical study was carried out at the CNHU-HKM and the CHU-MEL, two major tertiary referral hospitals for breast cancer management located in Cotonou, the capital city of Benin. All breast cancer medical records with histological evidence and immunohistochemistry studies were retrospectively collected between January 1, 2014, and September 30, 2020, in these two tertiary referral hospitals and analyzed in the current study.ResultsFinally, 319 medical records were included. The mean age at diagnosis was 48.74 years. The tumors were most frequently classified as T4 (47.6%) with lymph node involvement N2 (34.5%), and metastases were clinically noted in 21.9% of cases. Stage was reported in the medical records of 284 patients. Tumors were diagnosed at very late AJCC stages: stage III (47.5%) and stage IV (24.7%). Grades SBR 2 (49.2%) and SBR 3 (32.6%) were the most frequent grades. Triple-negative breast cancer (31.3%) was the most common molecular type. The overall 5-year survival was 48.49%. In multivariable analysis, the poor prognostic factors were lymph node invasion (HR = 2.63; p = 0.026; CI: [1.12, 6.17]), the presence of metastasis (HR = 3.64; p < 0.001); CI: [2.36, 5.62] and the immunohistochemical profile (HR = 1.29; p < 0.001; CI: [1.13, 1.48]).ConclusionsBreast cancer in Beninese is predominant in young adults and is often diagnosed at a late stage. The survival of breast cancer patients in Benin can be improved by enhancing early diagnosis and multidisciplinary management.

Unveiling Hidden Battles: Exploring the Link Between Breast Cancer Survival and Heart Failure Vulnerability.

This study explores the link between a history of breast cancer and the vulnerability to heart failure. Analyzing data from the National Inpatient Sample (NIS) for women diagnosed with breast cancer between 2016 and 2019 in the US, our research utilized logistic regression, adjusting for demographics, comorbidities, and lifestyle factors, and employed propensity score matching. With 2,276,639 weighted cases, our findings reveal a slight but significant elevation in heart failure risk among the breast cancer cohort, specifically in acute, chronic, and isolated systolic heart failure types. Racial differences were pronounced; Black women with breast cancer showed higher risks for all heart failure types, particularly chronic and systolic, while Asian or Pacific Islander patients had a lower incidence of certain heart failure types. This research underscores a modest increase in heart failure risk post-breast cancer, highlighting the critical need for integrated cardio-oncology care and personalized healthcare approaches to address and mitigate this risk effectively.

Wait times and breast cancer survival: a population-based retrospective cohort study using CanIMPACT data.

The time from breast cancer surgery to chemotherapy has been shown to affect survival outcomes; however, the effect of time from first breast cancer-related healthcare contact to first cancer specialist consultation, or the time from first breast cancer-related healthcare contact to adjuvant chemotherapy on survival has not been well explored. We aimed to determine whether various wait times along the breast cancer treatment pathway (contact-to-consultation, contact-to-chemotherapy, surgery-to-chemotherapy) were associated with overall survival in women within the Canadian province of Ontario. We performed a population-based retrospective cohort study of women diagnosed with stage I-III breast cancer in Ontario between 2007 and 2011 who received surgery and adjuvant chemotherapy. This was the Ontario cohort of a larger, nationwide study (the Canadian Team to improve Community-Based Cancer Care along the Continuum - CanIMPACT). We used Cox-proportional hazards regression to determine the association between the contact-to-consultation, contact-to-chemotherapy, and surgery-to-chemotherapy intervals and overall survival while adjusting for cancer stage, age, comorbidity, neighborhood income, immigration status, surgery type, and method of cancer detection. Among 12,782 breast cancer patients, longer surgery-to-chemotherapy intervals (HR 1.13, 95% CI 1.03-1.18 per 30-day increase), but not the contact-to-consultation (HR 0.979, 95% CI 0.95-1.01 per 30-day increase), nor the more comprehensive contact-to-chemotherapy intervals (HR 1.00, 95% CI 0.98-1.02 per 30-day increase) were associated with decreased survival in our adjusted analyses. Our findings emphasize the prognostic importance of a shorter surgery-to-chemotherapy interval, whereas the contact-to-consultation and contact-to-chemotherapy intervals have less impact on survival outcomes.

Exploring the prognostic significance of arm-level copy number alterations in triple-negative breast cancer.

Somatic copy number alterations (SCNAs) are prevalent in cancer and play a significant role in both tumorigenesis and therapeutic resistance. While focal SCNAs have been extensively studied, the impact of larger arm-level SCNAs remains poorly understood. Here, we investigated the association between arm-level SCNAs and overall survival in triple-negative breast cancer (TNBC), an aggressive subtype of breast cancer lacking targeted therapies. We identified frequent arm-level SCNAs, including 21q gain and 7p gain, which correlated with poor overall survival in TNBC patients. Further, we identified the expression of specific genes within these SCNAs associated with survival. Notably, we found that the expression of RIPK4, a gene located on 21q, exhibited a strong correlation with poor overall survival. In functional assays, we demonstrated that targeting Ripk4 in a murine lung metastatic TNBC model significantly reduced tumor burden, improved survival, and increased CD4+ and CD8+ T cell infiltration. RIPK4 enhanced the survival of triple-negative breast cancer cells at secondary sites, thereby facilitating the formation of metastatic lesions. Our findings highlight the significance of arm-level SCNAs in breast cancer progression and identify RIPK4 as a putative driver of TNBC metastasis and immunosuppression.

Examining the Associations Among Treatment Declination, Racial and Ethnic Inequities, and Breast Cancer Survival

Examining the Associations Among Treatment Declination, Racial and Ethnic Inequities, and Breast Cancer Survival

Critical Risk Assessment, Diagnosis, and Survival Analysis of Breast Cancer.

Breast cancer is the most prevalent type of cancer in women. Risk factor assessment can aid in directing counseling regarding risk reduction and breast cancer surveillance. This research aims to (1) investigate the relationship between various risk factors and breast cancer incidence using the BCSC (Breast Cancer Surveillance Consortium) Risk Factor Dataset and create a prediction model for assessing the risk of developing breast cancer; (2) diagnose breast cancer using the Breast Cancer Wisconsin diagnostic dataset; and (3) analyze breast cancer survivability using the SEER (Surveillance, Epidemiology, and End Results) Breast Cancer Dataset. Applying resampling techniques on the training dataset before using various machine learning techniques can affect the performance of the classifiers. The three breast cancer datasets were examined using a variety of pre-processing approaches and classification models to assess their performance in terms of accuracy, precision, F-1 scores, etc. The PCA (principal component analysis) and resampling strategies produced remarkable results. For the BCSC Dataset, the Random Forest algorithm exhibited the best performance out of the applied classifiers, with an accuracy of 87.53%. Out of the different resampling techniques applied to the training dataset for training the Random Forest classifier, the Tomek Link exhibited the best test accuracy, at 87.47%. We compared all the models used with previously used techniques. After applying the resampling techniques, the accuracy scores of the test data decreased even if the training data accuracy increased. For the Breast Cancer Wisconsin diagnostic dataset, the K-Nearest Neighbor algorithm had the best accuracy with the original dataset test set, at 94.71%, and the PCA dataset test set exhibited 95.29% accuracy for detecting breast cancer. Using the SEER Dataset, this study also explores survival analysis, employing supervised and unsupervised learning approaches to offer insights into the variables affecting breast cancer survivability. This study emphasizes the significance of individualized approaches in the management and treatment of breast cancer by incorporating phenotypic variations and recognizing the heterogeneity of the disease. Through data-driven insights and advanced machine learning, this study contributes significantly to the ongoing efforts in breast cancer research, diagnostics, and personalized medicine.

Overall Survival and Prognostic Factors in Metastatic Triple-Negative Breast Cancer: A National Cancer Database Analysis.

Metastatic triple-negative breast cancer (TNBC) is aggressive with poor median overall survival (OS) ranging from 8 to 13 months. There exists considerable heterogeneity in survival at the individual patient level. To better understand the survival heterogeneity and improve risk stratification, our study aims to identify the factors influencing survival, utilizing a large patient sample from the National Cancer Database (NCDB). Women diagnosed with metastatic TNBC from 2010 to 2020 in the NCDB were included. Demographic, clinicopathological, and treatment data and overall survival (OS) outcomes were collected. Kaplan-Meier curves were used to estimate OS. The log-rank test was used to identify OS differences between groups for each variable in the univariate analysis. For the multivariate analysis, the Cox proportional hazard model with backward elimination was used to identify factors affecting OS. Adjusted hazard ratios and 95% confidence intervals are presented. In this sample, 2273 women had a median overall survival of 13.6 months. Factors associated with statistically significantly worse OS included older age, higher comorbidity scores, specific histologies, higher number of metastatic sites, presence of liver or other site metastases in those with only one metastatic site (excluding brain metastases), presence of cranial and extra-cranial metastases, lack of chemotherapy, lack of immunotherapy, lack of surgery to distant sites, lack of radiation to distant sites, and receipt of palliative treatment to alleviate symptoms. In the multivariate analysis, comorbidity score, histology, number of metastatic sites, immunotherapy, and chemotherapy had a statistically significant effect on OS. Through NCDB analysis, we have identified prognostic factors for metastatic TNBC. These findings will help individualize prognostication at diagnosis, optimize treatment strategies, and facilitate patient stratification in future clinical trials.

Incidence and survival of primary metastatic breast cancer in Denmark; implication of breast cancer screening, classification, and staging practice.

Primary metastatic breast cancer (pMBC) accounts for 5-10% of annual breast cancers with a median survival of 3-4 years, varying among subtypes. In Denmark, the incidence of breast cancer increased until 2010, followed by a stabilisation. Several factors influencing pMBC incidence and survival, including screening prevalence, staging methods, and classification standards, remain pivotal but inadequately documented. This retrospective observational study involving pMBC patients diagnosed between 2000 and 2020 encompassed all Danish oncology departments. Data from the Danish Breast Cancer Group database and the National Patient Register included diagnosis specifics, demographics, treatment, and follow-up. Between 2000 and 2020, 3,272 patients were diagnosed with pMBC, a rise from 355 patients in 2000-2004 to 1,323 patients in 2015-2020. The increase was particularly observed in patients aged 70 years or older. Changes in tumour subtypes were observed, notably with a rise in human epidermal growth factor receptor 2 (HER2)-positive cases but a steady distribution of estrogen receptor (ER) status. Diagnostic practices changed over the two decades, with 6% evaluated with PET/CT (positron emission tomography-computed tomography) or CT (computed tomography) with a bone evaluation in 2000-2004 and 65% in 2015-2020. Overall survival (OS) improved from 23 months in 2000-2004 to 33 months in 2015-2020. In patients with ER-positive and HER2-positive disease, the multivariable model showed improved survival by year of diagnosis, and further, patients with ER-negative/HER2-negative disease fared worse the first 2 years after diagnosis. Our study delineates changes in the treatment and survival of pMBC over two decades. Stage migration, screening introduction, and changes in registration practice, however, prevent a valid assessment of a possible causal relationship.

Conditional survival of male breast cancer

Background The incidence of male breast cancer has been increasing in recent years; however, the long-term survival outcomes of diagnosed patients remain uncertain. This study was designed to evaluate the conditional survival of male breast cancer patients and to predict the future survival of patients through the conditional nomogram, to provide important suggestions for clinical decision-making. Methods Retrospective data from the SEER database included 3600 male breast cancer patients, divided into training and validation groups (7 : 3 ratio). Overall survival rates were calculated using Kaplan–Meier analysis. Conditional survival analysis described survival at specific years. Time-dependent multivariate Cox analysis identified prognostic factors’ impact. The conditional survival nomogram model predicted real-time survival rates. Results Over time, the 5-year real-time survival rate of patients gradually improved, increasing from 70.5 to 74.8, 79.4, 85.8, and 92.9% (respectively, representing 5-year survival rates of 1–4 years after diagnosis). In addition, the improvement in conditional survival rate CS5 showed a nonlinear trend. After 5 years of diagnosis, age, tumor size, and tumor stage had a sustained impact on patient prognosis. Finally, a conditional survival nomogram was constructed to predict the 10-year survival rate in real time. Conclusion Five years after diagnosis, the conditional survival rate of male patients with breast cancer has improved, but it is not nonlinear. In the first 5 years after diagnosis, patients with older age, larger tumor size, poorer tumor stage, and distant metastasis should be actively followed up and treated to improve their long-term survival.

Racialized economic segregation and inequities in treatment initiation and survival among patients with metastatic breast cancer

PurposeRacialized economic segregation, a form of structural racism, may drive persistent inequities among patients with breast cancer. We examined whether a composite area-level index of racialized economic segregation was associated with real-world treatment and survival in metastatic breast cancer (mBC).MethodsWe conducted a retrospective cohort study among adult women with mBC using a US nationwide electronic health record-derived de-identified database (2011–2022). Population-weighted quintiles of the index of concentration at the extremes were estimated using census tract data. To identify inequities in time to treatment initiation (TTI) and overall survival (OS), we employed Kaplan–Meier methods and estimated hazard ratios (HR) adjusted for clinical factors.ResultsThe cohort included 27,459 patients. Compared with patients from the most privileged areas, those from the least privileged areas were disproportionately Black (36.9% vs. 2.6%) or Latinx (13.2% vs. 2.6%) and increasingly diagnosed with de novo mBC (33.6% vs. 28.9%). Those from the least privileged areas had longer median TTI than those from the most privileged areas (38 vs 31 days) and shorter median OS (29.7 vs 39.2 months). Multivariable-adjusted HR indicated less timely treatment initiation (HR 0.87, 95% CI 0.83, 0.91, p < 0.01) and worse OS (HR 1.19, 95% CI 1.13, 1.25, p < 0.01) among those from the least privileged areas compared to the most privileged areas.ConclusionRacialized economic segregation is a social determinant of health associated with treatment and survival inequities in mBC. Public investments directly addressing racialized economic segregation and other forms of structural racism are needed to reduce inequities in cancer care and outcomes.

Abstract PO3-09-06: Role of Obesity-Related Biomarkers on Mortality Among Black Breast Cancer Survivors in the Women’s Circle of Health Followup Study

Abstract Background: Central obesity and higher adiposity have been recently associated with higher all-cause and breast cancer-specific mortality in Black breast cancer survivors participating in the Women’s Circle of Health Followup Study. Adipose tissue is a dynamic organ producing adipocytokines, including leptin, adiponectin, adipsin, resistin, lipocalin-2/NGAL, plasminogen-activator inhibitor type 1 (PAI-1) and CXCL11, TNFα, and IL-6, which modulate inflammatory markers in obesity, including the release of proinflammatory C-reactive protein (CRP). These circulating biomarkers play important roles linking obesity with insulin resistance, hyperinsulinemia, chronic inflammation, and altered immunity, which may impact overall and breast cancer mortality. The goal of this analysis was to determine if circulating adipocytokines and obesity-related biomarkers of systemic inflammation are associated with breast cancer and overall survival in Black breast cancer survivors. Methods: Circulating biomarkers were assayed for 460 Black breast cancer survivors who provided a blood sample 2 years post-diagnosis in the Women’s Circle of Health Followup Study, a population-based cohort of Black breast cancer survivors in New Jersey enrolled within 12 months of diagnosis. Associations between biomarkers (by tertiles) and overall survival were assessed using multivariable Cox regression models. Breast cancer specific survival was assessed based on competing risk analyses using the Fine and Gray subdistribution hazard model. Multivariable models were adjusted for age, body mass index as a measure of overall adiposity, education, menopausal status, stage, grade, subtype, and chemotherapy, hormonal therapy, and radiation treatments received. All tests were two-sided at Analyses were conducted at P=0.05. Results: In multivariable analyses, lipocalin-2, CXCL11, and CRP, biomarkers of adipose tissue inflammation closely related to insulin resistance, were associated with worse overall but not breast cancer specific survival. Compared to women in the lowest tertile of lipocalin-2, women in the highest tertile had a 3-fold increased risk of dying from any cause (T3 vs T1, HR=3.08, 95% CI: 1.29-7.39, p= 0.004) and a ~2-fold increased risk of dying from breast cancer, which was not statistically significant (HR= 1.84, 95% CI: 0.59-5.79, p=0.30). Similarly, women in the highest tertile of CXCL11 were at 2-fold increased risk of dying of any cause (HR: 2.10, 95% CI: 0.96-4.57, p=0.06) but no associations were observed with risk of dying from breast cancer (HR:1.31, 0.42-4.13, p=0.64). Circulating CRP, as a marker of systemic inflammation, was also associated with worse overall survival (T3 vs T1 HR: 2.51, 95% CI: 1.07-5.89, p=0.03), showing a borderline significant association with increased breast cancer specific survival (T3 vs T1 HR: 4.32, 95% CI: 0.87-21.38, p=0.07). No associations with overall or breast cancer specific mortality were observed for any of the other adipocytokines examined. Conclusion: In this population-based cohort study of Black breast cancer survivors, biomarkers associated with adipose tissue related inflammation and insulin resistance were associated with reduced overall survival. Relationships with breast cancer survival were not significant, possibly due to limited sample size. Citation Format: Shipra Gandhi, Chi-Chen Hong, Anthony George, Kristopher Attwood, Bo Quin, Nur Zeinomar, Yong Lin, Christine Ambrosone, Kitaw Demissie, Elisa Bandera. Role of Obesity-Related Biomarkers on Mortality Among Black Breast Cancer Survivors in the Women’s Circle of Health Followup Study [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-09-06.

Abstract PO4-05-12: High expression of SLC9A2 is correlation with lymphatic metastasis and poor survival in breast cancer

Abstract Background: SLC9A2 encodes Na+/H+ exchanger 2 which is an essential solute carrier protein on the surface of multiple cells. The prediction potentials of SLC9A2 in lymphatic metastasis and survival were unknow but explored in this study of breast cancer. Methods: Expression of SLC9A2 was determined in breast cancers (n=127) using real time quantitative polymerase chain reaction. Transcript levels of this gene was analysed in the breast cancers for the implication in lymph node involvement and survival using Mann-Whitney test with SPSS (Version 27). The relation of prognosis was also analysed by Kaplan Meier plotter in breast cancer. Results: In lymph node positive breast cancer, the expression of SLC9A2 shown an increase trend than no metastasis (n=43, median=25.9, interquartile range [IQR] [0.9-215.4] vs. n=44, median=4.9, IQR [0.2-31.8], p=0.1213). SLC9A2 expression in TNM stage Ⅱ was significantly higher than stage Ⅰ (n=31, median=42, IQR [0-195] vs. n=47, median=3.3, IQR [0.2- 31.6], p=0.0267) and also showed in the pathological type of invasive ductal carcinoma (n=27, median=42, IQR [3- 550] vs. n=35, median=3.3, IQR [0.2-31.8], p=0.0223). Kaplan Meier plotter showed over survival of SLC9A2 high expression was significantly worse than SLC9A2 low expression (66 months vs. 123.6 months, Hazard Ratio [HR]=1.57 [1.3-1.9], p=0.000), also found in estrogen receptor (ER) positive (63.8 months vs. 173.7 months, HR=2.19 [1.6-3.01], p=0.000). In patients with tamoxifen therapy, SLC9A2 high expression also had poor survival comparing to low expression (HR=2.86 [1.4-5.86], p=0.0026). Conclusions: High expression of SLC9A2 is correlation with lymph node metastasis and poor survival in breast cancer. SLC9A2 could be as a predictor for lymphatic involvement and survival and might be an indicator for detection of resistance to endocrine therapy. Citation Format: Binbin Cong, Xiaoshan Cao, Wen Jiang, Lin Ye. High expression of SLC9A2 is correlation with lymphatic metastasis and poor survival in breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-05-12.