Three-year survival of breast cancer patients attending a one-stop breast care clinic nested within a primary care health facility in sub-Saharan Africa-Zambia.

In Zambia, women with breast symptoms travel through multiple levels of the healthcare system before obtaining a definitive diagnosis. To eradicate this critical barrier to care, we nested a novel breast specialty service platform inside a large public-sector primary healthcare facility in Lusaka, Zambia to offer clinical breast examination, breast ultrasound, and ultrasound-guided core needle biopsy in a one-stop format, tightly linked to referral for treatment. The objective of the study was to determine the life expectancy and survival outcomes of a prospective cohort of women diagnosed with breast cancer who were attended to and followed up at the clinic. The effect of breast cancer stage on prognosis was determined by estimating stage-specific crude survival using the Kaplan-Meier method. Survival analysis was used to estimate mean lifespan according to age and stage at diagnosis. We enrolled 302 women with histologically confirmed breast cancer. The overall 3-year survival was 73%. An increase in patients presenting with early breast cancer and improvements in their survival were observed. Women with early-stage breast cancer had a lifespan similar to the general population, while loss of life expectancy was significant at more advanced stages of disease. Our findings suggest that implementing efficient breast care services at the primary care level can avert a substantial proportion of breast cancer-related deaths. The mitigating factor appears to be stage of disease at the time of diagnosis, the cause of which is multifactorial, with the most influential being delays in the referral process.

Breast cancer survival in India across 11 geographic areas under the National Cancer Registry Programme.

BACKGROUND: Population-based cancer survival is a key indicator for assessing the effectiveness of cancer control by a health care system in a specific geographic area. Breast cancer is the most common cancer among women in India, accounting for over one quarter of all female cancers. The objective of this study was to estimate the 5-year survival of female patients who were diagnosed with breast cancer between 2012 and 2015 from the existing Population-Based Cancer Registries (PBCRs) in India. METHODS: In total, 17,331 patients who had breast cancer diagnosed between 2012 and 2015 from 11 PBCRs were followed until June 30, 2021. Active methods were used to track the vital status of registered breast cancer cases. The study conducted survival analysis by calculating the difference between the date of first diagnosis and the date of death or censoring to estimate observed survival and relative survival using the actuarial survival approach and the Ederer-II approach, respectively. RESULTS: The 5-year age-standardized relative survival (95% confidence interval [CI]) of patients with breast cancer was 66.4% (95% CI, 65.5%-67.3%). Mizoram (74.9%; 95% CI, 68.1%-80.8%), Ahmedabad urban (72.7%; 95% CI, 70.3%-74.9%), Kollam (71.5%; 95% CI, 69.2%-73.6%), and Thiruvananthapuram (69.1%; 95% CI, 67.0%-71.2%) had higher survival rates than the national average. Conversely, Pasighat had the lowest survival rate (41.9%; 95% CI, 14.7%-68.6%). The 5-year observed survival rates for localized, regional, and distant metastasis in the pooled PBCRs were 81.0%, 65.5%, and 18.3%, respectively. CONCLUSIONS: The overall disparity in survival rates was observed across 11 PBCRs, with lower survival rates reported in Manipur, Tripura, and Pasighat. Therefore, it is imperative to implement comprehensive cancer control strategies widely throughout the country.

Should Palpable Nodes Be Exclusionary in Patients Who Are Otherwise Candidates for ACOSOG Z0011-Type Trials?

BACKGROUND: Palpable nodes were exclusionary in American College of Surgeons Oncology Group (ACOSOG) Z0011, while SINODAR-ONE excluded those with positive axillary nodes by palpation and ultrasound. To determine whether clinical nodal status should be exclusionary in those fulfilling pathologic criteria for ACOSOG Z0011 and similar trials, this study analyzed the accuracy and implications of clinical nodal positivity. METHODS: Patients ≥ 18 years old with cT1-T2, cN0-cN1, M0 breast cancer were identified in the National Cancer Database between 2004 and 2019. Subset characteristics of cN1 and cN0 were compared with respect to final pathologic nodal status and overall survival (OS). RESULTS: Of 57,823 patients identified, 77.0% were cT1 and 23.0% were cT2. Of the 93.9% of patients who were staged as cN0, 16.7% were pN1; of the remaining 6.1% staged as cN1, 9.6% were found to be pN0. Among cN1/pN0 patients, 14.9% underwent axillary dissection without sentinel node biopsy. There was no difference in adjusted OS for patients staged as cN0 versus cN1 who were found to be pN1 (HR 1.13, 95% CI 0.93-1.37, p = 0.22), a finding that persisted on subset analysis in those with two positive nodes (HR 0.91, 95% CI 0.62-1.33, p = 0.63). CONCLUSIONS: Clinical nodal stage does not affect OS in pN1 patients. Clinical nodal assessment can both overstage patients and result in unnecessary axillary surgery. These data suggest that cN1 patients who are otherwise candidates for a Z0011-like paradigm should still be considered eligible. Their final candidacy should be determined by surgical lymph node pathology and not preoperative clinical status.

Multi-metric comparison of machine learning imputation methods with application to breast cancer survival.

Handling missing data in clinical prognostic studies is an essential yet challenging task. This study aimed to provide a comprehensive assessment of the effectiveness and reliability of different machine learning (ML) imputation methods across various analytical perspectives. Specifically, it focused on three distinct classes of performance metrics used to evaluate ML imputation methods: post-imputation bias of regression estimates, post-imputation predictive accuracy, and substantive model-free metrics. As an illustration, we applied data from a real-world breast cancer survival study. This comprehensive approach aimed to provide a thorough assessment of the effectiveness and reliability of ML imputation methods across various analytical perspectives. A simulated dataset with 30% Missing At Random (MAR) values was used. A number of single imputation (SI) methods - specifically KNN, missMDA, CART, missForest, missRanger, missCforest - and multiple imputation (MI) methods - specifically miceCART and miceRF - were evaluated. The performance metrics used were Gower's distance, estimation bias, empirical standard error, coverage rate, length of confidence interval, predictive accuracy, proportion of falsely classified (PFC), normalized root mean squared error (NRMSE), AUC, and C-index scores. The analysis revealed that in terms of Gower's distance, CART and missForest were the most accurate, while missMDA and CART excelled for binary covariates; missForest and miceCART were superior for continuous covariates. When assessing bias and accuracy in regression estimates, miceCART and miceRF exhibited the least bias. Overall, the various imputation methods demonstrated greater efficiency than complete-case analysis (CCA), with MICE methods providing optimal confidence interval coverage. In terms of predictive accuracy for Cox models, missMDA and missForest had superior AUC and C-index scores. Despite offering better predictive accuracy, the study found that SI methods introduced more bias into the regression coefficients compared to MI methods. This study underlines the importance of selecting appropriate imputation methods based on study goals and data types in time-to-event research. The varying effectiveness of methods across the different performance metrics studied highlights the value of using advanced machine learning algorithms within a multiple imputation framework to enhance research integrity and the robustness of findings.

Postdiagnosis circulating osteoprotegerin and TRAIL concentrations and survival and recurrence after a breast cancer diagnosis: results from the MARIE patient cohort.

BACKGROUND: Experimental studies suggest a role for osteoprotegerin (OPG) and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) in mammary tumor development and progression. These biomarkers have been minimally investigated with respect to outcomes in breast cancer patients. METHODS: OPG and TRAIL were evaluated in blood samples collected from 2459 breast cancer patients enrolled in the MARIE study, a prospective population-based patient cohort, at median of 129 days after diagnosis. Participants were between ages 50 and 74 at diagnosis and recruited from 2002 to 2005 in two regions of Germany. Follow-up for recurrence and mortality was conducted through June 2015. Delayed-entry Cox proportional hazards regression was used to assess associations between OPG and TRAIL with all-cause and breast cancer-specific mortality, and recurrence, both overall and by tumor hormone receptor status. RESULTS: Median follow-up time was 11.7 years, with 485 deaths reported (277 breast cancer-specific). Higher OPG concentrations were associated with a higher risk of all-cause mortality (hazard ratio for 1-unit log2-transformed concentration (HRlog2) = 1.24 (95% confidence interval 1.03-1.49). Associations were observed in women diagnosed with ER-PR- tumors or discordant hormone receptor status (ER-PR-, HRlog2 = 1.93 (1.20-3.10); discordant ERPR, 1.70 (1.03-2.81)), but not for women with ER + PR + tumors (HRlog2 = 1.06 (0.83-1.35)). OPG was associated with a higher risk of recurrence among women with ER-PR- disease (HRlog2 = 2.18 (1.39-3.40)). We observed no associations between OPG and breast cancer-specific survival, or for TRAIL and any outcome. CONCLUSIONS: Higher circulating OPG may be a biomarker of a higher risk of poor outcome among women diagnosed with ER- breast cancer. Further mechanistic studies are warranted.

Postdiagnosis body fatness, recreational physical activity, dietary factors and breast cancer prognosis: Global Cancer Update Programme (CUP Global) summary of evidence grading.

Based on the Global Cancer Update Programme, formally known as the World Cancer Research Fund/American Institute for Cancer Research Continuous Update Project, we performed systematic reviews and meta-analyses to investigate the association of postdiagnosis body fatness, physical activity and dietary factors with breast cancer prognosis. We searched PubMed and Embase for randomised controlled trials and longitudinal observational studies from inception to 31 October 2021. We calculated summary relative risks (RRs) and 95% confidence intervals (CIs) using random-effects meta-analyses. An independent Expert Panel graded the quality of evidence according to predefined criteria. The evidence on postdiagnosis body fatness and higher all-cause mortality (RR per 5 kg/m2 in body mass index: 1.07, 95% CI: 1.05-1.10), breast cancer-specific mortality (RR: 1.10, 95% CI: 1.06-1.14) and second primary breast cancer (RR: 1.14, 95% CI: 1.04-1.26) was graded as strong (likelihood of causality: probable). The evidence for body fatness and breast cancer recurrence and other nonbreast cancer-related mortality was graded as limited (likelihood of causality: limited-suggestive). The evidence on recreational physical activity and lower risk of all-cause (RR per 10 metabolic equivalent of task-hour/week: 0.85, 95% CI: 0.78-0.92) and breast cancer-specific mortality (RR: 0.86, 95% CI: 0.77-0.96) was judged as limited-suggestive. Data on dietary factors was limited, and no conclusions could be reached except for healthy dietary patterns, isoflavone and dietary fibre intake and serum 25(OH)D concentrations that were graded with limited-suggestive evidence for lower risk of the examined outcomes. Our results encourage the development of lifestyle recommendations for breast cancer patients to avoid obesity and be physically active.

Postdiagnosis body fatness, weight change and breast cancer prognosis: Global Cancer Update Program (CUP global) systematic literature review and meta-analysis.

Previous evidence on postdiagnosis body fatness and mortality after breast cancer was graded as limited-suggestive. To evaluate the evidence on body mass index (BMI), waist circumference, waist-hip-ratio and weight change in relation to breast cancer prognosis, an updated systematic review was conducted. PubMed and Embase were searched for relevant studies published up to 31 October, 2021. Random-effects meta-analyses were conducted to estimate summary relative risks (RRs). The evidence was judged by an independent Expert Panel using pre-defined grading criteria. One randomized controlled trial and 225 observational studies were reviewed (220 publications). There was strong evidence (likelihood of causality: probable) that higher postdiagnosis BMI was associated with increased all-cause mortality (64 studies, 32 507 deaths), breast cancer-specific mortality (39 studies, 14 106 deaths) and second primary breast cancer (11 studies, 5248 events). The respective summary RRs and 95% confidence intervals per 5 kg/m2 BMI were 1.07 (1.05-1.10), 1.10 (1.06-1.14) and 1.14 (1.04-1.26), with high between-study heterogeneity (I2  = 56%, 60%, 66%), but generally consistent positive associations. Positive associations were also observed for waist circumference, waist-hip-ratio and all-cause and breast cancer-specific mortality. There was limited-suggestive evidence that postdiagnosis BMI was associated with higher risk of recurrence, nonbreast cancer deaths and cardiovascular deaths. The evidence for postdiagnosis (unexplained) weight or BMI change and all outcomes was graded as limited-no conclusion. The RCT showed potential beneficial effect of intentional weight loss on disease-free-survival, but more intervention trials and well-designed observational studies in diverse populations are needed to elucidate the impact of body composition and their changes on breast cancer outcomes.

Postdiagnosis recreational physical activity and breast cancer prognosis: Global Cancer Update Programme (CUP Global) systematic literature review and meta-analysis.

It is important to clarify the associations between modifiable lifestyle factors such as physical activity and breast cancer prognosis to enable the development of evidence-based survivorship recommendations. We performed a systematic review and meta-analyses to summarise the evidence on the relationship between postbreast cancer diagnosis physical activity and mortality, recurrence and second primary cancers. We searched PubMed and Embase through 31st October 2021 and included 20 observational studies and three follow-up observational analyses of patients enrolled in clinical trials. In linear dose-response meta-analysis of the observational studies, each 10-unit increase in metabolic equivalent of task (MET)-h/week higher recreational physical activity was associated with 15% and 14% lower risk of all-cause (95% confidence interval [CI]: 8%-22%, studies = 12, deaths = 3670) and breast cancer-specific mortality (95% CI: 4%-23%, studies = 11, deaths = 1632), respectively. Recreational physical activity was not associated with breast cancer recurrence (HR = 0.97, 95% CI: 0.91-1.05, studies = 6, deaths = 1705). Nonlinear dose-response meta-analyses indicated 48% lower all-cause and 38% lower breast cancer-specific mortality with increasing recreational physical activity up to 20 MET-h/week, but little further reduction in risk at higher levels. Predefined subgroup analyses across strata of body mass index, hormone receptors, adjustment for confounders, number of deaths, menopause and physical activity intensities were consistent in direction and magnitude to the main analyses. Considering the methodological limitations of the included studies, the independent Expert Panel concluded 'limited-suggestive' likelihood of causality for an association between recreational physical activity and lower risk of all-cause and breast cancer-specific mortality.

Postdiagnosis dietary factors, supplement use and breast cancer prognosis: Global Cancer Update Programme (CUP Global) systematic literature review and meta-analysis.

Little is known about how diet might influence breast cancer prognosis. The current systematic reviews and meta-analyses summarise the evidence on postdiagnosis dietary factors and breast cancer outcomes from randomised controlled trials and longitudinal observational studies. PubMed and Embase were searched through 31st October 2021. Random-effects linear dose-response meta-analysis was conducted when at least three studies with sufficient information were available. The quality of the evidence was evaluated by an independent Expert Panel. We identified 108 publications. No meta-analysis was conducted for dietary patterns, vegetables, wholegrains, fish, meat, and supplements due to few studies, often with insufficient data. Meta-analysis was only possible for all-cause mortality with dairy, isoflavone, carbohydrate, dietary fibre, alcohol intake and serum 25-hydroxyvitamin D (25(OH)D), and for breast cancer-specific mortality with fruit, dairy, carbohydrate, protein, dietary fat, fibre, alcohol intake and serum 25(OH)D. The results, with few exceptions, were generally null. There was limited-suggestive evidence that predefined dietary patterns may reduce the risk of all-cause and other causes of death; that isoflavone intake reduces the risk of all-cause mortality (relative risk (RR) per 2 mg/day: 0.96, 95% confidence interval (CI): 0.92-1.02), breast cancer-specific mortality (RR for high vs low: 0.83, 95% CI: 0.64-1.07), and recurrence (RR for high vs low: 0.75, 95% CI: 0.61-0.92); that dietary fibre intake decreases all-cause mortality (RR per 10 g/day: 0.87, 95% CI: 0.80-0.94); and that serum 25(OH)D is inversely associated with all-cause and breast cancer-specific mortality (RR per 10 nmol/L: 0.93, 95% CI: 0.89-0.97 and 0.94, 95% CI: 0.90-0.99, respectively). The remaining associations were graded as limited-no conclusion.

Machine learning approaches for predicting 5-year breast cancer survival: A multicenter study.

The study used clinical data to develop a prediction model for breast cancer survival. Breast cancer prognostic factors were explored using machine learning techniques. We conducted a retrospective study using data from the Taipei Medical University Clinical Research Database, which contains electronic medical records from three affiliated hospitals in Taiwan. The study included female patients aged over 20 years who were diagnosed with primary breast cancer and had medical records in hospitals between January 1, 2009 and December 31, 2020. The data were divided into training and external testing datasets. Nine different machine learning algorithms were applied to develop the models. The performances of the algorithms were measured using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F1-score. A total of 3914 patients were included in the study. The highest AUC of 0.95 was observed with the artificial neural network model (accuracy, 0.90; sensitivity, 0.71; specificity, 0.73; PPV, 0.28; NPV, 0.94; and F1-score, 0.37). Other models showed relatively high AUC, ranging from 0.75 to 0.83. According to the optimal model results, cancer stage, tumor size, diagnosis age, surgery, and body mass index were the most critical factors for predicting breast cancer survival. The study successfully established accurate 5-year survival predictive models for breast cancer. Furthermore, the study found key factors that could affect breast cancer survival in Taiwanese women. Its results might be used as a reference for the clinical practice of breast cancer treatment.

Timing of Presentation and Outcomes of Women with Stage IV Pregnancy-Associated Breast Cancer (PABC).

BACKGROUND: Pregnancy-associated breast cancer (PABC) and concurrent, or early development of, stage IV disease is uncommon. Given this rarity, and complexities surrounding pregnancy, data are limited regarding PABC treatment and outcomes. We evaluated oncologic, obstetric, and fetal outcomes of women with stage IV PABC in relation to presentation timing and treatment. PATIENTS AND METHODS: Our retrospective review of an institutional database identified women with stage IV PABC from 1998 to 2018. PABC was defined as diagnosis during pregnancy or ≤ 1 year postpartum. Clinicopathologic, treatment, and outcome variables were compared between women diagnosed during pregnancy versus postpartum. RESULTS: We identified 77 women (median age 35 years; interquartile range [IQR] 32-37 years): 51 (66%) in the postpartum group and 26 (34%) in the pregnant group, including 9 with therapeutic or spontaneous abortion. Among 17 women who continued pregnancy, no obstetric or fetal complications were noted. Clinicopathologic and treatment variables did not differ between groups. Of 43 women dead from disease, 15 had triple negative (TN) tumors. Median overall survival (OS) of TN tumors was 14 months (range 5-39 months); OS was associated with hormone receptor-positive and human epidermal growth factor receptor 2 (HER2) positive tumors (p < 0.01). At 31 months (range 0-137 months) median follow-up, the 5-year OS was 34% (95% confidence interval 21-46%), and did not differ among pregnant and postpartum groups (p = 0.2). CONCLUSIONS: Women with stage IV TN PABC had high mortality rates despite multimodality therapy. Timing of presentation did not affect management decisions or OS, even for women who completed pregnancy. Further research to understand PABC biology, focusing on TN tumors, is warranted.

Metabolic abnormalities and survival among patients with non-metastatic breast cancer.

BACKGROUND: Research on the impact of metabolic abnormalities on breast cancer prognosis is limited by small samples and assessment of laboratory values at a single time point, often prior to cancer diagnosis and treatment. In this population-based cohort, time-updated laboratory values were adjusted for cancer treatment to assess the association between metabolic risk factors (glucose, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides) and breast cancer survival. METHODS: 13,434 women diagnosed with stage I-III breast cancer from 2005-15 at Kaiser Permanente were included. All outpatient fasting glucose, HDL-C, LDL-C, and triglyceride values from diagnosis through 2019 or death were extracted from electronic medical records. Risk of breast cancer-specific mortality was evaluated with Cox proportional hazards models adjusted for metabolic labs, demographics, body mass index, diabetes, dyslipidemia and anti-hypertensive medications, tumor characteristics (stage, ER and HER2 receptor status) and cancer treatment (use of chemotherapy, tamoxifen, and aromatase inhibitors). RESULTS: Mean (SD) age at diagnosis was 62.3 (11.8) years. Over a median follow-up of 8.6 years, 2,876 patients died; 1,080 of breast cancer. Patients with low HDL-C (≤ 45 vs. > 45 mg/dL) had higher breast cancer-specific mortality (HR, 1.77; 95% CI, 1.53-2.05), as did those with elevated fasting glucose (> 99 vs. 60-99 mg/dL) (HR, 1.19; 95% CI, 1.03-1.37). Elevated levels of triglycerides and LDL-C were not associated with breast cancer-specific mortality. CONCLUSIONS: High fasting glucose and low HDL-C evaluated over time after cancer diagnosis were associated with higher breast cancer mortality independent of cancer treatments and changes in other metabolic risk factors. Future studies should address whether pharmacologic or lifestyle treatment of glucose and lipids after breast cancer diagnosis can optimize survival outcomes.

Investigating the breast cancer screening-treatment-mortality pathway of women diagnosed with invasive breast cancer: Results from linked health data.

OBJECTIVE: To examine the screening-treatment-mortality pathway among women with invasive breast cancer in 2006-2014 using linked data. METHODS: BreastScreen histories of South Australian women diagnosed with breast cancer (n = 8453) were investigated. Treatments recorded within 12 months from diagnosis were obtained from linked registry and administrative data. Associations of screening history with treatment were investigated using logistic regression and with cancer mortality outcomes using competing risk analyses, adjusting for socio-demographic, cancer and comorbidity characteristics. RESULTS AND CONCLUSION: For screening ages of 50-69 years, 70% had participated in BreastScreen SA ≤ 5 years and 53% ≤ 2 years of diagnosis. Five-year disease-specific survival post-diagnosis was 90%. Compared with those not screened ≤5 years, women screened ≤2 years had higher odds, adjusted for socio-demographic, cancer and comorbidity characteristics, and diagnostic period, of breast-conserving surgery (aOR 2.5, 95% CI 1.9-3.2) and radiotherapy (aOR 1.2, 95% CI 1.1-1.3). These women had a lower unadjusted risk of post-diagnostic cancer mortality (SHR 0.33, 95% CI 0.27-0.41), partly mediated by stage (aSHR 0.65, 95% CI 0.51-0.81), and less breast surgery (aSHR 0.78, 95% CI 0.62-0.99). Screening ≤2 years and conserving surgery appeared to have a greater than additive association with lower post-diagnostic mortality (interaction term SHR 0.42, 95% CI 0.23-0.78). The screening-treatment-mortality pathway was investigated using linked data.

The effect of omitting axillary dissection and the impact of radiotherapy on patients with breast cancer sentinel node macrometastases: a cohort study following the ACOSOG Z0011 and AMAROS trials.

PURPOSE: To report the outcomes of implementing the ACOSOG Z0011 and AMAROS trials relevant to clinical practice, and to define target groups in whom to avoid or recommend axillary radiotherapy (ART). We also aimed to analyse the reduction in morbidity when axillary lymph node dissection (ALND) was omitted. METHODS: A retrospective cohort study of T1-T2 patients with macrometastases at sentinel lymph node (SLN) who were treated between 2011 and 2020. Breast surgery included either lumpectomy or mastectomy. Patients with ≤ 2 positive SLN were divided into two cohorts by whether they received ART or not. Survival outcomes and morbidity were analysed by Kaplan-Meyer curves and Cox-regression, respectively. RESULTS: 260 pN1a patients were included and ALND was avoided in 167 (64.2%). According the Z0011 results, 72 (43.1%) received no further ART; and based on AMAROS criteria 95 (56.9%) received ART. Median follow-up was 54 months. The 5-year overall survival was 96.8% in the non-RT cohort and 93.4% in the RT cohort (p = 0.19), while the respective 5-year disease-free survivals were 100% and 92.3% (p = 1.06). Lymphedema developed in 3.6% of patients after SLNB versus 43% after ALND (OR 20.25; 95%CI 8.13-50.43). Decreased upper-extremity range of motion appeared in 8.4% of patients after SLNB versus 31.2% after ALND (OR 4.95; 95%CI 2.45-9.98%). CONCLUSIONS: Our study confirms that omitting ALND is safe and has high survival rates in patients with T1-T2 tumours and ≤ 2 positive SLNs. Adding ART could be a treatment option for patients who present other risk factors. Avoiding ALND with or without ART was associated with significantly less arm morbidity.

Breast cancer treatment and survival differences in women in remote and socioeconomically disadvantaged areas, as demonstrated by linked data from New South Wales (NSW), Australia.

INTRODUCTION: Reducing variations in cancer treatment and survival is a key aim of the NSW Cancer Plan. Variations in breast cancer treatment and survival in NSW by remoteness and socioeconomic status of residence were investigated to determine benchmarks. Reducing variations in cancer treatment and survival is a key aim of the NSW Cancer Plan. Variations in breast cancer treatment and survival in NSW by remoteness and socioeconomic status of residence were investigated to determine benchmarks. METHODS: A retrospective cohort study used linked data for invasive breast cancers, diagnosed in May 2002 to December 2015 from the NSW Cancer Registry, with corresponding inpatient, and medical and pharmaceutical insurance data. Associations between treatment modalities, area socioeconomic status and residential remoteness were explored using logistic regression. Predictors of breast cancer survival were investigated using Kaplan-Meier product-limit estimates and multivariate competing risk regression. RESULTS: Results indicated a high 5-year disease-specific survival in NSW of 90%. Crude survival was equivalent by residential remoteness and marginally lower in lower socioeconomic areas. Competing risk regression showed equivalent outcomes by area socioeconomic status, except for the least disadvantaged quintile, which showed a higher survival. Higher sub-hazard ratios for death occurred for women with breast cancer aged 70 + years, and more advanced stage. Adjusted analyses indicated more advanced stage in lower socioeconomic areas, with less breast reconstruction and radiotherapy, and marginally less hormone therapy for women from these areas. Conversely, among these women who had breast conserving surgery, there was higher use of chemotherapy. Remoteness of residence was associated in adjusted analyses with less radiotherapy and less immediate breast reconstruction. In these short term data, remoteness of residence was not associated with lower survival. CONCLUSION: This study provides benchmarks for monitoring future variations in treatment and survival.

Types of carbohydrate intake and breast cancer survival.

OBJECTIVE: To investigate the associations of different types of carbohydrate intake after breast cancer diagnosis with breast cancer-specific and all-cause mortality. METHODS: We prospectively assessed post-diagnostic intake of total sugar, added sugar, and natural sugar as well as carbohydrate from different sources, among 8932 women with stage I-III breast cancer that were identified in the Nurses' Health Study from 1980 to 2010 and Nurses' Health Study II from 1991 to 2011. Participants completed a validated food frequency questionnaire every four years after diagnosis and were followed up for death. RESULTS: We prospectively documented 1071 deaths due to breast cancer and 2532 all-cause deaths, over a mean of 11.5 years of follow-up. After adjustment for confounding variables, greater post-diagnostic total sugar intake was suggestively associated with greater risk of breast cancer-specific mortality [hazard ratio (HR)Q5vsQ1 = 1.16, 95% confidence interval (CI ) = 0.95-1.41; Ptrend = 0.02] and significantly associated with greater risk of all-cause mortality (HRQ5vsQ1 = 1.23, 95% CI = 1.08-1.41; Ptrend = 0.0001). Greater post-diagnostic added sugar intake was significantly associated with greater risk of all-cause mortality (HRQ5vsQ1 = 1.20, 95% CI = 1.06-1.36; Ptrend = 0.001). Post-diagnostic natural sugar (occurring in foods and not added as an ingredient) intake was not associated with mortality risk. Greater post-diagnostic fructose intake was significantly associated with greater risk of breast cancer-specific mortality (HRQ5vsQ1 = 1.34, 95% CI = 1.10-1.64; Ptrend = 0.005) and all-cause mortality (HRQ5vsQ1 = 1.16, 95% CI = 1.02-1.32; Ptrend = 0.01). High post-diagnostic intake of sucrose was associated with higher risk of breast cancer-specific and all-cause mortality. Increased post-diagnostic intake of carbohydrate from fruit juice was significantly associated with higher risk of breast cancer-specific and all-cause mortality and carbohydrate from vegetables was significantly associated with lower risk of all-cause mortality. High post-diagnostic intake of carbohydrate from potatoes was suggestively associated with higher risk of breast cancer-specific mortality and carbohydrate from refined grains was suggestively associated with higher risk of all-cause mortality. CONCLUSIONS: We found that higher total sugar intake, especially added sugar, sucrose, and fructose, as well as carbohydrate from fruit juice after a breast cancer diagnosis were associated with poorer prognosis. High post-diagnostic intake of carbohydrate from vegetables was associated with reduced risk of mortality.

Female breast cancer in New South Wales, Australia, by country of birth: implications for health-service delivery.

BACKGROUND: NSW has a multicultural population with increasing migration from South East Asia, the Western Pacific and Eastern Mediterranean. OBJECTIVE: To compare cancer stage, treatment (first 12 months) and survival for 12 country of birth (COB) categories recorded on the population-based NSW Cancer Registry. DESIGN: Historic cohort study of invasive breast cancers diagnosed in 2003-2016. PATIENTS: Data for 48,909 women (18+ ages) analysed using linked cancer registry, hospital inpatient and Medicare and pharmaceutical benefits claims data. MEASUREMENT: Comparisons by COB using multivariate logistic regression and proportional hazards regression with follow-up of vital status to April 30th, 2020. RESULTS: Compared with the Australia-born, women born in China, the Philippines, Vietnam and Lebanon were younger at diagnosis, whereas those from the United Kingdom, Germany, Italy and Greece were older. Women born in China, the Philippines, Vietnam, Greece and Italy lived in less advantaged areas. Adjusted analyses indicated that: (1) stage at diagnosis was less localised for women born in Germany, Greece, Italy and Lebanon; (2) a lower proportion reported comorbidity for those born in China, the Philippines and Vietnam; (3) surgery type varied, with mastectomy more likely for women born in China, the Philippines and Vietnam, and less likely for women born in Italy, Greece and Lebanon; (4) radiotherapy was more likely where breast conserving surgery was more common (Greece, Italy, and Lebanon) and the United Kingdom; and (5) systemic drug therapy was less common for women born in China and Germany. Five-year survival in NSW was high by international standards and increasing. Adjusted analyses indicate that, compared with the Australian born, survival from death from cancer at 5 years from diagnosis was higher for women born in China, the Philippines, Vietnam, Italy, the United Kingdom and Greece. CONCLUSIONS: There is diversity by COB of stage, treatment and survival. Reasons for survival differences may include cultural factors and healthier migrant populations with lower comorbidity, and potentially, less complete death recording in Australia if some women return to their birth countries for treatment and end-of-life care. More research is needed to explore the cultural and clinical factors that health services need to accommodate.

Diet Before and After Breast Cancer.

The incidence of breast cancer has dramatically increased recently in several Asian countries. This region has experienced rapid economic growth and demographic and environmental changes. Breast cancer rates vary substantially among countries, with a lower incidence in developing countries than that in Western countries. Given the upward trend of breast cancer incidence in Asian countries and the large variation in incidence around the world, dietary changes may contribute to breast cancer development. In particular, nutrients and foods from animal sources have drawn attention as potential causes of breast cancer given that obesity and energy balance appear to be important factors associated with breast cancer risk. However, prospective cohort and intervention studies do not support the hypothesis that diet in middle life influences breast cancer development. However, recent studies have provided better insight into the roles of dietary factors in specific types of breast cancers, such as estrogen receptor-negative (ER-) breast cancer. Some studies suggest that diet in early life may play a substantial role in breast cancer development, but data and evidence remain limited.Although etiologic and epidemiologic studies have long studied modifiable risk factors for breast cancer incidence, much remains to be explored regarding the role of diet after a breast cancer diagnosis. Several epidemiologic studies have explored the factors that improve breast cancer survival rates, including diet, physical activity, and body mass index (BMI). While there is evidence of the effect of BMI on breast cancer mortality, the effects of changing dietary habits after a breast cancer diagnosis on survival or recurrence are less clear. A report of the World Cancer Research Fund stated that evidence was not sufficient to draw firm conclusions about the effect of diet and nutrition on breast cancer prognosis, but it did suggest a link between diet and breast cancer survival.The global burden of breast cancer is increasing and breast cancer is a major and emerging health problem in both developed and developing countries. For example, the five-year survival rate for Korean breast cancer patients has improved from 78.0% in 1993-1995 to 92.7% in 2012-2016. This improvement emphasizes the importance of supportive care, diet, and quality of life for breast cancer survivors. However, we have limited data of non-Western breast cancer survivors. There is a need to examine the role of diet in breast cancer survival in both Western and non-Western regions.

E-cadherin deregulation in breast cancer.

E-cadherin protein (CDH1 gene) integrity is fundamental to the process of epithelial polarization and differentiation. Deregulation of the E-cadherin function plays a crucial role in breast cancer metastases, with worse prognosis and shorter overall survival. In this narrative review, we describe the inactivating mechanisms underlying CDH1 gene activity and its possible translation to clinical practice as a prognostic biomarker and as a potential targeted therapy.

A functional variant near XCL1 gene improves breast cancer survival via promoting cancer immunity.

Most genome-wide association studies (GWASs) identify genetic variants for breast cancer occurrence. In contrast, few are for recurrence and mortality. We conducted a GWAS on breast cancer survival after diagnosis in estrogen receptor-positive patients, including 953 Taiwanese patients with 159 events. Through Cox proportional hazard models estimation, we identified 24 risk SNPs with p < 1 × 10-5 . Based on imputation and integrated analysis, one SNP, rs1024176 (located in 1q24.2, p = 2.43 × 10-5 ) was found to be a functional variant associated with breast cancer survival and XCL1 gene expression. A series of experimental approaches, including cell-based analyses and CRISPR/Cas9 genome-editing system, were then used and identified the transcription factor MYBL2 was able to discriminately bind to the A allele of rs1024176, the protective variant for breast cancer survival, which promoted XCL1 expression, but not to the G allele of rs1024176. The chemokine XCL1 attracts type 1 dendritic cells (DC1s) to the tumor microenvironment. In breast cancer tissues, we applied a two-step Mendelian randomization analysis, using expression quantitative trait loci as instrumental variables, to confirm higher XCL1 expression was correlated with higher DC1 signatures and favorable disease progression, through the causal effect of rs1024176-A allele. Our study supports the genetic effect on preventing breast cancer survival through XCL1-induced DC1 recruitment in tumor microenvironment.