An overview of prognostic factors for long-term survivors of breast cancer

Breast cancer survival in Ethiopia: a systematic review and meta-analysis of rates and predictors

BACKGROUND

Evidence on breast cancer survival and factors affecting survival is crucial for evaluating treatment effectiveness and formulating breast cancer control strategies. Although original research has been conducted on the survival rate of breast cancer patients and their determinants in Ethiopia, there is a shortage of comprehensive scientific evidence. The present study systematically reviewed literature on the survival rate of breast cancer patients and the predictors of survival in Ethiopia.

METHODS

A comprehensive search was conducted in the PubMed, HINARI, Global Index Medicus, and Google Scholar databases up to August 26, 2024. Without any design restrictions, studies on breast cancer patients that measured survival at different time points in Ethiopia were included. The results are summarized in a table, the survival rates are pooled, and risk factors are narratively synthesized. To assess the risk of bias, the Newcastle Ottawa Scale was utilized. Heterogeneity between studies was assessed using the I2 statistic. Potential publication bias was assessed using a funnel plot. To examine robustness, a leave-one-out sensitivity analysis was performed.

RESULTS

The pooled survival rates in the first, second, third, fifth, and sixth years were 90%, 70%, 68%, 46%, and 44%, respectively. Advanced age, lower socioeconomic status, late clinical stage, delayed diagnosis, higher histological grade, metastasis, lymph node involvement, presence of comorbidity, tumor size, and estrogen receptor positive were factors that increased the risk of mortality in the included studies.

CONCLUSION

Survival rate of breast cancer patients in later time including fifth and sixth years was comparably lower than other countries. It is crucial to raise awareness about breast cancer screening, early diagnosis, and therapy initiation to increase the survival rate of breast cancer patients in Ethiopia. In addition, it is important to emphasize the risky population groups, which includes those with lower socioeconomic status and advanced clinical parameters.

Eating Disorders and Later Incidence of Cancer: A Nationwide Longitudinal Study in Denmark

Background

We examined the incidence of cancer types among individuals with eating disorders (EDs).

Methods

A nationwide longitudinal study of 6,807,731 individuals born between 1940 and 2015 was conducted using the Danish National Registries. Cox models with ED diagnosis as exposure and cancer diagnoses as outcomes were used to estimate hazard ratios (HRs) and 95% CIs while adjusting for sex, birth year, and comorbidities. The primary analysis comprised ICD-8 and ICD-10 codes for anorexia nervosa (AN) and other ED (OED). The secondary analysis comprised ICD-10 codes and included AN, bulimia nervosa (BN), and eating disorders not otherwise specified (EDNOS).

Results

AN was associated with a reduced incidence of breast cancer while adjusting for sex and birth year (HR, 0.80; 95% CI, 0.66-0.97) and elevated incidence of respiratory (HR, 1.59; 95% CI, 1.24-2.04), cervical (HR, 1.45; 95% CI, 1.05-1.98), and esophageal (HR, 4.77; 95% CI, 2.82-8.06) cancers. OED was associated with an elevated incidence of respiratory (HR, 1.57; 95% CI, 1.20-2.06) and cervical (HR, 1.60; 95% CI, 1.20-2.14) cancers. ICD-10-only analyses confirmed the association of AN with reduced incidence of breast cancer and elevated incidence of respiratory and cervical cancers. BN was associated with reduced incidence of breast cancer in sensitivity analysis. EDNOS was associated with reduced incidence of breast cancer and elevated incidence of respiratory and cervical cancers.

Conclusions

All EDs were associated with a reduced incidence of breast cancer. All EDs except BN were associated with a higher incidence of respiratory and cervical cancers. AN was associated with a higher incidence of esophageal cancer.

Impact of routine FDG-PET/CT on locoregional treatment decisions in breast cancer patients receiving preoperative systemic therapy

PURPOSE

This study evaluates the clinical impact of routine FDG-PET/CT on locoregional treatment in a large cohort of breast cancer patients scheduled for preoperative systemic therapy (PST).

METHODS

Patients scheduled for PST were identified from a retrospective database between 2011 and 2020 at our hospital. All patients underwent staging by FDG-PET/CT prior to PST. The rate of regional upstaging by FDG-PET/CT compared to initial locoregional staging was assessed, as well as its implications on surgical and radiotherapeutic management. Logistic regression analysis was used to evaluate the correlation between clinical characteristics and regional upstaging by FDG-PET/CT.

RESULTS

Among 1228 eligible patients, FDG-PET/CT detected additional regional lymph node involvement in 145 patients (12 %). This resulted in treatment modifications for 140 patients (11 %), including changes to the axillary surgical approach in 27 patients (2 %), and adjustments to the postoperative radiation therapy plans in 115 patients (9 %). The majority of these modifications occurred in patients initially staged as cN1(1-3) (92/140). Clinical T stage was significantly associated with regional upstaging by FDG-PET/CT.

CONCLUSION

FDG-PET/CT staging before PST frequently identifies additional regional lymph node involvement, significantly altering locoregional treatment strategies in the majority.

Association between radiotherapy and the risk of second primary malignancies in breast cancer patients with different estrogen receptor statuses

BACKGROUND

Breast cancer is the most common cancer among women. Second primary malignancies (SPMs) related to radiotherapy are significant complications. This study aims to investigate the correlation between radiotherapy and the occurrence of SPMs in breast cancer patients with different estrogen receptor statuses.

METHODS

We used data from the Surveillance, Epidemiology, and End Results (SEER) database, selecting estrogen receptor(+) and estrogen receptor(-) breast cancer patients from 1990 to 2015, with SPMs as the outcome measure. Fine-Gray competing risks regression and Poisson regression were employed to analyze the relationship between radiotherapy and the risk of SPMs in different estrogen receptor status groups.

RESULTS

Radiotherapy was associated with an increased risk of lung cancer, melanoma, non-Hodgkin lymphoma, and leukemia in estrogen receptor(+) patients. In estrogen receptor(-) patients, radiotherapy was linked to an increased risk of brain cancer and leukemia. The cumulative incidence, standardized incidence ratio, and subgroup analyses showed consistent results. In the dynamic assessment of radiotherapy-related risks, estrogen receptor(+) patients aged 50-70 exhibited a higher risk of leukemia and melanoma. Lung cancer risk was highest during a latency period of 20-30 years, while melanoma, non-Hodgkin lymphoma, and leukemia risks peaked within the first 10 years. For estrogen receptor(-) patients, brain cancer risk was higher between ages 50 and 70, and leukemia risk was elevated between ages 20 and 50.

CONCLUSION

Postoperative radiotherapy for breast cancer is associated with an increased risk of SPMs, with risks varying by estrogen receptor status and SPM type. Further research into the prevention of radiotherapy-related SPMs in different estrogen receptor status groups is crucial.

Molecular-Targeted Fluorescence Lymph Node Imaging Could Play a Clinical Role in the Surgical Setting: A Systematic Review

The lymphatic system plays a crucial role in the spread of solid tumors and is often the first site of metastasis, as cancer cells typically invade nearby lymph nodes (LN) before potentially spreading to other LNs through the lymphatic system and distant organs through the bloodstream [...].

Deep Learning: A Heuristic Three-Stage Mechanism for Grid Searches to Optimize the Future Risk Prediction of Breast Cancer Metastasis Using EHR-Based Clinical Data

Background: A grid search, at the cost of training and testing a large number of models, is an effective way to optimize the prediction performance of deep learning models. A challenging task concerning grid search is time management. Without a good time management scheme, a grid search can easily be set off as a "mission" that will not finish in our lifetime. In this study, we introduce a heuristic three-stage mechanism for managing the running time of low-budget grid searches with deep learning, sweet-spot grid search (SSGS) and randomized grid search (RGS) strategies for improving model prediction performance, in an application of predicting the 5-year, 10-year, and 15-year risk of breast cancer metastasis. Methods: We develop deep feedforward neural network (DFNN) models and optimize the prediction performance of these models through grid searches. We conduct eight cycles of grid searches in three stages, focusing on learning a reasonable range of values for each of the adjustable hyperparameters in Stage 1, learning the sweet-spot values of the set of hyperparameters and estimating the unit grid search time in Stage 2, and conducting multiple cycles of timed grid searches to refine model prediction performance with SSGS and RGS in Stage 3. We conduct various SHAP analyses to explain the prediction, including a unique type of SHAP analyses to interpret the contributions of the DFNN-model hyperparameters. Results: The grid searches we conducted improved the risk prediction of 5-year, 10-year, and 15-year breast cancer metastasis by 18.6%, 16.3%, and 17.3%, respectively, over the average performance of all corresponding models we trained using the RGS strategy. Conclusions: Grid search can greatly improve model prediction. Our result analyses not only demonstrate best model performance but also characterize grid searches from various aspects such as their capabilities of discovering decent models and the unit grid search time. The three-stage mechanism worked effectively. It not only made our low-budget grid searches feasible and manageable but also helped improve the model prediction performance of the DFNN models. Our SHAP analyses not only identified clinical risk factors important for the prediction of future risk of breast cancer metastasis, but also DFNN-model hyperparameters important to the prediction of performance scores.

Pan-cancer analysis and experimental verification of cytochrome B561 as a prognostic and therapeutic biomarker in breast cancer

OBJECTIVE

This study investigates Cytochrome B561 (CYB561) expression in Pan-Cancer, its relationship with immune invasion, and its prognostic value in Breast Cancer (BRCA) patients.

METHODS

Data from The Cancer Genome Atlas (TCGA) were analyzed. CYB561 expression in normal and tumor tissues was examined, with correlations to immune invasion, mutation, and immune checkpoints. Wilcoxon rank-sum test assessed expression differences. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted. Logistic regression, Kaplan-Meier, and Cox regression analyses evaluated clinicopathological features and survival outcomes. A Cox multivariate analysis-based Nomogram predicted CYB561's prognostic impact. CYB561 knockout in breast cancer cells assessed functional effects. Single-cell RNA sequencing identified prognostic biomarkers.

RESULTS

CYB561 was highly expressed in most tumors. BRCA showed the highest correlation with ESTIMATE scores and significant negative correlation with immune checkpoints. High CYB561 expression correlated with specific clinicopathological features and survival outcomes. The nomogram predicted BRCA prognosis. CYB561 knockout inhibited breast cancer cell proliferation. Seven predictive agents for CYB561 inhibition were identified.

CONCLUSIONS

CYB561 exhibits aberrant expression in tumors, particularly in BRCA, and serves as a predictive marker for immune-related therapies and a prognostic indicator in BRCA.

Multiparametric MRI assessment of primary tumours for predicting axillary tumour burden in women with invasive breast cancer

OBJECTIVE

To assess the association between multiparametric MRI features of primary tumours and axillary lymph node tumour burden in women with invasive breast cancer.

METHODS

In this retrospective study, women diagnosed with invasive breast cancer who underwent 3T multiparametric MRI, including diffusion-weighted imaging (DWI) from 2019 to 2020, were evaluated. Two radiologists reviewed T2-weighted images (T2WI) for peritumoural oedema and intratumoural necrosis and measured apparent diffusion coefficient (ADC) values by manually placing regions of interest within breast tumours. We also analysed quantitative kinetic features of breast cancer using computer-aided diagnosis (CAD) and clinical-pathologic characteristics. Uni- and multivariable logistic regression analyses were conducted to identify predictors of a high axillary nodal burden (≥3 positive nodes).

RESULTS

In total, 301 women (mean age, 54.13 years) were evaluated. Forty-three (14.3%) had a high axillary nodal burden by surgical pathology. Multivariate analysis revealed that factors significantly associated with high axillary nodal burden included peritumoural oedema (OR: 7.970; P < .001), lower tumour ADCmax (≤1.098 × 10-3 mm2/s) (OR: 6.978; P < .001), larger tumour size (>2 cm) (OR: 2.986; P = .046), lobular histology (OR: 12.620; P < .001), and the presence of lymphovascular invasion (OR: 3.622; P = .003). CAD-derived kinetic features did not show an association with axillary nodal burden. In subgroup analysis of 238 patients with early clinically node-negative breast cancer, both peritumoural oedema (OR: 7.831; P = .002) and lower tumour ADCmax (≤1.098 × 10-3 mm2/s) (OR: 8.002; P = .002) remained significant predictors.

CONCLUSION

Our results suggest that peritumoural oedema as viewed in T2WI and the ADCmax value of breast cancer in DWI are valuable for predicting axillary nodal burden in women with invasive breast cancer.

ADVANCES IN KNOWLEDGE

Multiparametric MRI features of a primary tumour are useful for predicting axillary nodal burden in patients with invasive breast cancer.

Artificial intelligence can extract important features for diagnosing axillary lymph node metastasis in early breast cancer using contrast-enhanced ultrasonography

Contrast-enhanced ultrasound (CEUS) plays a pivotal role in the diagnosis of primary breast cancer and in axillary lymph node (ALN) metastasis. However, the imaging features that are clinically crucial for lymph node metastasis have not been fully elucidated. Hence, we developed a bimodal model to predict ALN metastasis in patients with early breast cancer by integrating CEUS images with the annotated imaging features. The model adopted a light-gradient boosting machine to produce feature importance, enabling the extraction of clinically crucial imaging features. In this retrospective study, the diagnostic performance of the model was investigated using 788 CEUS images of ALNs obtained from 788 patients who underwent breast surgery between 2013 and 2021, with the ground truth defined by the pathological diagnosis. The results indicated that the test cohort had an area under the receiver operating characteristic curve (AUC) value of 0.93 (95% confidence interval: 0.88, 0.98). The model had an accuracy of 0.93, which was higher than the radiologist's diagnosis (accuracy of 0.85). The most important imaging features were heterogeneous enhancement, diffuse cortical thickening, and eccentric cortical thickening. Our model has an excellent diagnostic performance, and the extracted imaging features could be crucial for confirming ALN metastasis in clinical settings.

Overall Observed Survival of Female Breast, Cervical, Colorectal, and Prostate Cancers in Antigua and Barbuda, 2017-2021: Retrospective Data from Four Study Sites

Understanding cancer survival is important for countries such as Antigua and Barbuda, where female breast, cervical, colorectal, and prostate cancers are burdensome to the healthcare system. This study therefore aimed to estimate the survival probabilities of patients diagnosed with these cancers between 2017 and 2021. A retrospective analytical study design was used to evaluate cancer cases abstracted from medical records at key study sites. Estimates of observed survival probabilities were determined using a Kaplan-Meier analysis. Significant differences between survival curves were assessed using the log-rank test. Hazard ratios were calculated using Cox regression. A p-value < 0.05 indicated significance. A total of 391 diagnosed cases were included in this study (2017-2021): female breast cancer accounted for 42%, cervical cancer accounted for 10%, colorectal cancer accounted for 20%, and prostate cancer accounted for 28%. Overall, the mean age of the participants was 61.5 (±12.9) years; 62% were female, 73% were aged > 55 years, 56% were from St. John's, and 82% were alive at the end of 2021. The median overall survival (years) was 4.8 for female breast cancer, 4.1 for cervical cancer, 4.5 for colorectal cancer, and not reached for prostate cancer. The cancer-specific overall observed 5-year survival probabilities were 44.9% for female breast cancer, 10.8% for cervical cancer, 19.6% for colorectal cancer, and 69.0% for prostate cancer. Significant associations between disease stage and overall survival were observed in female breast and colorectal cancers. This study provides important evidence for the 5-year observed survival probabilities of the studied cancers. Healthcare improvements that support cancer survival are required.

A phase III trial of adjuvant ribociclib plus endocrine therapy versus endocrine therapy alone in patients with HR-positive/HER2-negative early breast cancer: final invasive disease-free survival results from the NATALEE trial

BACKGROUND

NATALEE assessed efficacy and tolerability of 3 years of adjuvant ribociclib plus a nonsteroidal aromatase inhibitor (NSAI) compared with an NSAI alone in a broad population of patients with hormone receptor (HR)-positive/human epidermal growth factor 2 (HER2)-negative early breast cancer, including a select group without nodal involvement. This is the final preplanned analysis of invasive disease-free survival (iDFS).

PATIENTS AND METHODS

Premenopausal/postmenopausal women and men were randomized 1 : 1 to ribociclib (n = 2549; 400 mg/day, 3 weeks on/1 week off for 36 months) plus NSAI (letrozole 2.5 mg/day or anastrozole 1 mg/day for 60 months) or NSAI alone (n = 2552). Men and premenopausal women also received goserelin (3.6 mg once every 28 days). Patients had anatomical stage IIA (N0 with additional risk factors or N1), IIB, or III disease. The primary endpoint was iDFS. Secondary efficacy endpoints were recurrence-free survival (RFS), distant DFS, and overall survival. This final iDFS analysis was planned after ∼500 events.

RESULTS

At data cut-off (21 July 2023), ribociclib was stopped for 1996 patients (78.3%); 1091 (42.8%) completed 3 years of ribociclib, and ribociclib treatment was ongoing for 528 (20.7%). Median follow-up for iDFS was 33.3 months. Overall, 226 and 283 iDFS events occurred with ribociclib plus NSAI versus NSAI alone, respectively. Ribociclib plus NSAI demonstrated significant iDFS benefit over NSAI alone [hazard ratio 0.749, 95% confidence interval (CI) 0.628-0.892; P = 0.0012]. The 3-year iDFS rates were 90.7% (95% CI 89.3% to 91.8%) versus 87.6% (95% CI 86.1% to 88.9%). A consistent benefit was observed across prespecified subgroups, including stage (II/III) and nodal status (positive/negative). Distant DFS and RFS favored ribociclib plus NSAI. Overall survival data were immature. No new safety signals were observed.

CONCLUSIONS

With longer follow-up and most patients off ribociclib, NATALEE continues to demonstrate iDFS benefit with ribociclib plus NSAI over NSAI alone in the overall population and across key subgroups. Observed adverse events remained stable.

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.

Artificial intelligence for breast cancer detection and its health technology assessment: A scoping review

BACKGROUND

Recent healthcare advancements highlight the potential of Artificial Intelligence (AI) - and especially, among its subfields, Machine Learning (ML) - in enhancing Breast Cancer (BC) clinical care, leading to improved patient outcomes and increased radiologists' efficiency. While medical imaging techniques have significantly contributed to BC detection and diagnosis, their synergy with AI algorithms has consistently demonstrated superior diagnostic accuracy, reduced False Positives (FPs), and enabled personalized treatment strategies. Despite the burgeoning enthusiasm for leveraging AI for early and effective BC clinical care, its widespread integration into clinical practice is yet to be realized, and the evaluation of AI-based health technologies in terms of health and economic outcomes remains an ongoing endeavor.

OBJECTIVES

This scoping review aims to investigate AI (and especially ML) applications that have been implemented and evaluated across diverse clinical tasks or decisions in breast imaging and to explore the current state of evidence concerning the assessment of AI-based technologies for BC clinical care within the context of Health Technology Assessment (HTA).

METHODS

We conducted a systematic literature search following the Preferred Reporting Items for Systematic review and Meta-Analysis Protocols (PRISMA-P) checklist in PubMed and Scopus to identify relevant studies on AI (and particularly ML) applications in BC detection and diagnosis. We limited our search to studies published from January 2015 to October 2023. The Minimum Information about CLinical Artificial Intelligence Modeling (MI-CLAIM) checklist was used to assess the quality of AI algorithms development, evaluation, and reporting quality in the reviewed articles. The HTA Core Model® was also used to analyze the comprehensiveness, robustness, and reliability of the reported results and evidence in AI-systems' evaluations to ensure rigorous assessment of AI systems' utility and cost-effectiveness in clinical practice.

RESULTS

Of the 1652 initially identified articles, 104 were deemed eligible for inclusion in the review. Most studies examined the clinical effectiveness of AI-based systems (78.84%, n= 82), with one study focusing on safety in clinical settings, and 13.46% (n=14) focusing on patients' benefits. Of the studies, 31.73% (n=33) were ethically approved to be carried out in clinical practice, whereas 25% (n=26) evaluated AI systems legally approved for clinical use. Notably, none of the studies addressed the organizational implications of AI systems in clinical practice. Of the 104 studies, only two of them focused on cost-effectiveness analysis, and were analyzed separately. The average percentage scores for the first 102 AI-based studies' quality assessment based on the MI-CLAIM checklist criteria were 84.12%, 83.92%, 83.98%, 74.51%, and 14.7% for study design, data and optimization, model performance, model examination, and reproducibility, respectively. Notably, 20.59% (n=21) of these studies relied on large-scale representative real-world breast screening datasets, with only 10.78% (n =11) studies demonstrating the robustness and generalizability of the evaluated AI systems.

CONCLUSION

In bridging the gap between cutting-edge developments and seamless integration of AI systems into clinical workflows, persistent challenges encompass data quality and availability, ethical and legal considerations, robustness and trustworthiness, scalability, and alignment with existing radiologists' workflow. These hurdles impede the synthesis of comprehensive, robust, and reliable evidence to substantiate these systems' clinical utility, relevance, and cost-effectiveness in real-world clinical workflows. Consequently, evaluating AI-based health technologies through established HTA methodologies becomes complicated. We also highlight potential significant influences on AI systems' effectiveness of various factors, such as operational dynamics, organizational structure, the application context of AI systems, and practices in breast screening or examination reading of AI support tools in radiology. Furthermore, we emphasize substantial reciprocal influences on decision-making processes between AI systems and radiologists. Thus, we advocate for an adapted assessment framework specifically designed to address these potential influences on AI systems' effectiveness, mainly addressing system-level transformative implications for AI systems rather than focusing solely on technical performance and task-level evaluations.

Staphylococcus epidermidis biofilm in inflammatory breast cancer and its treatment strategies

Bacterial biofilms represent a significant challenge in both clinical and industrial settings because of their robust nature and resistance to antimicrobials. Biofilms are formed by microorganisms that produce an exopolysaccharide matrix, protecting function and supporting for nutrients. Among the various bacterial species capable of forming biofilms, Staphylococcus epidermidis, a commensal organism found on human skin and mucous membranes, has emerged as a prominent opportunistic pathogen, when introduced into the body via medical devices, such as catheters, prosthetic joints, and heart valves. The formation of biofilms by S. epidermidis on these surfaces facilitates colonization and provides protection against host immune responses and antibiotic therapies, leading to persistent and difficult-to-treat infections. The possible involvement of biofilms for breast oncogenesis has recently created the curiosity. This paper therefore delves into S. epidermidis biofilm involvement in breast cancer. S. epidermidis biofilms can create a sustained inflammatory environment through their metabolites and can break DNA in breast tissue, promoting cellular proliferation, angiogenesis, and genetic instability. Preventing biofilm formation primarily involves preventing bacterial proliferation using prophylactic measures and sterilization of medical devices and equipment. In cancer treatment, common modalities include chemotherapy, surgery, immunotherapy, alkylating agents, and various anticancer drugs. Understanding the relationship between anticancer drugs and bacterial biofilms is crucial, especially for those undergoing cancer treatment who may be at increased risk of bacterial infections, for improving patient outcomes. By elucidating these interactions, strategies to prevent or disrupt biofilm formation, thereby reducing the incidence of infections associated with medical devices and implants, can be identified.

Identification of sentinel lymph node macrometastasis in breast cancer by deep learning based on clinicopathological characteristics

The axillary lymph node status remains an important prognostic factor in breast cancer, and nodal staging using sentinel lymph node biopsy (SLNB) is routine. Randomized clinical trials provide evidence supporting de-escalation of axillary surgery and omission of SLNB in patients at low risk. However, identifying sentinel lymph node macrometastases (macro-SLNMs) is crucial for planning treatment tailored to the individual patient. This study is the first to explore the capacity of deep learning (DL) models to identify macro-SLNMs based on preoperative clinicopathological characteristics. We trained and validated five multivariable models using a population-based cohort of 18,185 patients. DL models outperform logistic regression, with Transformer showing the strongest results, under the constraint that the sensitivity is no less than 90%, reflecting the sensitivity of SLNB. This highlights the feasibility of noninvasive macro-SLNM prediction using DL. Feature importance analysis revealed that patients with similar characteristics exhibited different nodal status predictions, indicating the need for additional predictors for further improvement.

Hub metastatic gene signature and risk score of breast cancer patients with small tumor sizes using WGCNA

BACKGROUND

Breast cancer (BC) is the most common cancer in women and accounts for approximately 15% of all cancer deaths among women globally. The underlying mechanism of BC patients with small tumor size and developing distant metastasis (DM) remains elusive in clinical practices.

METHODS

We integrated the gene expression of BCs from ten RNAseq datasets from Gene Expression Omnibus (GEO) database to create a genetic prediction model for distant metastasis-free survival (DMFS) in BC patients with small tumor sizes (≤ 2 cm) using weighted gene co-expression network (WGCNA) analysis and LASSO cox regression.

RESULTS

ABHD11, DDX39A, G3BP2, GOLM1, IL1R1, MMP11, PIK3R1, SNRPB2, and VAV3 were hub metastatic genes identified by WGCNA and used to create a risk score using multivariable Cox regression. At the cut-point value of the median risk score, the high-risk score (≥ median risk score) group had a higher risk of DM than the low-risk score group in the training cohort [hazard ratio (HR) 4.51, p < 0.0001] and in the validation cohort (HR 5.48, p = 0.003). The nomogram prediction model of 3-, 5-, and 7-year DMFS shows good prediction results with C-indices of 0.72-0.76. The enriched pathways were immune regulation and cell-cell signaling. EGFR serves as the hub gene for the protein-protein interaction network of PIK3R1, IL1R1, MMP11, GOLM1, and VAV3.

CONCLUSION

Prognostic gene signature was predictive of DMFS for BCs with small tumor sizes. The protein-protein interaction network of PIK3R1, IL1R1, MMP11, GOLM1, and VAV3 connected by EGFR merits further experiments for elucidating the underlying mechanisms.

A multi-model approach integrating whole-slide imaging and clinicopathologic features to predict breast cancer recurrence risk

Breast cancer is the most common malignancy affecting women worldwide and is notable for its morphologic and biologic diversity, with varying risks of recurrence following treatment. The Oncotype DX Breast Recurrence Score test is an important predictive and prognostic genomic assay for estrogen receptor positive/HER2 negative breast cancer that guides therapeutic strategies; however, such tests can be expensive, delay care, and are not widely available. The aim of this study was to develop a multi-model approach integrating the analysis of whole-slide images and clinicopathologic data to predict their associated breast cancer recurrence risks and categorize these patients into two risk groups according to the predicted score: low-risk and high-risk. The proposed novel methodology uses convolutional neural networks for feature extraction and vision transformers for contextual aggregation, complemented by a logistic regression model that analyzes clinicopathologic data for classification into two risk categories. This method was trained and tested on 956 hematoxylin and eosin-stained whole-slide images of 950 ER+/HER2- breast cancer patients with corresponding clinicopathological features that had prior Oncotype DX testing. The model's performance was evaluated using an internal test set of 192 patients from Dartmouth Health and an external test set of 405 patients from the University of Chicago. The multi-model approach achieved an AUC of 0.91 (95% CI: 0.87-0.95) on the internal set and an AUC of 0.84 (95% CI: 0.78-0.89) on the external cohort for predicting low- and high-breast cancer recurrence risk categories based on the Oncotype DX recurrence score. With further validation, the proposed methodology could provide an alternative to assist clinicians in personalizing treatment for breast cancer patients and potentially improving their outcomes.

Expression of Ki-67 in Invasive Breast Carcinoma and Its Correlation With Different Clinicopathological Features

Introduction Worldwide, breast cancer is still the most common cancer that affects women. Breast cancer prognosis is based on a number of clinical and pathological indicators. Further features are needed to predict early metastasis and prognosis of patients with breast carcinoma, as the current pathological characteristics, such as tumor differentiation, vascular infiltration, and TNM (tumor, node, and metastasis) staging, cannot fully describe the early metastatic biological behavior in breast carcinoma. High Ki-67 expression is seen to be associated with worse survival in cancer patients. Hence, this study was conducted to study the utility of Ki-67 as a prognostic marker in invasive breast carcinoma and its association with known clinicopathological factors. Methodology The study was a hospital-based cross-sectional study carried out in the Histopathology Section of the Department of Pathology, Shri BM Patil Medical College Hospital and Research Centre, Bijapur Lingayat District Education (BLDE) (Deemed to be University), Vijayapura. The study was conducted between September 1, 2022, and April 30, 2024. The study population consisted of 55 cases of mastectomy specimens of primary breast cancer admitted to our hospital. Data regarding the patient's age, tumor size, histological type, histological grade, lymph node status, and vascular invasion were noted from medical records. Immunohistochemical staining for estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2/neu (HER2/neu) proto-oncogene, and Ki-67 markers was performed according to standard protocol. The relationship of Ki-67 with these clinicopathological parameters was analyzed statistically. Results In the current study, high-grade Ki-67 nuclear positivity was seen in 30 cases out of 55 cases, and low-grade Ki-67 was seen in the remaining 25 cases. The association of Ki-67 with tumor size and histological grade showed statistical significance with a p-value of less than 0.05 and 0.001, respectively. However, no statistical significance was seen with lymph node status, vascular invasion, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2/neu (HER2/neu) proto-oncogene status with p-values greater than 0.05. Conclusion The expression of Ki-67 was statistically significant with histological grading and tumor size in our study. Immunohistochemical determination of the Ki-67 proliferation index should be performed in routine cases of breast cancer to obtain clinically useful information on tumor aggressiveness as reflected in their proliferative rate. Hence, Ki-67 can be used as a predictive and prognostic marker in managing breast cancer patients.

One-to-one peer-coaching for patients with cancer - results of a pilot study

PURPOSE

Cancer is a life threatening disease with negative impact on quality of life and psychological well-being. In international studies, one-to-one peer support and counseling have been shown to improve the psychological well-being of cancer patients. In the study presented, we developed and evaluated an innovative program of peer-coaching. In this program at the University Hospital of Freiburg, cancer survivors were trained to support peers by sharing experience.

METHODS

In the project, N = 25 cancer survivors were trained to conduct supportive one-to-one conversations with acute patients or patients in aftercare. Based on a prospective observational study, patients were interviewed using questionnaires before and after the conversations. We assessed expectations and experiences with the peer-coaching as well as psychosocial parameters (PHQ9, GAD7, SSUK, NCCN-distress thermometer).

RESULTS

A total of 52 patients had at least one contact with a peer-coach. Most of the patients attended 1-3 sessions. In total, 85 contacts pairing peer-coaches with patients were conducted. Patients showed on average a high level of distress but a low rate of psychiatric comorbidity. The supportive conversations met the patients` needs. Sharing experiences and empowerment were the most relevant benefits for the patients. Both patients and trained peers showed high satisfaction levels with the program.

CONCLUSION

Our findings support the feasibility and utility of a peer-coaching program in which trained cancer survivors, acting as peer-coaches, support other patients during or after their oncological treatment. In a further study, the efficacy of peer-coaching should be investigated based on a randomized-controlled trial.

TRIAL REGISTRATION

The trial was registered in the German Clinical Trials Register (No. DRKS DRKS00017500) on 12.12.2019.

Combining Molecular and Traditional Prognostic Factors: A Holistic Approach to Breast Cancer Prognostication

Breast cancer is a heterogeneous disease with various morphologies and molecular features, and it is the second leading cause of cancer death in women in developed countries. According to the literature, we currently lack both prognostic biomarkers and therapeutic targets. The most important prognostic factors are disease stage and Nottingham grade. We conducted a retrospective analysis involving 273 patients with BC who underwent neoadjuvant therapy before proceeding to curative surgical treatment between 1 January 2014 and 31 December 2023. Pathological procedures were conducted at the Department of Pathology, Emergency County Hospital of Targu Mureș, Romania. A statistical analysis was performed. Regarding the relationship between Nottingham grade and Ki67, grade I was associated with a Ki67 of less than 14. The relationship between tumor grade and luminal was similar (p = 0.0001): Grade I was associated with luminal A. Regarding TNM stage, it was statistically significantly correlated with TILs (p = 0.01) and RCB (p = 0.0001). Stages III and IV were associated with a high RCB and poor prognosis. Regarding the prognostic value, Nottingham grade 3 and TNM stages III and IV were correlated with low overall survival and disease-free survival, with poor prognosis, and, among the molecular variables, RCB played the most important prognostic role.

Red Blood Cell Polyunsaturated Fatty Acids and Mortality Following Breast Cancer

BACKGROUND

Intake of polyunsaturated fatty acids (PUFA) may affect mortality following breast cancer; however, epidemiological studies have relied on the self-reported assessment of PUFA intake. Herein, we examined the associations between red blood cell (RBC) PUFAs and mortality.

METHODS

This nested case-control study included 1,104 women from the Women's Healthy Eating and Living study, a multistate randomized controlled trial. Cases (n = 290) comprised women who died from 1995 to 2006. Matched controls (n = 814) comprised women who were alive at the end of follow-up. PUFAs were measured in baseline RBC samples and included four ω-3 and seven ω-6 PUFAs. We examined each PUFA individually and principal components factor analysis (PCFA)-derived scores in association with all-cause mortality (ACM) and breast cancer-specific mortality (BCM) using conditional logistic regression to estimate ORs and 95% confidence intervals (CIs).

RESULTS

In fully adjusted models, ACM ORs were elevated among women with PUFAs above the median  (>median) versus at the median or below (≤median) for α-linolenic acid (ALA; OR = 1.63, 95% CI, 1.18-2.24) and linolenic acid (LA; OR = 1.56, 95% CI, 1.16-2.09). BCM ORs were elevated for ALA (OR = 1.83, 95% CI, 1.27-2.63), LA (OR = 1.70, 95% CI, 1.23-2.37), and γ-linolenic acid (GLA; OR = 1.50, 95% CI, 1.04-2.16). PCFA Factor 1 (arachidonic acid-adrenic acid-docosapentaenoic acid) scores above the median (vs. ≤median) were associated with lower odds of ACM (OR = 0.71, 95% CI, 0.52-0.97) and BCM (OR = 0.69, 95% CI, 0.49-0.97). PCFA Factor 4 (ALA/GLA) scores above the median (vs. ≤median) were associated with increased odds of BCM (OR = 1.47, 95% CI, 1.04-2.09).

CONCLUSIONS

RBC ALA, LA, and GLA may be prognostic indicators among breast cancer survivors.

IMPACT

These results are important for understanding the associations between a biomarker of PUFA intake and mortality among BC survivors.

Pushing the envelope in breast conserving surgery - is multiple-wire localization (3 or more wires) associated with increased risk of compromised margins and long-term recurrence?

INTRODUCTION

In the last two decades there has been a paradigm shift with breast conserving surgery (BCS) being applied to larger and more extensive breast malignancies. The aim of this study is to examine the success of BCS being performed in patients with extensive breast malignancies requiring at least 3 wires for localization, and to assess possible risk factors for failure.

MATERIALS AND METHODS

We performed a retrospective single center review of 232 patients who underwent BCS between 2010 and 2020 requiring at least 3 wires for localization, thus comprising the multi-wire group (MWG). The cohort included a control group of 232 single-wire BCS patients (SWG) chronologically matched with the MWG. Patients with either invasive malignancy or ductal carcinoma in situ (DCIS) were included in the study. Clinical, radiological, and pathological data was collected. Proportions of positive surgical margins, re-lumpectomies and conversion to mastectomy were calculated. Survival analysis for locoregional and distant recurrence was performed.

RESULTS

Women in the MWG were younger (mean age 57 vs. 63.1, P < 0.001), had larger tumor size (mean size 5.1 cm vs. 1.3 cm, p < 0.001), a higher prevalence of calcifications on mammograms (72 % vs. 17 %, P < 0.001), a higher proportion of positive lymph nodes (75 % vs. 45 %, P = 0.019), and an elevated incidence of a ductal carcinoma in situ (DCIS) component (72 % vs. 38 %, P < 0.001). Positive surgical margins were higher in the MWG (13 % vs 7 %, P = 0.03), which lead to higher proportions of re-lumpectomies or conversion to mastectomies (7 % vs 4 %, P = 0.17). On multivariate analysis of the entire cohort, patients with positive margins were more likely to have a DCIS component (77 % vs 53 %, P = 0.001), an infiltrating lobular carcinoma (ILC) component (15 % vs 9 %, P = 0.013), and positive ER hormonal status (94 % vs 85 %, p = 0.05). The number of wires was not an independent predictor of positive margins. On long-term analysis, the locoregional disease-free survival was similar between the SWG and MWG (P = 0.1). However, the MWG showed higher rates of distant metastasis (12 % vs 4 %, P = 0.006).

CONCLUSIONS

BCS requiring 3 or more wires is associated with a slightly higher proportion of positive margins. The increased risk of positive margins appears to be related to the type of tumor (DCIS component, ILC component and ER status) rather than to the number of wires. The number of wires does not significantly impact locoregional disease-free survival.

Association of body composition and survival in patients with locally advanced breast cancer: a historical cohort study

BACKGROUND

Altered body composition has been attributed to major health problems globally, particularly in patients with cancer. To date, there have not been sufficient indices for body compositions in predicting the survival of locally advanced breast cancer (LABC).

PURPOSE

To assess the association between body composition and overall survival (OS) as well as disease-free survival (DFS) in patients with LABC.

MATERIAL AND METHODS

A retrospective study was conducted of patients with LABC diagnosed between 2010 and 2018. Body composition parameters, including skeletal muscle and adiposity parameters, were measured using computed tomography at the L3 vertebra using in-house software developed by MATLAB and freeware Python 3.6.13. The association between body composition and OS and DFS were analyzed using a log-rank test and multivariate Cox-proportional hazard regression.

RESULTS

Of 199 patients, 72 (36%) died during the follow-up period (range = 3.8-150.7 months). Median survival was 101 months. Low visceral-to-subcutaneous ratio ≤0.3 (adjusted hazard ratio [aHR] = 2.57, 95% confidence interval [CI] = 1.51-4.37; aHR = 2.46, 95% CI = 1.33-4.56), and high composite fat (aHR = 3.26, 95% CI = 1.69-6.29; aHR = 2.19, 95% CI = 1.11-4.3) were associated with lower OS and DFS. Positive lymph nodes ≥3, progesterone receptor negative, and total radiation dose >5000 cGy significantly decreased both OS and DFS. A history of previous treatment before body composition assessment and surgery had a protective effect on OS and DFS. No association of sarcopenia, body mass index, and adiposity areas with survival outcomes was observed.

CONCLUSION

Low visceral-to-subcutaneous ratio and high composite fat were independent prognostic factors for OS and DFS in patients with LABC. However, other body composition parameters showed no effect on survival.

Correlation Between Quantitative Parameters Obtained by Dual Energy Spectral CT and Prognostic Histopathological Factors and Biomarkers in Breast Cancer

RATIONALE AND OBJECTIVES

To investigate the correlation between quantitative parameters obtained by dual energy spectral computed tomography (DESCT) and various histopathological factors and biomarkers associated with the prognosis of breast cancer.

MATERIALS AND METHODS

Quantitative parameters such as iodine content (IC), normalized IC (nIC), iodine enhancement (IE) and normalized IE (nIE) were measured on virtual monochromatic images and iodine mapping images obtained from DESCT in 116 female breast cancer patients. The relationship between these parameters and prognostic biomarkers such as estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) status and Ki67 levels, as well as the correlation with histological grade (HG), lymphovascular invasion (LVI), and metastatic axillary lymphadenopathy (LAP) were evaluated.

RESULTS

ER-negative tumors had significantly higher values of IC, nIC, IE, and nIE compared to ER-positive tumors. PR-negative tumors had significantly higher values of IE and nIEc compared to PR-positive tumors. HER2 overexpressed and Ki-67 high proliferation tumors showed significantly higher values of all quantitative parameters compared to HER2 negative and Ki-67 low proliferation tumors. All quantitative parameters were significantly higher in HG 3 tumors, tumors with detected LVI, and tumors with metastatic axillary LAP compared to low-grade tumors, LVI-negative tumors and tumors without metastatic axillary lymph nodes, respectively.

CONCLUSION

Quantitative parameters of IC and IE obtained from DESCT have shown potential for predicting prognosis in breast cancer patients. Higher values of these parameters have been found to correlate with poor prognostic biomarkers and histopathological features. These results suggest that quantitative DESCT imaging may offer an additional benefit in the noninvasive prediction of breast cancer prognosis.

Preoperative Neutrophil-to-Lymphocyte Ratio in Postmenopausal Breast Cancer Patients

INTRODUCTION

Neutrophil-to-lymphocyte ratio (NLR) has been recognized as a marker of systemic inflammation with a prognostic impact in patients with various cancers, including breast cancer. The aim of this study was to investigate the relationships between the preoperative NLR and breast cancer prognosis in the patients before and after menopausal age, and its relationship with other prognostic factors.

METHODS

A total of 1868 patients with clinical Stage I-III primary breast cancer were enrolled. The associations between clinicopathological factors and the preoperative NLR were analyzed, and relapse-free survival (RFS) and overall survival (OS) were estimated.

RESULTS

Statistical analyses stratified by the menopausal status revealed that a high NLR was significantly associated with worse RFS (P < 0.001) and OS (P = 0.001) in postmenopausal patients, but not in premenopausal patients. Although the postmenopausal patients with relapsed cancer tended to have higher NLR levels than those without relapse (P = 0.079), NLR levels of premenopausal patients with relapsed cancer were significantly lower than that of relapse-free patients (P = 0.024). In postmenopausal patients, a high NLR was only associated with worse RFS in patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer (P < 0.001), in those managed without adjuvant chemotherapy (P = 0.003); this association was not observed in patients who received adjuvant chemotherapy.

CONCLUSIONS

The preoperative NLR can be a useful prognostic marker, especially in postmenopausal breast cancer patients. The relationships between the NLR and breast cancer prognosis may be more evident when patients are assessed according to their menopausal status.

Exploration of the relationship between tumor-infiltrating lymphocyte score and histological grade in breast cancer

BACKGROUND

The histological grade is an important factor in the prognosis of invasive breast cancer and is vital to accurately identify the histological grade and reclassify of Grade2 status in breast cancer patients.

METHODS

In this study, data were collected from 556 invasive breast cancer patients, and then randomly divided into training cohort (n = 335) and validation cohort (n = 221). All patients were divided into actual low risk group (Grade1) and high risk group (Grade2/3) based on traditional histological grade, and tumor-infiltrating lymphocyte score (TILs-score) obtained from multiphoton images, and the TILs assessment method proposed by International Immuno-Oncology Biomarker Working Group (TILs-WG) were also used to differentiate between high risk group and low risk group of histological grade in patients with invasive breast cancer. Furthermore, TILs-score was used to reclassify Grade2 (G2) into G2 /Low risk and G2/High risk. The coefficients for each TILs in the training cohort were retrieved using ridge regression and TILs-score was created based on the coefficients of the three kinds of TILs.

RESULTS

Statistical analysis shows that TILs-score is significantly correlated with histological grade, and is an independent predictor of histological grade (odds ratio [OR], 2.548; 95%CI, 1.648-3.941; P < 0.0001), but TILs-WG is not an independent predictive factor for grade (P > 0.05 in the univariate analysis). Moreover, the risk of G2/High risk group is higher than that of G2/Low risk group, and the survival rate of patients with G2/Low risk is similar to that of Grade1, while the survival rate of patients with G2/High risk is even worse than that of patients with G3.

CONCLUSION

Our results suggest that TILs-score can be used to predict the histological grade of breast cancer and potentially to guide the therapeutic management of breast cancer patients.

Proteomic-based electrochemical non-invasive biosensor for early breast cancer diagnosis

Breast cancer is the second highest cause of cancer-related mortality in women worldwide and in the United States, accounting for around 571,000 deaths per year. Early detection of breast cancer increases treatment results and the possibility of a cure. While existing diagnostic modalities such as mammography, ultrasound, and biopsy exist, some are prohibitively expensive, uncomfortable, time-consuming, and have limited sensitivity, necessitating the development of a cost-effective, rapid, and highly sensitive approach such as an electrochemical biosensor. Our research focuses on detecting breast cancer patients using the ECM1 biomarker, which has higher expression in synthetic urine. Our study has two primary objectives: (i) Diverse ECM1 protein concentrations are measured using electrochemical impedance spectroscopy and ELISA. Establishing a standard curve for the electrochemical biosensor by calibrating ECM-1 protein levels using electrochemical impedance spectroscopy. (ii) Validation of the effectiveness of the electrochemical biosensor. This aim entails testing the unknown concentration of ECM1 in the synthetic urine to ensure the efficiency of the biosensor to detect the biomarker in the early stages. The results show that the synthetic urine solution's ECM-1 detection range ranges from 1 pg/ml to 500 ng/ml. This shows that by detecting changes in ECM-1 protein levels in patient urine, the electrochemical biosensor can consistently diagnose breast cancer in its early stages or during increasing recurrence. Our findings highlight the electrochemical biosensor's efficacy in detecting early-stage breast cancer biomarkers (ECM-1) in patient urine. Further studies will be conducted with patient samples and develop handheld hardware for patient usage.

A D-Shaped Polymer Optical Fiber Surface Plasmon Resonance Biosensor for Breast Cancer Detection Applications

Fiber-optic biosensors have garnered significant attention and witnessed rapid development in recent years owing to their remarkable attributes such as high sensitivity, immunity to electromagnetic interference, and real-time monitoring. They have emerged as a potential tool in the realm of biomarker detection for low-concentration and small molecules. In this paper, a portable and cost-effective optical fiber biosensor based on surface plasmon resonance for the early detection of breast cancer is demonstrated. By utilizing the aptamer human epidermal growth factor receptor 2 (HER2) as a specific biomarker for breast cancer, the presence of the HER2 protein can be detected through an antigen-antibody binding technique. The detection method was accomplished by modifying a layer of HER2 aptamer on the flat surface of a gold-coated D-shaped polymer optical fiber (core/cladding diameter 120/490 μm), of which the residual thickness after side-polishing was about 245 μm, the thickness of the coated gold layer was 50 nm, and the initial wavelength in pure water was around 1200 nm. For low-concentration detection of the HER2 protein, the device exhibited a wavelength shift of ~1.37 nm with a concentration of 1 μg/mL (e.g., 5.5 nM), which corresponded to a limit of detection of ~5.28 nM. Notably, the response time of the biosensor was measured to be as fast as 5 s. The proposed biosensor exhibits the potential for early detection of HER2 protein in initial cancer serum and offers a pathway to early prevention of breast cancer.

Long-term locoregional recurrence in patients treated for breast cancer

BACKGROUND/PURPOSE

Locoregional control in breast cancer is a fundamental part of treatment and determinant for survival outcomes. It has been reported that most locoregional recurrence (LRR) events occur in the first 5 years after treatment. However, LRR continue to occur after this timeline, with unclear risk factors and unknown survival impact.

METHODS

Retrospective singe-centered cohort of patients treated for primary breast cancer, between January 2002 and December 2004. Primary outcome was LRR; secondary outcomes were overall survival (OS), disease-free survival (DFS), and predictive factors for LRR.

RESULTS

This analysis included 1001 patients, of which 959 (95%) had invasive carcinoma. A mastectomy was performed in 501 (50%) and 500 (50%) had breast conservative surgery (BCS). Median follow-up time was 197 [Inter-quartile range (IQR) 96-211] months. Global LRR rate was 7.6%, with median time to recurrence of 45 [IQR 21-91] months. There was no difference in LRR rate after mastectomy vs BCS, adjusted to tumor stage (p > 0.05). The 10-year OS and DFS rates were 68.4 and 77.8%, respectively. Factors associated with LRR were metastatic axillary lymph nodes and high histologic grade (p < 0.05). Estrogen-negative (ER) tumors had higher LRR rates than ER-positive tumors in the first 5 years (p < 0.05); but no difference was observed with longer follow-up (p > 0.05). LRR was associated with OS (p < 0.05).

DISCUSSION AND CONCLUSIONS

Global LRR in this cohort was 7.6% (with over 16 years of follow-up). LRR associates with decreased OS. Time to LRR varies significantly with tumor biology, supporting differentiation of follow-up regimens.

Construction and Validation of a Novel Nomogram for Predicting the Risk of Metastasis in a Luminal B Type Invasive Ductal Carcinoma Population

BACKGROUND

Postoperative distant metastasis is the main cause of death in breast cancer patients. We aimed to construct a nomogram to predict the risk of metastasis of luminal B type invasive ductal carcinoma.

METHODS

We applied the data of 364 luminal B type breast cancer patients between 2008 and 2013. Patients were categorized into modeling group and validation group randomly (1:1). The breast cancer metastasis nomogram was developed from the logistic regression model using clinicopathological variables. The area under the receiver-operating characteristic curve (AUC) was calculated in modeling group and validation group to evaluate the predictive accuracy of the nomogram.

RESULTS

The multivariate logistic regression analysis showed that tumor size, No. of the positive level 1 axillary lymph nodes, human epidermal growth factor receptor 2 (HER2) status and Ki67 index were the independent predictors of the breast cancer metastasis. The AUC values of the modeling group and the validation group were 0.855 and 0.818, respectively. The nomogram had a well-fitted calibration curve. The positive and negative predictive values were 49.3% and 92.7% in the modeling group, and 47.9% and 91.0% in the validation group. Patients who had a score of 60 or more were thought to have a high risk of breast cancer metastasis.

CONCLUSIONS

The nomogram has a great predictive accuracy of predicting the risk of breast cancer metastasis. If patients had a score of 60 or more, necessary measures, like more standard treatment methods and higher treatment adherence of patients, are needed to take to lower the risk of metastasis and improve the prognosis.

An optimization framework to guide the choice of thresholds for risk-based cancer screening

It is uncommon for risk groups defined by statistical or artificial intelligence (AI) models to be chosen by jointly considering model performance and potential interventions available. We develop a framework to rapidly guide choice of risk groups in this manner, and apply it to guide breast cancer screening intervals using an AI model. Linear programming is used to define risk groups that minimize expected advanced cancer incidence subject to resource constraints. In the application risk stratification performance is estimated from a case-control study (2044 cases, 1:1 matching), and other parameters are taken from screening trials and the screening programme in England. Under the model, re-screening in 1 year for the highest 4% AI model risk, in 3 years for the middle 64%, and in 4 years for 32% of the population at lowest risk, was expected to reduce the number of advanced cancers diagnosed by approximately 18 advanced cancers per 1000 diagnosed with triennial screening, for the same average number of screens in the population as triennial screening for all. Sensitivity analyses found the choice of thresholds was robust to model parameters, but the estimated reduction in advanced cancers was not precise and requires further evaluation. Our framework helps define thresholds with the greatest chance of success for reducing the population health burden of cancer when used in risk-adapted screening, which should be further evaluated such as in health-economic modelling based on computer simulation models, and real-world evaluations.

Fasting-mimicking diet: a metabolic approach for the treatment of breast cancer

PURPOSE OF REVIEW

Metabolic reprogramming is a new and potentially targetable hallmark of cancer. In recent years, fasting and fasting-mimicking diets (FMDs) have been tested as anticancer strategies both in preclinical experiments and in clinical trials. In this review, we aim at summarizing the available evidence about the antitumour activity of these approaches in preclinical breast cancer models, as well as results from clinical trials investigating fasting/FMD in breast cancer patients.

RECENT FINDINGS

Preclinical evidence demonstrated that nutrient deprivation boosts the antitumor activity of chemotherapy, immunotherapy or targeted therapies in triple-negative breast cancer (TNBC) and HR+/HER2 models through both cell-autonomous antitumour effects in cancer cells and favourable modifications in intratumor immune cells. Several clinical experiences demonstrated that fasting/FMD is feasible and well tolerated in combination with standard treatments in BC patients, and that it could reduce chemotherapy-related toxicities. Finally, despite the absence of randomized trials demonstrating the antitumor activity of fasting/FMD in breast cancer patients, preliminary clinical reports suggest that this experimental nutritional strategy may enhance chemotherapy activity. Randomized clinical trials are ongoing to validate these results at a larger scale.

SUMMARY

Fasting/FMD is a promising therapeutic approach in patients with breast cancer; ongoing and future trials will confirm their role in improving breast cancer care.

Associations of accumulated persistent organic pollutants in breast adipose tissue with the evolution of breast cancer after surgery

Chronic exposure to persistent organic pollutants (POPs) is suspected to contribute to the onset of breast cancer, but the impact on the evolution of patients after diagnosis is unclear. We aimed to analyze the contribution of long-term exposure to five POPs to overall mortality, cancer recurrence, metastasis, and development of second primary tumors over a global follow-up of 10 years after surgery in breast cancer patients in a cohort study. Between 2012 and 2014, a total of 112 newly diagnosed breast cancer patients were recruited from a public hospital in Granada, Southern Spain. Historical exposure to POPs was estimated by analyzing their concentrations in breast adipose tissue samples. Sociodemographic data were collected through face-to-face interviews, while data on evolution tumor were retrieved from clinical records. Statistical analyses were performed using Cox regression (overall survival, breast cancer recurrence or metastasis) and binary logistic regression models (joint outcome variable). We also tested for statistical interactions of POPs with age, residence, and prognostic markers. The third vs first tertile of hexachlorobenzene concentrations was associated with a lower risk of all-cause mortality (Hazard Ratio, HR = 0.26; 95 % Confidence Interval, CI = 0.07-0.92) and of the appearance of any of the four events (Odds Ratio = 0.37; 95 % CI = 0.14-1.03). Polychlorinated biphenyl 138 concentrations were significantly and inversely associated with risk of metastasis (HR = 0.65; 95 % CI = 0.44-0.97) and tumor recurrence (HR = 0.69; 95 % CI = 0.49-0.98). Additionally, p,p'-dichlorodiphenyldichloroethylene showed inverse associations with risk of metastasis in women with ER-positive tumors (HR = 0.49; 95 % CI = 0.25-0.93) and in those with a tumor size <2.0 cm (HR = 0.39; 95 % CI = 0.18-0.87). The observed paradoxical inverse associations of POP exposure with breast cancer evolution might be related to either a better prognosis of hormone-dependent tumors, which have an approachable pharmacological target, or an effect of sequestration of circulating POPs by adipose tissue.

Biomarkers Predictive of Distant Disease-free Survival Derived from Diffusion-weighted Imaging of Breast Cancer

PURPOSE

To investigate whether intravoxel incoherent motion (IVIM) and/or non-Gaussian diffusion parameters are associated with distant disease-free survival (DDFS) in patients with invasive breast cancer.

METHODS

From May 2013 to March 2015, 101 patients (mean age 60.0, range 28-88) with invasive breast cancer were evaluated prospectively. IVIM parameters (flowing blood volume fraction [fIVIM] and pseudodiffusion coefficient [D*]) and non-Gaussian diffusion parameters (theoretical apparent diffusion coefficient [ADC] at a b value of 0 s/mm2 [ADC0] and kurtosis [K]) were estimated using a diffusion-weighted imaging series of 16 b values up to 2500 s/mm2. Shifted ADC values (sADC200-1500) and standard ADC values (ADC0-800) were also calculated. The Kaplan-Meier method was used to generate survival analyses for DDFS, which were compared using the log-rank test. Univariable Cox proportional hazards models were used to assess any associations between each parameter and distant metastasis-free survival.

RESULTS

The median observation period was 80 months (range, 35-92 months). Among the 101 patients, 12 (11.9%) developed distant metastasis, with a median time to metastasis of 79 months (range, 10-92 months). Kaplan-Meier analysis showed that DDFS was significantly shorter in patients with K > 0.98 than in those with K ≤ 0.98 (P = 0.04). Cox regression analysis showed a marginal statistical association between K and distant metastasis-free survival (P = 0.05).

CONCLUSION

Non-Gaussian diffusion may be associated with prognosis in invasive breast cancer. A higher K may be a marker to help identify patients at an elevated risk of distant metastasis, which could guide subsequent treatment.

Breast cancer survival and the health system in Brazil: an analysis of public and private healthcare

Background

The incidence of breast cancer is increasing globally; however, survival outcomes vary and are lower in developing countries.

Methods

We analyzed the 5- and 10-year survival rates for breast cancer according to the type of healthcare insurance (public vs. private) in a referral center for cancer care in the Brazilian southeast region. This hospital-based cohort study included 517 women diagnosed with invasive breast cancer between 2003 and 2005. The Kaplan-Meier method was used to estimate the probability of survival, and the Cox proportional hazards regression model was used to assess prognostic factors.

Results

The 5- and 10-year breast cancer survival rates were as follows: private healthcare service survival rate of 80.6% (95% CI 75.0-85.0) and 71.5% (95% CI 65.4-77.1), respectively, and public healthcare service survival rate of 68.5% (95% CI 62.5-73.8) and 58.5% (95% CI 52.1-64.4), respectively. The main factors associated with the worst prognosis were lymph node involvement in both healthcare services and tumor size >2 cm only in public health services. The use of hormone therapy (private) and radiotherapy (public) was associated with the best survival rates.

Conclusions

The survival discrepancies found between health services can be explained mainly by the difference in the stage of the disease at the time of diagnosis, indicating inequalities in access to the early detection of breast cancer.

Carbonic anhydrase IX-related tumoral hypoxia predicts worse prognosis in breast cancer: A systematic review and meta-analysis

Background

Tumoral hypoxia is associated with aggressiveness in many cancers including breast cancer. However, measuring hypoxia is complicated. Carbonic anhydrase IX (CAIX) is a reliable endogenous marker of hypoxia under the control of the master regulator hypoxia-inducible factor-1α (HIF-1α). The expression of CAIX is associated with poor prognosis in many solid malignancies; however, its role in breast cancer remains controversial.

Methods

The present study performed a meta-analysis to evaluate the correlation between CAIX expression and disease-free survival (DFS) and overall survival (OS) in breast cancer.

Results

A total of 2,120 publications from EMBASE, PubMed, Cochrane, and Scopus were screened. Of these 2,120 publications, 272 full texts were reviewed, and 27 articles were included in the meta-analysis. High CAIX was significantly associated with poor DFS (HR = 1.70, 95% CI = 1.39–2.07, p &lt; 0.00001) and OS (HR = 2.02, 95% CI 1.40–2.91, p = 0.0002) in patients with breast cancer. When stratified by subtype, the high CAIX group was clearly associated with shorter DFS (HR = 2.09, 95% CI =1.11–3.92, p = 0.02) and OS (HR = 2.50, 95% CI =1.53–4.07, p = 0.0002) in TNBC and shorter DFS in ER+ breast cancer (HR = 1.81 95% CI =1.38–2.36, p &lt; 0.0001).

Conclusion

High CAIX expression is a negative prognostic marker of breast cancer regardless of the subtypes.

Analyzing breast cancer invasive disease event classification through explainable artificial intelligence

Introduction

Recently, accurate machine learning and deep learning approaches have been dedicated to the investigation of breast cancer invasive disease events (IDEs), such as recurrence, contralateral and second cancers. However, such approaches are poorly interpretable.

Methods

Thus, we designed an Explainable Artificial Intelligence (XAI) framework to investigate IDEs within a cohort of 486 breast cancer patients enrolled at IRCCS Istituto Tumori "Giovanni Paolo II" in Bari, Italy. Using Shapley values, we determined the IDE driving features according to two periods, often adopted in clinical practice, of 5 and 10 years from the first tumor diagnosis.

Results

Age, tumor diameter, surgery type, and multiplicity are predominant within the 5-year frame, while therapy-related features, including hormone, chemotherapy schemes and lymphovascular invasion, dominate the 10-year IDE prediction. Estrogen Receptor (ER), proliferation marker Ki67 and metastatic lymph nodes affect both frames.

Discussion

Thus, our framework aims at shortening the distance between AI and clinical practice.

Stage distinctive communication networks of the online breast cancer community

In this study, we reveal the distinctive communication network structures and contents of online breast cancer community posts in accordance with different cancer stages. Using data collected from community.breastcancer.org, a major online breast cancer community (28,139 original posts and 663,748 replies), we traced the communication network structures and contents of replies associated with its severity. By combining network and quantitative content analyses, we deciphered the functions and utilities of health-related online communication. We found an inverse relationship between offline epidemiological prevalence and online communication activation. Despite the relatively small percentage of breast cancer patients, it was found that the more severe the condition of breast cancer, the more active online communication was. We further found that as pathological severity advances, communication networks move from informational exchange to emotional support. The capture of online social networks based on the cancer stage can help unpack the distinctive communication patterns found across different cancer severities. Our results provide insights into a possible online communication intervention design tailored to symptom severity.

Microwave ablation without subsequent lumpectomy versus breast-conserving surgery for early breast cancer: a propensity score matching study

PURPOSE

To compare the efficacy of ultrasound-guided percutaneous microwave ablation (MWA) without subsequent lumpectomy and breast-conserving surgery (BCS) in patients with early breast cancer (BC).

MATERIALS AND METHODS

This retrospective cohort study enrolled 106 patients with early BC (T_0/1/2 N_0/1 M₀) treated by MWA (n = 21) or BCS (n = 85) from October 2014 to December 2020. Propensity score matching (PSM) was performed to balance the baseline characteristics between MWA and BCS groups. The tumor progression, overall survival (OS), disease-specific survival (DSS), complications, and cosmetic results were compared.

RESULTS

After PSM, there were 21 patients with balanced baseline characteristics in each group. After a median follow-up of 43 months (range, 15-89 months), there was no significant difference in tumor progression (10% vs 2%, p = 0.18), OS (96% vs 99%, p = 0.36), DSS (100% vs 99%, p > 0.99), and complications (0% vs 19%, p = 0.58). The operation time of MWA was shorter (60 min vs 101 min, p < 0.001) than that of BCS. For the management of metastatic lymph nodes, five (5/21, 24%) patients with six metastatic nodes underwent ablation in the MWA group and three patients (3/21, 14%) with six metastatic nodes underwent axillary lymph node dissection in the BCS group. All the patients in the MWA group reported excellent cosmetic results, but 29% of BCS patients expressed dissatisfaction with breast asymmetry (10%) and scar formation (19%) (p < 0.001).

CONCLUSION

This pilot study indicated that in selected early BC patients, microwave ablation without subsequent lumpectomy had comparable tumor control effect with breast-conserving surgery and better cosmetic results at an intermediate follow-up.HighlightsMWA without subsequent lumpectomy has a comparable interim survival effect and better cosmetic results as BCS in the treatment of selected early breast cancer.MWA has the potential to be a viable and promising therapeutic option for breast cancer patients reluctant or intolerant to surgery with the advantage of minimal invasion.

Risk of Breast Cancer Progression after Treatment in the Western Region of Saudi Arabia

Background:

The risk of breast cancer progression is one of the most difficult factors to predict as it is studied in different populations, patient groups, or time frames, resulting in conflicting estimates of incidence rates reported in the literature. The purpose of this study is to identify predictive factors for breast cancer recurrences in a sample of the Middle Eastern population.

Methodology:

A cohort retrospective study included all eligible breast cancer patients at the National Guard Health Affairs (NGHA) Hospital in Jeddah, Western region, from 2015 to 2021. Our primary outcome was the progression status of the patients; we adjusted for demographic, clinical, and molecule characteristics of the population. From 2015 to 2021, there were 319 patients diagnosed with breast cancer. Multiple logistic regression analysis was used to estimate predictors of breast cancer progression.

Results:

One of five breast cancer patients had breast cancer progression (20.83%), while 66.15% of the progression patients were between the ages of 41–65. In multivariate analysis, age, progesterone receptor (PR), family history, and tumor size were significant predictors of breast cancer progression. The age group of 20–40 years was a protective predictor of breast cancer progression, patients in the young age group were less likely to be diagnosed with progression (OR = 0.35; CI = 0.15, 0.81). While negative PRs and tumor size greater than 2 cm were significant predictor factors of breast cancer progression (OR = 2.07; CI = 1.09, 3.91, OR = 2.02; CI = 1.9, 3.78).

Conclusion:

Although the effect of young age as a protective factor for the progression of breast cancer remains controversial, our study revealed that patients between 41 and 60 years of age had a higher rate of progression. Future larger prospective studies are needed to delineate the role of age and PR hormone receptors in determining the best treatment options for women with breast cancer in the Saudi population.

Preoperative predictive factors affecting sentinel lymph node positivity in breast cancer and comparison of their effectiveness with existing nomograms

This study aimed to establish a strong regression model by revealing the preoperative predictive factors for sentinel lymph node (SLN) positivity in patients with early stage breast cancer (ESBC). In total, 445 patients who underwent SLN dissection for ESBC were included. All data that may be potential predictors of SLN positivity were retrospectively analyzed. Tumor size >2 cm, human epidermal growth factor receptor 2 (HER2) + status, lymphovascular invasion (LVI), palpable tumor, microcalcifications, multifocality or multicentricity, and axillary ultrasonographic findings were defined as independent predictors of SLN involvement. The area under the receiver operating characteristic (ROC) curve (AUC) values were 0.797, 0.808, and 0.870 for the Memorial Sloan-Kettering Cancer Center (MSKCC) nomogram, MD Anderson Cancer Center (MDACC) nomogram, and our regression model, respectively (P < .001). The recent model for predicting SLN status in ESBC was found to be stronger than existing nomograms. Parameters not included in current nomograms, such as palpable tumors, microcalcifications, and axillary ultrasonographic findings, are likely to make this model more meaningful.

The Benefits of Exercise in Breast Cancer

Breast cancer is the most prevalent cancer among women, accounting for nearly 30% of all cancers, while in men, it represents only 1% of cases. Breast cancer is the main cause of death for cancer, and its incidence and mortality vary according to patients' ethnicity, geographic region, and socioeconomic status. Due to the low prevalence of breast cancer among men and the scarcity of studies in the literature, exercises have been prescribed based on extrapolations from studies on female patients. Scientific evidence has suggested beneficial effects of physical exercises on breast cancer prevention, treatment, and post-treatment. In addition to combatting sedentary behavior, it is essential to maintain a healthy body weight, limit alcohol consumption, and follow a balanced diet, rich in fruit, vegetables, grains and fibers, and limited in red meat. The effects of exercises are not restricted to breast cancer, but extend to controlling modifiable risk factors, and reducing the incidence of cardiovascular diseases, and all-cause and cardiovascular mortality.

Estrone, the major postmenopausal estrogen, binds ERa to induce SNAI2, epithelial-to-mesenchymal transition, and ER+ breast cancer metastasis

Recent work showed that the dominant post-menopausal estrogen, estrone, cooperates with nuclear factor κB (NF-κB) to stimulate inflammation, while pre-menopausal 17β-estradiol opposes NF-κB. Here, we show that post-menopausal estrone, but not 17β-estradiol, activates epithelial-to-mesenchymal transition (EMT) genes to stimulate breast cancer metastasis. HSD17B14, which converts 17β-estradiol to estrone, is higher in cancer than normal breast tissue and in metastatic than primary cancers and associates with earlier metastasis. Treatment with estrone, but not 17β-estradiol, and HSD17B14 overexpression both stimulate an EMT, matrigel invasion, and lung, bone, and liver metastasis in estrogen-receptor-positive (ER+) breast cancer models, while HSD17B14 knockdown reverses the EMT. Estrone:ERα recruits CBP/p300 to the SNAI2 promoter to induce SNAI2 and stimulate an EMT, while 17β-estradiol:ERα recruits co-repressors HDAC1 and NCOR1 to this site. Present work reveals novel differences in gene regulation by these estrogens and the importance of estrone to ER+ breast cancer progression. Upon loss of 17β-estradiol at menopause, estrone-liganded ERα would promote ER+ breast cancer invasion and metastasis.

Association between genome-wide epigenetic and genetic alterations in breast cancer tissue and response to HER2-targeted therapies in HER2-positive breast cancer patients: new findings and a systematic review

Recent evidence suggests that genetic and epigenetic mechanisms might be associated with acquired resistance to cancer therapies. The aim of this study was to assess the association of genome-wide genetic and epigenetic alterations with the response to anti-HER2 agents in HER2-positive breast cancer patients. PubMed was screened for articles published until March 2021 on observational studies investigating the association of genome-wide genetic and epigenetic alterations, measured in breast cancer tissues or blood, with the response to targeted treatment in HER2-positive breast cancer patients. Sixteen studies were included in the review along with ours, in which we compared the genome-wide DNA methylation pattern in breast tumor tissues of patients who acquired resistance to treatment (case group, n = 6) to that of patients who did not develop resistance (control group, n = 6). Among genes identified as differentially methylated between the breast cancer tissue of cases and controls, one of them, PRKACA, was also reported as differentially expressed in two studies included in the review. Although included studies were heterogeneous in terms of methodology and study population, our review suggests that genes of the PI3K pathway may play an important role in developing resistance to anti-HER2 agents in breast cancer patients. Genome-wide genetic and epigenetic alterations measured in breast cancer tissue or blood might be promising markers of resistance to anti-HER2 agents in HER2-positive breast cancer patients. Further studies are needed to confirm these data.

Long-Term Oncologic Outcome of Breast Cancer in Southern Iran: A Retrospective Cohort Study

INTRODUCTION

Breast cancer remains the most frequent and lethal cancer among women worldwide. This study aimed to investigate the characteristics, prognostic factors and outcome of breast cancer patient treated and followed-up in Shiraz, southern Iran from 2000 to 2005.

METHODS

In this retrospective study, 1,024 patients with breast cancer who were treated in Namazi hospital of Shiraz University of Medical Sciences between 2000 and 2005 were included. Survival analysis was performed to determine potential factors influencing disease free-and overall survival in these patients.

RESULTS

Median age of the patients at diagnosis was 47 (range 19-83) years. Median follow-up for surviving patients was 68 months. The majority of patients presented at stage II (42%) and stage III (41%). Additionally, most (61%) patients had positive axillary node. The 5-, 10- and 15-year overall survival rates were 83.8%, 61.5% and 56.6% respectively. On multivariate analysis for overall survival, histologic type, Tumor stage, node stage, disease stage, M stage, hormone receptor status, adjuvant radiotherapy, and chemotherapy regimen remained independent prognostic factor for overall survival.

CONCLUSION

in this study, the poor long-term oncologic outcome of the patients with breast cancer may be due to the higher rate of locally advanced disease; as well as the lack of modern systemic therapies in the study period.

Nomogram for predicting overall survival in patients with invasive micropapillary carcinoma after breast-conserving surgery: A population-based analysis

Background

Due to the loss of prediction of overall survival (OS) for patients with invasive micropapillary carcinoma (IMPC) after breast-conserving surgery (BCS), this study aimed to construct a nomogram for predicting OS in IMPC patients after BCS.

Methods

In total, 481 eligible cases staged 0-III IMPC from 2000 to 2016 were retrieved from the SEER database. A nomogram was built based on the variables selected by LASSO regression to predict the 3-year and 5-year probabilities of OS.

Results

A total of 336 patients were randomly assigned to the training cohort and 145 cases in the validation cohort. The LASSO regression revealed that six variables (age at diagnosis, AJCC stage, marital status, ER status, PR status, and chemotherapy) were predictive variables of OS, and then a nomogram model and an easy-to-use online tool were constructed. The C-indices 0.771 in the training cohort and 0.715 in the validation cohort suggested the robustness of the model. The AUC values for 3-year and 5-year OS in the training cohort were 0.782, 0.790, and 0.674, and 0.682 in the validation cohort, respectively. Based on the cutoff values of 147.23 and 222.44 scores calculated by X-tile analysis, participants in the low-risk group (≤147.23 scores) had a more favorable OS in comparison with those in the medium (>147.23, but <222.44 scores)- and high-risk groups (≥222.44 scores).

Conclusions

By risk stratification, this model is expected to provide a precise and personalized prediction of the cumulative risk and guide treatment decision-making in improving OS strategies for IMPC patients.

Predicting the risk of axillary lymph node metastasis in early breast cancer patients based on ultrasonographic-clinicopathologic features and the use of nomograms: a prospective single-center observational study

OBJECTIVES

The purpose of this study was to establish two preoperative nomograms to evaluate the risk for axillary lymph node (ALN) metastasis in early breast cancer patients based on ultrasonographic-clinicopathologic features.

METHODS

We prospectively evaluated 593 consecutive female participants who were diagnosed with cT_1-3N_0-1M₀ breast cancer between March 2018 and May 2019 at Sun Yat-Sen Memorial Hospital. The participants were randomly classified into training and validation sets in a 4:1 ratio for the development and validation of the nomograms, respectively. Multivariate logistic regression analysis was performed to identify independent predictors of ALN status. We developed Nomogram A and Nomogram B to predict ALN metastasis (presence vs. absence) and the number of metastatic ALNs (≤ 2 vs. > 2), respectively.

RESULTS

A total of 528 participants were evaluated in the final analyses. Multivariable analysis revealed that the number of suspicious lymph nodes, long axis, short-to-long axis ratio, cortical thickness, tumor location, and histological grade were independent predictors of ALN status. The AUCs of nomogram A in the training and validation groups were 0.83 and 0.78, respectively. The AUCs of nomogram B in the training and validation groups were 0.87 and 0.87, respectively. Both nomograms were well-calibrated.

CONCLUSION

We developed two preoperative nomograms that can be used to predict ALN metastasis (presence vs. absence) and the number of metastatic ALNs (≤ 2 vs. > 2) in early breast cancer patients. Both nomograms are useful tools that will help clinicians predict the risk of ALN metastasis and facilitate therapy decision-making about axillary surgery.

KEY POINTS

• We developed two preoperative nomograms to predict axillary lymph node status based on ultrasonographic-clinicopathologic features. • Nomogram A was used to predict axillary lymph node metastasis (presence vs. absence). The AUCs in the training and validation groups were 0.83 and 0.78, respectively. Nomogram B was used to estimate the number of metastatic lymph nodes ( ≤ 2 vs. > 2). The AUCs in the training and validation group were 0.87 and 0.87, respectively. • Our nomograms may help clinicians weigh the risks and benefits of axillary surgery more appropriately.

Association between age and the presence and mortality of breast cancer synchronous brain metastases in the United States: A neglected SEER analysis

BACKGROUND

The extent of the relationship between age and the presence of breast cancer synchronous brain metastases (BCSBMs) and mortality has not yet been well-identified or sufficiently quantified. We aimed to examine the association of age with the presence of BCSBMs and all-cause and cancer-specific mortality outcomes using the SEER database.

METHODS

Age-associated risk of the presence and survival of BCSBMs were evaluated on a continuous scale (restricted cubic spline, RCS) with logistic or Cox regression models. The main endpoints were the presence of BCSBMs and all-cause mortality or cancer-specific mortality. Cox proportional hazards regression and competing risk models were used in survival analysis.

RESULTS

Among 374,132 adult breast cancer patients, 1,441 (0.38%) had BMs. The presence of BCSBMs displayed a U-shaped relationship with age, with the highest point of the curve occurring at the age of 62. In both the younger (age ≤ 61) and older (age ≥ 62) groups, the observed curve showed a nearly linear relationship between age and the presence of BCSBMs. The relationship between age and all-cause mortality (ASM) and cancer-specific mortality (CSM) was linear. Older age at diagnosis was associated with a higher risk of ASM (HR 1.019, 95% CI: 1.013-1.024, p < 0.001) and CSM (HR 1.016, 95% CI: 1.010-1.023, p < 0.001) in multivariable Cox models. Age (sHR 1.007, 95% CI 1-1.013, p = 0.049) was substantially related to a significantly increased risk of CSM in competing risk models.

CONCLUSION

Age had a non-linear U-shaped relationship with the presence of BCSBMs and a linear relationship with BCSBMs mortality.

Clinico-pathologic factors associated with the occurrence of early and late metastatic spread in a cohort of breast cancer patients

BACKGROUND AND OBJECTIVE

Distant metastatic spread in breast cancer patients is a complex phenomenon involving several prognostic factors. We focused our analysis on early metastatic breast cancer (EMBC) (occurring during the first 36 months) versus late metastatic breast cancer (LMBC) (occurring beyond 3 years) in order to ascertain their possible differential predictive factors.

METHODS

diagnostic, surgical, and follow-up data were assessed for consecutive patients with breast cancer undergoing surgery between 1997 and 2019. We analysed the predictive factors for distant metastasis using both univariate and multivariate analysis.

RESULTS

The median follow-up for this cohort of 2708 patients was 89 months. The median metastasis-free interval (FMI) for metastasis patients was 38 months (17 months for EMBC group and 76 months for LMBC group). Distant metastases developed in 12.9% (350/2708); 48% (168/350) of them as EMBC and 52% (182/350) as LMBC. Loco-regional recurrence and nodal extracapsular extension were the only common predictors for both.

CONCLUSIONS

EMBC and LMBC appeared as two separate conditions, with a different outcome. In the EMBC group, tumour proliferation related factors were significant (histological grade, tumour size, body mass index), whereas for LMBC, other slow-acting factors seemed to be involved (screening program, tumour burden, bilateral tumour).