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Introduction: Advancements in monoclonal antibodies, tyrosine kinase inhibitors, and antibody drug conjugates (ADCs) have notably enhanced outcomes for metastatic HER2-positive breast cancer patients. Despite the expanding treatment options and clinical complexities, determining the optimal sequence of HER2-targeted therapies remains partly uncertain, influenced by various factors. Methods: To refine HER2-positive metastatic breast cancer management, particularly regarding tucatinib's position, a Steering Committee of leading oncologists in breast cancer care devised a panel of statements via a Delphi approach, focusing on five key topics: general clinical management, therapeutic approaches for patients with HER2-positive breast cancer and brain metastases, treatment sequence, and tucatinib's safety and efficacy. Results: A total of 29 statements were deliberated, with strong consensus achieved for most. However, no consensus emerged regarding the management of brain progression alongside stable extracranial disease: 48 % advocated for switching to tucatinib, while 53 % favored a stereotactic brain radiotherapy (SBRT) approach if feasible. Conclusion: The unanimous consensus attained in this Delphi panel, particularly regarding tucatinib's efficacy and safety, underscores oncologists' recognition of its clinical significance based on existing trial data. These findings align closely with current literature, shedding light on areas necessitating further investigation, not thoroughly explored in prior studies. Moreover, the results underscore the scarcity of data on managing brain progression alongside stable extracranial disease, emphasizing the imperative for dedicated research to address these gaps and yield definitive insights.

Advancements in monoclonal antibodies, tyrosine kinase inhibitors, and antibody drug conjugates (ADCs) have notably enhanced outcomes for metastatic HER2-positive breast cancer patients. Despite the expanding treatment options and clinical complexities, determining the optimal sequence of HER2-targeted therapies remains partly uncertain, influenced by various factors. To refine HER2-positive metastatic breast cancer management, particularly regarding tucatinib's position, a Steering Committee of leading oncologists in breast cancer care devised a panel of statements via a Delphi approach, focusing on five key topics: general clinical management, therapeutic approaches for patients with HER2-positive breast cancer and brain metastases, treatment sequence, and tucatinib's safety and efficacy. A total of 29 statements were deliberated, with strong consensus achieved for most. However, no consensus emerged regarding the management of brain progression alongside stable extracranial disease: 48 % advocated for switching to tucatinib, while 53 % favored a stereotactic brain radiotherapy (SBRT) approach if feasible. The unanimous consensus attained in this Delphi panel, particularly regarding tucatinib's efficacy and safety, underscores oncologists' recognition of its clinical significance based on existing trial data. These findings align closely with current literature, shedding light on areas necessitating further investigation, not thoroughly explored in prior studies. Moreover, the results underscore the scarcity of data on managing brain progression alongside stable extracranial disease, emphasizing the imperative for dedicated research to address these gaps and yield definitive insights. [ABSTRACT FROM AUTHOR]

De-escalation of axillary surgery in breast cancer (BC) management began when sentinel lymph node biopsy (SLNB) replaced axillary lymph node dissection (ALND) as standard of care in patients with node-negative BC. The second step consolidated ALND omission in selected subgroups of BC patients with up to two macrometastases and recognized BC molecular and genomic implication in predicting prognosis and planning adjuvant treatment. Outcomes from the recent RxPONDER and monarchE trials have come to challenge the previous cut-off of two SLN in order to inform decisions on systemic therapies for hormone receptor-positive (HR+), human epidermal growth factor receptor type-2 (HER2) negative BC, as the criteria included a cut-off of respectively three and four SLNs. In view of the controversy that this may lift in surgical practice, the Italian National Association of Breast Surgeons (Associazione Nazionale Italiana Senologi Chirurghi, ANISC) reviewed data regarding the latest trials on this topic and proposes an implementation in clinical practice. We reviewed the available literature offering data on the pathological nodal status of cN0 breast cancer patients. The rates of pN2 status in cN0 patients ranges from 3.5 % to 16 %; pre-surgical diagnostic definition of axillary lymph node status in cN0 patients by ultrasound could be useful to inform about a possible involvement of ≥4 lymph nodes in this specific sub-groups of women. The Italian National Association of Breast Surgeons (ANISC) considers that for HR + HER2-/cN0-pN1(sn) BC patients undergoing breast conserving treatment the preoperative workup should be optimized for a more detailed assessment of the axilla and the technique of SLNB should be optimized, if considered appropriate by the surgeon, not considering routine ALND always indicated to determine treatment recommendations according to criteria of eligibility to RxPONDER and monarch-E trials. [ABSTRACT FROM AUTHOR]

Introduction: As the evaluation indices, cancer grading and subtyping have diverse clinical, pathological, and molecular characteristics with prognostic and therapeutic implications. Although researchers have begun to study cancer differentiation and subtype prediction, most of relevant methods are based on traditional machine learning and rely on single omics data. It is necessary to explore a deep learning algorithm that integrates multi-omics data to achieve classification prediction of cancer differentiation and subtypes. Methods: This paper proposes a multi-omics data fusion algorithm based on a multi-view graph neural network (MVGNN) for predicting cancer differentiation and subtype classification. The model framework consists of a graph convolutional network (GCN) module for learning features from different omics data and an attention module for integrating multi-omics data. Three different types of omics data are used. For each type of omics data, feature selection is performed using methods such as the chi-square test and minimum redundancy maximum relevance (mRMR). Weighted patient similarity networks are constructed based on the selected omics features, and GCN is trained using omics features and corresponding similarity networks. Finally, an attention module integrates different types of omics features and performs the final cancer classification prediction. Results: To validate the cancer classification predictive performance of the MVGNN model, we conducted experimental comparisons with traditional machine learning models and currently popular methods based on integrating multi-omics data using 5-fold cross-validation. Additionally, we performed comparative experiments on cancer differentiation and its subtypes based on single omics data, two omics data, and three omics data. Discussion: This paper proposed the MVGNN model and it performed well in cancer classification prediction based on multiple omics data. [ABSTRACT FROM AUTHOR]

Covid-19 infection influenced the screening test rate of breast cancer worldwide due to the quarantine measures, routine procedures reduction, and delay of early diagnosis, causing high mortality risk and severity of the disease. X-ray mammography is the gold standard for diagnosing early signs of breast cancer, and Artificial Intelligence enables the detection of suspicious lesions and classifying them in terms of malignancy. This paper aimed to investigate mass detection and classification in a large-scale OPTIMAM dataset with 6000 cases and extracted 3524 images with masses in the mammograms of the Hologic manufacturer. The methodology of the detection step is to train the RetinaNet architecture of ResNet50, ResNet101, and ResNet152 backbones with three types of initializations by ImageNet and COCO weights and from scratch. The dataset was pre-processed to generate two types of input with entire mammograms and patches, which are stated as the first and the second approaches. The results show that in the first approach, RetinaNet of ResNet50 backbone with ImageNet and COCO weights and ResNet152 with the same weights performed 0.91 True Positive Rate at 0.78 False Positive Per Image, respectively. In contrast, in the second approach, ResNet152 with ImageNet weights reached 0.88 TPR at 0.78 FPPI. In the classification step, the Transfer Learning approach was applied with fine-tuning by adding L2-regularization and class weights to balance class distribution in the datasets. [ABSTRACT FROM AUTHOR]

Background: After curative surgery for early-stage breast cancer, patients face a decision on whether to undergo surgery alone or to receive one or more adjuvant treatments, which may lower the risk of recurrence. Variations in survival outcomes are often marginal but there are differences in the side effects and other features of the options that patients may value differently. Hence, the patient's values and preferences are critical in determining what option to choose. It is well-researched that the use of shared decision making and patient decision aids can support this choice in a discussion between patient and clinician. However, it is still to be investigated what impact the timing and format of the patient decision aid have on shared decision making outcomes. In this trial, we aim to investigate the impact of a digital pre-consult compared to a paper-based in-consult patient decision aid on patients' involvement in shared decision making, decisional conflict and preparedness to make a decision. Methods: The study is a randomised controlled trial with 204 patients at two Danish oncology outpatient clinics. Eligible patients are newly diagnosed with early-stage breast cancer and offered adjuvant treatments after curative surgery to lower the risk of recurrence. Participants will be randomised to receive either an in-consult paper-based patient decision aid or a pre-consult digital patient decision aid. Data collection includes patient and clinician-reported outcomes as well as observer-reported shared decision making based on audio recordings of the consultation. The primary outcome is the extent to which patients are engaged in a shared decision making process reported by the patient. Secondary aims include the length of consultation, preparation for decision making, preferred role in shared decision making and decisional conflict. Discussion: This study is the first known randomised, controlled trial comparing a digital, pre-consult patient decision aid to an identical paper-based, in-consult patient decision aid. It will contribute evidence on the impact of patient decision aids in terms of investigating if pre-consult digital patient decisions aids compared to in-consult paper-based decision aids support the cancer patients in being better prepared for decision making. Trial registration: ClinicalTrials.gov (NCT05573022). [ABSTRACT FROM AUTHOR]

Purpose: Advances in breast cancer care have led to a high rate of survivorship. This meta-review (systematic review of reviews) assesses and synthesises the voluminous qualitative survivorship evidence-base, providing a comprehensive overview of the main themes regarding breast cancer survivorship experiences, and areas requiring further investigation. Methods: Sixteen breast cancer reviews identified by a previous mixed cancer survivorship meta-review were included, with additional reviews published between 1998 and 2020, and primary papers published after the last comprehensive systematic review between 2018 and 2020, identified via database searches (MEDLINE, Embase, CINAHL, PsycINFO). Quality was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Systematic Reviews and the CASP (Critical Appraisal Skills Programme Qualitative) checklist for primary studies. A meta-ethnographic approach was used to synthesise data. Results: Of 1673 review titles retrieved, 9 additional reviews were eligible (25 reviews included in total). Additionally, 76 individual papers were eligible from 2273 unique papers. Reviews and studies commonly focused on specific survivorship groups (including those from ethnic minorities, younger/older, or with metastatic/advanced disease), and topics (including return to work). Eight themes emerged: (1) Ongoing impact and search for normalcy, (2) Uncertainty, (3) Identity: Loss and change, (4) Isolation and being misunderstood, (5) Posttraumatic growth, (6) Return to work, (7) Quality of care, and (8) Support needs and coping strategies. Conclusions: Breast cancer survivors continue to face challenges and require interventions to address these. Implications for Cancer Survivors. Breast cancer survivors may need to prepare for ongoing psychosocial challenges in survivorship and proactively seek support to overcome these. [ABSTRACT FROM AUTHOR]

Background: Estrogen receptors express in nearly 70% of breast cancers (ER-positive). Estrogen receptor alpha plays a fundamental role as a significant factor in breast cancer progression for the early selection of therapeutic approaches. Accordingly, there has been a surge of attention to non-invasive techniques, including circulating Cell-free DNA (ccfDNA) or Cell-Free DNA (cfDNA), to detect and track ESR1 genotype. Therefore, this study aimed to examine the diagnosis accuracy of ESR1 mutation detection by cell-free DNA in breast cancer patientsthrough a systematic review and comprehensive meta-analysis. Methods: PubMed, Embase, and Web of Science databases were searched up to 6 April 2022. Diagnostic studies on ESR1 measurement by cfDNA, which was confirmed using the tumour tissue biopsy, have been included in the study. The sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR) and negative likelihood ratio (NLR) were considered to analyse the data. Results: Out of 649 papers, 13 papers with 15 cohorts, including 389 participants, entered the meta-analyses. The comprehensive meta-analysis indicated a high sensitivity (75.52, 95% CI 60.19–90.85), specificity (88.20, 95% CI 80.99–95.40), and high accuracy of 88.96 (95% CI 83.23–94.69) for plasma ESR1. We also found a moderate PPV of 56.94 (95% CI 41.70–72.18) but a high NPV of 88.53 (95% CI 82.61–94.44). We also found an NLR of 0.443 (95% CI 0.09–0.79) and PLR of 1.60 (95% CI 1.20–1.99). Conclusion: This systematic review and comprehensive meta-analysis reveal that plasma cfDNA testing exhibits high sensitivity and specificity in detecting ESR1 mutations in breast cancer patients. This suggests that the test could be a valuable diagnostic tool. It may serve as a dependable and non-invasive technique for identifying ESR1 mutations in breast cancer patients. However, more extensive research is needed to confirm its prognostic value. [ABSTRACT FROM AUTHOR]

This scientific paper focuses on the treatment of breast cancer, one of the most common cancers among women. Despite increased awareness and the popularity of screening tests, statistics indicate a significant rise in incidence. The paper presents breast-conserving treatment methods, including brachytherapy, as a modern technique with promising outcomes. It describes the physical properties of ionizing radiation used in brachytherapy, discussing the photoelectric effect, Compton effect, and the phenomenon of pair production. The paper then delves into the biological effects of ionizing radiation, emphasizing the dependence on the cell cycle phase. It highlights lethal, sublethal, and potentially lethal cellular damage, categorizing the effects of radiation interaction into early and late responses. The discussion transitions to the application of brachytherapy in breast cancer treatment, focusing on various techniques such as LDR, PDR, and HDR. The paper provides a detailed description of brachytherapy's use in breast-conserving treatment, considering contraindications, treatment planning, and Accelerated Partial Breast Irradiation (APBI) techniques. The radioisotopes used in brachytherapy are also presented, with special attention to Iridium-192. The physical and practical aspects related to this isotope are discussed, along with other commonly used radioisotopes such as Cesium-137, Cobalt-60, and Strontium-90. The paper concludes with a summary, emphasizing the significance of brachytherapy in breast cancer treatment and outlining its prospects for development. The authors highlight precision and shortened therapy duration. Aim of the study The following paper aims to present a review of current knowledge regarding brachytherapy in the treatment of breast cancer and the treatment outcomes associated with this method. The main goal is to raise awareness among healthcare professionals about current issues with improvement of breast cancer treatment procedures based on brachytherapy. Materials and methods This article presents the current state of knowledge about brachytherapy for breast cancer, as found in various scientific articles. The following English keywords and their Polish equivalents were used to search Google Scholar's medical databases: brachytherapy, conservative treatment, breast cancer, BT, MammoSite. The most relevant articles on the subject were selected. [ABSTRACT FROM AUTHOR]

Aims: This study was conducted to examine the effect of monthly telephone message reminders after training on women's beliefs and practice behaviours regarding breast self‐examination. Methods: This randomized controlled study was conducted with 83 women aged 20–69 years living in Turkey between September 2021 and July 2022. Women were randomly assigned (1:1) to the intervention (n = 41) or control group (n = 42), both groups received online breast self‐examination training, and the intervention group received monthly reminders on their mobile phones for 3 months. Participants completed the Champion's Health Belief Model Scale and breast self‐examination practice evaluation form at baseline and 3 months after intervention. Results: After the intervention, the mean scores of the benefits and self‐efficacy subscales of Champion's Health Belief Model Scales were significantly higher in the intervention group compared to the control group, and the mean score of barriers was lower. The rate of performing breast self‐exam regularly and at the appropriate time was higher in the intervention group. The rate of forgetting to perform breast self‐examination was higher in control group. Conclusion: A monthly reminder message may be recommended to increase women's belief in breast self‐examination and increase regular practice. Summary statement: What is already known about this topic? Breast cancer is common, it is a type of cancer that progresses slowly and can be treated with early diagnosis and regular application of breast self‐examination is one of the effective non‐invasive screening methods for early diagnosis of breast cancer among women.Studies have found that forgetfulness and neglect, lack of awareness about BSE techniques and lack of knowledge are important obstacles to breast self‐examination. What this paper adds? Breast self‐examination training and then a monthly phone message reminder approach was used in women.It has been observed that the monthly telephone reminder message is an intervention that increases the belief in breast self‐examination in women, along with an increase in the rate of regular and timely examination practice and a decrease in the rate of forgetting to do so. The implications of this paper: The importance of regular phone message reminders about breast self‐examination should be included in the in‐service training given to all health professionals, especially midwives and nurses working in the delivery of primary health care services.A central message system could be developed to remind women of breast self‐examination at the national level. [ABSTRACT FROM AUTHOR]

Background: Breast cancer is the most common malignancy among women in the UK. Reconstruction – of which implant-based breast reconstruction (IBBR) is the most common – forms a core part of surgical management of breast cancer. More recently, pre-pectoral IBBR has become common as technology and operative techniques have evolved. Many surgeons use acellular dermal matrix (ADM) in reconstruction however there is little evidence in literature that this improves surgical outcomes. This review will assess available evidence for surgical outcomes for breast reconstructions using ADM versus non-use of ADM. Methods: A database search was performed of Ovid Medline, Embase, Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Reviews (2012–2022). Studies were screened using inclusion and exclusion criteria. Risk of Bias was assessed using the Newcastle Ottawa scale and ROBIS tools. Analysis and meta-analysis were performed. Results: This review included 22 studies (3822 breast reconstructions). No significant difference between overall complications and failure rates between ADM and non-ADM use was demonstrated. Capsular contracture, wound dehiscence and implant rippling had significant differences however these results demonstrated high heterogeneity thus wider generalisation may be inaccurate. Patient quality of life scores were not recorded consistently or comparably between papers. Conclusions: This review suggests a lack of significant differences in most complications between ADM use and non-use for pre-pectoral IBBR. If no increase in complications exists between groups, this has significant implications for surgical and legislative decision-making. There is, however, inadequate evidence available on the topic and further research is required. [ABSTRACT FROM AUTHOR]

Even though accurate detection of dangerous malignancies from mammogram images is mostly dependent on radiologists' experience, specialists occasionally differ in their assessments. Computer-aided diagnosis provides a better solution for image diagnosis that can help experts make more reliable decisions. In medical applications for diagnosing cancerous growths from mammogram images, computerized and accurate classification of breast cancer mammogram images is critical. The deep learning approach has been widely applied in medical image processing and has had considerable success in biological image classification. The Convolutional Neural Network (CNN), Inception, and EfficientNet are proposed in this paper. The proposed models attain better performance compared to the conventional CNN. The models are used to automatically classify breast cancer mammogram images from Kaggle into benign and malignant. Simulation results demonstrated that EfficientNet, with an accuracy between 97.13 and 99.27%, and overall accuracy of 98.29%, perform better than the other models in this paper. [ABSTRACT FROM AUTHOR]

Breast cancer (BC) is one of the most common cancers worldwide and a leading cause of cancer-related deaths among women. The escalating incidence of BC underscores the necessity of multi-level treatment. BC is a complex and heterogeneous disease involving many genetic, lifestyle, and environmental factors. Growing evidence suggests that nutrition intervention is an evolving effective prevention and treatment strategy for BC. In addition, the human microbiota, particularly the gut microbiota, is now widely recognized as a significant player contributing to health or disease status. It is also associated with the risk and development of BC. This review will focus on nutrition intervention in BC, including dietary patterns, bioactive compounds, and nutrients that affect BC prevention and therapeutic responses in both animal and human studies. Additionally, this paper examines the impacts of these nutrition interventions on modulating the composition and functionality of the gut microbiome, highlighting the microbiome-mediated mechanisms in BC. The combination treatment of nutrition factors and microbes is also discussed. Insights from this review paper emphasize the necessity of comprehensive BC management that focuses on the nutrition–microbiome axis. [ABSTRACT FROM AUTHOR]

Background: Breast cancer is the most prevalent cancer globally and is associated with significant mortality. Recent research has provided crucial insights into the role of gut microbiota in the onset and progression of breast cancer, confirming its impact on the disease's management. Despite numerous studies exploring this relationship, there is a lack of comprehensive bibliometric analyses to outline the field's current state and emerging trends. This study aims to fill that gap by analyzing key research directions and identifying emerging hotspots. Method: Publications from 2013 to 2023 were retrieved from the Web of Science Core Collection database. The VOSviewer, R language and SCImago Graphica software were utilized to analyze and visualize the volume of publications, countries/regions, institutions, authors, and keywords in this field. Results: A total of 515 publications were included in this study. The journal Cancers was identified as the most prolific, contributing 21 papers. The United States and China were the leading contributors to this field. The University of Alabama at Birmingham was the most productive institution. Peter Bai published the most papers, while James J. Goedert was the most cited author. Analysis of highly cited literature and keyword clustering confirmed a close relationship between gut microbiota and breast cancer. Keywords such as "metabolomics" and "probiotics" have been prominently highlighted in the keyword analysis, indicating future research hotspots in exploring the interaction between metabolites in the breast cancer microenvironment and gut microbiota. Additionally, these keywords suggest significant interest in the therapeutic potential of probiotics for breast cancer treatment. Conclusion: Research on the relationship between gut microbiota and breast cancer is expanding. Attention should be focused on understanding the mechanisms of their interaction, particularly the metabolite-microbiota-breast cancer crosstalk. These insights have the potential to advance prevention, diagnosis, and treatment strategies for breast cancer. This bibliometric study provides a comprehensive assessment of the current state and future trends of research in this field, offering valuable perspectives for future studies on gut microbiota and breast cancer. [ABSTRACT FROM AUTHOR]

Background: Breast cancer is the most common cause of cancer-related deaths among women globally and the most deadly illness for them. New advances in nanotechnology have led to the development of strategies intended to target breast cancer cells more precisely while causing the least amount of damage to healthy cells. We retrieved articles about nanomaterials for the diagnosis and treatment of breast cancer from the Web of Science Core Collection (WoSCC) database between 2008 and 2023. Our research aims to assess publications on the use of nanomaterials for breast cancer treatment and diagnosis to predict future research directions. Results: A total of 457 papers on nanomaterials in breast cancer were discovered from various nations, with China being the primary source and the United States having the highest H index. The number of papers in this discipline is increasing on an annual basis. The Egyptian Knowledge Bank is an important research center in this sector. The International Journal of Nanomedicine has the most papers, and Kesharwani P is the most frequently referenced author. The most quoted article was written by Miele, Evelina of India in 2009. Topics such as drug delivery may be emerging areas of research. Conclusion: Our findings predict that the use of nanomaterials in medication delivery will become a significant research area in the future, and provide valuable references for scholars investigating the role of nanotechnology in breast cancer. [ABSTRACT FROM AUTHOR]

Background: Breast cancer persists as a major public health issue on a global scale. Lymphangiogenesis is an indispensable element in the promotion of breast cancer metastasis. Inhibiting the metastasis of breast cancer can be accomplished through targeting lymphangiogenesis. The purpose of this study was to examine research trends, major topics, and development directions of lymphangiogenesis in breast cancer through a bibliometric analysis, which may serve as a reference for future research and clinical practice. Methods: English publications with article type article or review about lymphangiogenesis in breast cancer from inception to September 30, 2023, retrieved from the Web of Science Core Collection Database (WOSCC), and VOSviewer, CiteSpace, and Microsoft Excel were applied for bibliometric study. Results: In this paper, a total of 369 articles and reviews were included. The 369 papers were written by 2120 authors from 553 organizations across 42 countries, published in 199 journals, and cited 12458 references from 1801 journals up to September 30, 2023. Moreover, the annual publications had a rising trajectory between 2004 to 2014 but declined from 2015. The US was the leading nation in publications and citations. Meanwhile, academics Mousumi Majumder and Peeyush Lala had the highest cumulative number of publications. Based on the number of publications/citations, Cancer Research was the most influential journal. The most cited paper was "Lymphangiogenesis: Molecular Mechanisms and Future Promise" by Tuomas Tammela, published in the Journal of Cell. Additionally, keywords frequency analysis demonstrated that "lymphangiogenesis," "breast cancer," "VEGF-C," "angiogenesis," and "metastasis" were the most frequent keywords, and the newly emergent topics could be represented by "tumor microenvironment," "metastasis," "stem-cell," "triple-negative breast cancer," and "blood vessels." Conclusions: Currently, there is a strong research basis for lymphangiogenesis in breast cancer. The core research team was primarily situated in the US. Investigating the mechanism of lymphangiogenesis in breast cancer will always remain a highly discussed topic. In particular, it was essential to emphasize the relationship between lymphangiogenesis and tumor microenvironment, stem cells, triple-negative breast cancer, and metastasis, which could be the frontiers. [ABSTRACT FROM AUTHOR]

Background: The effects of military environmental exposures (MEE) such as volatile organic compounds (VOCs), endocrine-disrupting chemicals (EDCs), tactile herbicides, airborne hazards and open burn pits (AHOBP), and depleted uranium on health are salient concerns for service members and Veterans. However, little work has been done to investigate the relationship between MEE and risk of breast cancer. Data sources and Methods: We conducted a scoping review on MEE, military deployment/service, and risk of breast cancer among active-duty service members and Veterans. PRISMA was used. PubMed, Embase, and citations of included articles were searched, resulting in 4,364 articles to screen: 28 articles were included. Results: Most papers on military deployment and military service found a lower/equivalent risk of breast cancer when comparing rates to those without deployment or civilians. Exposure to VOCs due to military occupation or contaminated groundwater was associated with a slightly higher risk of breast cancer. Exposure to Agent Orange was not associated with an increased risk of breast cancer. Evidence regarding EDCs was limited. No paper directly measured exposure to AHOBP or depleted uranium, but deployments with known exposures to AHOBP or depleted uranium were associated with an equivalent/lower risk of breast cancer. Conclusions: Women are the fastest growing population within the military, and breast cancer poses a unique risk to women Veterans who were affected by MEE during their service. Unfortunately, the literature on MEE and breast cancer is mixed and limited, in part due to the Healthy Soldier Paradox and poor classification of exposure(s). [ABSTRACT FROM AUTHOR]

Circulating microRNAs (c-miRNAs) are non-coding RNAs found in different bodily fluids and are highly investigated for their prognostic potential and biological role in cancer. In this narrative review, we provide an update of the last five years' published papers (2018–2023) on PubMed about c-miRNAs in cancer research. We aim to capture the latest research interests in terms of the highly studied cancers and the insights about c-miRNAs. Our analysis revealed that more than 150 papers focusing on c-miRNAs and cancer were published in the last five years. Among these, there was a high prevalence of papers on breast cancer (BC) and lung cancer (LC), which are estimated to be the most diagnosed cancers globally. Thus, we focus on the main evidence and research trends about c-miRNAs in BC and LC. We report evidence of the effectiveness of c-miRNAs in hot topics of cancer research, such as, early detection, therapeutic resistance, recurrence risk and novel detection platform approaches. Moreover, we look at the deregulated c-miRNAs shared among BC and LC papers, focusing on miR-21 and miR-145. Overall, these data clearly indicate that the role of c-miRNAs in cancer is still a hot topic for oncologic research and that blood is the most investigated matrix. [ABSTRACT FROM AUTHOR]

There is a life after breast cancer. The prerequisite is early detection. Breast cancer is curable when detected early, tiny, and has not spread – regular screening aids in early detection. Clinical Thermography and artificial intelligence are potentially a good fit for early breast cancer screening. This survey paper presents a systematic review of artificial intelligence-based breast cancer screening using thermal infrared cameras. Initially, we will present the qualitative analysis of the existing literature regarding the trend and distribution. This review manuscript will then explore the literature about infrared thermal image acquisition and storage techniques. We will then highlight various segmentation techniques used for processing infrared thermal images. This paper presents the experimental results of the traditional image processing and deep learning-based segmentation techniques available in the literature using infrared breast thermal images. We then summarize the works that have used artificial intelligence to segment and classify infrared thermal images. The existing literature shows opportunities to explore the area of explainable artificial intelligence (AI). Explainable AI will make clinical Thermography into assistive technology for the medical community. [ABSTRACT FROM AUTHOR]

The incidence rate of breast cancer is high, and endocrine therapy for breast cancer frequently causes bone loss. We conducted a systematic review and meta-analysis to review the effect of TCM on bone loss associated with endocrine therapy in patients with breast cancer. Medline (Ovid), EMBASE, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), VIP full-text Database, Wanfang Database, Chinese Biomedical Literature data (CBM), relevant Chinese and foreign periodicals, conference papers, degree papers, and supplemented by literature tracing were searched. Data from randomized controlled trials (RCTs) on the effects of TCM on bone loss associated with endocrine therapy in patients with breast cancer were collected according to the inclusion and exclusion criteria from the establishment of each database to May 2022. Twenty-two clinical controlled studies were eventually selected. The results of the meta-analysis showed effectiveness (RR (Risk Ratio): 1.22, 95% CI (confidence interval): 1.10-1.36, I² = 0%), improvement of lumbar bone mineral density (BMD) (WMD (weighted mean difference): 0.07, 95% CI: 0.06-0.08, I² = 23%), improvement of BMD T value (WMD: 0.37, 95% CI: 0.28-0.46, I² = 66%), and improvement of BMD in the femoral neck (WMD: 0.07, 95% CI: 0.05-0.09, I² = 33%). The funnel chart suggested that a publication bias was observed in the literature, which may be explained by the heterogeneity in the study data and the limited number of included examples. Sensitivity analysis was conducted to confirm that the differences among the studies were acceptable. No study reported adverse effects. Our results indicated that TCM is helpful for bone loss associated with endocrine therapy in patients with breast cancer based on the effectiveness, lumbar BMD, BMD T value, and BMD of the femoral neck. The use of TCM is thus safe. [ABSTRACT FROM AUTHOR]

Background: Breast cancer is a significant public health issue, exhibiting the most pronounced occurrence and fatality rates among malignant neoplasms globally. Targeted therapy is a medical intervention that focuses on specific molecular markers. This study aims to investigate and evaluate the current research trends and directions in the field of targeted therapy for breast cancer using bibliometric analysis. Method: The Web of Science database was utilized to retrieve relevant articles published between 2003 and 2022. The VOSviewer software and Bibliometrix package in the R language were employed to conduct co-occurrence and clustering analyses of authors, countries, institutions, journals, references, and the CiteSpace tool was utilized for keyword burst detection. Results: A total of 2,258 articles were included and the annual number of publications increased rapidly. The most prolific country on this topic was the USA (n=898, 39.77%) and the University of Texas MD Anderson Cancer Center published most papers (n=93). Dennis J. Slamon and Gabriel N. Hortobagyi stood out in the field, with Dennis J. Slamon leading in terms of co-citations(n=653) and Gabriel N. Hortobagyi topping the list in terms of published articles(n=18). The most productive journal was Breast Cancer Research and Treatment and the most cited journal was Journal of Clinical Oncology. The clustering of keywords indicated that the primary focus of researches in the past two decades was on the development and clinical evaluation of tumor-targeted drugs associated with the epidermal growth factor receptor (EGFR) family signaling pathway, and explored mechanisms related to biological behavior of breast cancer. Keywords cooccurrence and burst analysis identified current research hotspots and potential research trends. Conclusion: This study employed bibliometric analysis to examine research on targeted therapy for breast cancer over a span of 20 years, and identified development trends of research and elucidated potential research trajectories in the domain of this topic. This study helps in the identification of prospective collaborators and partner institutions for researchers. [ABSTRACT FROM AUTHOR]

Aim: We aimed to evaluate the quality of clinical practice guidelines (CPGs) for breast cancer related lymphoedema (BCRL) and compare the similarities and differences in recommendations. Background: Many CPGs of BCRL have been developed; however, their recommendations and quality are controversial. Methods: Relevant papers were retrieved from electronic databases, professional associations and guideline development organizations, from 1 January 2015 to 30 September 2021. The Appraisal of Guidelines Research and Evaluation (AGREE) II instrument was used to evaluate the quality of the guidelines. Intraclass correlation coefficient (ICC) analysis was used to evaluate the overall consistency among evaluators. Results: Eight CPGs were included. The ICC values evaluation for CPGs ranged from 0.76 to 0.95, with good consensus among evaluators. The highest median score was 68.75% (61.46, 72.22%) for clarity, and the lowest was 37.50% (25.78, 51.30%) for applicability. The NICE, ACS/ACSO and APTA CPGs were rated well in most areas. Professional health education, individualized exercise programme and regular surveillance are the main methods to prevent lymphoedema. Conclusion: In the past 6 years, the quality of BCRL guidelines has varied greatly, especially in the domains of rigour and applicability. Interrater agreement was excellent, but recommendation showed some inconsistencies in the details. Summary statement: What is already known about this topic? Providing recommendations based on evidence‐based guidelines for care of cancer treatment‐related lymphoedema will help to improve outcomes for patients with this chronic condition. What this paper adds? The rigour of the guidelines needs to be improved.Guideline‐making organizations have the responsibility to promote the application of guidelines into practice using a variety of methods.Multifactorial reasons were responsible for the differences inguidelines' recommendations The implications of this paper Nurses need to be more aware of guideline recommendations.There are inconsistencies in the details, despite many similarities.The formulation of individual nursing care programmes should be tailored to the local clinical situation and working environment. [ABSTRACT FROM AUTHOR]

Background: This research goes into in deep learning technologies within the realm of medical imaging, with a specific focus on the detection of anomalies in medical pathology, emphasizing breast cancer. It underscores the critical importance of segmentation techniques in identifying diseases and addresses the challenges of scarce labelled data in Whole Slide Images. Additionally, the paper provides a review, cataloguing 61 deep learning architectures identified during the study. Objectives: The aim of this study is to present and assess a novel quantitative approach utilizing specific deep learning architectures, namely the Feature Pyramid Net-work and the Linknet model, both of which integrate a ResNet34 layer encoder to enhance performance. The paper also seeks to examine the efficiency of a semi-supervised training regimen using a dual model architecture, consisting of 'Teacher' and 'Student' models, in addressing the issue of limited labelled datasets. Methods: Employing a semi-supervised training methodology, this research enables the 'Student' model to learn from the 'Teacher' model's outputs. The study methodically evaluates the models' stability, accuracy, and segmentation capabilities, employing metrics such as the Dice Coefficient and the Jaccard Index for comprehensive assessment. Results: The investigation reveals that the Linknet model exhibits good performance, achieving an accuracy rate of 94% in the detection of breast cancer tissues utilizing a 21-seed parameter for the initialization of model weights. It further excels in generating annotations for the 'Student' model, which then achieves a 91% accuracy with minimal computational demands. Conversely, the Feature Pyramid Network model demonstrates a slightly lower accuracy of 93% in the Teacher model but exhibits improved and more consistent results in the 'Student' model, reaching 95% accuracy with a 42-seed parameter. Conclusions: This study underscores the efficacy and potential of the Feature Pyra-mid Network and Linknet models in the domain of medical image analysis, particularly in the detection of breast cancer, and suggests their broader applicability in various medical segmentation tasks related to other pathology disorders. Furthermore, the research enhances the understanding of the pivotal role that deep learning technologies play in advancing diagnostic methods within the field of medical imaging. [ABSTRACT FROM AUTHOR]

Aim: The overamplification of human epidermal growth factor (HER2) in breast cancer (BC) has been the subject of numerous research publications since its discovery in 1987. This is the first bibliometric analysis (BA) conducted on HER2-positive (HER2+) BC. The purpose of this BA is to analyze the published research on HER2+ BC from 1987 to 2024, highlighting the most significant scientific literature, as well as the main contributing authors and journals, and evaluating the impact of clinical and lab-based publications on HER2+ BC research. Methods: The Web of Science Core Collection (WoSCC) was searched using the terms "Breast cancer" OR "Breast carcinoma" OR "Breast tumor" AND "HER2 positive" OR "HER2+". The search was limited by publication year (1987-2024) and only full English articles were included. WoS returned 7,469 relevant results, and from this dataset, a bibliometric analysis was conducted using the "analyze results" and "journal citation report" functions in WoS and the VOSviewer 1.6.16 software to generate bibliographic coupling and co-citation analysis of authors. Results: The analysis encompassed a total of 7,469 publications, revealing a notable increase in the annual number of publications, particularly in recent years. The United States, China, Italy, Germany, and Spain were the top five most prolific countries. The top five significant institutions that published HER2+ research were the University of Texas System, Unicancer, UTMD Anderson Cancer Center, Harvard University, and University of California System. Breast Cancer Research and Treatment, Clinical Cancer Research, and Clinical Breast Cancer were the top three notable journals with the highest number of HER2+ BC publications. Dennis Slamon (Nc = 45,411, H-index = 51) and Jose Baselga (Nc = 32,592, H-index = 55) were the most prolific authors. Evolving research topics include anti-HER2 therapy in the neoadjuvant setting, treatment of metastatic HER2+ BC, and overcoming therapy resistance. Conclusion: This study provides an overview of HER2+ BC research published over the past three decades. It provides insight into the most cited papers and authors, and the core journals, and identifies new trends. These manuscripts have had the highest impact in the field and reflect the continued evolution of HER2 as a therapeutic target in BC. [ABSTRACT FROM AUTHOR]

Simple Summary: This position paper aims to address specific clinical questions regarding the use of cyclin-dependent kinase 4/6 inhibitors in elderly patients with early or advanced breast cancer. Its objectives are to delineate the current state of knowledge regarding the efficacy of these treatments in the elderly population and their tolerance profile, including the impact on quality of life, with a particular focus on the frailest subgroups, and to attempt to define the optimal treatment strategy for elderly and fragile patients (dosage and therapeutic sequence). Background: Breast cancer (BC) incidence increases with age, particularly in HR-positive/HER2-negative subtypes. Cyclin-dependent kinase 4 and 6 inhibitors (CDK 4/6is) alongside endocrine therapy (ET) have emerged as promising treatments for HR-positive/HER2-negative advanced and early BC. However, their efficacy, safety, and impact on quality of life (QoL) in older and frail patients remain underexplored. Methods: This position paper assesses the existing literature from 2015 to 2024, focusing on CDK4/6is use in patients aged 65 years and older with HR-positive/HER2-negative BC. Results: Our analysis methodically addresses critical questions regarding the utilization of CDK4/6is in the elderly BC patient population, organizing findings from the metastatic and adjuvant settings. In the metastatic setting, CDK4/6is significantly improve progression-free survival (PFS), paralleling benefits observed in younger patients, and suggest potential overall survival (OS) benefits, warranting further investigation. Despite an increased incidence of grade ≥ 3 adverse events (AEs), such as neutropenia and asthenia, CDK4/6is present a markedly lower toxicity profile compared to traditional chemotherapy, with manageable side effects. QoL analysis indicates that integrating CDK4/6is into treatment regimens does not significantly impact elderly BC patients' daily life and symptom management. Special attention is given to frail subgroups, and personalized approaches are recommended to balance efficacy and adverse effects, such as starting with ET alone and introducing CDK4/6is upon progression in patients with a low disease burden. Transitioning to the adjuvant setting, early results, particularly with abemaciclib, indicate positive effects on disease-free survival (DFS), emphasizing the need for continued analysis to validate these findings and assess long-term implications. However, data on older patients are insufficient to conclude whether they truly benefit from this treatment. Conclusion: Overall, CDK4/6is present a favorable benefit-risk profile in older BC patients, at least in advanced BC; however, further research is warranted to optimize treatment strategies and improve outcomes in this population [ABSTRACT FROM AUTHOR]

In recent years, deep convolutional neural networks (DCNNs) have shown promising performance in medical image analysis, including breast lesion classification in 2D ultrasound (US) images. Despite the outstanding performance of DCNN solutions, explaining their decisions remains an open investigation. Yet, the explainability of DCNN models has become essential for healthcare systems to accept and trust the models. This paper presents a novel framework for explaining DCNN classification decisions of lesions in ultrasound images using the saliency maps linking the DCNN decisions to known cancer characteristics in the medical domain. The proposed framework consists of three main phases. First, DCNN models for classification in ultrasound images are built. Next, selected methods for visualization are applied to obtain saliency maps on the input images of the DCNN models. In the final phase, the visualization outputs and domain-known cancer characteristics are mapped. The paper then demonstrates the use of the framework for breast lesion classification from ultrasound images. We first follow the transfer learning approach and build two DCNN models. We then analyze the visualization outputs of the trained DCNN models using the EGrad-CAM and Ablation-CAM methods. We map the DCNN model decisions of benign and malignant lesions through the visualization outputs to the characteristics such as echogenicity, calcification, shape, and margin. A retrospective dataset of 1298 US images collected from different hospitals is used to evaluate the effectiveness of the framework. The test results show that these characteristics contribute differently to the benign and malignant lesions' decisions. Our study provides the foundation for other researchers to explain the DCNN classification decisions of other cancer types. [ABSTRACT FROM AUTHOR]

With the increasing dominance of artificial intelligence (AI) techniques, the important prospects for their application have extended to various medical fields, including domains such as in vitro diagnosis, intelligent rehabilitation, medical imaging, and prognosis. Breast cancer is a common malignancy that critically affects women's physical and mental health. Early breast cancer screening—through mammography, ultrasound, or magnetic resonance imaging (MRI)—can substantially improve the prognosis for breast cancer patients. AI applications have shown excellent performance in various image recognition tasks, and their use in breast cancer screening has been explored in numerous studies. This paper introduces relevant AI techniques and their applications in the field of medical imaging of the breast (mammography and ultrasound), specifically in terms of identifying, segmenting, and classifying lesions; assessing breast cancer risk; and improving image quality. Focusing on medical imaging for breast cancer, this paper also reviews related challenges and prospects for AI. [ABSTRACT FROM AUTHOR]

Internationally, the relentless toll of breast cancer on women's lives persists, emphasizing the critical need for advancements in early detection methods. This paper delves into the promising domain of microwave imaging technology, where antennas play a pivotal role. It explores the performance of a single Antipodal Vivaldi Antenna (AVA) positioned at various angles around a breast phantom, with the paramount goal of revolutionizing breast cancer detection by meticulously comparing the antenna's Reflection loss, Gain, and H-field characteristics at 0°, 30°, and 60° angles. Considering the antenna's intended use in bioapplications, the paper also evaluates its Specific Absorption Rate (SAR) performance. Simulations are conducted using the designed antenna and a breast phantom model featuring four layers of tissue, and the results are scrutinized against established safety standards for bio applications [ABSTRACT FROM AUTHOR]