Genetic counseling and genetic testing for pathogenic germline mutations among high-risk patients previously diagnosed with breast cancer: a traceback approach.

Genetic counseling and testing are more accessible than ever due to reduced costs, expanding indications and public awareness. Nonetheless, many patients missed the opportunity of genetic counseling and testing due to barriers that existed at that time of their cancer diagnoses. Given the identified implications of pathogenic mutations on patients' treatment and familial outcomes, an opportunity exists to utilize a 'traceback' approach to retrospectively examine their genetic makeup and provide consequent insights to their disease and treatment. In this study, we identified living patients diagnosed with breast cancer (BC) between July 2007 and January 2022 who would have been eligible for testing, but not tested. Overall, 422 patients met the eligibility criteria, 282 were reached and invited to participate, and germline testing was performed for 238, accounting for 84.4% of those invited. The median age (range) was 39.5 (24-64) years at BC diagnosis and 49 (31-75) years at the date of testing. Genetic testing revealed that 25 (10.5%) patients had pathogenic/likely pathogenic (P/LP) variants; mostly in BRCA2 and BRCA1. We concluded that long overdue genetic referral through a traceback approach is feasible and effective to diagnose P/LP variants in patients with history of BC who had missed the opportunity of genetic testing, with potential clinical implications for patients and their relatives.

PPIH acts as a potential predictive biomarker for patients with common solid tumors.

BACKGROUND: Our previous studies have indicated that mRNA and protein levels of PPIH are significantly upregulated in Hepatocellular Carcinoma (LIHC) and could act as predictive biomarkers for patients with LIHC. Nonetheless, the expression and implications of PPIH in the etiology and progression of common solid tumors have yet to be explored, including its potential as a serum tumor marker. METHODS: We employed bioinformatics analyses, augmented with clinical sample evaluations, to investigate the mRNA and protein expression and gene regulation networks of PPIH in various solid tumors. We also assessed the association between PPIH expression and overall survival (OS) in cancer patients using Kaplan-Meier analysis with TCGA database information. Furthermore, we evaluated the feasibility and diagnostic efficacy of PPIH as a serum marker by integrating serological studies with established clinical tumor markers. RESULTS: Through pan-cancer analysis, we found that the expression levels of PPIH mRNA in multiple tumors were significantly different from those in normal tissues. This study is the first to report that PPIH mRNA and protein levels are markedly elevated in LIHC, Colon adenocarcinoma (COAD), and Breast cancer (BC), and are associated with a worse prognosis in these cancer patients. Conversely, serum PPIH levels are decreased in patients with these tumors (LIHC, COAD, BC, gastric cancer), and when combined with traditional tumor markers, offer enhanced sensitivity and specificity for diagnosis. CONCLUSION: Our findings propose that PPIH may serve as a valuable predictive biomarker in tumor patients, and its secreted protein could be a potential serum marker, providing insights into the role of PPIH in cancer development and progression.

Determination of Breast Cancer Risk and Knowledge Levels in Women: The Case of Cyprus.

BACKGROUND: Breast cancer is the type of cancer that is seen all over the world and ranks first among female cancers in terms of incidence and cause of death. OBJECTIVE: This research was conducted to determine the breast cancer risk level and breast cancer knowledge level in women living in Northern Cyprus. METHODS: The study, which was planned as a relational survey, was carried out as web-based. The research was completed with 657 adult female participants living in Northern Cyprus who volunteered to participate in the study. In order to collect data, the first section includes the introductory features, the second section includes the "Breast Cancer Risk Assessment Form" for determining breast cancer risk levels, the third section includes the "Comprehensive Breast Cancer Knowledge Test" to determine the breast cancer knowledge levels of the participants, and the fourth section includes the "Champion Health Belief Model Scale" was used. RESULTS: It was determined that 95.2% of women were in the low risk group for breast cancer. The knowledge test mean score is 12.05, and it can be said that the scores obtained are above the average (min:4- max:18). It was found that 55.7% of the women knew how to do Breast Self-Examination (BSE), but only 15.4% of them regularly performed BSE every month. It was found that 80.9% of the women never had mammography and their knowledge scores increased with increasing education level (p< 0.001) and there was a significant relationship between non-smokers and their knowledge levels (p< 0.01). IMPLICATIONS FOR PRACTICE: Despite the high scores of women in knowledge tests, it was observed that the frequency of applying BSE and having mammography was very low. Regardless of the risk factors for breast cancer, the importance of regular check-ups and BSE for every woman should be taught to women by health professionals, and group trainings should be planned for women who do not have training on this subject.

Health literacy and mammography screening behaviors among women living in a rural area of Turkey.

INTRODUCTION: Breast cancer is the most common cause of cancer-related deaths. and early diagnosis could reduce breast cancer deaths. Therefore, health literacy is one of the most important determinants of participation in cancer screening for early diagnosis. This study aimed to determine the relationship between women's mammography screening behaviors and health literacy levels. METHODS: The cross-sectional study included 312 women aged 40-69 years living in a rural area. Data were collected through face-to-face interviews using a personal information form and the Turkish Health Literacy Scale (THLS-32). RESULTS: Of the women, 28.5% had mammography in the last 2 years. Of concern was the low health literacy levels. In addition, there were significant differences in the THLS-32 subgroup scores, including the THLS-32 total score, among the mammography screening groups. CONCLUSION: Health literacy levels of women were related to mammography screening rates. For this reason, effective intervention studies aiming to increase society's health literacy levels may contribute to an increase in breast cancer screenings.

Cancer Screening in Low- and Middle-Income Countries.

The worldwide cancer burden is growing, and populations residing in low- and middle-income countries (LMICs) are experiencing a disproportionate extent of this growth. Breast, colorectal, and cervical cancers are among the top 10 most frequently diagnosed malignancies, and they also account for a substantial degree of cancer mortality internationally. Effective screening strategies are available for all three of these cancers. Individuals from LMICs face substantial cost and access barriers to early detection programs, and late stage at diagnosis continues to be a major cause for cancer mortality in these communities. This chapter will review the epidemiology of breast, colorectal, and cervical cancers, and will explore prospects for improving global control through novel approaches to screening in cost-constrained environments.

Inflammation at diagnosis and cognitive impairment two years later in breast cancer patients from the Canto-Cog study.

BACKGROUND: Inflammation could be related to cancer-related cognitive impairment (CRCI) and might be used as a predictive marker of long-term CRCI. We evaluated associations between inflammatory markers assessed at diagnosis of breast cancer and CRCI two years afterwards. METHODS: Newly diagnosed stage I-III patients with breast cancer from the French CANTO-Cog (Cognitive sub-study of CANTO, NCT01993498) were included at diagnosis (baseline). Serum inflammatory markers (IL-2, IL-4, IL-6, IL-8, IL-10, TNFα, CRP) were assessed at baseline. Outcomes at year 2 post-baseline included overall cognitive impairment (≥ 2 impaired domains) and the following domains: episodic memory, working memory, attention, processing speed, and executive functions. Multivariable logistic regression models evaluated associations between markers and outcomes, controlling for age, education, and baseline cognitive impairment. RESULTS: Among 200 patients, the mean age was 54 ± 11 years, with 127 (64%) receiving chemotherapy. Fifty-three (27%) patients had overall cognitive impairment at both timepoints. Overall cognitive impairment at year 2 was associated with high (> 3 mg/L) baseline CRP (OR = 2.84, 95%CI: 1.06-7.64, p = 0.037). In addition, associations were found between high CRP and processing speed impairment (OR = 2.47, 95%CI:1.05-5.87, p = 0.039), and between high IL-6 and episodic memory impairment (OR = 5.50, 95%CI:1.43-36.6, p = 0.010). CONCLUSIONS: In this cohort, high levels of CRP and IL-6 assessed at diagnosis were associated with overall CRCI, processing speed and episodic memory impairments two years later. These findings suggest a potential inflammatory basis for long-term CRCI. CRP may represent an easily measurable marker in clinical settings and be potentially used to screen patients at greater risk of persistent CRCI.

Breast Cancer Screening: Can We Justify Deescalation?

Novel breast cancer screening methods that detect greater numbers of occult (nonpalpable) tumors have been rapidly incorporated into clinical practice, with the aim of reducing mortality. Yet, tumor detection has never been validated as a proper surrogate outcome measure for breast cancer mortality. Moreover, the detection of greater numbers of occult cancers increases the risk of overdiagnosis, which refers to detection of tumors that pose no threat to life and would never have been detected in the absence of screening. With recent advances in breast cancer therapy, many cancers that were previously curable only if detected as occult tumors with mammography screening are perhaps now curable even when detected as small palpable tumors, thereby giving us an opportunity to deescalate screening and mitigate the risk of overdiagnosis. Thus, a randomized trial comparing screening mammography versus screening clinical breast examination (CBE), with breast cancer mortality as the endpoint, is now warranted. In such a trial, hand-held ultrasound might aid in the interpretation of screening CBE findings. In conclusion, recent improvements in breast cancer therapy provide the justification to assess the deescalation of breast cancer screening. See related article by Farber et al., p. 671.

Implementing Standard Diagnosis and Treatment for Locally Advanced Breast Cancer Through Global Research in Latin America: Results From a Multicountry Pragmatic Trial.

PURPOSE: Breast cancer mortality rates in Latin America (LA) are higher than those in the United States, possibly because of advanced disease presentation, health care disparities, or unfavorable molecular subtypes. The Latin American Cancer Research Network was established to address these challenges and to promote collaborative clinical research. The Molecular Profiling of Breast Cancer Study (MPBCS) aimed to evaluate the clinical characteristics and treatment outcomes of LA participants with locally advanced breast cancer (LABC). PATIENTS AND METHODS: The MPBCS enrolled 1,449 participants from Argentina, Brazil, Chile, Mexico, and Uruguay. Through harmonized procedures and quality assurance measures, this study evaluated clinicopathologic characteristics, neoadjuvant chemotherapy response, and survival outcomes according to residual cancer burden (RCB) and the type of surgery. RESULTS: Overall, 711 and 480 participants in the primary surgery and neoadjuvant arms, respectively, completed the 5-year follow-up period. Overall survival was independently associated with RCB (worse survival for RCBIII-adjusted hazard ratio, 8.19, P < .001, and RCBII [adjusted hazard ratio, 3.69, P < .008] compared with RCB0 [pathologic complete response or pCR]) and type of surgery (worse survival in mastectomy than in breast-conserving surgery [BCS], adjusted hazard ratio, 2.97, P = .001). The hormone receptor-negative-human epidermal growth factor receptor 2-positive group had the highest proportion of pCR (48.9%). The analysis of the ASCO Quality Oncology Practice Initiative breast module revealed high compliance with pathologic standards but lower adherence to treatment administration standards. Notably, compliance with trastuzumab administration varied widely among countries (33.3%-88.7%). CONCLUSION: In LABC, we demonstrated the survival benefit of BCS and the prognostic effect of the response to available neoadjuvant treatments despite an important variability in access to key treatments. The MPBCS represents a significant step forward in understanding the real-world implementation of oncologic procedures in LA.

Structured illumination microscopy for cancer identification in diagnostic breast biopsies.

Breast cancer is the second most common cancer diagnosed in women in the US with almost 280,000 new cases anticipated in 2023. Currently, on-site pathology for location guidance is not available during the collection of breast biopsies or during surgical intervention procedures. This shortcoming contributes to repeat biopsy and re-excision procedures, increasing the cost and patient discomfort during the cancer management process. Both procedures could benefit from on-site feedback, but current clinical on-site evaluation techniques are not commonly used on breast tissue because they are destructive and inaccurate. Ex-vivo microscopy is an emerging field aimed at creating histology-analogous images from non- or minimally-processed tissues, and is a promising tool for addressing this pain point in clinical cancer management. We investigated the ability structured illumination microscopy (SIM) to generate images from freshly-obtained breast tissues for structure identification and cancer identification at a speed compatible with potential on-site clinical implementation. We imaged 47 biopsies from patients undergoing a guided breast biopsy procedure using a customized SIM system and a dual-color fluorescent hematoxylin & eosin (H&E) analog. These biopsies had an average size of 0.92 cm2 (minimum 0.1, maximum 4.2) and had an average imaging time of 7:29 (minimum 0:22, maximum 37:44). After imaging, breast biopsies were submitted for standard histopathological processing and review. A board-certified pathologist returned a binary diagnostic accuracy of 96% when compared to diagnoses from gold-standard histology slides, and key tissue features including stroma, vessels, ducts, and lobules were identified from the resulting images.

A stakeholder analysis to prepare for real-world evaluation of integrating artificial intelligent algorithms into breast screening (PREP-AIR study): a qualitative study using the WHO guide.

BACKGROUND: The national breast screening programme in the United Kingdom is under pressure due to workforce shortages and having been paused during the COVID-19 pandemic. Artificial intelligence has the potential to transform how healthcare is delivered by improving care processes and patient outcomes. Research on the clinical and organisational benefits of artificial intelligence is still at an early stage, and numerous concerns have been raised around its implications, including patient safety, acceptance, and accountability for decisions. Reforming the breast screening programme to include artificial intelligence is a complex endeavour because numerous stakeholders influence it. Therefore, a stakeholder analysis was conducted to identify relevant stakeholders, explore their views on the proposed reform (i.e., integrating artificial intelligence algorithms into the Scottish National Breast Screening Service for breast cancer detection) and develop strategies for managing 'important' stakeholders. METHODS: A qualitative study (i.e., focus groups and interviews, March-November 2021) was conducted using the stakeholder analysis guide provided by the World Health Organisation and involving three Scottish health boards: NHS Greater Glasgow & Clyde, NHS Grampian and NHS Lothian. The objectives included: (A) Identify possible stakeholders (B) Explore stakeholders' perspectives and describe their characteristics (C) Prioritise stakeholders in terms of importance and (D) Develop strategies to manage 'important' stakeholders. Seven stakeholder characteristics were assessed: their knowledge of the targeted reform, position, interest, alliances, resources, power and leadership. RESULTS: Thirty-two participants took part from 14 (out of 17 identified) sub-groups of stakeholders. While they were generally supportive of using artificial intelligence in breast screening programmes, some concerns were raised. Stakeholder knowledge, influence and interests in the reform varied. Key advantages mentioned include service efficiency, quicker results and reduced work pressure. Disadvantages included overdiagnosis or misdiagnosis of cancer, inequalities in detection and the self-learning capacity of the algorithms. Five strategies (with considerations suggested by stakeholders) were developed to maintain and improve the support of 'important' stakeholders. CONCLUSIONS: Health services worldwide face similar challenges of workforce issues to provide patient care. The findings of this study will help others to learn from Scottish experiences and provide guidance to conduct similar studies targeting healthcare reform. STUDY REGISTRATION: researchregistry6579, date of registration: 16/02/2021.

Radiological features of screening-detected and interval breast cancers and subsequent survival in Eastern Finnish women.

Interval breast cancers are diagnosed between scheduled screenings and differ in many respects from screening-detected cancers. Studies comparing the survival of patients with interval and screening-detected cancers have reported differing results. The aim of this study was to investigate the radiological and histopathological features and growth rates of screening-detected and interval breast cancers and subsequent survival. This retrospective study included 942 female patients aged 50-69 years with breast cancers treated and followed-up at Kuopio University Hospital between January 2010 and December 2016. The screening-detected and interval cancers were classified as true, minimal-signs, missed, or occult. The radiological features were assessed on mammograms by one of two specialist breast radiologists with over 15 years of experience. A χ2 test was used to examine the association between radiological and pathological variables; an unpaired t test was used to compare the growth rates of missed and minimal-signs cancers; and the Kaplan-Meier estimator was used to examine survival after screening-detected and interval cancers. Sixty occult cancers were excluded, so a total of 882 women (mean age 60.4 ± 5.5 years) were included, in whom 581 had screening-detected cancers and 301 interval cancers. Disease-specific survival, overall survival and disease-free survival were all worse after interval cancer than after screening-detected cancer (p < 0.001), with a mean follow-up period of 8.2 years. There were no statistically significant differences in survival between the subgroups of screening-detected or interval cancers. Missed interval cancers had faster growth rates (0.47% ± 0.77%/day) than missed screening-detected cancers (0.21% ± 0.11%/day). Most cancers (77.2%) occurred in low-density breasts (< 25%). The most common lesion types were masses (73.9%) and calcifications (13.4%), whereas distortions (1.8%) and asymmetries (1.7%) were the least common. Survival was worse after interval cancers than after screening-detected cancers, attributed to their more-aggressive histopathological characteristics, more nodal and distant metastases, and faster growth rates.

Strategies for Accessible Breast Screening for People With Intellectual Disability.

INTRODUCTION: People with intellectual disability are less likely to participate in breast screening than people without intellectual disability. They experience a range of barriers to accessing breast screening, however, there is no consensus on strategies to overcome these barriers. Our objective was to reach consensus on the strategies required for accessible breast screening for people with intellectual disability. METHODS: Fourteen experts participated in a modified on-line Delphi that used Levesque's model of health care access as the theoretical framework. At the end of each round descriptive and thematic analyses were completed. Data was then triangulated to determine if consensus was reached. RESULTS: After 3 rounds, 9 strategies were modified, 24 strategies were added and consensus was reached for 52 strategies across the 5 dimensions of access. Key areas of action related to (i) decision making and consent, (ii) accessible information, (iii) engagement of peer mentors, (iv) service navigators, and (v) equipping key stakeholders. CONCLUSIONS: The resulting strategies are the first to articulate how to make breast screening accessible and can be used to inform health policy and quality improvement practices.

Consumer electronics based smart technologies for enhanced terahertz healthcare having an integration of split learning with medical imaging.

The proposed work contains three major contribution, such as smart data collection, optimized training algorithm and integrating Bayesian approach with split learning to make privacy of the patent data. By integrating consumer electronics device such as wearable devices, and the Internet of Things (IoT) taking THz image, perform EM algorithm as training, used newly proposed slit learning method the technology promises enhanced imaging depth and improved tissue contrast, thereby enabling early and accurate disease detection the breast cancer disease. In our hybrid algorithm, the breast cancer model achieves an accuracy of 97.5 percent over 100 epochs, surpassing the less accurate old models which required a higher number of epochs, such as 165.

Pseudo-class part prototype networks for interpretable breast cancer classification.

Interpretability in machine learning has become increasingly important as machine learning is being used in more and more applications, including those with high-stakes consequences such as healthcare where Interpretability has been regarded as a key to the successful adoption of machine learning models. However, using confounding/irrelevant information in making predictions by deep learning models, even the interpretable ones, poses critical challenges to their clinical acceptance. That has recently drawn researchers' attention to issues beyond the mere interpretation of deep learning models. In this paper, we first investigate application of an inherently interpretable prototype-based architecture, known as ProtoPNet, for breast cancer classification in digital pathology and highlight its shortcomings in this application. Then, we propose a new method that uses more medically relevant information and makes more accurate and interpretable predictions. Our method leverages the clustering concept and implicitly increases the number of classes in the training dataset. The proposed method learns more relevant prototypes without any pixel-level annotated data. To have a more holistic assessment, in addition to classification accuracy, we define a new metric for assessing the degree of interpretability based on the comments of a group of skilled pathologists. Experimental results on the BreakHis dataset show that the proposed method effectively improves the classification accuracy and interpretability by respectively 8 % and 18 % . Therefore, the proposed method can be seen as a step toward implementing interpretable deep learning models for the detection of breast cancer using histopathology images.

Advanced-stage breast cancer diagnosis and its determinants in Ethiopia: a systematic review and meta-analysis.

INTRODUCTION: Worldwide, breast cancer is the primary cause of illness and death. Unless early detected and treated breast cancer is a life-threatening tumor. Advanced-stage presentation is greatly linked with short survival time and increased mortality rates. In Ethiopia nationally summarized evidence on the level of advanced-stage breast cancer diagnosis is scarce. Therefore, this systematic review and meta-analysis aimed to determine the pooled prevalence of advanced-stage breast cancer diagnosis and its determinants in Ethiopia. METHOD: By following PRISMA guidelines, a systematic review and meta-analysis were carried out. To include relevant publications, a broad literature search was conducted in the African Online Journal, PubMed, Google Scholar, and Embase which are published until last search date; June 15, 2023. To prevent further duplication this review was registered in PROSPERO database with ID no of CRD42023435096. To determine the pooled prevalence, a weighted inverse variance random effect model was applied. I2 statistics and the Cochrane Q-test were computed to determine heterogeneity. To evaluate publication bias, a funnel plot, and Egger's regression test were used. RESULT: A total of 924 articles were sought and finally 20 articles were included in this review. The pooled prevalence of advanced-stage breast cancer diagnosis in Ethiopia was 72.56% (95%CI; 68.46-76.65%). Use of traditional medicine as first choice (AOR = 1.32, 95% CI: (1.13-1.55)), delay of > 3 months in seeking care (AOR = 1.24, 95% CI: (1.09-1.41)), diagnosis or health system delay of > 2 months (AOR = 1.27, 95% CI: (1.11-1.46)), rural residence (AOR = 2.04, 95% CI: (1.42 - 2.92)), and chief complaint of a painless breast lump (AOR = 2.67, 95% CI: (1.76-4.06)) were significantly associated to advanced-stage diagnosis. CONCLUSION: In Ethiopia, more than two-thirds of breast cancer cases are diagnosed at an advanced stage. Use of traditional medicine before diagnostic confirmation, delay in seeking care, health system delay, rural residence, and chief complaint of painless breast lump were positively associated with an advanced-stage diagnosis. Policymakers and program designers give great focus to those delays so as to seek and access modern diagnosis and treatment as early as possible specifically focusing on those who are rurally residing.

Circulating tumor DNA: from discovery to clinical application in breast cancer.

Breast cancer (BC) stands out as the cancer with the highest incidence of morbidity and mortality among women worldwide, and its incidence rate is currently trending upwards. Improving the efficiency of breast cancer diagnosis and treatment is crucial, as it can effectively reduce the disease burden. Circulating tumor DNA (ctDNA) originates from the release of tumor cells and plays a pivotal role in the occurrence, development, and metastasis of breast cancer. In recent years, the widespread application of high-throughput analytical technology has made ctDNA a promising biomarker for early cancer detection, monitoring minimal residual disease, early recurrence monitoring, and predicting treatment outcomes. ctDNA-based approaches can effectively compensate for the shortcomings of traditional screening and monitoring methods, which fail to provide real-time information and prospective guidance for breast cancer diagnosis and treatment. This review summarizes the applications of ctDNA in various aspects of breast cancer, including screening, diagnosis, prognosis, treatment, and follow-up. It highlights the current research status in this field and emphasizes the potential for future large-scale clinical applications of ctDNA-based approaches.

A prediction model based on digital breast pathology image information.

BACKGROUND: The workload of breast cancer pathological diagnosis is very heavy. The purpose of this study is to establish a nomogram model based on pathological images to predict the benign and malignant nature of breast diseases and to validate its predictive performance. METHODS: In retrospect, a total of 2,723 H&E-stained pathological images were collected from 1,474 patients at Qingdao Central Hospital between 2019 and 2022. The dataset consisted of 509 benign tumor images (adenosis and fibroadenoma) and 2,214 malignant tumor images (infiltrating ductal carcinoma). The images were divided into a training set (1,907) and a validation set (816). Python3.7 was used to extract the values of the R channel, G channel, B channel, and one-dimensional information entropy from all images. Multivariable logistic regression was used to select variables and establish the breast tissue pathological image prediction model. RESULTS: The R channel value, B channel value, and one-dimensional information entropy of the images were identified as independent predictive factors for the classification of benign and malignant pathological images (P < 0.05). The area under the curve (AUC) of the nomogram model in the training set was 0.889 (95% CI: 0.869, 0.909), and the AUC in the validation set was 0.838 (95% CI: 0.7980.877). The calibration curve results showed that the calibration curve of this nomogram model was close to the ideal curve. The decision curve results indicated that the predictive model curve had a high value for auxiliary diagnosis. CONCLUSION: The nomogram model for the prediction of benign and malignant breast diseases based on pathological images demonstrates good predictive performance. This model can assist in the diagnosis of breast tissue pathological images.

Metaplastic breast cancer with a unique presentation and complete response to chemotherapy: a case report.

BACKGROUND: Metaplastic breast carcinomas are a rare variant group of breast carcinomas. They are usually high-grade and triple-negative tumors. They often present with large primary tumor sizes. However, the involvement of axillary lymph nodes is infrequent at the time of diagnosis. Metaplastic breast carcinomas are associated with a worse prognosis and a poorer response to chemotherapy in comparison with other non-metaplastic triple-negative breast cancers. Up until this point, there are no specific treatment recommendations for metaplastic breast carcinomas beyond those intended for invasive breast cancer in general. CASE PRESENTATION: A 40-year-old woman complained of a palpable mass in her left axilla. On ultrasonography, the mass was solid, spindle-shaped, hypoechoic with regular borders, and exhibited decreased vascularity. At first, the mass appeared to be of a muscular origin. There was not any clinical nor ultrasonic evidence of a primary breast tumor. On magnetic resonance imaging, the axillary mass was a well-defined with regular borders, measuring 24 × 35 mm. Needle biopsy showed a spindle cell tumor with mild to moderate atypia. The subsequent surgical resection revealed a spindle cell neoplasm within a lymph node, favoring a metastatic origin of the tumor. The tumor cells lacked expression of estrogen, progesterone, and HER2 receptors. PET-CT scan indicated pathological uptake in the left breast. Accordingly, the patient was diagnosed with metaplastic breast cancer that had metastasized to the axillary lymph node. She commenced a combined chemotherapy regimen of doxorubicin and cyclophosphamide. After six treatment cycles, she underwent left modified radical mastectomy with axillary lymph node dissection. Pathological examination of the specimens revealed a total burn-out tumor in the breast due to excellent treatment response. There were no residual tumor cells. All dissected lymph nodes were free of tumor. At the one-year follow-up, the patient showed no signs of tumor recurrence. CONCLUSION: This report sheds light on a distinctive presentation of metaplastic breast carcinoma, emphasizing the need for vigilance in diagnosing this rare and aggressive breast cancer variant. In addition, the patient's remarkable response to chemotherapy highlights potential treatment avenues for metaplastic breast cancer.

Clinical and economic outcomes of adding [18F]FES PET/CT in estrogen receptor status identification in metastatic and recurrent breast cancer in the US.

BACKGROUND AND OBJECTIVES: Correct identification of estrogen receptor (ER) status in breast cancer (BC) is crucial to optimize treatment; however, standard of care, involving biopsy and immunohistochemistry (IHC), and other diagnostic tools such as 2-deoxy-2-[18F]fluoro-D-glucose or 2-[18F]fluoro-2-deoxy-D-glucose ([18F]FDG), can yield inconclusive results. 16α-[18F]fluoro-17ß-fluoroestradiol ([18F]FES) can be a powerful tool, providing high diagnostic accuracy of ER-positive disease. The aim of this study was to estimate the budget impact and cost-effectiveness of adding [18F]FES PET/CT to biopsy/IHC in the determination of ER-positive status in metastatic (mBC) and recurrent breast cancer (rBC) in the United States (US). METHODS: An Excel-based decision tree, combined with a Markov model, was developed to estimate the economic consequences of adding [18F]FES PET/CT to biopsy/IHC for determining ER-positive status in mBC and rBC over 5 years. Scenario A, where the determination of ER-positive status is carried out solely through biopsy/IHC, was compared to scenario B, where [18F]FES PET/CT is used in addition to biopsy/IHC. RESULTS: The proportion of true positive and true negative test results increased by 0.2 to 8.0 percent points in scenario B compared to scenario A, while re-biopsies were reduced by 94% to 100%. Scenario B resulted in cost savings up to 142 million dollars. CONCLUSIONS: Adding [18F]FES PET/CT to biopsy/IHC may increase the diagnostic accuracy of the ER status, especially when a tumor sample cannot be obtained, or the risk of a biopsy-related complication is high. Therefore, adding [18F]FES PET/CT to biopsy/IHC would have a positive impact on US clinical and economic outcomes.