Design of NBW-MHO with BERT model for prediction of Breast Cancer in IoT Healthcare System

The role of radiation therapy in the management of primary breast cancer

Health care is informed first and foremost by scientific and medical understanding of how to treat and prevent disease. Economics can, however, provide useful insights to inform policy in the design and implementation of the systems to provide health care, as well as in the process of prioritizing interventions to make the best use of scarce resources. Treating a single cancer patient may require the coordination of many inputs and may cost tens or even hundreds of thousands of dollars in high-income countries (HICs). Ongoing population cancer screening and early detection also require considerable coordination, including treatment for cases detected, and costs. Finally, although knowledge of cancer prevention is inadequate, prevention can be a costly endeavor—as demonstrated by the large sums spent on behavior change promotion (such as smoking cessation) or on vaccines to prevent cancer, such as against human papilloma virus to prevent cervical cancer and hepatitis B virus to prevent liver cancer—and economics can be informative.The second section of this chapter reviews how the availability of resources for cancer care varies by economic status, using the World Bank’s categories of low-income countries (LICs), middle-income countries (MICs) (comprising lower-middle-income countries and upper-middle-income countries), and HICs. At the same time, economy is not destiny. Countries at the same level of economic development differ because other factors intervene. Urbanization affects the patterns of cancer and the ability to access care. Local champions, governmental political leadership, and international partnerships can all loosen the constraints of local economic resources. Conversely, some countries are underachievers in cancer care despite their income level, perhaps because of leadership failures.The third section reviews the cost-effectiveness of interventions for cancer care, where care is here defined to include prevention. The cost-effectiveness of interventions has been well studied in HICs, but much less so in low- and middle-income countries (LMICs). This section summarizes the literature on the economics of cancer care in LMICs; the section also draws on the literature from HICs, particularly for cancer treatment, in areas where reliable studies for LMICs are particularly scarce. It may be possible to make inferences for one country using results from another country; the validity of these inferences rises with the extent of the similarities in the two countries. Where possible, we separate out the findings for high-income economies in Asia, since they are likely to be more relevant for LMICs in this region than the results from North America or Western Europe.We use the resource grouping suggested by Anderson and others (see chapter 3) for the Breast Health Global Initiative and apply this to other cancers. In this framework, facility resource environments fall into four categories of resource availability: Basic Limited Enhanced Maximal These categories are correlated with the World Bank income groupings. LICs have a preponderance of Basic facilities, rural areas in MICs have more facilities with Limited capabilities, urban areas in MICs have more facilities with Enhanced capabilities, and much of the population in HICs has access to facilities with Maximal capabilities. The implications for the availability of resources specific to cancer care are described. This section requires some interpolation on the authors’ part because of the paucity of previous work in the area and is subject to further validation by experts.The fourth and final section contains conclusions, consisting of summary recommendations of packages of cancer care appropriate for each of the four resource environments, as well as priority areas where further research is required. The appropriateness of a package is defined by feasibility (those resources can be expected to exist or could exist with reasonable investments) and by likely cost-effectiveness (within the limits of available data). Although there are internationally validated resource-specific care guidelines for breast cancer (the Breast Health Global Initiative), no such guidelines are available as yet for other cancers. The packages presented here have been validated in consultation with the chapter authors of this volume (chapters 3 through 8), but need to be further refined by expert consultation.

A systematic review of IoT in healthcare: Applications, techniques, and trends

A fuzzy-rough nearest neighbor classifier combined with consistency-based subset evaluation and instance selection for automated diagnosis of breast cancer

Forkhead box A1 (FOXA1) is a pioneer factor for the nuclear hormone receptors: estrogen receptor and androgen receptor. FOXA1 plays a major role inducing endocrine resistance in breast cancer (BC) and prostate cancer (PC), the two most prevalent cancers in the United States. In this study, we investigated FOXA1 gene alterations across different race and ethnicity using the TCGA PanCan Atlas dataset for BC and PC patients. The BC and PC dataset included 1084 and 494 patient samples, respectively, profiled for copy number alterations (CNA), gene expression, and mutations. In the BC dataset, the samples were from 877 non-Hispanic (81%), 38 Hispanic (3.5%) and 169 patients with no ethnicity data (15.5%). Among them, the majority of patients were White (n=751, 69.3%) followed by Black/African American (AA) (n=182, 16.8%), Asian (n=60, 5.5%), and American Indian or Alaska Native (n=1, 0.09%). Ninety BC patients (8.3%) had no race information. The PC dataset included 152 non-Hispanic (30.8%), 0 Hispanic, and 342 patients with no ethnicity data (69.2%). The samples obtained for the PC study were from White (n=147, 29.8%), Black/AA (n=7, 1.4%), and Asian (n=2, 0.4%) patients. Majority of the PC patients had no racial information (n=338, 68.4%) recorded. In the BC dataset, the incidence of FOXA1 alterations was 16/1070 (1.5%) CNA 24/1082 (2.2%) high mRNA expression, and 31/1066 (2.9%) mutations. Only amplifications were found within the BC patients. In the PC dataset, there were 15/489 (3.1%) CNA, 16/493 (3.2%) high mRNA expression, and 28/494 (5.7%) mutations reported in FOXA1. Deep deletion was found in one of the PC patients while the rest had amplifications. Due to insufficient numbers of Hispanic patients in the datasets, we compared the incidence of various FOXA1 alterations in White vs. Black/AA population using Fisher's exact test. Only FOXA1 mutation rate was significantly higher (p =0.03) in Blacks/AA (2/7, 28.6%) compared to Whites (5/147, 3.4%) in PC, but not in the BC dataset. Comparing the separate results of the FOXA1 CNA and gene overexpression White vs. Black/AA patients were statistically significant in both BC and PC datasets. A majority of FOXA1 mutations were missense mutations with a few frame shifts in BC and PC. The missense mutation reported in both BC and PC datasets were D226G, D226N, and H247Y. Additional studies are necessary to understand the functional significance of these mutations on the development of cancer. Complete and larger datasets that include the race and ethnicity information from diverse group of patients as well as tumor molecular subtyping are also needed for the assessment of the mechanism of health disparity in BC and PC in minority population in the United States. Citation Format: Jennifer Torres, Hariprasad Thangavel, Xiaoyong Fu, Rachel Schiff, Meghana V. Trivedi. FOXA1 genetic alterations in whites versus blacks or African Americans in breast and prostate cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3508.

Forkhead box A1 (FOXA1) is a pioneer factor for the nuclear hormone receptors: estrogen receptor and androgen receptor. FOXA1 plays a major role inducing endocrine resistance in breast cancer (BC) and prostate cancer (PC), the two most prevalent cancers in the United States. In this study, we investigated FOXA1 gene alterations across different race and ethnicity using the TCGA PanCan Atlas dataset for BC and PC patients. The BC and PC dataset included 1084 and 494 patient samples, respectively, profiled for copy number alterations (CNA), gene expression, and mutations. In the BC dataset, the samples were from 877 non-Hispanic (81%), 38 Hispanic (3.5%) and 169 patients with no ethnicity data (15.5%). Among them, the majority of patients were White (n=751, 69.3%) followed by Black/African American (AA) (n=182, 16.8%), Asian (n=60, 5.5%), and American Indian or Alaska Native (n=1, 0.09%). Ninety BC patients (8.3%) had no race information. The PC dataset included 152 non-Hispanic (30.8%), 0 Hispanic, and 342 patients with no ethnicity data (69.2%). The samples obtained for the PC study were from White (n=147, 29.8%), Black/AA (n=7, 1.4%), and Asian (n=2, 0.4%) patients. Majority of the PC patients had no racial information (n=338, 68.4%) recorded. In the BC dataset, the incidence of FOXA1 alterations was 16/1070 (1.5%) CNA 24/1082 (2.2%) high mRNA expression, and 31/1066 (2.9%) mutations. Only amplifications were found within the BC patients. In the PC dataset, there were 15/489 (3.1%) CNA, 16/493 (3.2%) high mRNA expression, and 28/494 (5.7%) mutations reported in FOXA1. Deep deletion was found in one of the PC patients while the rest had amplifications. Due to insufficient numbers of Hispanic patients in the datasets, we compared the incidence of various FOXA1 alterations in White vs. Black/AA population using Fisher’s exact test. Only FOXA1 mutation rate was significantly higher (p =0.03) in Blacks/AA (2/7, 28.6%) compared to Whites (5/147, 3.4%) in PC, but not in the BC dataset. Comparing the separate results of the FOXA1 CNA and gene overexpression White vs. Black/AA patients were statistically significant in both BC and PC datasets. A majority of FOXA1 mutations were missense mutations with a few frame shifts in BC and PC. The missense mutation reported in both BC and PC datasets were D226G, D226N, and H247Y. Additional studies are necessary to understand the functional significance of these mutations on the development of cancer. Complete and larger datasets that include the race and ethnicity information from diverse group of patients as well as tumor molecular subtyping are also needed for the assessment of the mechanism of health disparity in BC and PC in minority population in the United States. Citation Format: Jennifer Torres, Hariprasad Thangavel, Xiaoyong Fu, Rachel Schiff, Meghana V. Trivedi. FOXA1 genetic alterations in Whites versus Blacks or African Americans in breast and prostate cancer [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr B078.

MD, FRCS, FRCRMeyerstein Institute of Oncology and Academic Department of Surgery, University College London Hospitals NHS Trust,London, UKIn Time magazine’s extensively researched breast cancerissue (June 10, 2002), one particular quote had a specialresonance for us. In the introduction to a remarkablycomprehensive article, Dr Julie Gralow, an Oncologist atthe Fred Hutchinson Cancer Research Centre in Seattle,stated ‘‘We may be far overtreating our patients… We’venow got women being diagnosed with tumours that wouldprobably never have been treated if we didn’t havemammography. They probably would have lived long,natural, healthy lives never knowing they had breastcancer’’ (J Gralow, quoted in [1]).For some years it has been apparent that, for manypatients, powerful treatment by surgery (even when limitedto tumour excision with breast preservation) together witha 6 week programme of radiation therapy may be morethan sufficient. We already know a good deal (althoughnot of course enough) about the profile of a typical breastcancer patient with low risk of local and distant recur-rence: a small, low or moderate grade tumour, surgicallycompletely excised, positive for oestrogen and/or proges-terone receptors, negative for HER2 and with negativeaxillary nodes. Post-menopausal patients clearly have alower incidence of local recurrence; for example, in thelarge study by Bartelink et al [2], patients over the age of60 years had a rate of local recurrence following 50 Gywhole breast radiation of only 4% (without an additionalboost), the rate reducing still further to 2.5% with anadditional 16 Gy given by electron beam therapy. Forpatients aged 41 to 50 years, the rates were 9.5% and 5.8%,respectively (median follow-up 5.1 years). What’s more, anever increasing number of patients now present with smalltumours (,1 cm) identified on mammographic screening,of whom approximately three-quarters will have oestrogenreceptor (ER)/progesterone receptor (PR) positive tumours,for which targeted hormone therapy with tamoxifen offerssustained long-term benefit for both local and distantrelapse [3, 4]. Using a well tolerated oral aromataseinhibitor such as Anastrazole reduces the risk still further(for both local and distant relapse), also, incidentally,reducing by three-quarters the risk of development of acontralateral primary breast cancer [5].For all these reasons, we strongly support Gralow’sview. Even in younger women known to be at higher riskof relapse, including those with axillary node-positivedisease, the use of systemic adjuvant cytotoxics sharplyreduces the risk of recurrence [3, 4, 6]. For hormonereceptor-positive patients, i.e. the large majority, adjuvanthormone therapy as well as surgical or medical oophor-ectomy all add further benefit [2–4, 6].What is the consequence of Gralow’s observation? Inthe past, it has been regarded as mere flight of fancy toimagine that we can identify patients at such low risk ofrecurrence that a less intensive form of treatment thanlocal surgical excision followed by whole breast irradiationcould be regarded as ‘‘adequate’’. In this sense, thisgeneral policy remains little different in principle from theequally compelling (in its day) policy of radical, then lessdamaging forms of mastectomy – although admittedly,using local excision, breast preservation and post-operativeradiotherapy is generally regarded as more ‘‘humane’’ eventhough attempts at demonstrating an improved quality oflife have been largely elusive [7]. None the less, theevolving history of local treatment for early breast cancerhas centred on an ever increasing recognition of theimportance of breast conservation for body image andcosmesis, an essential requirement for most women. Thishas largely been achieved by the increasing acceptance ofbreast-conserving surgery with post-operative radiotherapy[8]. Yet despite this ready acceptance, recent data from theworld’s largest ever randomized breast cancer study, withexcellent quality control and a high level of expertise,confirm a mastectomy rate approaching 50% [ATACTrialists Group, unpublished data].We believe that the time has come to move on further.For many patients, particularly those presenting over theage of 50 years with small, low grade, ER positive, axillarynode negative tumours, it is surely right to question thenecessity of a lengthy and sometimes damaging course ofradiation therapy. Radiation oncologists who are totallysatisfied with their often excellent cosmetic results and lowrelapse rates following standard treatment should bearin mind the work of the Oxford-based Early BreastCancer Trialists’ Collaborative Group, namely that despitea lower breast cancer cause-specific death rate in irradiatedpatients, the increased mortality for other non-cancercauses wipes out this advantage [9]. The assumption thatthe excess non-cancer-related deaths in this large meta-analysis were due essentially to reliance on older outmodedradiation techniques may be correct – but it remains anassumption only, and considerable additional data attestto the cardiac, pulmonary and neurological dangers ofwhole breast irradiation [10–12]. Moreover, the use ofanthracycline-based chemotherapy regimens apparentlyincreases some of these risks still further [13].

Does adjuvant therapy reduce postmetastatic survival?

Effects of radiotherapy and of differences in the extent of surgery for early breast cancer on local recurrence and 15-year survival: an overview of the randomised trials

In today’s healthcare setting, the accurate and timely diagnosis of breast cancer is critical for recovery and treatment in the early stages. In recent years, the Internet of Things (IoT) has experienced a transformation that allows the analysis of real-time and historical data using artificial intelligence (AI) and machine learning (ML) approaches. Medical IoT combines medical devices and AI applications with healthcare infrastructure to support medical diagnostics. The current state-of-the-art approach fails to diagnose breast cancer in its initial period, resulting in the death of most women. As a result, medical professionals and researchers are faced with a tremendous problem in early breast cancer detection. We propose a medical IoT-based diagnostic system that competently identifies malignant and benign people in an IoT environment to resolve the difficulty of identifying early-stage breast cancer. The artificial neural network (ANN) and convolutional neural network (CNN) with hyperparameter optimization are used for malignant vs. benign classification, while the Support Vector Machine (SVM) and Multilayer Perceptron (MLP) were utilized as baseline classifiers for comparison. Hyperparameters are important for machine learning algorithms since they directly control the behaviors of training algorithms and have a significant effect on the performance of machine learning models. We employ a particle swarm optimization (PSO) feature selection approach to select more satisfactory features from the breast cancer dataset to enhance the classification performance using MLP and SVM, while grid-based search was used to find the best combination of the hyperparameters of the CNN and ANN models. The Wisconsin Diagnostic Breast Cancer (WDBC) dataset was used to test the proposed approach. The proposed model got a classification accuracy of 98.5% using CNN, and 99.2% using ANN.

PurposeThe COVID-19 pandemic has impacted early breast cancer (EBC) treatment worldwide. This study analyzed how Brazilian breast specialists are managing EBC.MethodsAn electronic survey was conducted with members of the Brazilian Society of Breast Cancer Specialists (SBM) between April 30 and May 11, 2020. Bivariate analysis was used to describe changes in how specialists managed EBC at the beginning and during the pandemic, according to breast cancer subtype and oncoplastic surgery.ResultsThe response rate was 34.4% (503/1462 specialists). Most of the respondents (324; 64.4%) lived in a state capital city, were board-certified as breast specialists (395; 78.5%) and either worked in an academic institute or one associated with breast cancer treatment (390; 77.5%). The best response rate was from the southeast of the country (240; 47.7%) followed by the northeast (128; 25.4%). At the beginning of the pandemic, 43% changed their management approach. As the outbreak progressed, this proportion increased to 69.8% (p < 0.001). The southeast of the country (p = 0.005) and the state capital cities (p < 0.001) were associated with changes at the beginning of the pandemic, while being female (p = 0.001) was associated with changes during the pandemic. For hormone receptor-positive tumors with the best prognosis (Ki-67 < 20%), 47.9% and 17.7% of specialists would recommend neoadjuvant endocrine therapy for postmenopausal and premenopausal women, respectively. For tumors with poorer prognosis (Ki-67 > 30%), 34% and 10.9% would recommend it for postmenopausal and premenopausal women, respectively. Menopausal status significantly affected whether the specialists changed their approach (p < 0.00001). For tumors ≥ 1.0 cm, 42.9% of respondents would recommend neoadjuvant systemic therapy for triple-negative tumors and 39.6% for HER2 + tumors. Overall, 63.4% would recommend immediate total breast reconstruction, while only 3.4% would recommend autologous reconstruction. In breast-conserving surgery, 75% would recommend partial breast reconstruction; however, 54.1% would contraindicate mammoplasty. Furthermore, 84.9% of respondents would not recommend prophylactic mastectomy in cases of BRCA mutation.ConclusionsImportant changes occurred in EBC treatment, particularly for hormone receptor-positive tumors, as the outbreak progressed in each region. Systematic monitoring could assure appropriate breast cancer treatment, mitigating the impact of the pandemic.

Taxanes are tubulin-targeting agents that are highly active in the treatment of breast cancer. The lack of cross-resistance and limited overlapping toxicities of taxanes with other agents, such as anthracycline, made it possible to incorporate them in the adjuvant treatment of early breast cancer. When used alone or in combination with other cytotoxic agents, taxanes significantly improved response rate, time to progression, disease-free and in some trials over-all survival in patients with advanced or metastatic breast cancer. Mature data are now emerging from the early randomized clinical trials that consistently demonstrate a clear survival benefit of taxanes when combined with anthracycline. However, increased toxicities, especially hematological toxicities, were also observed. Various strategies to decrease the taxanes toxicities have been explored, including appropriate dosing and scheduling to optimize the therapeutic index, sequential rather than concurrent use of anthracycline and taxanes, the use of growth factor support and the removal of anthracycline, with encouraging results. The development of novel taxanes with less toxicities and use of molecular markers to target patients with taxane-responsive tumors are in early clinical trials. This review focuses on safety issues of taxanes in the adjuvant treatment of early breast cancer. Strategies to reduce the taxane toxicity and future direction of taxane research in early breast cancer will be discussed.

Reply to the letter to the editor ‘Patients' preference and informed consent’ by Pumo et al.

This study aims to develop an efficient and accurate breast cancer classification model using meta-learning approaches and multiple convolutional neural networks. This Breast Ultrasound Images (BUSI) dataset contains various types of breast lesions. The goal is to classify these lesions as benign or malignant, which is crucial for the early detection and treatment of breast cancer. The problem is that traditional machine learning and deep learning approaches often fail to accurately classify these images due to their complex and diverse nature. In this research, to address this problem, the proposed model used several advanced techniques, including meta-learning ensemble technique, transfer learning, and data augmentation. Meta-learning will optimize the model’s learning process, allowing it to adapt to new and unseen datasets quickly. Transfer learning will leverage the pre-trained models such as Inception, ResNet50, and DenseNet121 to enhance the model’s feature extraction ability. Data augmentation techniques will be applied to artificially generate new training images, increasing the size and diversity of the dataset. Meta ensemble learning techniques will combine the outputs of multiple CNNs, improving the model’s classification accuracy. The proposed work will be investigated by pre-processing the BUSI dataset first, then training and evaluating multiple CNNs using different architectures and pre-trained models. Then, a meta-learning algorithm will be applied to optimize the learning process, and ensemble learning will be used to combine the outputs of multiple CNN. Additionally, the evaluation results indicate that the model is highly effective with high accuracy. Finally, the proposed model’s performance will be compared with state-of-the-art approaches in other existing systems’ accuracy, precision, recall, and F1 score.

Adjuvant therapy of primary breast cancer. 4th International Conference on Adjuvant Therapy of Primary Breast Cancer St. Gallen, Switzerland.