Number Of Breast Cancer Cases Research Articles

Random effects models of tumour growth for investigating interval breast cancer.

In Nordic countries and across Europe, breast cancer screening participation is high. However, a significant number of breast cancer cases are still diagnosed due to symptoms between screening rounds, termed "interval cancers". Radiologists use the interval cancer proportion as a proxy for the screening false negative rate (ie, 1-sensitivity). Our objective is to enhance our understanding of interval cancers by applying continuous tumour growth models to data from a study involving incident invasive breast cancer cases. Building upon previous findings regarding stationary distributions of tumour size and growth rate distributions in non-screened populations, we develop an analytical expression for the proportion of interval breast cancer cases among regularly screened women. Our approach avoids relying on estimated background cancer rates. We make specific parametric assumptions concerning tumour growth and detection processes (screening or symptoms), but our framework easily accommodates alternative assumptions. We also show how our developed analytical expression for the proportion of interval breast cancers within a screened population can be incorporated into an approach for fitting tumour growth models to incident case data. We fit a model on 3493 cases diagnosed in Sweden between 2001 and 2008. Our methodology allows us to estimate the distribution of tumour sizes at the most recent screening for interval cancers. Importantly, we find that our model-based expected incidence of interval breast cancers aligns closely with observed patterns in our study and in a large Nordic screening cohort. Finally, we evaluate the association between screening interval length and the interval cancer proportion. Our analytical expression represents a useful tool for gaining insights into the performance of population-based breast cancer screening programs.

Feature Selection-based Machine Learning Comparative Analysis for Predicting Breast Cancer

ABSTRACT Breast cancer is a serious disease, and therefore early detection is crucial for successful treatment and patient management. Unfortunately, globally, the number of breast cancer cases is increasing due to various multifaceted factors. It is currently one of the leading causes of cancer deaths in women, worldwide. Cancerous cells in the breast can form lumps that impact the patient’s health, and even seemingly harmless tumors could be fatal if undiagnosed early enough. Fortunately, artificial intelligence techniques have proven effective in detecting diseases, and doctors can therefore use them to effectively and accurately diagnose breast cancer early. This paper explores the use of genetic algorithms, ant colony optimization, and Hybrid Hopfield Neural Network-E2SAT (HHNN-E2SAT) models, for breast cancer prediction. The HHNN-E2SAT models outperform standard algorithms like the Random Forest and Support Vector Machines, achieving over 98% on all performance metrics (i.e. Accuracy, F1-score, Sensitivity, Specificity, and Precision).

Breast Cancer Detection Using Deep Learning

The most frequently occurring cancer among Indian women is breast cancer. The second major cause of women's death is breast cancer (after lung cancer). 246,660 of women's new cases of invasive breast cancer are expected to be diagnosed in the US during 2016 and 40,450 of women’s death is estimated. The number of breast cancer cases is steadily growing especially with increasing number of ageing population. Breast cancer is a type of cancer that starts in the breast. Cancer starts when cells begin to grow out of control. Breast cancer cells usually form a tumour that can often be seen on an x-ray or felt as a lump. The screening practice using mammography needs to be better and potentially efficient. There is always room for advancement when it comes to medical imaging. Early detection of cancer can reduce the risk of death for cancer patients. Breast cancer can spread when the cancer cells get into the blood or lymph system and are carried to other parts of the body. This overview looks at the results of a proposed system for automatically diagnosing breast cancer using several convolutional neural network (CNN) designs and compares them to those achieved using machine learning (ML) techniques. All buildings were built from a large database. Validation tests were conducted in order to provide quantifiable results using the performance parameters of each approach. Functions like VGG16 and ResNet50 are used in this model to improve the accuracy of the model. The cause of Breast Cancer includes changes and mutations in DNA. Women are seriously threatened by breast cancer with high morbidity and mortality. The breast cancer dataset is publicly available on the UCI Machine Learning Repository and therefore the implementation phase dataset is going to be partitioned as 80% for the training phase and 20% for the testing phase then apply a significant performance in respect of all parameters.

Screening Mammography for Males With Elevated Breast Cancer Risk, Mutation Carriers, and Gynecomastia

IntroductionThe recommendations for annual mammography for male carriers with gynecomastia are controversial. This study investigated the potential link between gynecomastia and breast cancer in male carriers. Patients and MethodsThe database of a tertiary medical center was retrospectively searched for all male patients who underwent at least 1 digital mammography study from 2016 to 2023. Known carriers of a pathogenic variant in a high-risk breast-cancer gene were identified. Patients were stratified by carrier status, diagnosis of breast cancer, and diagnosis of gynecomastia. Data on demographics, hormone profile, and pathology results were compared. ResultsThe cohort included 446 men of whom 82 were known carriers. Gynecomastia was diagnosed by mammography in 251 patients: 239/364 noncarriers (66%) and 12/82 carriers (15%) (P < .0001). Breast cancer was found in 21/364 noncarriers (6%) and 6/82 carriers (7%) (P < .6), and in 10/251 patients with gynecomastia (4%) and 17/193 (9%) without gynecomastia (P < .05). Among patients without gynecomastia, the number of breast cancer cases was similar in carriers and noncarriers (P = .3). Among patients with gynecomastia, the rate of breast cancer was higher in carriers (P < .08). On logistic regression analysis, the effect of gynecomastia on carriers was significant (P = .02). The odds ratio for a breast cancer diagnosis was 5.8 in the presence of gynecomastia (95% CI, 1.1-31, P < .04) and 0.52 in the absence of gynecomastia (95% CI, 0.2-1.7, P < .3). ConclusionGynecomastia may be associated with an increased risk of breast cancer in carriers. Larger studies are needed to determine whether and when to screen male carriers.

Clinicopathological Profile Of Her2 Positive (Non-Luminal) Breast Cancer Subtype At Haji Adam Malik General Hospital From 2020-2021

Background: Breast cancer is one of the cancers with the highest prevalence in Indonesia. According to GLOBOCAN data for 2020, the number of breast cancer cases reached 68,858 (16.6%) cases out of a total of 396,914 new cancer cases in Indonesia. There are many factors that can trigger cancer with different clinical manifestations and subtypes from one event to another, so researchers are interested in researching the profile of breast cancer patients with the HER2 subtype at H. Adam Malik General Hospital in 2020-2021.Objective: In the present study, we aim to determine the clinicopathological profile of Her2 positive (non-luminal) breast cancer subtype patients at Haji Adam Malik General Hospital from 2020-2021.Methods: The method used in this study is descriptive quantitative with total sampling technique. The data samples was obtained from medical records of breast cancer patient with her2 positive (non-luminal) subtype which was then sorted according to the availability of characteristic needed for this study. Results: majority of breast cancer patients with her2 positive (non-luminal) subtype at H Adam Malik General Hospital in 2020-2021 was within the age group of &gt; 50 years, with all married status. the BMI of the majority of patients (68.6%) was normal weight, all respondent admit there was no family history diagnosed with cancer (100%), majority tumor size (52,9%) is &gt;5 cm, with most patients having cancer metastasized to 1-3 lymph nodes (54,9%), distant metastases only in 39,2% of the total sample observed, majority (35,3%) histopathological degree is in grade 1 and grade 3 , the histopathological classification of the majority (86,3%) was IDC type. Conclusion: Overall there is diversity of frequencies within the observed clinicopathological characteristics.

Work Ability, Anxiety, and Depression among Long-Term Breast Cancer Survivors of Northern Kerala, India; A Historical Cohort Study.

Increasing number of breast cancer cases, and improved survival due to advancements in early detection, and treatment resulted in an increase in women living beyond a cancer diagnosis. Survivors have to face long-term physical effects as well as psychosocial issues post-treatment. This study aims to study survivourship in terms of work ability, anxiety and depression. Retrospective cohort study on female breast cancer survivors from Hospital Based Cancer Registry (HBCR) of a Tertiary Cancer Centre (TCC). Data from 2016 (n=534) were collected from the medical records, and a follow-up survey (n=209) was conducted in 2022 to study their survivorship issues. In 2022, the mean age of the cohort (n=209) was 55.45 ± 9.36. The mean work ability score was 40.7±5.73 (95% CI 39.92 to 41.48). In the multivariate binary logistic regression model, those who were married (OR 7.15, 95%CI 2.61 to 19.55), disease-free (OR 15.27, 95% CI 2.36 to 98.7), employed (OR 9.09, 95%CI 1.12 to 73.5), having no fatigue (OR 2.6, 95% CI 1.05 to 6.48), no pain (OR 3.11, 95% CI 1.16 to 8.35), and no depression (OR 6.58, 95% CI 1.82-23.8) were found to have optimal work ability. Anxiety (OR 4.93, 95% CI 1.76 to 13.76), and sub-optimal work ability (OR 4.22, 95% CI 1.39 to 12.77) were predictors of depression among survivors. Disease status and fatigue were associated with all three dimensions of survivorship in our study. Understanding survivorship will help improve health outcomes in this population. In our study, work ability, anxiety, depression, and their associated factors were found to be interrelated. Interventions in these areas can go a long way in improving breast cancer survivorship.

Pengaruh Promosi Kesehatan dan Teknologi Tepat Guna Pemeriksaan Payudara Sendiri (SADARI) pada Remaja Putri di SMP Negeri Tandam Hulu 1

Information from the Indonesian Ministry of Health in 2013, data obtained on the number of breast cancer cases was 819 and the number of deaths was 217. There is a lack of public awareness of breast cancer detection so that every year breast cancer cases increase. The aim of the research for students is to increase knowledge and skills through BSE training for Young Women. The activity was carried out at SMP N 3 Tandam Hulu 1 for young women aged 13 to 15 years totaling 55 female students. The research used the form of outreach activities, providing material about breast cancer and awareness training. The measurements carried out provided a questionnaire as a measuring tool. The method used is a measuring instrument that provides pre-test and post-test questionnaires to measure the level of knowledge and skills of young women in BSE training.

Impacts of the COVID-19 pandemic on the breast cancer control pathway in Ireland

Abstract Background The COVID-19 pandemic caused unprecedented disruption to healthcare services worldwide including cancer services. The aim of this study is to assess the impact of the COVID-19 pandemic on aspects of the breast cancer control pathway in Ireland, including case counts, method of presentation, stage distribution, and treatment. Methods Analyses used data from the National Cancer Registry Ireland available as of April 2023. For assessments of case counts, 2020 data was compared to ‘expected’ case counts projected from a Joinpoint regression model of the last stable trend in breast cancer cases up to 2019. For assessments of method of presentation, stage distribution, and treatment, 2020 data was compared to equivalent 2019 data. Results There was a 23% reduction in number of breast cancer cases diagnosed in in Ireland in 2020 than expected from pre-2020 trends. Comparing methods of presentation, screen-detected tumours showed the largest reduction from 2019 to 2010. There was comparatively little change in numbers of breast cancers presenting through symptoms. Comparing cancer stage from 2019 to 2020, there was a significantly larger reduction in pT1 tumours than in pT2, or pT2-3, or pT2-4 tumours. Similarly, there was a larger reduction in Stage I than in any other stage and in Grade 1 than in Grade 2 or Grade 2-4 cancers. Investigation of breast cancer treatment showed a small reduction in the percentage of cases treated by surgery and by radiotherapy but no apparent change in the percentage of cases receiving chemotherapy/immunotherapy. Conclusions Patient behavioural changes, pauses in screening, and restricted healthcare access as a result of COVID-19 likely contributed to the observed reductions in case counts and screen-detection of breast cancer. The reduction in early stage breast cancers in 2020 is likely also related to screening disruption. Treatment modes may have been altered during the pandemic to reduce infection risk to cancer patient in hospitals. Key messages • The COVID-19 pandemic caused disruption to the breast cancer control pathway in Ireland. • Case counts and screen-detection of breast cancer as well as the proportion of early stage breast cancers diagnosed were reduced in Ireland in 2020.

Diagnosis and treatment of breast cancer in Denmark during the COVID-19 pandemic: a nationwide population-based study

Background The COVID-19 pandemic was a global health crisis with population-wide behavioural restrictions imposed worldwide to reduce transmission of infection and to limit the potential burden on the healthcare systems. We examined whether there was any change in the diagnosis or treatment of breast cancer during the pandemic as compared to previous years. Material and Methods The study population comprised all women aged ≥18 years diagnosed with breast cancer in 2015-2021 with data obtained from the clinical quality registry of the Danish Breast Cancer Cooperative Group (DBCG). Data on socioeconomic factors were retrieved from Statistics Denmark. Prevalence ratios (PR) with 95% confidence intervals (CI) were estimated from a generalised linear model (GLM) with a log link for the Poisson family with robust standard errors (SE) of each outcome, using the COVID-19 pandemic period in Denmark as the exposure of interest. Results In total, 30,598 breast cancers were diagnosed during the study period. There was a small decrease (4.5%) in the total number of breast cancer cases in 2020 compared with previous years. During the pandemic, a lower proportion of the patients diagnosed with breast cancer had a short educational level (28.5 vs. 26.9%; PR = 0.91; 95% CI: 0.88–0.95), a low income (20.5 vs. 19.0%; PR = 0.90; 0.85-0.95) and fewer than expected in the age group 60-69 years (27.8 vs. 25.3; PR = 0.90; 0.86-0.94) were diagnosed, as compared with the pre-pandemic period. No difference in type of surgery or tumour size was observed. A higher proportion of patients received neo-adjuvant chemotherapy (49.0 vs 55.0%; PR = 1.15; 1.06–1.24), whereas a lower proportion received adjuvant chemotherapy (93.5 vs 85.6%; PR = 0.92; 0.90–0.93) during the pandemic, compared with the pre-pandemic period. Conclusions During the pandemic, a small decrease in the number of breast cancer diagnoses was observed particularly among socially disadvantaged groups. Overall, the quality of breast cancer treatment was maintained.

Correlation between Age at First Menarche and Breast Cancer in Dr. Cipto Mangunkusumo National General Hospital Jakarta in 2010-2014

Background: Breast cancer is one of the most common cancer among Indonesian females. Many risk factors can increase the chance of developing breast cancer. Hormonal factor seems to play a role in many cases of breast cancer. The aim of this research is to determine the relationship between age at menarche and breast cancer in Dr. Cipto Mangunkusumo National General Hospital Jakarta in 2010-2014.Methods: The retrospective research is using cross-sectional design study with random sampling technique. There are 98 samples. The samples were taken in Archive Unit of Anatomical Pathology of FMUI with a further investigation in Medical Record Unit and Medical Department of Surgery in Dr. Cipto Mangunkusumo National General Hospital Jakarta. The data were analyzed by using chi square test then Fisher test. Results: There is no statistically significant between age at menarche and breast cancer in Dr. Cipto Mangunkusumo National General Hospital Jakarta in 2010-2014 (p&gt;0,05). The results of this study also indicate that the 40-49 year age group is the age group that has the highest number of breast cancer cases compared to other age groups. The age at first menstruation &gt; 12 years was associated with the highest frequency of breast cancer cases in the study population. Conclusion: The age at first menstruation statistically did not significantly affect breast cancer incidence in Dr. Cipto Mangunkusumo Hospital Jakarta in 2010-2014. However, further research using different study designs and larger sample sizes required.

Comparison of 5- and 10-year breast cancer risk predictions.

10529 Background: Breast cancer risk assessment is valuable in personalizing risk-reduction and screening approaches for the general population. Maximizing the benefits while reducing the harms associated with current breast cancer screening and risk-reduction recommendations should increase the efficacy of these paradigms. Because healthcare providers have limited time with their patients, we developed a risk prediction model, BRISK, which uses the most important clinical risk factors for breast cancer (in an easily collected format), polygenic risk and mammographic density. We previously validated BRISK 5-year risk predictions and found that it performed better than IBISv7 and BCRAT. Methods: The dataset comprised 241,633 women (mean age at baseline assessment = 56.6 years). We included all races/ethnicities available in the UK Biobank. There were 3726 women affected during the first five years of follow-up and 7482 women affected during the full 10 years of follow-up. We compared the performance of the 5-year and 10-year risk predictions by assessing the association with breast cancer using Cox regression to estimate the hazard ratio (HR) per SD of risk, discrimination using calculating Harrell’s C-index and calibration using logistic regression to estimate the slope and the intercept of the logit of the risk predictions. Nelson–Aalen estimates of the hazard function by quintiles of risk and standardized incidence ratios (SIRs) of the number of breast cancer cases expected were used to illustrate performance. Results: The predictive performance of BRISK was consistent for 5-year and 10-year risk predictions. Discrimination was similar, with a Harrell’s C-index of 0.645 (95% CI = 0.636, 0.654) for the 5-year risk and of 0.638 (95% CI = 0.632, 0.645) for the 10-year risk. We used Nelson_Aalen cumulative hazard estimates to compare breast cancer incidence by risk quintile for both 5 and 10-year risk. Both risk scores overestimated risk in the top two deciles with the 5-year expected risks of 2.8% and 5.0% corresponding to observed risks of 2.3% and 3.3%. The 10-year expected risks for the top two deciles were 5.6% and 9.8% while the corresponding observed risks were 4.6% and 6.4%. Finally, we used clinically actionable thresholds to show the standard incidence ratios (SIR) of 1.77 (95% CI = 1.69, 1.85) for women ≥3% 5-year risk and 2.05 (95% CI = 1.93, 2.18) ≥8% 10-year risk. Conclusions: The BRISK 5-year and 10-year risk prediction perform equally well. There is an overestimation of risk for the top decile in both models. This is important to consider in risk-management conversations between clinician and patient. While the observed risk of the top decile remained above the 3% 5-year risk threshold used in the United States, the top decile observed risk dropped below the 8% 10-year risk threshold used in the United Kingdom. Risk scores are not used in isolation, but it may be preferable to err on the side of overestimation rather than underestimation.

Breast Cancer and SARS-Cov2: Lessons from a Pandemic.

The COVID-19 pandemic introduced drastic containment measures, which had a direct impact on breast cancer management. During the first wave, a delay in care and a decrease in new consultation numbers was observed. It would be interesting to study the resulting long-term consequences on breast cancer presentation and time to first treatment. This retrospective cohort study was conducted at the surgery Department of the Anti-Cancer Center of Nice, France. Two periods of 6 months were compared: a pandemic period from June to December 2020 (after the end of the first wave), and a control period one year earlier. The primary endpoint was to measure the time to care access. The patients and cancer characteristics and the management type were also compared. A total of 268 patients underwent diagnosis for breast cancer in each period. The time from biopsy to consultation was shortened after the containment was lifted (16 days vs. 18 days, p=0.024). The time between first consultation and treatment was unchanged between the two periods. The tumor size was larger in the pandemic period (21 mm vs. 18 mm, p=0.028). The clinical presentation was different: 59.8% of patients consulted for a palpable mass in the pandemic period, vs. 49.6% in the control period (p=0.023). There was no significant change in therapeutic management. The use of genomic testing was significantly increased. The number of breast cancer cases diagnosed decreased by 30% during the first COVID-19 lockdown. Even though a rebound was expected after the first wave, the number of consultations for breast cancer remained constant. This finding shows the fragility of screening adherence. It is necessary to reinforce education in the face of crises that may be repeated. Management of breast cancer did not change, which is a reassuring aspect regarding the care pathway in anticancer centers.

Health-Seeking Behavior Returning to Normalcy Overcoming COVID-19 Threat in Breast Cancer.

The coronavirus disease 2019 (COVID-19) outbreak has significantly impacted the diagnosis and treatment of breast cancer. Our study investigated the change in diagnosis and treatment of breast cancer with the progress of COVID-19 pandemic. The study group comprised 6,514 recently diagnosed breast cancer patients between January 1, 2019, and February 28, 2021. The patients were divided into two groups: pre-COVID-19 period (3,182; January 2019 to December 2019) and COVID-19 pandemic period (3,332; January 2020 to February 2021). Clinicopathological information related to the first treatment after breast cancer diagnosis was retrospectively collected and analyzed in the two groups. Among the 6,514 breast cancer patients, 3,182 were in the pre-COVID-19 period and 3,332 were in the COVID-19 pandemic period. According to our evaluation, the least breast cancer diagnosis (21.8%) was seen in the first quarter of 2020. The diagnosis increased gradually except for the fourth quarter in 2020. While early-stage breast cancer was diagnosed 1,601 (48.1%) during the COVID-19 pandemic (p=0.001), the number of surgical treatments increased 4.6% (p < 0.001), and the treatment time was slightly shorter 2 days (p=0.001). The breast cancer subtype distribution was not statistically different between the pre-COVID-19 and COVID-19 period groups. In the early stages of the pandemic, the number of breast cancer cases temporarily decreased; however, they stabilized soon, and no significant differences could be identified in the diagnosis and treatment when compared to the period before the pandemic.

Abstract P4-03-08: Breast cancer incidence rates in Japan turned into bimodal age distribution in this decade

Abstract BACKGROUND: Japan is the globe’s fastest ageing country: 32.0 % of the female population are 65 or older in 2021. The birth rate was 1.30 children per woman in 2021. Japan’s population has been constantly shrinking since 2011 with aging. The number of breast cancer cases has increased rapidly in the course of low birth rate and aging population. Breast cancer has increased and accounted for the first place of all of cancers in Japanese women. OBJECTIVES; Number of breast cancer has increased recently and accounted for the first place of all of female cancers in Japan. Detailed analytics of the increase and aging of breast cancer are not studied. We elucidate the transformation of Japanese breast cancer by ages at diagnosis over the past decade. MATERIALS: We used the registry data of Japanese Breast Cancer Society and Statistics Bureau of Japan in 2018. Female breast cancer new cases were 59,389 patients in 2008 and 93,858 patients in 2018, respectively. The total female population was 65.441 million in 2008 and 64.911 million in 2018, respectively. 65 years and older women accounted for 23.4% in 2008 and 31.0 % in 2018, respectively. METHODS: We compared incidences and incidence rates of breast cancer by ages in 2008 and 2018, respectively. We used the statistical method of Ameijeiras-Alonso et al for mode assessment. RESULTS; Total number of incidences and incidence rates of breast cancer in 2018 were higher than those in 2008 among all ages. Difference of number of incidences were maximum in age of 60-69 in both years. Difference of incidence rates in both years reached maximum in age of 75-79. Incidence rates in 2008 showed unimodal age distribution with the gentle peak. Incidence rates in 2018 showed bimodal age distribution with two peaks of 45-49 and 65-69. CONCLUSIONS; Incidences and incidence rates of breast cancer increased rapidly among all ages in this decade in Japan. The incidence rates increased most in ages of 75-79 and turned into bimodal age distribution in 2018. Citation Format: Ken Uchida, Hitoshi Ohashi, Hiroko Nogi, Satoki Kinoshita, Ryouko Nosaka, Makiko Kamio. Breast cancer incidence rates in Japan turned into bimodal age distribution in this decade. [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P4-03-08.

Study on Breast Cancer in Kazakhstan Using the Functional Time Series.

In Kazakhstan and Central Asia, breast cancer (BC) is the most common malignancy among women. However, no large-scale study on breast cancer using the functional time series approach has been carried out in Kazakhstan. A functional assessment of the age-period-cohort model (APC) and the survival rate (period 2017-2021) was used in the retrospective study. Clinical and demographic information on patients was analysed, including age, gender, region of residence, kind and stage of tumour, occupation, socioeconomic standing, nationality, and specifics of treatment and its outcomes. Additionally, the relationship between nationality, stage, and residency region and the survival rate of breast cancer patients was investigated too. The data of n=22,736 breast cancer patients were analysed. The highest number of breast cancer cases reported was 4,945 (21.7%), in 2019. In 2021, n =4,939 (21.7%) cases were detected, while in 2020, n=4,222 (18.6%) cases were observed. The patients with breast cancer in stages I and Ia were recognized in 6,585 (29% of cases), while those in stages Ib and Ic were confirmed in 8687 (38.2% of cases). In n=10,147 (44.6%) cases, a malignant tumour of the upper outer quadrant of the breast (C50.4) was predominant. Kazakhs made up the majority (n=10,939, 48.1%) of patients with a primary validated diagnosis of breast cancer, followed by Russians (n=7527, 33.1%). Germans had the lowest survival rate overall (11.4 ± 1.7 months) (p ≤ 0.05) (95% CI: 8.0-14.7 months). Uzbeks showed relatively high survival rates of 18.3 ± 1.6 months (95% CI: 15.1-21.5 months) (p ≤ 0.05). The Aktobe region had the lowest breast cancer survival rates, measuring 12.1±0.9 months (95% CI: 10.3-13.9 months) (p ≤ 0.05). The highest survival rates, 18.0±1.3 months (95% CI: 15.5-20.5 months) and 17.9±1.4 months (95% CI: 15.3-20.7 months), were seen in Shymkent and Zhambyl regions (p ≤ 0.05), respectively. The prevalence of breast cancer increases after 37.5 years, according to the results of the APC analysis, with an indicator of 0.572 (95% CI: -0.41 - 1.56), maintaining a steady upward trend in the age range from 42.5 years to 62.5 years. Despite a slight drop in the disease's frequency, the incidence of breast cancer in women 37.5 years and older has been stable over the past five years. Additionally, it was shown that the country's northern regions had a higher incidence of breast cancer cases than the southern and western regions. Our results show the significance of demographic characteristics such as age and location for the development of preventive measures and effective treatment.

Toward Better Analysis of Breast Cancer Diagnosis: Interpretable AI for Breast Cancer Classification

Recently, some countries have been distressing with the increasing number of breast cancer cases. Those cases were extremely increased in every year. Practicaly, the increasing number of patients was caused by the manual examination. Recently, some researchers have been done in the development of AI method for solving this problem. However, AI itself still has limitation since it worked in the black-box approach which was difficult to be trusted. Thus, to overcome those problems, we proposed a method that was able to classify breast ultrasound images into two classes (benign and malignant) and able to explain how the prediction was made. Our proposed method consisted of four processes i.e., pre-processing step, development of CNN model, interpretable step and evaluation. In this research work, our proposed method performed into 780 breast ultrasound images divided into three classes (133 normal, 210 malignant, and 437 benign). In the training process, our proposed method obtained training accuracy of 0.9795, training loss of 0.0675. The validation process obtained validation accuracy of 0.8000 and validation loss of 0.5096. While, in the testing process, our proposed method achieved accuracy of 0.7923. In the interpretable process using LIME, the LIME result is covered by doctor visualization. It was indicated that LIME was suitable enough in visualizing the important features of breast cancer severity. Regarding to the results, our proposed method has a potensial to be implemented as an early detection method for classifying malignancy of breast cancer in order to help the doctor in the screening process

Delayed Diagnosis and Prognostic Impact of Breast Cancer During the COVID-19 Pandemic

BackgroundBreast screening services were suspended for several months owing to the coronavirus disease 2019 (COVID-19) pandemic. We estimated the potential impact on breast cancer mortality using long-term global observations. However, the magnitude of the impact may vary across countries; therefore, we conducted an analysis and modeling study of this impact in Japan. Patients and MethodsWe compared the clinicopathological features of breast cancers between the nonpandemicgroup (April 1, 2019 to October 31, 2019) and the pandemic group (April 1, 2020 to October 31, 2020). We also compared the estimated 10-year survival rates between the two groups based on the weighted average of the 10-year survival rate by clinical stage and site (2004–2007). ResultsResults...Pandemic-related disruption decreased the number of breast cancer cases from296 to 249 during both 7-month periods. The percentage of patients with stage IIB or higher disease was significantly higher in the pandemic group than in the non-pandemic group (22.0% vs. 31.3%, P = 0.0133). The percentage of cases with a Ki-67 labeling index higher than 20% tended to be higher in the pandemic group than in the non-pandemic group (62.2% vs. 54.4%). The estimated 10-year survival rate was lower in the pandemic group than in the non-pandemic group (83.9% vs. 87.9%, 95% confidence interval of the difference: 0.87−8.8, P > 0.05). ConclusionWe found more aggressive and advanced disease afterthe suspension of breast cancer screening services owing to the COVID-19 pandemic. This may have affected the long-term clinical outcomes of patients with breast cancer.

The Detection of Breast Cancer for Young Woman in Covalima Municipality, Republica Democratica de Timor Leste

Introduction: According to the World Health Organization, there are 2.3 million breast cancer diagnoses and globally 685,000 breast cancer mortality rates. In 2020 women who have had problems with breast cancer are 7.8 million annually worldwide. A study by the Global International Agency for Research of Cancer (2018) reported that the highest number of breast cancer cases was 674,693, with 25.5% and a mortality rate of 310.577 or 13.8%. And continues to be published by the Global Cancer Observatory (2019), showing that the incidence of breast cancer is 136.2% of the population, and the highest rate of breast cancer occurs in women with 42.1%, followed by population mortality. Objective: To find out how to detect breast cancer in adolescent girls in Covalima City, Timor Leste. Method: This study used quantitative and quantitative methods together, specifically a cross-sectional study of adolescent girls in the municipality of Covalima where interviews with young girls continued their studies in secondary schools. Results: Based on the results of research conducted by young women in high schools in the city, the understanding of describing early detection of breast cancer is 49%, and most young women know information about breast cancer even though the information they have is accessed or someone shares about breast cancer. Conclusion: Students have sufficient experience in how to detect breast cancer early and prevent breast cancer

Breast Cancer in Geriatric Patients: Current Landscape and Future Prospects.

Breast cancer is the most common cancer diagnosed among women worldwide and more than half are diagnosed above the age of 60 years. Life expectancy is increasing and the number of breast cancer cases diagnosed among older women are expected to increase. Undertreatment, mostly due to unjustifiable fears of advanced-age and associated comorbidities, is commonly practiced in this group of patients who are under-represented in clinical trials and their management is not properly addressed in clinical practice guidelines. With modern surgery and anesthesia, breast surgeries are considered safe and is usually associated with very low complication rates, regardless of extent of surgery. However, oncoplastic surgery and management of the axilla can be tailored based on patients’- and disease-related factors. Most of chemotherapeutic agents, along with targeted therapy and anti-Human epidermal growth factor receptor-2 (HER2) drugs can be safely given for older patients, however, dose adjustment and close monitoring of potential adverse events might be needed. The recently introduced cyclin-D kinase (CDK) 4/6-inhibitors in combination with aromatase inhibitors (AI) or fulvestrant, which changed the landscape of breast cancer therapy, are both safe and effective in older patients and had substituted more aggressive and potentially toxic interventions. Despite its proven efficacy, adjusting or even omitting adjuvant radiation therapy, at least in low-risk older patients, is safe and frequently practiced. In this paper, we review existing data related to breast cancer management among older patients across the continuum; from resection of the primary tumor through adjuvant chemotherapy, radiation and endocrine therapy up to the management of recurrent and advanced-stage disease.

Estrogen, Progestrone Receptor and Her2/Neu Expressions incases of Breast Cancer

To correlate ER, PR and HER2/neu expressions with established prognostic factors viz. type of tumour, tumour size, tumour grade, tumour necrosis, lymphovascular invasion (tumor emboli), and axillary lymph node metastasis status. To correlate immunehistochemical marker status ( ER, PR and HER2/neu) with clinical details (age and sex) of patients. The investigative research of Progesterone receptor (PR), Estrogen receptor (ER), as well as HER-2/neu expressions in cases of developing breast carcinoma was carried out over a period of 2 years from June 2015 to May 2017 which included 101 breast cancer cases. Palpable breast lump with or without pain were most frequent complaints. Maximum number of breast cancer cases revealed involvement of left breast. It was found that ER and PR expression was strongly correlated. No significant association was found between the presence of ER, PR expression as well as the size of the tumor. ER and PR negativity was associated with breast carcinoma cases having axillary lymph node metastasis. Out of 101 breast cancer cases tumor necrosis was present in 38.61%. However, the occurrence or absence of tumour necrosis in ER, PR expression was not strongly linked. Tumor emboli were noted in 31.68% of cases. In case of breast cancer with tumor emboli decreased ER and PR expression was observed.