Early Cancer Detection Research Articles

Performance of the National Cancer Screening Program for Gastric Cancer in Korea

In Korea, the National Cancer Screening Program for Gastric Cancer (NCSP-GC) was implemented in 1999 to reduce the mortality associated with gastric cancer, the most common cancer in Korea until 2018. In 2021, approximately 7.76 million screening endoscopies were performed as part of the NCSP-GC, including 10664 participants (37.2% of the total gastric cancer cases in 2021; 10909 of the 29361 cases) with histologically confirmed gastric cancer, according to data from the Korean National Health Insurance Service. The endoscopic screening component of the NCSP-GC has contributed to the early detection of gastric cancer and the reduction of its mortality. This review evaluates the performance and limitations of the endoscopic screening component of the NCSP-GC and discusses strategies to overcome limitations.

Abstract B025: Surveillance outcome in individuals at high risk of pancreatic cancer

Abstract INTRODUCTION: Pancreatic ductal adenocarcinoma (PDAC) has a poor 5-year survival rate. PDAC surveillance is recommended in high-risk individuals (HRIs) with strong PDAC family history or a pathogenic germline variant (PGV) in a PDAC susceptibility gene. We aimed to explore a potential correlation between genetic status, extent of family history, pancreatic findings, and surveillance implications in heterogeneous PDAC HRIs. METHODS: from January 2015 up to date, a total of 340 HRIs from 291 families visited our pancreatic cancer high-risk clinic. Surveillance included annual clinic visits, EUS/MRI imaging, genetic and laboratory blood testing. Participants completed a questionnaire that included personal and familial medical history, dietary habits, daily activities with emphasis on smoking habits, alcohol use, and physical activity. RESULTS: Our cohort was divided into 3 groups: familial pancreatic cancer that include individuals with family history of 2 or more first degree family (FDR) with PDAC (FPC; 96 individuals), familial non-FPC, families with at least 2 biological relatives with PDAC and not meeting FPC criteria, (119 individuals), and hereditary pancreatic cancer (PC), individuals with PGV in a PC susceptibility gene and a family member with PDAC carrying the same PGV (124 individuals). The cohort average age at first visit was 54 years with 44% male and 56% female ratio. Seventy percent of the cohort was of Jewish Ashkenazi decent. Genetic testing was performed in several steps, first BRCA1/2 founder mutations was performed in all individuals followed by genetic panels and whole exome sequencing (WES). PGVs were detected in 36.4% of all families. There was no significant difference in the genetic finding between the FPC and non-FPC groups (11% and 9.6% respectively). Of the study cohort 35% were screened by EUS and 8% by MRI/MRCP. Pancreatic lesions detected included 11 cases of new PDAC (3.2%), 69 cystic lesions (20.3%), 43 cases early chronic pancreatitis (12.6%) and 11 cases of main pancreatic duct dilation (3.2%). To better understand the risk of PDAC development in HRIs we recently added a novel cell-free chromatin blood test for early cancer detection (in collaboration with SENSEERA, Israel) and compared it to EUS imaging results. The test provides multidimensional epigenetic information that sheds light on the identity and the transcriptional state of the cells that are dying in the body of the patient. Our preliminary results show nice separation between the healthy control and PC groups. PC HRIs show slight increase in score compared to the general population while individuals with worrisome features show substantial increase compared to HRIs with no EUS findings. DISCUSSION: Surveillance seems effective for detection of early-stage PDAC and precursor lesions. However, screening strategy can be improved by adding newer modalities like chromatin-based tests that might help to further define the risk of cancer development in HRIs. Citation Format: Merav Ben Yehoyada, Erez Scapa, Oren Shibolet, Guy Rosner. Surveillance outcome in individuals at high risk of pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr B025.

Abstract B023: Unravelling fibroinflammatory and immune signatures for pancreatic cancer early detection

Abstract Pancreatic cancer is associated with late-stage diagnosis and poor patient prognosis. The disease is characterised by chronic dysregulated immunity and inflammation. Moreover, chronic pancreatitis is linked with an increased risk of pancreatic cancer. Tissue remodelling during disease progression involves a complex network of cells and a crosstalk between cancer cells, stromal components and immune cells, but it remains poorly explored. Thus, to improve the outcome of patients, there is a need for better understanding of biological changes associated with the initiation and progression of pancreatic cancer at the molecular and spatial levels. Using samples obtained from our Accelerated Diagnosis of neuroEndocrine and Pancreatic TumourS (ADEPTS) biobank, we have evaluated blood samples for the discovery of non- invasive biomarkers to discriminate patients with pancreatic cancer from symptomatic patients without cancer. In this pilot study, the transcriptome of peripheral blood mononuclear cells (PBMCs), isolated using a ficoll gradient was explored to identify PDAC-associated mRNA signatures. Moreover, the Olink® Explore Inflammation and Oncology panels were performed in a cohort of 40 patients with early stage (I-II) PDAC, 40 chronic pancreatitis samples and 40 control patients with benign symptomatic upper GI diseases. To validate and enrich these results, a panel of inflammatory and immune markers including immunoglobulins, cytokines and chemokines was also run using multiplex techniques. Symptoms observed in our cohort were also analysed together with clinical (e.g diabetic status, biochemistry profile) and demographic data (age, sex, ethnicity, post code etc). We have identified mRNA transcriptome signatures and differentially expressed proteins associated with inflammatory and immunological processes in PDAC compared to benign symptomatic samples. Our results offer potential diagnostic utility for early-stage disease. Additionally, our unique cohort of patient samples comprising of those with confirmed PDAC and those presenting to clinic with benign disease and similar non-specific symptoms, allows for the development of non-invasive diagnostic tests with better translational applicability. Future work will involve the validation of these findings in a larger patient cohort and the use of NanoString GeoMx® Digital Spatial Profiler to perform whole transcriptome and proteome profiling in human chronic pancreatic and pancreatic cancer tissue samples. Citation Format: Kyra Fraser, Maria Rosado, Stephen P Pereira, Pilar Acedo. Unravelling fibroinflammatory and immune signatures for pancreatic cancer early detection [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr B023.

Serum-Based Biomarker Panels are Crucial Tools for the Early Detection of Lung Cancer in High-Risk Individuals in North Indian Population

Serum-Based Biomarker Panels are Crucial Tools for the Early Detection of Lung Cancer in High-Risk Individuals in North Indian Population

Health Insurance Continuity and Mortality in Children and Adolescents/Young Adults with Blood Cancer.

Many uninsured patients do not receive Medicaid coverage until a cancer diagnosis, potentially delaying access to care for early cancer detection and treatment. We examine the association of Medicaid enrollment timing and patterns with survival among children and adolescents/young adults (AYAs) diagnosed with blood cancers, where disease onset can be acute and early detection is critical. We identified 28,750 children and AYAs (0-39 years) newly diagnosed with blood cancers from the 2006-2013 SEER-Medicaid data. Enrollment patterns included continuous Medicaid (preceding through diagnosis), newly gained Medicaid (at/shortly after diagnosis), other noncontinuous Medicaid enrollment, and private/other insurance. We assessed cumulative incidence of death from diagnosis, censoring at last follow-up, five years post-diagnosis, or December 2018, whichever occurred first. Multivariable survival models estimated the association of insurance enrollment patterns with risk of death. One-fourth (26.1%) of the cohort were insured by Medicaid; of these, 41.1% had continuous Medicaid, 34.9% had newly gained Medicaid, and 24.0% had other noncontinuous enrollment. The cumulative incidence of all-cause death five-year post-diagnosis was highest in patients with newly gained Medicaid (30.2%, 95%CI = 28.4-31.9%), followed by other noncontinuous enrollment (23.2%, 95%CI = 21.3-25.2%), continuous Medicaid (20.5%, 95%CI = 19.1-21.9%), and private/other insurance (11.2%; 95%CI = 10.7-11.7%). In multivariable models, newly gained Medicaid was associated with a higher risk of all-cause (hazard ratio = 1.39, 95%CI = 1.27-1.53) and cancer-specific death (hazard ratio = 1.50, 95%CI = 1.35-1.68), compared to continuous Medicaid. Continuous Medicaid coverage is associated with survival benefits among pediatric and AYA patients diagnosed with blood cancers; however, less than half of Medicaid-insured patients have continuous coverage before diagnosis.

Research advances in tumor diagnosis and early detection

This review explores recent advances in tumor diagnosis and early detection, focusing on cutting-edge developments in molecular diagnostic technologies, imaging techniques, and the integration of multi-omics data. Current tumor diagnostic methods have limitations in terms of sensitivity and specificity, particularly for early tumor detection. However, with continuous progress in research and emerging technologies, especially the advent of liquid biopsy, which enables the detection of circulating tumor DNA (ctDNA), exosomes, and tumor-educated platelets (TEPs), the sensitivity and accuracy of early cancer detection have significantly improved. Moreover, the combined application of artificial intelligence and high-resolution imaging technology has enhanced the precision of diagnosis. Despite these advances, challenges, such as the high cost of technology and difficulties in data integration, continue to impede widespread clinical adoption. Therefore, I believe that future research should prioritize the innovation of these technologies to improve their applicability for early detection across various cancer types, ultimately contributing to the advancement of personalized therapy.

Unleashing the power of Manta Rays Foraging Optimizer: A novel approach for hyper-parameter optimization in skin cancer classification

Optimizing hyperparameters is crucial for improving the performance of deep learning (DL) models, especially in complex applications like skin cancer classification from dermoscopic images. This study introduces a novel hyperparameter optimization strategy using the Manta Rays Foraging Optimizer (MRFO). A model tailored for skin cancer classification is created by fine-tuning a Convolutional Neural Network (CNN) with MRFO, coupled with in-depth image preprocessing. Empirical evaluations on diverse datasets (ISIC, PH2, HAM10000) showcase the significant superiority of the MRFO-based model over conventional optimization algorithms. The model achieves impressive accuracy and loss metrics (ISIC: 99.43 %, 0.0250; PH2: 99.96 %, 0.0033; HAM10000: 97.70 %, 0.0626), outperforming alternative optimization algorithms such as the Grey Wolf Optimizer (98.33 % accuracy, 0.17 loss), Whale Optimization Algorithm (96 % accuracy), Grasshopper Optimization Algorithm (97.2 % accuracy), Densnet121-MRFO (99.26 % accuracy), InceptionV3 with GA (99.9 % accuracy), and African Vulture Optimization Algorithm (92.7 % accuracy). The novel approach demonstrates superior accuracy and loss metrics, underscoring its potential for precise and efficient skin cancer detection. Additionally, narrow confidence intervals and balanced precision-recall confirm the model’s generalizability and effectiveness, paving the way for early and accurate skin cancer detection and potentially improving patient outcomes.

Serum mRNA levels of cytokeratin-19 and vascular endothelial growth factor in oral squamous cell carcinoma and oral potentially malignant disorders using RT-PCR

BackgroundOral cancers, which include tumors of the oral cavity, salivary glands, and pharynx, are becoming increasingly prevalent worldwide. Squamous cell carcinoma accounts for over 90% of malignant oral lesions, with oral squamous cell carcinoma (OSCC) being notably common in the Indian subcontinent and other regions of Asia. This is especially true in South-Central Asia, including Sri Lanka, where it is particularly prevalent among men. This study aims to evaluate the levels of Vascular Endothelial Growth Factor-A (VEGF-A) and Cytokeratin-19 (CK-19) mRNAs in whole blood as a potential method for the early detection of OSCC.MethodsThe study included 40 patients (each from OSCC, Oral Submucous Fibrosis (OSF), Oral Leukoplakia (OLK), Oral Lichen Planus (OLP), and 10 healthy controls. The expression levels of VEGF-A and CK-19 mRNAs were measured from extracellular RNA extracted from whole blood samples using real-time reverse transcription polymerase chain reaction (RT-PCR) with sequence-specific primers. Receiver operating characteristic (ROC) curve analysis was used to evaluate the effectiveness of these biomarkers in detecting OSCC.ResultsThe results demonstrated a significant increase in blood transcripts of the candidate mRNAs CK-19 and VEGF-A in patients with OSCC, OSF, OLK, and OLP. The Wilcoxon signed-rank test revealed a p-value of 0.002 for each specific comparison between diseased patients and healthy controls (i.e., OSCC vs. HC, OSF vs. HC, OLP vs. HC, OLK vs. HC) for both CK-19 and VEGF-A. When these two biomarkers were used together, they provided a 60% predictive probability for patients with OSCC (p = 0.023).ConclusionThis study highlights the efficacy of blood mRNA transcriptome diagnostics in detecting OSCC. This innovative clinical approach has the potential to be a robust, efficient, and reliable tool for early cancer detection. Blood-based transcriptomes could be further explored for their effectiveness in various health contexts and for routine health monitoring.

A consultation and work-up diagnosis protocol for a multicancer early detection test: a case series study.

The emergence of multicancer early detection (MCED) tests holds promise for improving early cancer detection and public health outcomes. However, positive MCED test results require confirmation through recommended cancer diagnostic imaging modalities. To address these challenges, we have developed a consultation and work-up protocol for definitive diagnostic results post MCED testing, named SPOT-MAS. Developed through circulating tumor DNA (ctDNA) analysis and in line with professional guidelines and advisory board consensus, this protocol standardizes information to aid general practitioners in accessing, interpreting and managing SPOT-MAS results. Clinical effectiveness is demonstrated through a series of identified cancer cases. Our research indicates that the protocol could empower healthcare professionals to confidently interpret circulating tumor DNA test results for 5 common types of cancer, thereby facilitating the clinical integration of MCED tests.

George N. Papanicolaou (1883-1962): The Pioneer of Cytology and Early Cancer Detection.

George N. Papanicolaou (1883-1962) is recognized as a pioneer in cytology and early cancer detection, whose groundbreaking work revolutionized women's healthcare. His development of the Pap smear, a simple yet powerful screening tool, dramatically improved the early diagnosis of cervical cancer, leading to a significant reduction in mortality rates and saving millions of lives worldwide. Born in Greece and extensively trained in medicine and biology, Papanicolaou conducted meticulous research at Cornell University, laying the foundation for modern preventive medicine. This historical vignette explores Papanicolaou's life, transformative achievements, and the innovative processes he championed. By examining his enduring contributions, we highlight his profound impact on public health and medical practice, which continues to inspire and guide healthcare professionals across generations.

Nose-on-Chip Nanobiosensors for Early Detection of Lung Cancer Breath Biomarkers.

Lung cancer remains a global health concern, demanding the development of noninvasive, prompt, selective, and point-of-care diagnostic tools. Correspondingly, breath analysis using nanobiosensors has emerged as a promising noninvasive nose-on-chip technique for the early detection of lung cancer through monitoring diversified biomarkers such as volatile organic compounds/gases in exhaled breath. This comprehensive review summarizes the state-of-the-art breath-based lung cancer diagnosis employing chemiresistive-module nanobiosensors supported by theoretical findings. It unveils the fundamental mechanisms and biological basis of breath biomarker generation associated with lung cancer, technological advancements, and clinical implementation of nanobiosensor-based breath analysis. It explores the merits, challenges, and potential alternate solutions in implementing these nanobiosensors in clinical settings, including standardization, biocompatibility/toxicity analysis, green and sustainable technologies, life-cycle assessment, and scheming regulatory modalities. It highlights nanobiosensors' role in facilitating precise, real-time, and on-site detection of lung cancer through breath analysis, leading to improved patient outcomes, enhanced clinical management, and remote personalized monitoring. Additionally, integrating these biosensors with artificial intelligence, machine learning, Internet-of-things, bioinformatics, and omics technologies is discussed, providing insights into the prospects of intelligent nose-on-chip lung cancer sniffing nanobiosensors. Overall, this review consolidates knowledge on breathomic biosensor-based lung cancer screening, shedding light on its significance and potential applications in advancing state-of-the-art medical diagnostics to reduce the burden on hospitals and save human lives.

FP1.3 - SPEC MDT in Aneurin Bevan University Health Board

Abstract Aims The SPEC (significant polyp and early cancer) multi-disciplinary team (MDT) meeting was started in ABUHB in 2022 to discuss complex colonic and rectal polyp cases, such as polyps >20mm, likely to be sessile, or difficult to remove endoscopically. The aim was to evaluate the effectiveness and clinical role of the SPEC MDT. Methods Data for patients discussed in SPEC MDT since its conception in January 2022 until September 2023 was retrospectively collected from the SPEC MDT database, a prospectively collected database. This included patient demographics, reason for referral, polyp characteristics and MDT outcomes. Results In 21 months, there have been 38 SPEC MDTs, with 355 cases discussed (average of 9 cases per MDT). There was at least one laparoscopic colorectal surgeon, gastroenterologist and a histopathologist in every MDT in accordance with BSG guidelines. Main referral reasons included endoscopy findings (72%) and re-discussion post-procedure (22%). Twenty-three patients had adenocarcinomas and three had NETs. MDT outcomes were EMR (23%), endoscopic surveillance (21%), clinic to discuss (no) surgery (19%), TAMIS (16%), urgent endoscopy (13%) or other (8%). Conclusion As the busiest Health Board in Wales for Colorectal Cancers, the formation of SPEC MDT has been an important step in improving the detection and treatment of advanced polyps and early cancers. Although too early to measure the impact on early cancer detection rates and improved decision making for these patients, formalising the MDT process in line with BSG guidelines has been an important step in improving the service offered to patients.

Early Breast Cancer Detection Using Artificial Intelligence Techniques Based on Advanced Image Processing Tools

The early detection of breast cancer is essential for improving treatment outcomes, and recent advancements in artificial intelligence (AI), combined with image processing techniques, have shown great potential in enhancing diagnostic accuracy. This study explores the effects of various image processing methods and AI models on the performance of early breast cancer diagnostic systems. By focusing on techniques such as Wiener filtering and total variation filtering, we aim to improve image quality and diagnostic precision. The novelty of this study lies in the comprehensive evaluation of these techniques across multiple medical imaging datasets, including a DCE-MRI dataset for breast-tumor image segmentation and classification (BreastDM) and the Breast Ultrasound Image (BUSI), Mammographic Image Analysis Society (MIAS), Breast Cancer Histopathological Image (BreakHis), and Digital Database for Screening Mammography (DDSM) datasets. The integration of advanced AI models, such as the vision transformer (ViT) and the U-KAN model—a U-Net structure combined with Kolmogorov–Arnold Networks (KANs)—is another key aspect, offering new insights into the efficacy of these approaches in different imaging contexts. Experiments revealed that Wiener filtering significantly improved image quality, achieving a peak signal-to-noise ratio (PSNR) of 23.06 dB and a structural similarity index measure (SSIM) of 0.79 using the BreastDM dataset and a PSNR of 20.09 dB with an SSIM of 0.35 using the BUSI dataset. When combined filtering techniques were applied, the results varied, with the MIAS dataset showing a decrease in SSIM and an increase in the mean squared error (MSE), while the BUSI dataset exhibited enhanced perceptual quality and structural preservation. The vision transformer (ViT) framework excelled in processing complex image data, particularly with the BreastDM and BUSI datasets. Notably, the Wiener filter using the BreastDM dataset resulted in an accuracy of 96.9% and a recall of 96.7%, while the combined filtering approach further enhanced these metrics to 99.3% accuracy and 98.3% recall. In the BUSI dataset, the Wiener filter achieved an accuracy of 98.0% and a specificity of 98.5%. Additionally, the U-KAN model demonstrated superior performance in breast cancer lesion segmentation, outperforming traditional models like U-Net and U-Net++ across datasets, with an accuracy of 93.3% and a sensitivity of 97.4% in the BUSI dataset. These findings highlight the importance of dataset-specific preprocessing techniques and the potential of advanced AI models like ViT and U-KAN to significantly improve the accuracy of early breast cancer diagnostics.

A Hybrid VGG 19 and Capsule Network Based Deep Learning Model for Lung Cancer Diagnosis using CT S can Images

Objectives: Lung cancer is one of the most prevalent causes of carcinoma-related fatalities globally; precise and effective diagnostic instruments are desperately needed. Researchers and physicians continue to encounter difficulties when aiming to employ deep learning models in healthcare environments for recognizing lung cancer and to achieve higher sensitivity and accuracy on large data sets, despite several advancements in this field. Our study builds upon an extensive review of existing lung cancer detection methods, highlighting their strengths and weaknesses. The performance of this model deteriorates when there are variances in Lung CT image features such as rotation, tiling, and other aberrant image orientations. This study aims to address the issues associated with variations in lung CT images. Methods: A hybrid deep learning model that blends the potency of CNNs with the cutting-edge design of capsule networks is proposed. Inspired by recent advancements, our model integrates the VGG19 and Capsule Network architectures to address orientation-related challenges often encountered in traditional CNN-based approaches. The creation, training, and assessment of this hybrid model for lung nodule identification and categorization are our main research goals. Findings: We anticipate that our research has yielded several valuable outcomes, including improved nodule classification accuracy of 99.20%, reduced false positive rates, and minimized training times. Novelty: This research employing a hybrid deep learning model that combines the capabilities of the VGG-19 and capsule network could lead to more widespread utilization in cancer diagnosis by enhancing early lung cancer detection and developing the field of medical image analysis. The shortcomings of convolutional neural networks are addressed with Capsule Network. Leveraging the knowledge and insights gained from lung cancer detection, our research also investigates the potential applicability of our methodology to identify other types of medical image classification such as breast and ovarian cancer. Keywords: Computed Tomography, Lung cancer, Deep Learning, CNN, VGG19, Capsule Network

Retraction Note: A graphene-based triple-band THz metamaterial absorber for cancer early detection

Retraction Note: A graphene-based triple-band THz metamaterial absorber for cancer early detection

Identification and evaluation of a serum microRNA panel to diagnose colorectal cancer patients.

Screening plays a crucial role in the early detection of colorectal cancer, greatly reducing mortality rates. The objective of this study was to identify a non-invasive diagnostic method utilizing serum microRNA expression for the diagnosis of colorectal cancer patients. The study consisted of three stages. In the first stage, 129 patients with colorectal cancer and 129 normal subjects were recruited as the training set for the development of a blood miRNA panel. The second stage involved recruiting 200 patients from each group as the validation cohort. Finally, a blinded study was conducted in the third stage, with 260 patients recruited to determine the predictive value of our miRNA panel. Serum samples were prospectively collected from colorectal cancer patients and normal subjects between 2017 and 2021 at Queen Mary Hospital in Hong Kong. Quantitative PCR was utilized to detect the serum levels of candidate microRNAs, and a multiple linear regression model was employed to formulate a serum microRNA panel for diagnosing colorectal cancer patients. The performance of the panel was evaluated using ROC analysis. Our study showed that the values of three pairs of serum microRNAs, namely miR-106b-5p/miR-1246, miR-106b-5p/miR-16 and miR-106b-5p/miR-21-5p, exhibited statistically significant differences between colorectal cancer patients and normal subjects. A serum microRNA panel formulated from these three pairs of microRNAs demonstrated high accuracy in diagnosing colorectal cancer patients from normal subjects, with an AUC of approximately 0.9. The serum miRNA test proved to be a feasible and promising non-invasive biomarker for the diagnosis of colorectal cancer patients in comparison to normal subjects.

Socioeconomic inequalities in uptake of outreach mammography before and after accessibility improvement of Taiwan’s national universal breast cancer screening policy

BackgroundTaiwan implemented the Cancer Screening Quality Improvement Program (CAQIP) in 2010. The program sought to enhance mass breast cancer screening accessibility. This study aimed to examine socioeconomic disparities in outreach screening utilization pre-CAQIP (2005–2009) and post-CAQIP (2010–2014).MethodWe conducted a nationwide population-based observational study in Taiwan, analyzing four population databases to evaluate socioeconomic disparities among women aged 50 to 69 years undergoing their first mammography screening pre-CAQIP. Multivariate logistic regression was used to examine changes in utilization of outreach screening pre- and post-CAQIP implementation, and to estimate the Slope Index of Inequity (SII) and Relative Index of Inequity (RII) values.ResultsUtilization of outreach screening through mobile mammography units (MMUs) increased from 6.12 to 32.87% between the two periods. Following CAQIP, a higher proportion of screened women were older, less educated, and from suburban or rural areas. The SII and RII for age, income, and urbanization levels decreased post-CAQIP. However, regarding education level, SII was − 0.592 and RII was 0.392 in the pre-CAQIP period, increasing to -0.173 and 0.804 post-CAQIP, respectively.ConclusionsOur study observed that utilization of outreach screening through MMUs increased after CAQIP. The MMUs made outreach screening services more accessible in Taiwan. Expanding outreach screening services and educational programs to promote mammography uptake in local communities could help reduce the potential effect of socioeconomic disparities, and thus may enhance early detection of breast cancer. Further study could focus on the accessibility of outreach screening and breast cancer outcomes.

Women’s empowerment and its influence on the uptake of breast cancer screening in Tanzania: an analysis of 2022 Tanzania demographic health survey data

BackgroundBreast cancer is the second most commonly diagnosed cancer worldwide, with a high mortality rate in developing countries, including sub-Saharan Africa. Screening is one way to ensure early detection and management of breast cancer, and it is influenced by several factors. Education and socio-economic status may also affect the utilization of breast cancer screening services as these impact decision-making. This study aimed to investigate women’s empowerment and its influence on the uptake of breast cancer screening among women in Tanzania.MethodsThis study utilized the 2022 Tanzania Demographic and Health Survey data, and included 4216 women aged 20 to 49 years. Women empowerment variables used include social independence, decision-making, ownership of assets, and attitude towards violence. Statistical Package for Social Sciences version 26 was used for data cleaning and analysis. Descriptive statistics and bivariate analysis were done, including a multivariate logistic regression to assess the level of association between independent variables with breast cancer screening.ResultsFindings indicate that the prevalence of breast cancer screening is 5.2%. Age, education level, literacy, ownership of assets, attitude towards violence, and decision making are associated with ever going for breast cancer screening. Women aged 45 to 49 years (AOR = 6.28, 95% CI = 6.27–6.28), those with secondary or higher education (AOR 1.1, 95% CI = 1.05–1.06), literate women (AOR = 1.13, 95% CI = 1.13–1.13), those who own a house (AOR = 3.08, 95% CI = 3.08–3.09), who jointly decide on their healthcare with partners on healthcare (AOR = 1.18, 95% CI = 1.18–1.19) had significantly higher odds of going for breast cancer screening.ConclusionWomen’s empowerment is significantly associated with the likelihood of engaging in breast cancer screening. Empowered women are more likely to undergo screening. Focus should be on empowering women through education, businesses, and community involvement. Country-specific interventions and breast cancer screening awareness campaigns should include empowerment initiatives to promote screening uptake.

EDUCATION ABOUT BREAST CANCER IN THE COMMUNITY AT NGLUYU HEALTH CENTER, NGANJUK

Breast cancer is the most common cancer found in the world and this cancer is the second cause of death due to cancer after lung cancer in Indonesia. This high mortality rate can be prevented by carrying out early detection. However, this is still not done well, especially in communities living in remote areas with low to medium economic and educational levels. The aim is to convey knowledge about breast cancer and training in the self-examination of the breast. It was held on Tuesday, 12 September 2023 at the Ngluyu Community Health Center, Nganjuk, from 07.00 to 14.00 WIB and was attended by 111 people. Data on breast cancer risk factors was collected through questionnaires. There were 96 participants who filled out the questionnaire, aged between 22-63 years. Risk factors data showed that 3.13% did not have children, 15.63% breastfed children less than 6 months, 5.21% were exposed to X-rays more than once a year; 1.04% had breast tumors, and 4.17% had family members suffering from cancer. In addition, 89.58% were over 25 years old and 42.71% had doing self-examination of breast. There was an increase in public understanding at the Ngluyu Community Health Center from 77.70% to 84.12%, namely an increase of 6.42%. This can increase public understanding about breast cancer and procedures to self-examination of breast and contribute in early detection of breast cancer as well as reducing the incidence of breast cancer. The results of this counseling can be used as recommendations by health centers in the Nganjuk district area.

Analysis of urine cell-free DNA in bladder cancer diagnosis by emerging bioactive technologies and materials.

Urinary cell-free DNA (UcfDNA) is gaining recognition as an important biomarker for diagnosing bladder cancer. UcfDNA contains tumor derived DNA sequences, making it a viable candidate for non-invasive early detection, diagnosis, and surveillance of bladder cancer. The quantification and qualification of UcfDNA have demonstrated high sensitivity and specificity in the molecular characterization of bladder cancer. However, precise analysis of UcfDNA for clinical bladder cancer diagnosis remains challenging. This review summarizes the history of UcfDNA discovery, its biological properties, and the quantitative and qualitative evaluations of UcfDNA for its clinical significance and utility in bladder cancer patients, emphasizing the critical role of UcfDNA in bladder cancer diagnosis. Emerging bioactive technologies and materials currently offer promising tools for multiple UcfDNA analysis, aiming to achieve more precise and efficient capture of UcfDNA, thereby significantly enhancing diagnostic accuracy. This review also highlights breakthroughs in detection technologies and substrates with the potential to revolutionize bladder cancer diagnosis in clinic.