Population-level impact of the BMJ Rapid Recommendation for colorectal cancer screening: a microsimulation analysis.

OBJECTIVE: In 2019, a BMJ Rapid Recommendation advised against colorectal cancer (CRC) screening for adults with a predicted 15-year CRC risk below 3%. Using Switzerland as a case study, we estimated the population-level impact of this recommendation. DESIGN: We predicted the CRC risk of all respondents to the population-based Swiss Health Survey. We derived the distribution of risk-based screening start age, assuming predicted risk was calculated every 5 years between ages 25 and 70 and screening started when this risk exceeded 3%. Next, the MISCAN-Colon microsimulation model evaluated biennial faecal immunochemical test (FIT) screening with this risk-based start age. As a comparison, we simulated screening initiation based on age and sex. RESULTS: Starting screening only when predicted risk exceeded 3% meant 82% of women and 90% of men would not start screening before age 65 and 60, respectively. This would require 43%-57% fewer tests, result in 8%-16% fewer CRC deaths prevented and yield 19%-33% fewer lifeyears gained compared with screening from age 50. Screening women from age 65 and men from age 60 had a similar impact as screening only when predicted risk exceeded 3%. CONCLUSION: With the recommended risk prediction tool, the population impact of the BMJ Rapid Recommendation would be similar to screening initiation based on age and sex only. It would delay screening initiation by 10-15 years. Although halving the screening burdens, screening benefits would be reduced substantially compared with screening initiation at age 50. This suggests that the 3% risk threshold to start CRC screening might be too high.

The role of clinical breast examination and fine needle aspiration cytology in early detection of breast cancer: A cross-sectional study nested in a cohort in a low-resource setting.

BACKGROUND: Breast cancer is prevalent worldwide, with disparities in screening, diagnosis, treatment outcomes, and survival. In Africa, the majority of women are diagnosed at advanced stages, affecting treatment outcomes. Screening is one of the best strategies to reduce mortality rates caused by this cancer. Yet in a resource-constrained setting, there is limited access to screening and early detection services, which are available only at a few referral hospitals. OBJECTIVES: We aimed to evaluate the prevalence and screening results of breast cancer using clinical breast examination coupled with fine needle aspiration cytology in a resource-constraint setting. DESIGN: A combined cross-sectional and cohort study. METHODS: Women at risk of developing breast cancer in the Kilimanjaro region of Tanzania were invited, through public announcements, to their primary healthcare facilities. A questionnaire was used to assess the participants' characteristics. The women received a clinical breast examination, and detectable lesions were subjected to a confirmatory fine needle aspiration cytology or an excisional biopsy. Preliminary data from this ongoing breast cancer control program were extracted and analyzed for this study. RESULTS: A total of 3577 women were screened for breast cancer; their mean age was 47 ± 7.53 years. About a third of them (1145, 32%) were practicing self-breast examination at least once a month. Of 200 (5.6%) with abnormal clinical breast examination, 18 (9%) were confirmed to be breast cancer, making the prevalence to be 0.5%. The vast majority of participants with breast cancer (13, 72.2%) had early disease stages, and infiltrating ductal carcinoma, no special type, was the most common (15, 83.3%) histopathology subtype. Hormonal receptor status determination results indicated that 11 (61.1%), 7 (38.9%), and 5 (27.8%) of the tumors overexpressed estrogen receptor, progesterone receptor, and human epidermal receptor-2, respectively. CONCLUSION: Our study demonstrates 5.6% of Tanzanian women have abnormal clinical breast examination findings, with 9% having breast cancer. Nearly three-quarters (72.2%) of breast cancer screened for early disease were detected in the early disease stages. This finding suggests that organized screening with clinical breast examination coupled with fine needle aspiration cytology, which is a simple and cost-effective screening method, has the potential to improve early detection and outcomes for breast cancer patients in a resource-constraint setting.

Early detection of HCC in patients with cirrhosis using AI; a Systematic Review.

Introduction: Hepatocellular carcinoma constitutes for approximately 75% of primary cancers of liver. Around 80- 90% of patients with HCC have cirrhosis at the time of diagnosis. Use of AI has recently gained significance in the field of hepatology, especially for the detection of HCC, owing to its increasing incidence and specific radiological features which have been established for its diagnostic criteria. Objectives: A systematic review was performed to evaluate the current literature for early diagnosis of hepatocellular carcinoma in cirrhotic patients. METHODS: Systematic review was conducted using PRISMA guidelines and the relevant studies were narrated in detail with assessment of quality for each paper. RESULTS: This systematic review displays the significance of AI in early detection and prognosis of HCC with the pressing need for further exploration in this field. CONCLUSIONS: AI can have a significant role in early diagnosis of HCC in cirrhotic patients.

Integrating artificial intelligence techniques for advancements in colorectal cancer management: navigating past and predicting future direction.

Artificial Intelligence (AI) in the last few years has emerged as a valuable tool in managing colorectal cancer, revolutionizing its management at different stages. In early detection and diagnosis, AI leverages its prowess in imaging analysis, scrutinizing CT scans, MRI, and colonoscopy views to identify polyps and tumors. This ability enables timely and accurate diagnoses, initiating treatment at earlier stages. AI has helped in personalized treatment planning because of its ability to integrate diverse patient data, including tumor characteristics, medical history, and genetic information. Integrating AI into clinical decision support systems guarantees evidence-based treatment strategy suggestions in multidisciplinary clinical settings, thus improving patient outcomes. This narrative review explores the multifaceted role of AI, spanning early detection of colorectal cancer, personalized treatment planning, polyp detection, lymph node evaluation, cancer staging, robotic colorectal surgery, and training of colorectal surgeons.

Establishment and validation of an artificial intelligence-based model for real-time detection and classification of colorectal adenoma.

Colorectal cancer (CRC) prevention requires early detection and removal of adenomas. We aimed to develop a computational model for real-time detection and classification of colorectal adenoma. Computationally constrained background based on real-time detection, we propose an improved adaptive lightweight ensemble model for real-time detection and classification of adenomas and other polyps. Firstly, we devised an adaptive lightweight network modification and effective training strategy to diminish the computational requirements for real-time detection. Secondly, by integrating the adaptive lightweight YOLOv4 with the single shot multibox detector network, we established the adaptive small object detection ensemble (ASODE) model, which enhances the precision of detecting target polyps without significantly increasing the model's memory footprint. We conducted simulated training using clinical colonoscopy images and videos to validate the method's performance, extracting features from 1148 polyps and employing a confidence threshold of 0.5 to filter out low-confidence sample predictions. Finally, compared to state-of-the-art models, our ASODE model demonstrated superior performance. In the test set, the sensitivity of images and videos reached 87.96% and 92.31%, respectively. Additionally, the ASODE model achieved an accuracy of 92.70% for adenoma detection with a false positive rate of 8.18%. Training results indicate the effectiveness of our method in classifying small polyps. Our model exhibits remarkable performance in real-time detection of colorectal adenomas, serving as a reliable tool for assisting endoscopists.

Plasma Metabolite Profiling in the Search for Early-Stage Biomarkers for Lung Cancer: Some Important Breakthroughs.

Lung cancer is the leading cause of cancer-related mortality worldwide. In order to improve its overall survival, early diagnosis is required. Since current screening methods still face some pitfalls, such as high false positive rates for low-dose computed tomography, researchers are still looking for early biomarkers to complement existing screening techniques in order to provide a safe, faster, and more accurate diagnosis. Biomarkers are biological molecules found in body fluids, such as plasma, that can be used to diagnose a condition or disease. Metabolomics has already been shown to be a powerful tool in the search for cancer biomarkers since cancer cells are characterized by impaired metabolism, resulting in an adapted plasma metabolite profile. The metabolite profile can be determined using nuclear magnetic resonance, or NMR. Although metabolomics and NMR metabolite profiling of blood plasma are still under investigation, there is already evidence for its potential for early-stage lung cancer diagnosis, therapy response, and follow-up monitoring. This review highlights some key breakthroughs in this research field, where the most significant biomarkers will be discussed in relation to their metabolic pathways and in light of the altered cancer metabolism.

Costs and Projected Effect of a Federally Qualified Health Center-Based Mailed Colorectal Cancer Screening Program in Texas.

Introduction: Mailed stool testing for colorectal cancer (CRC) may improve screening uptake and reduce the incidence and mortality of CRC, especially among patients at federally qualified health centers (FQHCs). To expand screening programs it is important to identify cost-effective approaches. Methods: We developed a decision-analytic model to estimate the cost, effects on screening and patient outcomes (CRCs detected, CRCs prevented, CRC deaths prevented), and cost-effectiveness of implementing a state-wide mailed stool testing program over 5 years among unscreened, age-eligible (aged 50-75 y) patients at FQHCs in Texas. We compared various outreach strategies and organizational structures (centralized, regional, or a hybrid). We used data from our existing regional mailed stool testing program and recent systematic reviews to set parameters for the model. Costs included start-up and ongoing activities and were estimated in 2022 US dollars from the perspective of a hypothetical third-party payer. Cost-effectiveness was assessed by using both incremental and average cost-effectiveness ratios. Results: Using either a statewide centralized or hybrid organizational configuration to mail stool tests to newly eligible FQHC patients and patients who have responded at least once since program inception is likely to result in the best use of resources over 5 years, enabling more than 110,000 additional screens, detecting an incremental 181 to 194 CRCs, preventing 91 to 98 CRCs, and averting 46 to 50 CRC deaths, at a cost of $10 million to $11 million compared with no program. Conclusions: A statewide mailed stool testing program for FQHC patients can be implemented at reasonable cost with considerable effects on CRC screening outcomes, especially when its structure maximizes program efficiency while maintaining effectiveness.

Potential application of body fluids autofluorescence in the non-invasive diagnosis of endometrial cancer.

BACKGROUND: Endometrial carcinoma (EC) is the most common cancer of the female reproductive tract in developed countries. The prognosis and 5-year survival rates are closely tied to the stage diagnosis. Current routine diagnostic methods of EC are either lacking specificity or are uncomfortable, invasive and painful for the patient. As of now, the gold diagnostic standard is endometrial biopsy. Early and non-invasive diagnosis of EC requires the identification of new biomarkers of disease and a screening test applicable to routine laboratory diagnostics. The application of untargeted metabolomics combined with artificial intelligence and biostatistics tools has the potential to qualitatively and quantitatively represent the metabolome, but its introduction into routine diagnostics is currently unrealistic due to the financial, time and interpretation challenges. Fluorescence spectral analysis of body fluids utilizes autofluorescence of certain metabolites to define the composition of the metabolome under physiological conditions. PURPOSE: This review highlights the potential of fluorescence spectroscopy in the early detection of EC. Data obtained by three-dimensional fluorescence spectroscopy define the quantitative and qualitative composition of the complex fluorescent metabolome and are useful for identifying biochemical metabolic changes associated with endometrial carcinogenesis. Autofluorescence of biological fluids has the prospect of providing new molecular markers of EC. By integrating machine learning and artificial intelligence algorithms in the data analysis of the fluorescent metabolome, this technique has great potential to be implemented in routine laboratory diagnostics.

Machine learning models to predict submucosal invasion in early gastric cancer based on endoscopy features and standardized color metrics.

Conventional endoscopy is widely used in the diagnosis of early gastric cancers (EGCs), but the graphical features were loosely defined and dependent on endoscopists' experience. We aim to establish a more accurate predictive model for infiltration depth of early gastric cancer including a standardized colorimetric system, which demonstrates promising clinical implication. A retrospective study of 718 EGC cases was performed. Clinical and pathological characteristics were included, and Commission Internationale de l'Eclariage (CIE) standard colorimetric system was used to evaluate the chromaticity of lesions. The predicting models were established in the derivation set using multivariate backward stepwise logistic regression, decision tree model, and random forest model. Logistic regression shows location, macroscopic type, length, marked margin elevation, WLI color difference and histological type are factors significantly independently associated with infiltration depth. In the decision tree model, margin elevation, lesion located in the lower 1/3 part, WLI a*color value, b*color value, and abnormal thickness in enhanced CT were selected, which achieved an AUROC of 0.810. A random forest model was established presenting the importance of each feature with an accuracy of 0.80, and an AUROC of 0.844. Quantified color metrics can improve the diagnostic precision in the invasion depth of EGC. We have developed a nomogram model using logistic regression and machine learning algorithms were also explored, which turned out to be helpful in decision-making progress.

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

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

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

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

Unlocking the complete blood count as a risk stratification tool for breast cancer using machine learning: a large scale retrospective study.

Optimizing early breast cancer (BC) detection requires effective risk assessment tools. This retrospective study from Brazil showcases the efficacy of machine learning in discerning complex patterns within routine blood tests, presenting a globally accessible and cost-effective approach for risk evaluation. We analyzed complete blood count (CBC) tests from 396,848 women aged 40-70, who underwent breast imaging or biopsies within six months after their CBC test. Of these, 2861 (0.72%) were identified as cases: 1882 with BC confirmed by anatomopathological tests, and 979 with highly suspicious imaging (BI-RADS 5). The remaining 393,987 participants (99.28%), with BI-RADS 1 or 2 results, were classified as controls. The database was divided into modeling (including training and validation) and testing sets based on diagnostic certainty. The testing set comprised cases confirmed by anatomopathology and controls cancer-free for 4.5-6.5 years post-CBC. Our ridge regression model, incorporating neutrophil-lymphocyte ratio, red blood cells, and age, achieved an AUC of 0.64 (95% CI 0.64-0.65). We also demonstrate that these results are slightly better than those from a boosting machine learning model, LightGBM, plus having the benefit of being fully interpretable. Using the probabilistic output from this model, we divided the study population into four risk groups: high, moderate, average, and low risk, which obtained relative ratios of BC of 1.99, 1.32, 1.02, and 0.42, respectively. The aim of this stratification was to streamline prioritization, potentially improving the early detection of breast cancer, particularly in resource-limited environments. As a risk stratification tool, this model offers the potential for personalized breast cancer screening by prioritizing women based on their individual risk, thereby indicating a shift from a broad population strategy.

Oesophageal cell collection device and biomarker testing to identify high-risk Barrett's patients requiring endoscopic investigation.

BACKGROUND: Barrett's oesophagus surveillance places significant burden on endoscopy services yet is vital to detect early cancerous change. Oesophageal cell collection device (OCCD) testing was introduced across Scotland for Barrett's surveillance in response to the COVID-19 pandemic. This national pragmatic retrospective study presents the CytoSCOT programme results and evaluates whether OCCD testing is successfully identifying high-risk Barrett's patients requiring urgent endoscopy. METHODS: All patients undergoing OCCD testing for Barrett's surveillance across 11 Scottish health boards over a 32-month period were identified. Patients who underwent endoscopy within 12 months of OCCD test were included. Individual patient records were interrogated to record clinical information and OCCD test result to categorize patients into risk groups. Endoscopic histopathology results were analysed according to risk group and segment length. Patients were deemed high risk if the OCCD test demonstrated atypia and/or p53 positivity. RESULTS: 4204 OCCD tests were performed in 3745 patients: 608 patients underwent endoscopy within 12 months and were included in this analysis. Patients with longer Barrett's segments were significantly more likely to have an abnormal OCCD test. 50/608 patients (8.2%) had high-grade dysplasia or cancer on endoscopic biopsies: this equates to 1.3% of the total group (50/3745). 46/50 patients (92.0%) were deemed high risk, triggering urgent endoscopy: this rose to 100% with insufficient tests removed. There were no cancers diagnosed within 12 months post-OCCD in the low-risk group. CONCLUSION: OCCD testing is an effective triage tool to identify high-risk patients with Barrett's oesophagus requiring further investigation with endoscopy within the real-world setting.

Detecting colorectal cancer using genetic and epigenetic biomarkers: screening and diagnosis.

Colorectal cancer (CRC) is one of the most frequent types of cancer, with high incidence rates and mortality globally. The extended timeframe for developing CRC allows for the potential screening and early identification of the disease. Furthermore, studies have shown that survival rates for patients with cancer are increased when diagnoses are made at earlier stages. Recent research suggests that the development of CRC, including its precancerous lesion, is influenced not only by genetic factors but also by epigenetic variables. Studies suggest epigenetics plays a significant role in cancer development, particularly CRC. While this approach is still in its early stages and faces challenges due to the variability of CRC, it shows promise as a potential method for understanding and addressing the disease. This review examined the current evidence supporting genetic and epigenetic biomarkers for screening and diagnosis. In addition, we also discussed the feasibility of translating these methodologies into clinical settings. Several markers show promising potential, including the methylation of vimentin (VIM), syndecan-2 (SDC2), and septin 9 (SEPT9). However, their application as screening and diagnostic tools, particularly for early-stage CRC, has not been fully optimized, and their effectiveness needs validation in large, multi-center patient populations. Extensive trials and further investigation are required to translate genetic and epigenetic biomarkers into practical clinical use. biomarkers, diagnostic biomarkers.

Early detection and prognosis evaluation for hepatocellular carcinoma by circulating tumour DNA methylation: A multicentre cohort study.

BACKGROUND: Early diagnosis of hepatocellular carcinoma (HCC) can significantly improve patient survival. We aimed to develop a blood-based assay to aid in the diagnosis, detection and prognostic evaluation of HCC. METHODS: A three-phase multicentre study was conducted to screen, optimise and validate HCC-specific differentially methylated regions (DMRs) using next-generation sequencing and quantitative methylation-specific PCR (qMSP). RESULTS: Genome-wide methylation profiling was conducted to identify DMRs distinguishing HCC tumours from peritumoural tissues and healthy plasmas. The twenty most effective DMRs were verified and incorporated into a multilocus qMSP assay (HepaAiQ). The HepaAiQ model was trained to separate 293 HCC patients (Barcelona Clinic Liver Cancer (BCLC) stage 0/A, 224) from 266 controls including chronic hepatitis B (CHB) or liver cirrhosis (LC) (CHB/LC, 96), benign hepatic lesions (BHL, 23), and healthy controls (HC, 147). The model achieved an area under the curve (AUC) of 0.944 with a sensitivity of 86.0% in HCC and a specificity of 92.1% in controls. Blind validation of the HepaAiQ model in a cohort of 523 participants resulted in an AUC of 0.940 with a sensitivity of 84.4% in 205 HCC cases (BCLC stage 0/A, 167) and a specificity of 90.3% in 318 controls (CHB/LC, 100; BHL, 102; HC, 116). When evaluated in an independent test set, the HepaAiQ model exhibited a sensitivity of 70.8% in 65 HCC patients at BCLC stage 0/A and a specificity of 89.5% in 124 patients with CHB/LC. Moreover, HepaAiQ model was assessed in paired pre- and postoperative plasma samples from 103 HCC patients and correlated with 2-year patient outcomes. Patients with high postoperative HepaAiQ score showed a higher recurrence risk (Hazard ratio, 3.33, p < .001). CONCLUSIONS: HepaAiQ, a noninvasive qMSP assay, was developed to accurately measure HCC-specific DMRs and shows great potential for the diagnosis, detection and prognosis of HCC, benefiting at-risk populations.

Gold nanostructure-enhanced immunosensing: ultra-sensitive detection of VEGF tumor marker for early disease diagnosis.

We present an advanced electrochemical immunosensor designed to detect the vascular endothelial growth factor (VEGF) precisely. The sensor is constructed on a modified porous gold electrode through a fabrication process involving the deposition of silver and gold on an FTO substrate. Employing thermal annealing and a de-alloying process, the silver is eliminated from the electrode, producing a reproducible porous gold substrate. Utilizing a well-defined protocol, we immobilize the heavy-chain (VHH) antibody against VEGF on the gold substrate, facilitating VEGF detection through various electrochemical methods. Remarkably, this immunosensor performs well, featuring an impressive detection limit of 0.05 pg/mL and an extensive linear range from 0.1 pg/mL to 0.1 µg/mL. This emphasizes it's to measure biomarkers across a wide concentration spectrum precisely. The robust fabrication methodology in this research underscores its potential for widespread application, offering enhanced precision, reproducibility, and remarkable detection capabilities for the developed immunosensor.

[Earlier detection of lung cancer through analysis of circulating tumor DNA from blood]. / Tidigare upptäckt av lungcancer med analys av tumör-DNA i blod.

To investigate the  clinical use of analyzing circulating tumor DNA in a clinical setting we present a pilot study comprising 93 patients from individuals with suspected lung cancer. The study aimed to evaluate the capability of analyzing circulating tumor DNA at the initial medical visit in order to detect genetic changes and mutations associated with lung cancer in plasma samples. Tumor DNA from plasma was extracted and analyzed with Next Generation Sequencing (NGS) and the result was compared with a matched tumor tissue collected in close connection from the same individual. Cancer-associated genetic mutations could be confirmed in about 60 percent of the plasma samples, and we observed a higher degree of conformance in patients with a more advanced disease. The results from the study provide valuable insights for an early clinical use of analyzing circulating tumor DNA in cases of suspected lung cancer, which could contribute to improving early diagnosis and treatment strategies for patients with lung cancer.

Culturally Competent Education and Human Papillomavirus Self-Sampling Achieves Healthy People 2030 Cervical Screening Target Among Low-Income Non-Hispanic Black and Hispanic Women.

PURPOSE: Disparities in cervical cancer screening, incidence, and mortality exist in the United States. Cervical cancer incidence and mortality rates in Texas are 20% and 32% higher, respectively, than national averages. Within Texas, these rates are significantly higher among non-Hispanic (NH) Black and Hispanic women. Cervical cancer screening uptake is lower among NH Black and Hispanic women (72.9% and 75.9%, respectively) compared with White women (85.5%) in Texas. METHODS: During March-August 2023, we conducted a pilot study that offered culturally competent education and human papillomavirus (HPV) self-sampling kits to women in two public housing projects in Houston, TX, that have predominantly NH Black or Hispanic residents. Among those eligible for cervical cancer screening, 35% (n = 24) of the NH Black and 34% (n = 16) of the Hispanic women were found to be underscreened per the US Preventive Services Task Force Guideline. We recruited 40 (24 NH Black and 16 Hispanic) eligible women for our study. The study was approved by the MD Anderson institutional review board and registered with ClinicalTrials.gov (NCT04614155-March 11, 2020). RESULTS: Seventy-five percent of the NH Black and 87% of the Hispanic participants completed the HPV self-sampling procedures per protocol. Samples of 17% NH Black and 12% Hispanic participants showed a performance error. Overall, cervical cancer screening uptake improved from 65% to 91% among NH Black and from 66% to 96% among Hispanic participants. CONCLUSION: Culturally competent education and HPV self-sampling resulted in remarkable improvement in cervical cancer screening uptake among underscreened NH Black and Hispanic women residents of Houston public housing projects. Implementing this strategy could significantly reduce cervical cancer incidence and mortality among similar populations in the United States and globally.

Analysis of the diagnostic performance of PAX1/SOX1 gene methylation in cervical precancerous lesions and its role in triage diagnosis.

Methylation panels, tools for investigating epigenetic changes associated with diseases like cancer, can identify DNA methylation patterns indicative of disease, providing diagnostic or prognostic insights. However, the application of methylation panels focusing on the sex-determining region Y-box 1 (SOX1) and paired box gene 1 (PAX1) genes for diagnosing cervical lesions is under-researched. This study aims to examine the diagnostic performance of PAX1/SOX1 gene methylation as a marker for cervical precancerous lesions and its potential application in triage diagnosis. From September 2022 to April 2023, 181 patients with abnormal HPV-DNA tests or cytological exam results requiring colposcopy were studied at Hubei Maternal and Child Health Hospital, China. Data were collected from colposcopy, cytology, HPV-DNA tests, and PAX1/SOX1 methylation detection. Patients were categorized as control, cervical intraepithelial neoplasia Grade 1 (CIN1), Grade 2 (CIN2), Grade 3 (CIN3), and cervical cancer (CC) groups based on histopathology. We performed HPV testing, liquid-based cytology, and PAX1/SOX1 gene methylation testing. We evaluated the diagnostic value of methylation detection in cervical cancer using DNA methylation positivity rate, sensitivity, specificity, and area under the curve (AUC), and explored its potential for triage diagnosis. PAX1/SOX1 methylation positivity rates were: control 17.1%, CIN1 22.5%, CIN2 100.0%, CIN3 90.0%, and CC 100.0%. The AUC values for PAX1 gene methylation detection in diagnosing CIN1+, CIN2+, and CIN3+ were 0.52 (95% confidence interval [CI]: 0.43-0.62), 0.88 (95% CI: 0.80-0.97), and 0.88 (95% CI: 0.75-1.00), respectively. Corresponding AUC values for SOX1 gene methylation detection were 0.47 (95% CI: 0.40-0.58), 0.80 (95% CI: 0.68-0.93), and 0.92 (95% CI: 0.811-1.00), respectively. In HPV16/18-negative patients, methylation detection showed sensitivity of 32.4% and specificity of 83.7% for CIN1+. For CIN2+ and CIN3+, sensitivity was all 100%, with specificities of 83.0% and 81.1%. Among the patients who underwent colposcopy examination, 166 cases had cytological examination results ≤ASCUS, of which 37 cases were positive for methylation, and the colposcopy referral rate was 22.29%. PAX1/SOX1 gene methylation detection exhibits strong diagnostic efficacy for cervical precancerous lesions and holds significant value in triage diagnosis.