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3D printing techniques allow for the precise placement of living cells, biological substances, and biochemical components, establishing themselves as a promising approach in bioengineering. Recently, 3D printing has been applied to develop human-relevant in vitro cancer models with highly controlled complexity and as a potential method for drug screening and disease modeling. Compared to 2D culture, 3D-printed in vitro cancer models more closely replicate the in vivo microenvironment. Additionally, they offer a reduction in the complexity and ethical issues associated with using in vivo animal models. This focused review discusses the relevance of 3D printing technologies and the applied cells and materials used in cutting-edge in vitro cancer models and microfluidic device systems. Future prospective solutions were discussed to establish 3D-printed in vitro models as reliable tools for drug screening and understanding cancer disease mechanisms. [ABSTRACT FROM AUTHOR]

As a lung cancer biomarker, exosomes were utilized for in vitro diagnosis to overcome the lack of sensitivity of conventional imaging and the potential harm caused by tissue biopsy. However, given the inherent heterogeneity of exosomes, the challenge of accurately and reliably recognizing subtle differences in the composition of exosomes from clinical samples remains significant. Herein, we report an artificial intelligence-assisted surface-enhanced Raman spectroscopy (SERS) strategy for label-free profiling of plasma exosomes for accurate diagnosis of early-stage lung cancer. Specifically, we build a deep learning model using exosome spectral data from lung cancer cell lines and normal cell lines. Then, we extracted the features of cellular exosomes by training a convolutional neural network (CNN) model on the spectral data of cellular exosomes and used them as inputs to a support vector machine (SVM) model. Eventually, the spectral features of plasma exosomes were combined to effectively distinguish adenocarcinoma in situ (AIS) from healthy controls (HC). Notably, the approach demonstrated significant performance in distinguishing AIS from HC samples, with an area under the curve (AUC) of 0.84, sensitivity of 83.3%, and specificity of 83.3%. Together, the results demonstrate the utility of exosomes as a biomarker for the early diagnosis of lung cancer and provide a new approach to prescreening techniques for lung cancer. [ABSTRACT FROM AUTHOR]

Globally, breast cancer is the leading cause of mortality for women. It has had an impact on the lives of all individuals, regardless of gender—males, females, and transgender people. However, it is more common among women. Its fatality rate can be decreased with early discovery and treatment. Machine Learning (ML) is critical to the early detection of breast cancer. ML's use has grown in a variety of fields during the last decade. Analytical modelling with ML is mostly restricted to statistical approaches such as image recognition, resonance spectroscopy, and mass spectrometry. This study gives an in-depth look at breast cancer and the many ML approaches used to identify it. A thorough examination of breast cancer diagnosis using machine learning is provided, comprising classification, prediction, and detection. Technical concerns with present prediction models and measuring methods (used to determine how active malignant and healthy tissues are) are highlighted to make future recommendations. [ABSTRACT FROM AUTHOR]

Cervical cancer is a prevalent disease affecting the cervix cells in women and is one of the leading causes of mortality for women globally. The Pap smear test determines the risk of cervical cancer by detecting abnormal cervix cells. Early detection and diagnosis of this cancer can effectively increase the patient's survival rate. The advent of artificial intelligence facilitates the development of automated computer-assisted cervical cancer diagnostic systems, which are widely used to enhance cancer screening. This study emphasizes the segmentation and classification of various cervical cancer cell types. An intuitive but effective segmentation technique is used to segment the nucleus and cytoplasm from histopathological cell images. Additionally, handcrafted features include different properties of the cells generated from the distinct cervical cytoplasm and nucleus area. Two feature rankings techniques are conducted to evaluate this study's significant feature set. Feature analysis identifies the critical pathological properties of cervical cells and then divides them into 30, 40, and 50 sets of diagnostic features. Furthermore, a graph dataset is constructed using the strongest correlated features, prioritizes the relationship between the features, and a robust graph convolution network (GCN) is introduced to efficiently predict the cervical cell types. The proposed model obtains a sublime accuracy of 99.11% for the 40-feature set of the SipakMed dataset. This study outperforms the existing study, performing both segmentation and classification simultaneously, conducting an in-depth feature analysis, attaining maximum accuracy efficiently, and ensuring the interpretability of the proposed model. To validate the model's outcome, we tested it on the Herlev dataset and highlighted its robustness by attaining an accuracy of 98.18%. The results of this proposed methodology demonstrate the dependability of this study effectively, detecting cervical cancer in its early stages and upholding the significance of the lives of women. [ABSTRACT FROM AUTHOR]

Polyp segmentation in colorectal images is the most effective and necessary tool for the early detection of colorectal cancer, and deep learning has become popular for efficiently segmenting polyps. The complex morphological characteristics of polyps, such as the unclear boundary between polyps and mucosa, and the lack of training data could cause great difficulties in network fitting. Transformer-based semantic segmentation networks have achieved more promising performance than traditional convolutional neural networks. However, the dispersion of self-attention and the less accurate local feature recognition limit the further development and applications of Transformer-based networks. This paper proposes a novel Stepwise Attention Emphasis module to refocus self-attention for Transformer-based polyp segmentation in colorectal images, where a reverse fuse module is used to better fuse different levels of features. Furthermore, a new decoder network, called the densely smooth fusion decoder, is also proposed to enhance local details and provide more useful information from deep features to shallow features. Experimental comparisons are conducted, and result analysis shows that the proposed network achieves promising performance in both learning and generalization ability on public datasets. [ABSTRACT FROM AUTHOR]

Breast carcinoma or breast cancer is the most common type of cancer in women. It is very dangerous, and early detection is important for proper diagnosis and reduction of mortality rate. Cancer starts in a benign state, and if there is no proper treatment, it becomes malignant. Computer-aided diagnosis (CAD) techniques can be used for early detection of cancers. These techniques can significantly and effectively help in the diagnosis of cancer. Deep learning is the most popular technique used for accurate data analysis. It is also a powerful tool for categorizing histopathological images of breast cancer and analyzing breast cell shapes and densities. This paper proposes a hybrid EfficientNet with an SVM to categorize breast mass density with consideration of tumor types. (i.e., malignant or benign). In this hybrid, EfficientNet, the mammography images are applied to EfficientNet, and then the classification is carried out using a Support Vector Machine (SVM). The proposed model achieved accuracy of 94.48%, precision of 94.79%, specificity of 99.21%, Precision of 94.79%, FPR of 0.79%, score of 94.45%, MCC of 93.78%, and Kappa of 74.76%. The model outperformed state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

Skin cancer is a disorder that is becoming more prevalent around the world and is responsible for numerous mortality. Skin cancer starts in one organ and slowly moves to other parts of the body before killing the patient. Early detection of skin cancer is important for reducing the number of deaths all over the world. Because it takes time and money to manually diagnose skin cancer, it is critical to create automated diagnostic techniques to categorize skin lesions more accurately. Medical image enhancement and deep learning-based segmentation techniques are developed in this proposed work. Cancer affected and non-affected skin images are given as input for the proposed method. Data collection consists of raw data that cannot produce high accuracy. So, a certain pre-processing technique is used in the proposed method to achieve high accuracy. Dingo Optimized Texture based Histogram Equalization (DOTHE) strategy is utilized to improve the skin image. Then the pre-processed image is partitioned into different parts or regions according to the features and properties of the pixels in the image. U-Net network architecture is used in the proposed method to segment the enhanced image. The performances of the proposed model are analyzed using the Convolutional Neural Network (CNN) model. This proposed model is tested with several metrics which attain better performances like 97% accuracy, 96% sensitivity, 95% specificity, 94% precision, and 3% error. Thus the designed model enhances and segments the image effectively, and it is useful for effective skin cancer prediction. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer (CRC) screening is underused, particularly among low‐income and minoritized populations, for whom the coronavirus disease 2019 (COVID‐19) pandemic has challenged progress in achieving equity. Methods: A hub‐and‐spoke model was used. The hub was a nonacademic organization and the spokes were three community health center (CHC) systems overseeing numerous clinic sites. Via a cluster‐randomized trial design, nine clinic sites were randomized to intervention and 16 clinic sites were randomized to usual care. Patient‐level interventions included invitation letters, mailed fecal immunochemical tests (FITs), and call/text‐based reminders. Year 1 intervention impact, which took place during the COVID‐19 pandemic, was assessed as the proportion completing screening among individuals not up to date at baseline, which compared intervention and nonintervention clinics accounting for intraclinic cluster variation; confidence intervals (CIs) around differences not including 0 were interpreted as statistically significant. Results: Among 26,736 patients who met eligibility criteria, approximately 58% were female, 55% were Hispanic individuals, and 44% were Spanish speaking. The proportion completing screening was 11.5 percentage points (ppts) (95% CI, 6.1–16.9 ppts) higher in intervention versus usual care clinics. Variation in differences between intervention and usual care clinics was observed by sex (12.6 ppts [95% CI, 7.2–18.0 ppts] for females; 8.8 ppts [95% CI, 4.7–13.9 ppts] for males) and by racial and ethnic group (13.8 ppts [95% CI, 7.0–20.6 ppts] for Hispanic individuals; 13.0 ppts [95% CI, 3.6–22.4 ppts] for Asian individuals; 11.3 ppts [95% CI, 5.8–16.8 ppts] for non‐Hispanic White individuals; 6.1 ppts [95% CI, 0.8–10.4 ppts] for Black individuals). Conclusions: A regional mailed FIT intervention was effective for increasing CRC screening rates across CHC systems serving diverse, low‐income populations. The results of this pragmatic randomized controlled trial conducted in three community health center systems show that among 26,736 randomized patients, a regional mailed fecal immunochemical test intervention conducted during the coronavirus disease 2019 pandemic was effective for increasing colorectal cancer screening. Effectiveness was shown across multiple demographic groups, including Hispanic/Latino and Asian populations, as well as Spanish‐speaking individuals. [ABSTRACT FROM AUTHOR]

A compact ultra-wide band antenna for breast cancer detection in bio-medical applications is presented in this study. The proposed antenna is printed on 1.6 mm thick FR4 substrate with a dielectric constant of 4.6 and tangential loss of 0.02. The uniform ground plane on the substrate (PCB) has been altered by shortening its length and making minimal changes to its side edges in order to improve overall bandwidth. The suggested antenna is functioning from 3 to 10.2 GHz which covers the ultra-wide band recommended by Federal Communication Commission (FCC) over the 10 dB impedance bandwidth. Additionally, the antenna has a significant overall gain of 3.2 dBi and an overall radiation efficiency of between 89 % and 92 %. Furthermore, the antenna maintains a uniform radiation pattern across its operating band. Parametric research has been conducted on the different parameters to tune the antenna into the required operating band, and placement analysis of the antenna is then investigated by assessing specific absorption rate (SAR). [ABSTRACT FROM AUTHOR]

With the objective to investigate associations between sociodemographic characteristics and participation in interventions designed to increase participation in cervical cancer screening among under‐screened women, we randomized a random sample of 6000 women in Norway aged 35–69 years who had not attended cervical screening for ≥10 years to receive either (i) a reminder to attend regular screening (control), (ii) an offer to order a self‐sampling kit (opt‐in), or (iii) a self‐sampling kit unsolicited (send‐to‐all). We analyzed how sociodemographic characteristics were associated with screening participation within and between screening arms. In the send‐to‐all arm, increased screening participation ranged from 17.1% (95% confidence interval [95% CI] = 10.3% to 23.8%) to 30.0% (95% CI = 21.5% to 38.6%) between sociodemographic groups. In the opt‐in arm, we observed smaller, and at times, non‐significant increases within the range 0.7% (95% CI = −5.8% to 7.3%) to 19.1% (95% CI = 11.6% to 26.7%). In send‐to‐all versus control comparisons, there was greater increase in participation for women in the workforce versus not (6.1%, 95% CI = 1.6% to 10.6%), with higher versus lower income (7.6%, 95% CI = 2.2% to 13.1%), and with university versus primary education (8.5%, 95% CI = 2.4% to 14.6%). In opt‐in versus control comparisons, there was greater increase in participation for women in the workforce versus not (4.6%, 95% CI = 0.7% to 8.5%), with higher versus lower income (6.3%, 95% CI = 1.5% to 11.1%), but lower increase for Eastern European versus Norwegian background (−12.7%, 95% CI = −19.7% to −5.7%). Self‐sampling increased cervical screening participation across all sociodemographic levels, but inequalities in participation should be considered when introducing self‐sampling, especially with the goal to reach long‐term non‐attending women. [ABSTRACT FROM AUTHOR]

People living with HIV (PLWH) are at highest risk of anal cancer and will benefit from optimized screening for early disease detection. We compared host DNA methylation markers in high‐grade squamous intraepithelial lesions (HSIL) versus samples negative for intraepithelial lesions (NILM) or low‐grade intraepithelial lesions (LSIL) in PLWH. We recruited PLWH identifying as male aged ≥18 years undergoing high‐resolution anoscopy (HRA) in Seattle, Washington, 2015–2016. Anal brush samples were collected for HPV detection, genotyping, and pyrosequencing methylation (host genes ASCL1, PAX1, FMN2, and ATP10A); clinical data were abstracted from medical records. We assessed associations between methylation and presence and extent of HSIL using generalized estimating equation logistic regression, adjusting for age, CD4 count and HIV viral load. Marker panels using HPV DNA and methylation were also evaluated to predict prevalent HSIL. We analyzed 125 samples from 85 participants (mean age 50.1; standard deviation 11.0 years). ASCL1 (adjusted odds ratio [aOR] per 1 unit increase mean percent methylation: 1.07, 95% CI: 1.01–1.13) and FMN2 (aOR per 1 unit increase mean percent methylation: 1.14, 95% CI: 1.08–1.20) methylation were significantly associated with HSIL versus NILM/LSIL. ASCL1 (aOR: 1.06, 95% CI: 1.01–1.11) and FMN2 (aOR: 1.13, 95% CI: 1.08–1.17) methylation were positively associated with increasing HSIL extent. A panel combining methylation (ASCL1 and FMN2) and HPV DNA (HPV16, HPV18, and HPV31) demonstrated best balance of sensitivity (78.2%) and specificity (73.9%) for HSIL detection compared with methylation or HPV alone. Increasing levels of DNA methylation of ASCL1 and FMN2 were positively associated with HSIL detection in PLWH. Host gene methylation testing shows promise for HSIL screening and triage. [ABSTRACT FROM AUTHOR]

Epidemiological evidence regarding the relationship between coffee and tea consumption and the risk of ovarian cancer (OC) is inconsistent. Therefore, we aimed to quantitatively investigate this topic in a large prospective cohort study. This cohort study included 24,715 individuals recruited from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trials between 1993 and 2001. The data used for our analysis included the latest follow‐up information collected up to 2015. Coffee intake of ≥4 cups/day (hazard ratio [HR], 0.586; 95% confidence interval [CI]: 0.356–0.966) or caffeine intake of 458.787 mg/day (HR, 0.607; 95% CI: 0.411–0.895) were associated with the lowest HR of incident OC in the fully adjusted model. Participants who consumed varying amounts of tea did not exhibit a statistically significant reduction in the risk of OC. Our findings suggest that a higher consumption of coffee or caffeine is associated with a reduced risk of OC. However, no statistically significant association was observed between tea consumption and the risk of OC. [ABSTRACT FROM AUTHOR]

Melanoma of the skin is the 17th most common cancer worldwide. Early detection of suspicious skin lesions (melanoma) can increase 5-year survival rates by 20%. The 7-point checklist (7PCL) has been extensively used to suggest urgent referrals for patients with a possible melanoma. However, the 7PCL method only considers seven meta-features to calculate a risk score and is only relevant for patients with suspected melanoma. There are limited studies on the extensive use of patient metadata for the detection of all skin cancer subtypes. This study investigates artificial intelligence (AI) models that utilise patient metadata consisting of 23 attributes for suspicious skin lesion detection. We have identified a new set of most important risk factors, namely "C4C risk factors", which is not just for melanoma, but for all types of skin cancer. The performance of the C4C risk factors for suspicious skin lesion detection is compared to that of the 7PCL and the Williams risk factors that predict the lifetime risk of melanoma. Our proposed AI framework ensembles five machine learning models and identifies seven new skin cancer risk factors: lesion pink, lesion size, lesion colour, lesion inflamed, lesion shape, lesion age, and natural hair colour, which achieved a sensitivity of 80.46 ± 2.50 % and a specificity of 62.09 ± 1.90 % in detecting suspicious skin lesions when evaluated using the metadata of 53,601 skin lesions collected from different skin cancer diagnostic clinics across the UK, significantly outperforming the 7PCL-based method (sensitivity 68.09 ± 2.10 % , specificity 61.07 ± 0.90 % ) and the Williams risk factors (sensitivity 66.32 ± 1.90 % , specificity 61.71 ± 0.6 % ). Furthermore, through weighting the seven new risk factors we came up with a new risk score, namely "C4C risk score", which alone achieved a sensitivity of 76.09 ± 1.20 % and a specificity of 61.71 ± 0.50 % , significantly outperforming the 7PCL-based risk score (sensitivity 73.91 ± 1.10 % , specificity 49.49 ± 0.50 % ) and the Williams risk score (sensitivity 60.68 ± 1.30 % , specificity 60.87 ± 0.80 % ). Finally, fusing the C4C risk factors with the 7PCL and Williams risk factors achieved the best performance, with a sensitivity of 85.24 ± 2.20 % and a specificity of 61.12 ± 0.90 % . We believe that fusing these newly found risk factors and new risk score with image data will further boost the AI model performance for suspicious skin lesion detection. Hence, the new set of skin cancer risk factors has the potential to be used to modify current skin cancer referral guidelines for all skin cancer subtypes, including melanoma. [ABSTRACT FROM AUTHOR]

Background: Breast 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. Methods: This 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. Results: Findings 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. Conclusion: Women'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. [ABSTRACT FROM AUTHOR]

Background: Risk-stratified approaches to breast screening show promise for increasing benefits and reducing harms. But the successful implementation of such an approach will rely on public acceptability. To date, research suggests that while increased screening for women at high risk will be acceptable, any de-intensification of screening for low-risk groups may be met with less enthusiasm. We report findings from a population-based survey of women in England, approaching the age of eligibility for breast screening, to compare the acceptability of current age-based screening with two hypothetical risk-adapted approaches for women at low risk of breast cancer. Methods: An online survey of 1,579 women aged 40–49 with no personal experience of breast cancer or mammography. Participants were recruited via a market research panel, using target quotas for educational attainment and ethnic group, and were randomised to view information about (1) standard NHS age-based screening; (2) a later screening start age for low-risk women; or (3) a longer screening interval for low-risk women. Primary outcomes were cognitive, emotional, and global acceptability. ANOVAs and multiple regression were used to compare acceptability between groups and explore demographic and psychosocial factors associated with acceptability. Results: All three screening approaches were judged to be acceptable on the single-item measure of global acceptability (mean score > 3 on a 5-point scale). Scores for all three measures of acceptability were significantly lower for the risk-adapted scenarios than for age-based screening. There were no differences between the two risk-adapted scenarios. In multivariable analysis, higher breast cancer knowledge was positively associated with cognitive and emotional acceptability of screening approach. Willingness to undergo personal risk assessment was not associated with experimental group. Conclusion: We found no difference in the acceptability of later start age vs. longer screening intervals for women at low risk of breast cancer in a large sample of women who were screening naïve. Although acceptability of both risk-adapted scenarios was lower than for standard age-based screening, overall acceptability was reasonable. The positive associations between knowledge and both cognitive and emotional acceptability suggests clear and reassuring communication about the rationale for de-intensified screening may enhance acceptability. [ABSTRACT FROM AUTHOR]

Background: Early detection through screening dramatically improves lung cancer survival rates, including among war Veterans, who are at heightened risk. The effectiveness of low dose computed tomography scans in lung cancer screening (LCS) prompted the Veteran's Affairs Lung Precision Oncology Program (VA LPOP) to increase screening rates. We aimed to develop an adaptive population health tool to determine adequate resource allocation for the program, with a specific focus on primary care providers, nurse navigators, and radiologists. Methods: We developed a tool using C + + that uses inputs that represents the process of the VA LCS program in Ann Arbor, Michigan to calculate FTEs of human resource needs to screen a given population. Further, we performed a sensitivity analysis to understand how resource needs are impacted by changes in population, screening eligibility, and time allocated for the nurse navigators' tasks. Results: Using estimates from the VA LCS Program as demonstrative inputs, we determined that the greatest number of full-time equivalents required were for radiologists, followed by nurse navigators and then primary care providers, for a target population of 75,000. An increase in the population resulted in a linear increase of resource needs, with radiologists experiencing the greatest rate of increase, followed by nurse navigators and primary care providers. These resource requirements changed with primary care providers, nurse navigators and radiologists demonstrating the greatest increase when 1–20, 20–40 and > 40% of Veterans accepted to be screened respectively. Finally, when increasing the time allocated to check eligibility by the nurse navigator from zero to three minutes, there was a linear increase in the full-time equivalents required for the nurse navigator. Conclusion: Variation of resource utilization demonstrated by our user facing tool emphasizes the importance of tailored strategies to accommodate specific population demographics and downstream work. We will continue to refine this tool by incorporating additional variability in system parameters, resource requirements following an abnormal test result, and resource distribution over time to reach steady state. While our tool is designed for a specific program in one center, it has wider applicability to other cancer screening programs. [ABSTRACT FROM AUTHOR]

Background: Population mail-out bowel cancer screening programs save lives through prevention and early detection; however, their effectiveness is constrained by low participation rates. Many non-participants are "intenders"; that is, they intend to screen but fail to do so, often forgetting or procrastinating. This study aimed to co-design interventions to increase screening participation among intenders in the Australian National Bowel Cancer Screening Program. Methods: Three semi-structured interviews, and one online cross-sectional survey, were conducted between August 2021 and December 2022. Interviews with people who had completed and returned their latest screening kit ("completers") were first conducted to identify the planning strategies they had used. Using survey data, logistic regressions were conducted to analyse strategies predictive of participants having returned their latest bowel cancer screening kit. Then, intenders were interviewed to explore their opinions of these strategies and worked with researchers to adapt these strategies into prototype interventions to facilitate screening participation. All interviews were analysed using the framework approach of codebook thematic analysis. Results: Interview participants who returned their kit shared their effective planning strategies, such as putting the kit in a visible place or by the toilet, planning a time at home to complete the kit, and using reminders. Survey participants who reported using such strategies were more likely to have completed their screening kit compared to those who did not. Prototype interventions developed and endorsed by intenders included providing a prompt to place the kit or a sticker near the toilet as a reminder, a deadline for kit return, the option to sign up for reminders, and a bag to store the sample in the fridge. Conclusions: These novel, consumer-led interventions that are built upon the needs and experience of screening invitees provide potential solutions to improve participation in population bowel cancer screening. [ABSTRACT FROM AUTHOR]

DNA methylation biomarkers have emerged as promising tools for cancer detection. Common methylation patterns across tumor types allow multi‐cancer detection. Droplet digital PCR (ddPCR) has gained considerable attention for methylation detection. However, multi‐cancer detection using multiple targets in ddPCR has never been performed before. Therefore, we developed a multiplex ddPCR assay for multi‐cancer detection. Based on previous data analyses using The Cancer Genome Atlas (TCGA), we selected differentially methylated targets for eight frequent tumor types (lung, breast, colorectal, prostate, pancreatic, head and neck, liver, and esophageal cancer). Three targets were validated using ddPCR in 103 tumor and 109 normal adjacent fresh frozen samples. Two distinct ddPCR assays were successfully developed. Output data from both assays is combined to obtain a read‐out from the three targets together. Our overall ddPCR assay has a cross‐validated area under the curve (cvAUC) of 0.948. Performance between distinct cancer types varies, with sensitivities ranging from 53.8% to 100% and specificities ranging from 80% to 100%. Compared to previously published single‐target parameters, we show that combining targets can drastically increase sensitivity and specificity, while lowering DNA input. In conclusion, we are the first to report a multi‐cancer methylation ddPCR assay, which allows for highly accurate tumor predictions. [ABSTRACT FROM AUTHOR]

Background: Prostate cancer is well known as the commonest cancer in men and the second leading cause of cancer-related death. CT, MRI and bone scintigraphy are considered the commonly widely used imaging diagnostic tools for detection, staging and follow-up of prostate cancer. Prostate-specific membrane antigen (PSMA) is a membrane glycoprotein, that can be concentrated in prostate cancer cells up to 100 times higher than in normal cells. PSMA-targeted imaging modalities have now proven their efficacy in diagnosis, staging and follow-up of prostate cancer. The use of 68Ga PSMA PET-CT has efficiently improved the detection of loco-regional and metastatic disease. 68Ga PSMA PET-CT also has an effective role in the primary diagnosis, staging, and detecting biochemical recurrence after curative treatment and in metastasis-targeted therapy. This work aims to review the role of 68Ga PSMA PET-CT in anatomical staging of prostate cancer in correlation with histopathological staging. Results: Zonal correlation between 68Ga PSMA findings and biopsy results showed sensitivity ranging between 76.9 and 90.6% and specificity ranging from 85.7 to 100%. There was high significant correlation between the SUVmax uptake and the biopsy results, between the SUVmax uptake and the local staging as well as between the Gleason score and 68Ga PSMA PET/CT findings. Conclusions: 68Ga PSMA PET/CT is a highly promising imaging modality with an effective role in detection of prostate cancer showing high sensitivity and specificity in prediction of zonal histopathological results and loco-regional Gleason score staging with significant positive correlation between the SUV uptake results, Gleason score and the PSA levels. [ABSTRACT FROM AUTHOR]

Pancreatic ductal adenocarcinoma (PDAC) is frequently detected in late stages, which leads to limited therapeutic options and a dismal overall survival rate. To date, no robust method for the detection of early-stage PDAC that can be used for targeted screening approaches is available. Liquid biopsy allows the minimally invasive collection of body fluids (typically peripheral blood) and the subsequent analysis of circulating tumor cells or tumor-associated molecules such as nucleic acids, proteins, or metabolites that may be useful for the early diagnosis of PDAC. Single biomarkers may lack sensitivity and/or specificity to reliably detect PDAC, while combinations of these circulating biomarkers in multimarker panels may improve the sensitivity and specificity of blood test-based diagnosis. In this narrative review, we present an overview of different liquid biopsy biomarkers for the early diagnosis of PDAC and discuss the validity of multimarker panels. [ABSTRACT FROM AUTHOR]

Background: More efficient methods to detect and treat precancerous lesions of the cervix at a single visit, such as low-cost confocal microscopy, could improve early diagnosis and hence outcomes. We piloted a prototype smartphone-compatible confocal micro-endoscope (SCME) among women presenting to a public cervical cancer screening clinic in Kampala, Uganda. We describe the piloting of the SCME device at an urban clinic used by lower cadre staff. Methods: We screened women aged 18 and 60 years, who presented for cervical cancer screening at the Kawempe National Referral Hospital Kampala, and evaluated the experience of their providers (nurses). Nurses received a 2-day training by the study doctors on how to use the SCME, which was added to the standard Visual Inspection with Acetic acid (VIA)-based cervical cancer screening. The SCME was used to take colposcopy images before and after VIA at positions 12 and 6 O'clock if VIA negative, and on precancer-suspicious lesions if VIA positive. We used questionnaires to assess the women's experiences after screening, and the experience of the nurses who operated the SCME. Results: Between November 2021 and July 2022, we screened 291 women with a median age of 36 years and 65.7% were HIV positive. Of the women screened, 146 were eligible for VIA, 123 were screened with the SCME, and we obtained confocal images from 103 women. Of those screened with the SCME, 60% found it comfortable and 81% were willing to screen again with it. Confocal images from 79% of the women showed distinguishable cellular features, while images from the remaining 21% were challenging to analyze. Nurses reported a mean score of 85% regarding the SCME's usefulness to their work, 71% regarding their satisfaction and willingness to use it again, 63% in terms of ease of use, and 57% concerning the ease of learning how to operate the SCME. Conclusion: Our findings demonstrate the feasibility of using the SCME by lower cadre staff in low-resource settings to aid diagnosis of precancerous lesions. However, more work is needed to make it easier for providers to learn how to operate the SCME and capture high-quality confocal images. [ABSTRACT FROM AUTHOR]

Background: Ethiopia's health system is overwhelmed by the growing burden of non-communicable diseases (NCDs). In this study, we assessed the availability of and readiness for NCD services and the interaction of NCD services with other essential and non-NCD services. Methods: The analysis focused on four main NCD services: diabetes mellitus, cardiovascular diseases, chronic respiratory diseases, and cancer screening. We used data from the 2018 Ethiopian Service Availability and Readiness Assessment (SARA) survey. As defined by the World Health Organization, readiness, both general and service-specific, was measured based on the mean percentage availability of the tracer indicators, such as trained staff and guidelines, equipment, diagnostic capacity, and essential medicines and commodities needed for delivering essential health services and NCD-specific services, respectively. The survey comprised 632 nationally representative healthcare facilities, and we applied mixed-effects linear and ordered logit models to identify factors affecting NCD service availability and readiness. Results: Only 8% of facilities provided all four NCD services. Availability varied for specific services, with cervical cancer screening being the least available service in the country: less than 10% of facilities, primarily higher-level hospitals, provided cervical cancer screening. General service readiness was a strong predictor of NCD service availability. Differences in NCD service availability and readiness between regions and facility types were significant. Increased readiness for specific NCD services was significantly associated with increased readiness for communicable disease services and interacted with the readiness for other NCD services. Conclusion: NCD service availability has considerable regional variation and is positively associated with general and communicable disease services readiness. Readiness for specific NCD services interacted with one another. The findings suggest an integrated approach to service delivery, focussing holistically on all disease services, is needed. There also needs to be increased attention to reducing resource allocation variation between facility types and locations. [ABSTRACT FROM AUTHOR]

Background: Preserved Ratio Impaired Spirometry (PRISm) is considered to be a precursor of chronic obstructive pulmonary disease. Radiomics nomogram can effectively identify the PRISm subjects from non-COPD subjects, especially when during large-scale CT lung cancer screening. Methods: Totally 1481 participants (864, 370 and 247 in training, internal validation, and external validation cohorts, respectively) were included. Whole lung on thin-section computed tomography (CT) was segmented with a fully automated segmentation algorithm. PyRadiomics was adopted for extracting radiomics features. Clinical features were also obtained. Moreover, Spearman correlation analysis, minimum redundancy maximum relevance (mRMR) feature ranking and least absolute shrinkage and selection operator (LASSO) classifier were adopted to analyze whether radiomics features could be used to build radiomics signatures. A nomogram that incorporated clinical features and radiomics signature was constructed through multivariable logistic regression. Last, calibration, discrimination and clinical usefulness were analyzed using validation cohorts. Results: The radiomics signature, which included 14 stable features, was related to PRISm of training and validation cohorts (p < 0.001). The radiomics nomogram incorporating independent predicting factors (radiomics signature, age, BMI, and gender) well discriminated PRISm from non-COPD subjects compared with clinical model or radiomics signature alone for training cohort (AUC 0.787 vs. 0.675 vs. 0.778), internal (AUC 0.773 vs. 0.682 vs. 0.767) and external validation cohorts (AUC 0.702 vs. 0.610 vs. 0.699). Decision curve analysis suggested that our constructed radiomics nomogram outperformed clinical model. Conclusions: The CT-based whole lung radiomics nomogram could identify PRISm to help decision-making in clinic. Key message: What is already known on this topic: Identifying PRISm subjects among non-COPD subjects, especially in the context of large-scale CT lung cancer screening, is currently a challenge. What this study adds: In this retrospective, and multicentric study that included 1481 subjects, radiomics nomogram developed by integrating radiomics signature and clinical features achieved good performance for the identification of PRISm, with AUC of 0.787, 0.773 and 0.702 in training, internal and external validation cohort. How this study might affect research, practice or policy: Radiomics nomogram, as a promising tool for identifying the PRISm from non-COPD subjects, hold great potential for guiding timely treatment and showing the added value of chest CT to evaluate the lung function status besides the morphological evaluation, especially during large-scale CT lung cancer screening. [ABSTRACT FROM AUTHOR]

Background: Circulating tumour DNA (ctDNA) is a subset of cell free DNA (cfDNA) released by tumour cells into the bloodstream. Circulating tumour DNA has shown great potential as a biomarker to inform treatment in cancer patients. Collecting ctDNA is minimally invasive and reflects the entire genetic makeup of a patient's cancer. ctDNA variants in NGS data can be difficult to distinguish from sequencing and PCR artefacts due to low abundance, particularly in the early stages of cancer. Unique Molecular Identifiers (UMIs) are short sequences ligated to the sequencing library before amplification. These sequences are useful for filtering out low frequency artefacts. The utility of ctDNA as a cancer biomarker depends on accurate detection of cancer variants. Results: In this study, we benchmarked six variant calling tools, including two UMI-aware callers for their ability to call ctDNA variants. The standard variant callers tested included Mutect2, bcftools, LoFreq and FreeBayes. The UMI-aware variant callers benchmarked were UMI-VarCal and UMIErrorCorrect. We used both datasets with known variants spiked in at low frequencies, and datasets containing ctDNA, and generated synthetic UMI sequences for these datasets. Variant callers displayed different preferences for sensitivity and specificity. Mutect2 showed high sensitivity, while returning more privately called variants than any other caller in data without synthetic UMIs – an indicator of false positive variant discovery. In data encoded with synthetic UMIs, UMI-VarCal detected fewer putative false positive variants than all other callers in synthetic datasets. Mutect2 showed a balance between high sensitivity and specificity in data encoded with synthetic UMIs. Conclusions: Our results indicate UMI-aware variant callers have potential to improve sensitivity and specificity in calling low frequency ctDNA variants over standard variant calling tools. There is a growing need for further development of UMI-aware variant calling tools if effective early detection methods for cancer using ctDNA samples are to be realised. [ABSTRACT FROM AUTHOR]

Introduction Methods Results Conclusions Lung and bronchus cancer is a leading cause of death in the United States. Compared with the national average, Michigan has an increased mortality rate and low early screening and treatment rates. This study aimed to explore the epidemiological trends and assess overall survival (OS) of patients diagnosed with lung cancer in Michigan from 1996 to 2017.Data was acquired from the Michigan Cancer Surveillance Program (MCSP). Log‐rank test was used to test OS among the time periods, univariate and multivariate cox regression models were employed to determine factors that significantly affected OS. We hypothesized that the introduction of more inclusive lung cancer screening guidelines in 2013 would improve OS for patients diagnosed after its implementation and that individual characteristics and tumor characteristics would both affect OS.Notably, 153 742 individuals met inclusion criteria: 54.22% male and 45.78% female. Mean age at diagnosis was 69 years. No significant difference in OS was found among the three time periods (p = 0.99). Univariate analyses identified four individual characteristics associated with reduced OS: age at diagnosis, male sex, American Indian race, and living in rural or urban area. Reduced OS was associated with primary sites tumors at main bronchus, lung base, or within overlapping lobes, and SEER stage 7.This study highlights several factors that influence OS. Consideration of these factors may be helpful as a community outreach tool to help increase early detection and reduce overall mortality. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusions Lung cancer screening with low‐dose computed tomography (CT) scans (LDCT) has reduced mortality for patients with high‐risk smoking histories, but it has significant limitations: LDCT screening implementation remains low, high rates of false‐positive scans, and current guidelines exclude those without smoking histories. We sought to explore the utility of liquid biopsy (LBx) in early cancer screening and diagnosis of lung cancer.Using the high‐definition single‐cell assay workflow, we analyzed 99 peripheral blood samples from three cohorts: normal donors (NDs) with no known pathology (n = 50), screening CT patients (n = 25) with Lung‐RADS score of 1–2, and biopsy (BX) patients (n = 24) with abnormal CT scans requiring tissue biopsy.For CT and BX patients, demographic information was roughly equivalent; however, average pack‐years smoked differed. A total of 14 (58%) BX patients were diagnosed with primary lung cancer (BX+). The comparison of the rare event enumerations among the cohorts revealed a greater incidence of total events, rare cells, and oncosomes, as well as specific cellular phenotypes in the CT and BX cohorts compared with the ND cohort. LBx analytes were also significantly elevated in the BX compared with the CT samples, but there was no difference between BX+ and BX− samples.The data support the utility of the LBx in distinguishing patients with an alveolar lesion from those without, providing a potential avenue for prescreening before LDCT. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusion Sessile serrated lesions (SSL) account for up to 30% of colorectal carcinoma pathogenesis. With multiple classification changes and improvements in colonoscopy equipment and technique, historical reporting may have underestimated the true incidence of SSLs. This study aimed to determine the incidence of SSLs in patients undergoing colonoscopic investigation in Canterbury, New Zealand over a 1‐year period and describe their clinical and pathological characteristics.Electronic records were searched to identify all lower endoscopy procedures with polypectomy performed from 1 January 2022 to 1 December 2022 (inclusive). Patients' electronic records were used to collect histological classification, location and size of each polyp removed during their procedure. The primary outcome was the number of procedures that had one or more SSL, adenoma or hyperplastic polyp identified. Secondary outcomes included histological classification, location and size of each polyp removed.There were 4346 procedures completed during the study period. Of these, 64.1% (2786) had a polypectomy and 18.6% (808) had at least one SSL excised. Individual polyp analysis was completed on 9166 polyps and found that 24.0% of polyps removed were SSLs and they were found predominately in the right colon (65.1% right colon, 32.6% left colon, 2.3% rectum). SSLs were typically <10 mm (84.8%).This study found a higher incidence of SSLs compared to previous research. These results raise questions regarding whether SLL rates have been historically underestimated, whether SSL detection rate should be included as a key performance indicator and raises further concerns regarding the use of computed tomography colonography as a screening tool. [ABSTRACT FROM AUTHOR]

Introduction: Cervical cancer is a prevalent cancer among women in low and middle-income countries, but it can be largely prevented through screening programs and HPV vaccination. This study aimed to determine the level of knowledge, attitudes, and practices regarding cervical cancer screening among healthcare providers in Sub-Saharan African countries. Methods: Systematic review and meta-analysis were conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Relevant databases including PubMed, Cochrane Library, AJOL, Google Scholar, and ScienceDirect databases were used to retrieve and search articles. The study included published and unpublished research written in English between January 2013 and May 16, 2024 for studies reporting knowledge, attitude, and practice towards cervical cancer screening among healthcare providers in Sub-Saharan Africa. This review has been registered on PROSPERO. The heterogeneity of the data was evaluated using the I² statistic. A meta-analysis was conducted using STATA 17 software, with a 95% confidence interval. The researchers also conducted publication bias and sensitivity analysis. Results: The review included 30 studies involving 7542 healthcare providers. The pooled magnitude of good knowledge status towards cervical cancer was 67.93% (95% CI: 53.36-82.50) whereas the pooled magnitude of positive attitude towards cervical cancer was 55.26% (95% CI: 34.28-76.23). The results also showed that about 49.68% (95% CI: 33.18-66.17) of healthcare providers had good knowledge status about cervical cancer screening, 66.63%(95% CI: 50.36-82.89) had a positive attitude towards it, and only 17.23% (95% CI; 6.08-28.37) had ever screened for cervical cancer. Conclusion: The overall magnitude of knowledge and attitude of healthcare providers in Sub-Saharan Africa towards cervical cancer and its screening was suboptimal. Furthermore, a low percentage of female healthcare providers in the region had undergone screening for cervical cancer. As a result, policymakers and program administrators should focus on improving the knowledge, attitude, and practices of healthcare providers to meet the global health goal of cervical cancer screening and effectively eliminating cervical cancer. Healthcare providers must serve as role models for other women who should also undergo screening. [ABSTRACT FROM AUTHOR]

Objective: The research aims to develop an advanced and precise lung cancer screening model based on Convolutional Neural Networks (CNN). Methods: Based on the health medical big data platform of Shandong University, we developed a VGG16-Based CNN lung cancer screening model. This model was trained using the Computed Tomography scans data of patients from Pingyi Traditional Chinese Medicine Hospital in Shandong Province, from January to February 2023. Data augmentation techniques, including random resizing, cropping, horizontal flipping, color jitter, random rotation and normalization, were applied to improve model generalization. We used five-fold cross-validation to robustly assess performance. The model was fine-tuned with an SGD optimizer (learning rate 0.001, momentum 0.9, and L2 regularization) and a learning rate scheduler. Dropout layers were added to prevent themodel from relying too heavily on specific neurons, enhancing its ability to generalize. Early stopping was implemented when validation loss did not decrease over 10 epochs. In addition, we evaluated the model's performance with Area Under the Curve (AUC), Classification accuracy, Positive Predictive Value (PPV), and Negative Predictive Value (NPV), Sensitivity, Specificity and F1 score. External validation used an independent dataset from the same hospital, covering January to February 2022. Results: The training and validation loss and accuracy over iterations show that both accuracy metrics peak at over 0.9 by iteration 15, prompting early stopping to prevent overfitting. Based on five-fold cross-validation, the ROC curves for the VGG16-Based CNN model, demonstrate an AUC of 0.963 ± 0.004, highlighting its excellent diagnostic capability. Confusion matrices provide average metrics with a classification accuracy of 0.917 ± 0.004, PPV of 0.868 ± 0.015, NPV of 0.931 ± 0.003, Sensitivity of 0.776 ± 0.01, Specificity of 0.962 ± 0.005 and F1 score of 0.819 ± 0.008, respectively. External validation confirmed the model's robustness across different patient populations and imaging conditions. Conclusion: The VGG16-Based CNN lung screening model constructed in this study can effectively identify lung tumors, demonstrating reliability and effectiveness in real-world medical settings, and providing strong theoretical and empirical support for its use in lung cancer screening. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) readers of mammograms compare favourably to individual radiologists in detecting breast cancer. However, AI readers cannot perform at the level of multi-reader systems used by screening programs in countries such as Australia, Sweden, and the UK. Therefore, implementation demands human-AI collaboration. Here, we use a large, high-quality retrospective mammography dataset from Victoria, Australia to conduct detailed simulations of five potential AI-integrated screening pathways, and examine human-AI interaction effects to explore automation bias. Operating an AI reader as a second reader or as a high confidence filter improves current screening outcomes by 1.9–2.5% in sensitivity and up to 0.6% in specificity, achieving 4.6–10.9% reduction in assessments and 48–80.7% reduction in human reads. Automation bias degrades performance in multi-reader settings but improves it for single-readers. This study provides insight into feasible approaches for AI-integrated screening pathways and prospective studies necessary prior to clinical adoption. Successful human-AI collaboration could greatly contribute to breast cancer mammographic screening. Here, the authors use a large-scale retrospective mammography dataset to simulate and compare five plausible AI-integrated screening pathways, finding optimal ways in which human-AI collaboration could be implemented in real-world settings. [ABSTRACT FROM AUTHOR]

Computer Aided Detection (CAD) has been used to help readers find cancers in mammograms. Although these automated systems have been shown to help cancer detection when accurate, the presence of CAD also leads to an over-reliance effect where miss errors and false alarms increase when the CAD system fails. Previous research investigated CAD systems which overlayed salient exogenous cues onto the image to highlight suspicious areas. These salient cues capture attention which may exacerbate the over-reliance effect. Furthermore, overlaying CAD cues directly on the mammogram occludes sections of breast tissue which may disrupt global statistics useful for cancer detection. In this study we investigated whether an over-reliance effect occurred with a binary CAD system, which instead of overlaying a CAD cue onto the mammogram, reported a message alongside the mammogram indicating the possible presence of a cancer. We manipulated the certainty of the message and whether it was presented only to indicate the presence of a cancer, or whether a message was displayed on every mammogram to state whether a cancer was present or absent. The results showed that although an over-reliance effect still occurred with binary CAD systems miss errors were reduced when the CAD message was more definitive and only presented to alert readers of a possible cancer. [ABSTRACT FROM AUTHOR]

The article examines the state of prostate cancer (PCa) screening in Canada. Topics include the high incidence of PCa in Canadian men and the benefits and risks associated with prostate-specific antigen (PSA) screening; the financial barriers and inequities in screening access, such as Black and Indigenous men, are disproportionately affected; and the need for more context-specific research to address these disparities and improve screening practices.

OBJECTIVES: Text messaging could be effective for determining patient eligibility for lung cancer screening (LCS). We explored people's willingness to share their tobacco use history via text message among diverse groups. STUDY DESIGN: Cross-sectional survey. METHODS: In 2020, we conducted a cross-sectional survey asking respondents about cellular phone usage, smoking habits, sociodemographic characteristics, and the likelihood of responding to a text message from their health care provider's office about tobacco use. We used χ² and analysis of variance tests for.comparisons. RESULTS: Among 745 respondents, 90% used text messaging casually. Overall, 54% never smoked, 33% currently smoked, and 13% previously smoked. Six percent were LCS eligible, and 20% used both cigarettes and e-cigarettes (dual users). Current smokers were significantly younger, less likely to be female, and more likely to use text messaging. LCS-eligible respondents were older and less likely to have a high income. Dual users were younger, less likely to report female gender and live in rural areas, and more likely to have a college education and high income. Most respondents (83%) indicated they were likely to respond to text message inquiries regarding smoking status. Middle-aged respondents (mean age, 37 years) were significantly more willing to report smoking status than younger or older respondents (91% vs 84% and 84%, respectively). Respondents with no college education (83% vs 88%) or with a low income vs a middle or high income (81% vs 86% and 88%, respectively) were significantly less willing to report smoking status via text messages. CONCLUSIONS: Text messaging showed promise for evaluating smoking history and for simplifying the process of identifying LCS-eligible individuals. However, achieving equity in identifying eligibility for LCS requires the implementation of multimodal strategies. [ABSTRACT FROM AUTHOR]

Background Population screening for colorectal cancer (CRC) remains low, requiring alternative approaches for increasing participation. Opportunistic screening of hospitalized patients may aid in increasing uptake rates. Objective To assess whether inpatients can be recruited for opportunistic CRC screening using fecal immunochemical testing (FIT). Methods Inpatient charts were prospectively reviewed for study eligibility on admission of patients to the medical wards of 3 hospitals in Winnipeg, Canada. Eligible patients were approached for participation and consent. Inoculated FIT specimen collection tubes were sent to the hospital laboratory for testing. Patients with positive FIT results received a follow-up colonoscopy. Results In total, 1542 inpatient charts were screened for eligibility; 53 patients were identified for enrollment (51.9% were male; median age, 59 years), of whom 13 patients consented to participate but only 7 provided a stool specimen. One of those 7 patients had a positive FIT result. The overall screening rate was low, at 0.45%. The primary reason for exclusion of patients was age (outside of the range of 50-75 years), followed by patients having recent gastrointestinal bleeding and/or known intestinal diseases. Conclusions Our data suggest that it is infeasible to recruit inpatients for opportunistic CRC screening in routine clinical practice. [ABSTRACT FROM AUTHOR]

Background: Polyps are the predominant precursors of colorectal cancer. In the past three decades, the incidence and mortality rates of colorectal cancer have been increasing in adults younger than 50 years. Aims: The aim of this clinical audit was to evaluate the prevalence, characteristics and clinical associations of polyps in adults aged 18–49 years presenting to an established private gastroenterology clinic in the Toowoomba Darling Downs region. Methods: The audit included data from 353 patient records held by the Toowoomba Gastroenterology Clinic. Data extracted from patient medical records through the Medical Director program software contained structured endoscopy/colonoscopy and histology reports of excised lesions of patients presenting to the clinic. The extract involved identifying all patients aged 18–49 years in the database from January 2019 to March 2022. Patients were screened based on audit inclusion and exclusion criteria. Patients were risk stratified for recommended surveillance intervals as per Australian Clinical Guidelines. Results: Of the sample population, 33.4% were identified with polyps and 22.4% were identified with neoplastic polyps (NPs). A total of 6.7% of 18‐ to 29‐year‐old patients were identified with intermediate risk for colorectal cancer (CRC) screening, and 19.8% and 19.3% of 30‐ to 39‐year‐old and 40‐ to 49‐year‐old patients identified with intermediate or high risk for CRC screening respectively. Increased age, greater size of polyps and surveillance of previous polyps were associated with increased NP prevalence. Conclusions: Data from this audit supported the temporal trend of increasing prevalence of polyps in adults younger than 50 years. Patient cohorts aged 30–39 and 40–49 years may benefit from earlier first colonoscopies. Findings could be the impetus for future research in young adults presenting for colonoscopy. [ABSTRACT FROM AUTHOR]

Gender‐affirming hormone therapy (GAHT) is used by many transgender and gender‐diverse adults to align physical characteristics with their gender identity, reduce gender incongruence and improve psychological functioning. This narrative review provides an overview of the initiation and monitoring of GAHT in an Australian context. Trans individuals treated with testosterone typically receive standard testosterone doses and formulations recommended for cisgender men, whereas those receiving estradiol GAHT are typically treated with estradiol in combination with an anti‐androgen in those without orchidectomy. Proactive monitoring and mitigation of cardiovascular risk factors is pertinent in all transgender and gender‐diverse adults and bone health is an important consideration in those using estradiol GAHT. [ABSTRACT FROM AUTHOR]

Introduction: The study explored the effects of SHOX2 and RASSF1A DNA methylation in lung cancer (LC). Method: Bronchoalveolar lavage fluid (BALF) samples as well as LC and normal adjacent tissues were collected from 72 LC patients and 35 patients with benign pulmonary nodules. Quantitative analysis of SHOX2 and RASSF1A DNA methylation was performed in benign pulmonary nodules and different stages of LC. The diagnostic value of SHOX2 and RASSF1A DNA methylation in LC and benign pulmonary nodules was determined by receiver operating characteristics analysis. Gain/loss-of-function experiments were constructed in LC cells and mouse models of xenograft and pulmonary nodule metastasis. The levels of SHOX2 and transfer-associated genes were tested through quantitative reverse transcription polymerase chain reaction and Western blot. Malignant phenotype of LC cells was assessed by functional experiment. The tumor volume and weight of mice in xenograft models were measured. Pulmonary nodule metastasis was determined through HE staining assay. 5-azacytidine appeared as a positive control drug. Result: SHOX2 DNA methylation or RASSF1A DNA methylation had diagnostic efficiency in pulmonary nodules and early LC, with the two combined having better diagnostic value. SHOX2 expression was upregulated in LC. Similar to 5-azacytidine, SHOX2 knockdown inhibited LC cell viability, migration, and invasion in vitro as well as restrained LC tumorigenesis and pulmonary nodule metastasis in vivo, whereas overexpressed SHOX2 had the opposite effects. Conclusion: The combination of SHOX2 and RASSF1A DNA methylation had a diagnostic value in pulmonary nodules and early LC. SHOX2 positively modulated the tumorigenesis and metastasis of LC by regulating DNA methylation processes. [ABSTRACT FROM AUTHOR]

In a tragically ironic twist, antiretroviral therapy (ART) that promised an end to AIDS ushered in a syndemic of viral cancers, transforming hope to despair. In this article we draw from the illness narratives of HIV positive women attending a cervical cancer screening clinic in Johannesburg, South Africa, and chart their pathways from HIV to cancer, and their quest for treatment. Our interlocutors described protracted struggles to access surgical procedures to prevent the onset of cervical cancer. Dealt a double blow of HIV and cervical cancer, women's narratives reveal the intersections of exposure to pathogens and the precarity of hope. [ABSTRACT FROM AUTHOR]