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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]

BACKGROUND: The intricate balance between the advantages and risks of low-dose computed tomography (LDCT) impedes the utilization of lung cancer screening (LCS). Guiding shared decision-making (SDM) for well-informed choices regarding LCS is pivotal. There has been a notable increase in research related to SDM. However, these studies possess limitations. For example, they may ignore the identification of decision support and needs from the perspective of health care providers and high-risk groups. Additionally, these studies have not adequately addressed the complete SDM process, including pre-decisional needs, the decision-making process, and post-decision experiences. Furthermore, the East-West divide of SDM has been largely ignored. This study aimed to explore the decisional needs and support for shared decision-making for LCS among health care providers and high-risk groups in China. METHODS: Informed by the Ottawa Decision-Support Framework, we conducted qualitative, face-to-face in-depth interviews to explore shared decision-making among 30 lung cancer high-risk individuals and 9 health care providers. Content analysis was used for data analysis. RESULTS: We identified 4 decisional needs that impair shared decision-making: (1) LCS knowledge deficit; (2) inadequate supportive resources; (3) shared decision-making conceptual bias; and (4) delicate doctor-patient bonds. We identified 3 decision supports: (1) providing information throughout the LCS process; (2) providing shared decision-making decision coaching; and (3) providing decision tools. CONCLUSIONS: This study offers valuable insights into the decisional needs and support required to undergo LCS among high-risk individuals and perspectives from health care providers. Future studies should aim to design interventions that enhance the quality of shared decision-making by offering LCS information, decision tools for LCS, and decision coaching for shared decision-making (e.g., through community nurses). Simultaneously, it is crucial to assess individuals needs for effective deliberation to prevent conflicts and regrets after arriving at a decision.

BACKGROUND: Following a breast cancer diagnosis, it is uncertain whether womens breast density knowledge influences their willingness to undergo pre-operative imaging to detect additional cancer in their breasts. We evaluated womens breast density knowledge and their willingness to delay treatment for pre-operative testing. METHODS: We surveyed women identified in the Breast Cancer Surveillance Consortium aged ≥ 18 years, with first breast cancer diagnosed within the prior 6-18 months, who had at least one breast density measurement within the 5 years prior to their diagnosis. We assessed womens breast density knowledge and correlates of willingness to delay treatment for 6 or more weeks for pre-operative imaging via logistic regression. RESULTS: Survey participation was 28.3% (969/3,430). Seventy-two percent (469/647) of women with dense and 11% (34/322) with non-dense breasts correctly knew their density (p

BACKGROUND: Rural residents have a higher prevalence of colorectal cancer (CRC) mortality compared to urban individuals. Policies have been aimed at improving access to CRC screening to reduce these outcomes. However, little attention has been paid to other determinants of CRC-related outcomes, such as stage at diagnosis, treatment, or survivorship care. The main objective of this analysis was to evaluate literature describing differences in CRC screening, stage at diagnosis, treatment, and survivorship care between rural and urban individuals. MATERIALS AND METHODS: We conducted a systematic review of electronic databases using a combination of MeSH and free-text search terms related to CRC screening, stage at diagnosis, treatment, survivorship care, and rurality. We identified 921 studies, of which 39 were included. We assessed methodological quality using the ROBINS-E tool and summarized findings descriptively. A meta-analysis was performed of studies evaluating CRC screening using a random-effects model. RESULTS: Seventeen studies reported disparities between urban and rural populations in CRC screening, 12 on treatment disparities, and 8 on staging disparities. We found that rural individuals were significantly less likely to report any type of screening at any time period (pooled odds ratio = 0.81, 95% CI, 0.76-0.86). Results were inconclusive for disparities in staging at diagnosis and treatment. One study reported a lower likelihood of use of CRC survivorship care for rural individuals compared to urban individuals. CONCLUSION: There remains an urgent need to evaluate and address CRC disparities in rural areas. Investigators should focus future work on assessing the quality of staging at diagnosis, treatment, and survivorship care in rural areas.

OBJECTIVE: To investigate current screening behaviors among high-risk individuals and analyse the factors that influence them. METHODS: A cross-sectional of 1652 high-risk individuals were recruited in Fujian Province, China from February to October 2022. Socio-demographic characteristics of participants were collected and other survey measures included a lung cancer and lung cancer screening knowledge questionnaire and a stage of adoption algorithm. Standardized measures on surveys were comprised of the: Lung Cancer Screening Health Belief Scales, Cataldo Lung Cancer Stigma Scale, Generalized Anxiety Disorder Scale-7, Patient Health Questionnaire-9, and the Patient Trust in the Medical Profession Scale. Factors associated with screening behavior were identified using binary logistic regression analysis. RESULTS: Lung cancer screening behavior stages were largely reported as Stage 1 and Stage 2 (64.4%). The facilitators of lung cancer screening included urban residence (OR = 1.717, 95% CI: 1.224-2.408), holding administrative positions (OR = 16.601, 95% CI: 2.118-130.126), previous lung cancer screening behavior (OR = 10.331, 95% CI: 7.463-14.302), media exposure focused on lung cancer screening (OR = 1.868, 95% CI: 1.344-2.596), a high level of knowledge about lung cancer and lung cancer screening (OR = 1.256, 95% CI: 1.185-1.332), perceived risk of lung cancer (OR = 1.123, 95% CI: 1.029-1.225) and lung cancer screening health beliefs (OR = 1.090, 95% CI: 1.067-1.113). A barrier to lung cancer screening was found to be social influence (influence of friends or family) (OR = 0.669, 95% CI: 0.465-0.964). CONCLUSIONS: This study found a low participation rate in lung cancer screening and identified eight factors that affected lung cancer screening behaviors among high-risk individuals. Findings suggest targeted lung cancer screening programs should be developed based on identified influencing factors in order to effectively promote awareness and uptake of lung cancer screening.

BACKGROUND: The decision to screen for breast cancer among older adults with dementia is complex and must often be individualized, as these individuals have an elevated risk of harm from over-screening. Medicare beneficiaries with dementia are increasingly enrolling in Medicare Advantage plans, which typically promote receipt of preventive cancer screening among their enrollees. This study examined the utilization of breast cancer screening among Medicare enrollees with dementia, in Medicare Advantage and in fee-for-service Medicare. METHODS: We conducted a pooled cross-sectional study of women with Alzheimers disease and related dementias or cognitive impairment who were eligible for mammogram screening. We used Medicare Current Beneficiary Survey data to identify utilization of biennial mammogram screening between 2012 and 2019. Poisson regression models were used to estimate prevalence ratios of mammogram utilization and to calculate adjusted mammogram rates for Medicare Advantage and fee-for-service Medicare enrollees with dementia, and further stratified by rurality and by dual eligibility for Medicare and Medicaid. RESULTS: Mammogram utilization was 16% higher (Prevalence Ratio [PR] 1.16; 95% CI: 1.05, 1.29) among Medicare Advantage enrollees with dementia, compared to their counterparts in fee-for-service Medicare. Rural enrollees experienced no significant difference (PR 0.99; 95% CI: 0.72, 1.37) in mammogram use between Medicare Advantage and fee-for-service Medicare enrollees. Among urban enrollees, Medicare Advantage enrollment was associated with a 21% higher mammogram rate (PR 1.21; 95% CI: 1.09, 1.35). Dual-eligible Medicare Advantage enrollees had a 34% higher mammogram rate (PR 1.34; 95% CI: 1.10, 1.63) than dual-eligible fee-for-service Medicare enrollees. Among non-dual-eligible enrollees, adjusted mammogram rates were not significantly different (PR 1.11; 95% CI: 0.99, 1.24) between Medicare Advantage and fee-for-service Medicare enrollees. CONCLUSIONS: Medicare beneficiaries age 65-74 with Alzheimers disease and related dementias or cognitive impairment had a higher mammogram use rate when they were enrolled in Medicare Advantage plans compared to fee-for-service Medicare, especially when they were dual-eligible or lived in urban areas. However, some Medicare Advantage enrollees with Alzheimers disease and related dementias or cognitive impairment may have experienced over-screening for breast cancer.

PURPOSE: To achieve the WHO cervical cancer elimination targets, countries globally must achieve 70% cervical cancer screening (CCS) coverage. We evaluated CCS uptake and predictors of screening positive at two public HIV care programs in western Kenya. METHODS: From October 2007 to February 2019, data from the Family AIDS Care and Education Services (FACES) and Academic Model Providing Access to Healthcare (AMPATH) programs in western Kenya were analyzed. The study population included women age 18-65 years enrolled in HIV care. Screening uptake was calculated annually and overall, determining the proportion of eligible women screened. Multivariate logistic regression assessed predictors of positive screening outcomes. RESULTS: There were 57,298 women living with HIV (WLWHIV) eligible for CCS across both programs during the study period. The mean age was 31.4 years (IQR, 25.9-37.8), and 39% were on antiretroviral therapy (ART) at the first CCS-eligible visit. Of all eligible women, 29.4% (95% CI, 29.1 to 29.8) underwent CCS during the study period, 27.0% (95% CI, 26.5 to 27.4) in the AMPATH program, and 35.6% (95% CI, 34.9 to 36.4) in the FACES program. Annual screening uptake varied greatly in both programs, with coverage as low as 1% of eligible WLWHIV during specific years. Age at first screening, CD4 count within 90 days of screening, current use of ART, and program (AMPATH v FACES) were each statistically significant predictors of positive screening. CONCLUSION: CCS uptake at two large HIV care programs in Kenya fell short of the WHOs 70% screening target. Screening rates varied significantly on the basis of the availability of funding specific to CCS, reflecting the limitations of vertical funding programs.

BackgroundRecently-updated global guidelines for cervical cancer screening incorporated new technologies-most significantly, the inclusion of HPV DNA detection as a primary screening test-but leave many implementation decisions at countries' discretion. We sought to develop recommendations for Malawi as a test case since it has the second-highest cervical cancer burden globally and high HIV prevalence. We incorporated updated epidemiologic data, the full range of ablation methods recommended, and a more nuanced representation of how HIV status intersects with cervical cancer risk and exposure to screening to model outcomes of different approaches to screening.MethodsUsing a Markov model, we estimate the relative health outcomes and costs of different approaches to cervical cancer screening among Malawian women. The model was parameterized using published data, and focused on comparing "triage" approaches-i.e., lesion treatment (cryotherapy or thermocoagulation) at differing frequencies and varying by HIV status. Health outcomes were quality-adjusted life years (QALYs) and deaths averted. The model was built using TreeAge Pro software.ResultsThermocoagulation was more cost-effective than cryotherapy at all screening frequencies. Screening women once per decade would avert substantially more deaths than screening only once per lifetime, at relatively little additional cost. Moreover, at this frequency, it would be advisable to ensure that all women who screen positive receive treatment (rather than investing in further increases in screening frequency): for a similar gain in QALYs, it would cost more than four times as much to implement once-per-5 years screening with only 50% of women treated versus once-per-decade screening with 100% of women treated. Stratified screening schedules by HIV status was found to be an optimal approach.ConclusionsThese results add new evidence about cost-effective approaches to cervical cancer screening in low-income countries. At relatively infrequent screening intervals, if resources are limited, it would be more cost-effective to invest in scaling up thermocoagulation for treatment before increasing the recommended screening frequency. In Malawi or countries in a similar stage of the HIV epidemic, a stratified approach that prioritizes more frequent screening for women living with HIV may be more cost-effective than population-wide recommendations that are HIV status neutral.

ImportanceEarly-onset colorectal cancer (EOCRC), defined as a diagnosis at younger than age 50 years, is increasing, and so-called red flag signs and symptoms among these individuals are often missed, leading to diagnostic delays. Improved recognition of presenting signs and symptoms associated with EOCRC could facilitate more timely diagnosis and impact clinical outcomes.ObjectiveTo report the frequency of presenting red flag signs and symptoms among individuals with EOCRC, to examine their association with EOCRC risk, and to measure variation in time to diagnosis from sign or symptom presentation.Data sourcesPubMed/MEDLINE, Embase, CINAHL, and Web of Science were searched from database inception through May 2023.Study selectionStudies that reported on sign and symptom presentation or time from sign and symptom presentation to diagnosis for patients younger than age 50 years diagnosed with nonhereditary CRC were included.Data extraction and synthesisData extraction and quality assessment were performed independently in duplicate for all included studies using Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting guidelines. Joanna Briggs Institute Critical Appraisal tools were used to measure risk of bias. Data on frequency of signs and symptoms were pooled using a random-effects model.Main outcomes and measuresOutcomes of interest were pooled proportions of signs and symptoms in patients with EOCRC, estimates for association of signs and symptoms with EOCRC risk, and time from sign or symptom presentation to EOCRC diagnosis.ResultsOf the 12 859 unique articles initially retrieved, 81 studies with 24 908 126 patients younger than 50 years were included. The most common presenting signs and symptoms, reported by 78 included studies, were hematochezia (pooled prevalence, 45% [95% CI, 40%-50%]), abdominal pain (pooled prevalence, 40% [95% CI, 35%-45%]), and altered bowel habits (pooled prevalence, 27% [95% CI, 22%-33%]). Hematochezia (estimate range, 5.2-54.0), abdominal pain (estimate range, 1.3-6.0), and anemia (estimate range, 2.1-10.8) were associated with higher EOCRC likelihood. Time from signs and symptoms presentation to EOCRC diagnosis was a mean (range) of 6.4 (1.8-13.7) months (23 studies) and a median (range) of 4 (2.0-8.7) months (16 studies).Conclusions and relevanceIn this systematic review and meta-analysis of patients with EOCRC, nearly half of individuals presented with hematochezia and abdominal pain and one-quarter with altered bowel habits. Hematochezia was associated with at least 5-fold increased EOCRC risk. Delays in diagnosis of 4 to 6 months were common. These findings highlight the need to identify concerning EOCRC signs and symptoms and complete timely diagnostic workup, particularly for individuals without an alternative diagnosis or sign or symptom resolution.

Introduction/objectivesColonoscopy completion rates after an abnormal fecal immunochemical test (FIT) are suboptimal, resulting in missed opportunities for early detection and prevention of colorectal cancer. Patient navigation and structured follow-up may improve colonoscopy completion, but implementation of these strategies is not widespread.MethodsWe conducted a quality improvement study using a Plan-Do-Study-Act (PDSA) Model to increase colonoscopy completion after abnormal FIT in a large federally qualified health center serving a diverse and low-income population. Intervention components included patient navigation, and a checklist to promote completion of key steps required for abnormal FIT follow-up. Primary outcome was proportion of patients achieving colonoscopy completion within 6 months of abnormal FIT, assessed at baseline for 156 patients pre-intervention, and compared to 208 patients during the intervention period from April 2017 to December 2019. Drop offs at each step in the follow-up process were assessed.ResultsColonoscopy completion improved from 21% among 156 patients with abnormal FIT pre-intervention, to 38% among 208 patients with abnormal FIT during the intervention (P

ObjectiveDetermine diagnostic yield of chest, abdomen, and 4-site screening to diagnose metastatic disease and secondary diseases of prognostic significance in dogs with oral cancer.SampleMedical records from 381 dogs with histologically confirmed oral tumors that underwent preoperative screening were retrospectively reviewed.ResultsThoracic metastasis was diagnosed in 4.9% (0.9% odontogenic, 6.5% nonodontogenic) of oral tumors. Oral malignant melanoma and multilobular osteochondrosarcoma were most at risk. Abdominal metastasis was diagnosed in 2% of oral tumors (0% odontogenic, 3.1% nonodontogenic) and cytologically confirmed in 2 cases (0.6% [2/295)] of all abdominal ultrasounds (AUS) 5.5% [2/36] of all AUS that had cytology). Both cases had oral malignant melanoma. Incidental disease was diagnosed in 53.1% and 81.3% of thoracic and abdominal screenings, respectively. Major findings were more common in AUS (7.8%) compared to thoracic screening (1.9%). The prevalence of incidental findings was similar for odontogenic and nonodontogenic tumors. Both metastasis and major findings were diagnosed more commonly with thoracic CT compared to radiographs. Metastasis or a major finding of prognostic significance was diagnosed in at least 1 test in 27.8% of patients that had head CT, lymph node cytology, thoracic screening, and AUS (n = 115).Clinical relevanceMajor incidental findings were more commonly detected with AUS and were diagnosed in 1 in every 12 patients. However, metastatic disease was most commonly detected with thoracic screening. When all 4 screening tests are performed, there is an approximately 1 in 4 chance of diagnosing metastasis or major significant disease regardless of tumor type.

ObjectiveDetermine locoregional diagnostic yield of 4-site screening (head, neck, chest, and abdomen) to diagnose metastatic disease or clinically significant comorbid diseases in dogs with oral cancer.Animals381 dogs with histologically confirmed oral tumors.MethodsMedical records from 381 dogs with histologically confirmed oral tumors that underwent preoperative screening were retrospectively reviewed.ResultsSkull and neck CT scan was performed on 348 patients. Bone lysis was present in 74.4% of tumors. Oral squamous cell carcinoma, sarcomas, and T2-T3 (> 2 cm) tumors had a significantly (P < .05) increased incidence of lysis compared to odontogenic and T1 (< 2 cm) tumors, respectively. Minor incidental findings were present in 60.6% of CT scans. Major incidental findings were found in 4.6% of scans. The risk of diagnosing an incidental finding increased by 10% and 20% per year of age for minor and major findings, respectively. Lymph node metastasis was diagnosed with CT or cytology in 7.5% of cases (10.7% of nonodontogenic tumors, 0% of odontogenic tumors). Oral malignant melanoma, oral squamous cell carcinoma, and T3 tumors had the highest prevalence of metastatic disease at the time of staging. The presence of bone lysis was not associated with cervical metastasis.Clinical relevanceMajor incidental findings were rare (< 5%) but primarily included secondary extraoral tumors. Lymphatic metastasis was diagnosed in 10.7% of nonodontogenic tumors, but cytology was not performed in the majority of cases and often included only a single mandibular node. Therefore, these results likely underestimate the incidence of lymphatic metastasis. Guided lymph node sampling is highly recommended, especially for oral malignant melanoma, squamous cell carcinoma, and T2-T3 tumors.

Background and Aim Methods Results Conclusion This study aimed to compare the determinants and impact of hepatocellular carcinoma (HCC) surveillance rates for people with metabolic dysfunction‐associated steatotic liver disease (MASLD) versus other chronic liver diseases.A dataset of HCC patients from a UK hospital (2007–2022) was analyzed. The Mann–Whitney U‐test compared continuous variables. The χ2 and two‐tailed Fisher exact tests compared categorical data. Regression modeling analyzed the impact of MASLD on the size and number of HCC nodules and curative treatment. The Cox proportional hazards model assessed the influence of MASLD on overall survival.A total of 176 of 687 (25.6%) HCC patients had MASLD. Fewer people with MASLD HCC were enrolled in HCC surveillance compared to non‐MASLD HCC (38 [21.6%] vs 215 [42.1%], P < 0.001). Patients with MASLD HCC were less likely to have been under secondary care (n = 57 [32.4%] vs 259 [50.7%], P < 0.001) and less likely to have cirrhosis (n = 113 [64.2%] vs 417 [81.6%], P < 0.001). MASLD was associated with a 12.3‐mm (95% confidence interval [CI] 10.8–14.0 mm) greater tumor diameter compared to people without MASLD (P = 0.002). Patients with MASLD HCC had 0.62 reduced odds (95% CI 0.43–0.91) of receiving curative treatment compared to non‐MASLD HCC (P = 0.014). Overall survival was similar for patients with MASLD HCC versus non‐MASLD HCC (hazard ratio 1.03, 95% CI 0.85–1.25, P = 0.748).Patients with MASLD are less likely to have been enrolled in HCC surveillance due to undiagnosed cirrhosis or presenting with non‐cirrhotic HCC. Patients with MASLD HCC present with larger tumors and are less likely to receive curative treatment. [ABSTRACT FROM AUTHOR]

Background: Breast cancer is the leading cause of cancer-related death among women worldwide. Mortality from breast cancer can be reduced through early detection and prevention. Despite the availability of breast cancer screening methods, the uptake of screening services remains very low, especially in low-resource countries like Tanzania. This low uptake of screening services may be attributed to a lack of awareness regarding the importance of early detection of the disease. Objectives: This study was set to determine breast cancer awareness and the uptake of breast cancer screening services among undergraduate female students in Dar es Salaam, Tanzania. Design: The study was a descriptive cross-sectional study using the quantitative approach. Methods: The sample size calculated for this study was 434 undergraduate female students. The tool used for data collection was self-administered questionnaires, with data collection taking place in July 2022. Data were analyzed using Stata Version 15 and presented using descriptive and inferential statistics. Results: We found that most of the participants (92.38%) had heard about breast cancer, and only 39% of the participants were able to correctly identify the risk factors for breast cancer. Participants who had ever used breast cancer screening services by at least 1 method were 37 (9.23%), and the most common screening method practiced by the study participants was breast self-examination (48.65%). Conclusions: Most of the participants were not aware of the screening methods for early detection of breast cancer. In addition, they lacked knowledge of some of the risk factors as evidenced by the low uptake of breast cancer screening services among the study participants. This calls for an awareness-raising campaign on the importance of breast cancer screening. [ABSTRACT FROM AUTHOR]

The early detection of cancer is of paramount importance in the medical field, as it can lead to more precise and effective interventions for successful cancer treatments. Cancer datasets typically contain numerous gene expression levels as features but with a limited number of samples. Thus, feature selection is a crucial initial step to streamline prediction algorithms. These selected features, or genes, play a pivotal role in cancer identification, treatment selection, and variation analysis among different techniques. To address this challenge, present two novel methodologies, by combining Cuckoo Search (CS) and Spider Monkey Optimization (SMO), referred to as SMOCS (Cuckoo Search followed by Spider Monkey Optimization) and CSSMO (Spider Monkey Optimization followed by Cuckoo Search). These approaches are designed for harnessing the strengths of both metaheuristic algorithms to identify a subset of genes that aid in early-stage cancer prediction. Additionally, to enhance the accuracy of the both algorithms, we employ a gene expression reduction method known as minimum Redundancy Maximum Relevance (mRMR) to reduce redundancy in cancer datasets. Subsequently, these gene subsets are classified using Deep Learning (DL) to identify distinct groups or classes associated with specific cancer types. We evaluate the performance of our proposed approaches using six different cancer datasets, assessing cancer sample classification and prediction through metrics such as Recall, Precision, F1-Score, and confusion matrix analysis. Our gene selection methods, in conjunction with DL, achieves significantly improved prediction accuracy when applied to large gene expression datasets compared to existing Deep Learning (DL) and Machine learning models. Experimental results shows that both SMOCS and CSSMO tend to classify cancer with high prediction accuracy, but SMOCS algorithm gives higher prediction accuracy for all the six datasets used with a maximum accuracy of 100%. [ABSTRACT FROM AUTHOR]

Skin cancer is a dreadful disease, which is mainly caused due to the heavy exposure of the human body to the ultraviolet rays emitted from the sun. Although the mortality rate is very high, the survival rate is found to be superior when it is detected at its early stage. In this research, Chronological Dingo Optimizer (CDO)-based Deep Maxout Network (DMN) is developed for the skin cancer detection. Here, initially the images are pre-processed and then, the skin lesion segmentation is accomplished effectively by employing Double U-Net. Then, data augmentation is performed and the detection process is carried out by employing DMN, where the network is optimally fine-tuned utilizing designed CDO. The CDO is the integration of chronological concept with Dingo Optimizer (DOX). The proposed scheme shows better outcomes with superior sensitivity of 0.959, F-measure of 0.908, accuracy of 0.923 and specificity of 0.837. [ABSTRACT FROM AUTHOR]

A double-check process helps prevent errors and ensures quality control. However, it may lead to decreased personal accountability, reduced effort, and declining quality checks. Introducing an artificial intelligence (AI)-based system in such scenarios could effectively address the risk of oversights. This study introduces an innovative AI-integrated workflow for cervical cytology screening that substantially improves efficiency and reduces the burden on cytologists. The AI model prioritizes cases for review based on anomaly scores and streamlines the first screening process to approximately 10 s per case. The model enhances the identification of high-risk cases via detailed microscopic observation, high anomaly scores cases, and a targeted review of low-score cases. The workflow highlights its capability for rapid, accurate, and less labor-intensive evaluations, demonstrating the potential to transform cervical cancer screening. This study highlights the importance of AI in modern medical diagnostics, particularly in areas with a high demand for accuracy and efficiency. [ABSTRACT FROM AUTHOR]

Phosphoinositide-3-kinases (PI3 K) are pivotal regulators of cell signaling implicated in various cancers. Particularly, mutations in the PIK3CA gene encoding the p110α catalytic subunit drive oncogenic signaling, making it an attractive therapeutic target. Our study conducted in silico exploration of 31 PIK3CA mutations across breast, endometrial, colon, and ovarian cancers, assessing their impacts on response to PI3Kα inhibitors and identifying potential non-toxic inhibitors and also elucidating their effects on protein stability and flexibility. Specifically, we observed significant alterations in the stability and flexibility of the PI3 K protein induced by these mutations. Through molecular docking analysis, we evaluated the binding interactions between the selected inhibitors and the PI3 K protein. The filtration of ligands involved calculating chemical descriptors, incorporating Veber and Lipinski rules, as well as IC50 values and toxicity predictions. This process reduced the initial dataset of 1394 ligands to 12 potential non-toxic inhibitors, and four reference inhibitors with significant biological activity in clinical trials were then chosen based on their physico-chemical properties. This analysis revealed Lig5's exceptional performance, exhibiting superior affinity and specificity compared to established reference inhibitors such as pictilisib. Lig5 formed robust binding interactions with the PI3 K protein, suggesting its potential as a highly effective therapeutic agent against PI3 K-driven cancers. Furthermore, molecular dynamics simulations provided valuable insights into Lig5's stability and its interactions with PI3 K over 100 ns. These simulations supported Lig5's potential as a versatile inhibitor capable of effectively targeting various mutational profiles of PI3 K, thereby mitigating issues related to resistance and toxicity commonly associated with current inhibitors. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusion Oral cancer screening requires analysis capable of detecting changes preceding the clinical manifestation. Oral cytopathology studies as an oral cancer screening have shown promising results. This study aims to evaluate the use of cytopathology in a quali‐quantitative analysis using Papanicoloau staining.Four experimental groups were evaluated: control (CG), exposed to carcinogens (EG), potentially malignant disorder with and without epithelial dysplasia (D‐OPMDG and ND‐OPMDG) and oral squamous cell carcinoma (OSCCG). Oral smears were collected using a Cytobrush® and conventional exfoliative cytology.Oral Papanicolaou smears from 143 individuals were analysed in 8100 images. Qualitatively, non‐lesional groups exhibited minimal suspected cases (20% in CG and 5% in EG), in the OPMD groups the ability to identify altered cells was low (40% in D‐OPMDG and 0% in ND‐OPMDG). Conversely, a notable 100% accuracy was achieved in the OSCCG. Quantitatively, a higher percentage of anucleated and a lower percentage of intermediate cells were observed in the OPMDG; a higher proportion of parabasal/suspicious cells was observed in OSCCG. The optimal threshold for improved accuracy in detecting suspected malignancies occurs when the count of parabasal/suspicious cells exceeds 8/100 cells examined. Cytomorphometric analysis revealed a higher nucleus/cytoplasm ratio (N/C) in OSCCG, with a best cutoff point indicating enhanced accuracy in discerning suspected malignancies when exceeding 17% of cells exhibiting this elevated ratio.It is possible to suggest updates in cytomorphometric and quantitative analysis in the modified Bethesda system for the oral cavity including objective criteria in the risk classification, therefore improving oral cancer screening. [ABSTRACT FROM AUTHOR]

ABSTRACT Background Method Result Conclusion Salivary biomarkers play an important role in the preventive strategy for oral cancer detection at an early stage. The aim of this study was to carry out a comparative quantitative analysis of the research material on the topic in one established database, Scopus and another emerging database, Dimensions.An electronic search was performed in Scopus and Dimensions in April 2024 with the search subjects “Saliva,” “Biomarkers,” “Diagnosis,” and “Oral Cancer.” The retrieved data were analyzed using Biblioshiny for RStudio and MS Excel.The search yielded 229 and 158 documents in Scopus and Dimensions, respectively. The data were studied to understand the coverage, concentration, and diversion of research articles. The analysis revealed high singularity index for Scopus and low overlap percentage between the two databases. Scopus was found to have higher citation count per article, however, the citation correlation between Scopus and Dimensions was found to be strong. Author productivity was found to be low in both the databases.Scopus and Dimensions vary in their scope, volume of data, and coverage policies. Both the databases have complimentary coverage on salivary biomarkers for oral cancer diagnosis. However, Scopus has a greater number of articles, sources, and citations resulting in better coverage of the topic. [ABSTRACT FROM AUTHOR]

The novel approach uses the V-Net architecture to segment pulmonary nodules from computed tomography (CT) scans, enhancing lung cancer detection's efficiency. Addressing lung cancer, a major global mortality cause, underscores the urgency for improved diagnostic methods. The aim of this research is to refine segmentation, a critical step for early cancer detection. The study leverages V-Net, a three-dimensional (3D) convolutional neural network (CNN) tailored for medical image segmentation, applied to lung nodule identification. It utilizes the LUNA16 dataset, containing 888 annotated CT images, for model training and evaluation. This dataset's variety of pulmonary conditions allows for a comprehensive method of assessment. The tailored V-Net architecture is optimized for lung nodule segmentation, with a focus on data preprocessing to elevate input image quality. Outcomes reveal significant progress in segmentation precision, achieving a loss score of 0.001 and a mIOU of 98%, setting new standards in the domain. Visuals of segmented lung nodules illustrate the method's effectiveness, indicating a promising avenue for early lung cancer detection and potentially better patient prognoses. The study contributes significantly to enhancing lung cancer diagnostic methodologies through advanced image analysis. An improved segmentation method based on V-Net architecture surpasses current techniques and encourages further deep learning exploration in medical diagnostics. [ABSTRACT FROM AUTHOR]

In this study, we propose a framework that enhances breast cancer classification accuracy by preserving spatial features and leveraging in situ cooling support. The framework utilizes real-time thermography video streaming for early breast cancer detection using Deep Learning models. Inception v3, Inception v4, and a modified Inception Mv4 were developed using MATLAB 2019. However, the thermal camera was connected to a mobile phone to capture images of the breast area for classification of normal and abnormal breast. This study's training dataset included 1000 thermal images, where a FLIR One Pro thermal camera connected to a mobile device was used for the imaging process. Of the 1000 images obtained, 700 images were considered for the normal breast thermography class while the 300 images were suitable for the abnormal class. We evaluate Deep Convolutional Neural Network models, such as Inception v3, Inception v4, and a modified Inception Mv4. Our results demonstrate that Inception Mv4, with real-time video streaming, efficiently detects even the slightest temperature contrast in breast tissue sequences achieving a 99.748% accuracy in comparison to a 99.712% and 96.8% for Inception v4 and v3, respectively. The use of in situ cooling gel further enhances image acquisition efficiency and detection accuracy. Interestingly, increasing the tumor surface temperature by 0.1% leads to an average 7% improvement in detection and classification accuracy. Our findings support the effectiveness of Inception Mv4 for real-time breast cancer detection, especially when combined with in situ cooling gel and varying tumor temperatures. In conclusion, future research directions should focus on incorporating thermal video clips into the thermal images database, utilizing high-quality thermal cameras, and exploring alternative Deep Learning models for improved breast cancer detection. [ABSTRACT FROM AUTHOR]

Lung cancer is currently the leading cause of cancer-related death. To lower the mortality from lung cancer, early detection is crucial. A precise and effective method of diagnosis by medical professionals is necessary for early detection of lung-related cancers in order to maximize the success rate of treatment. It is particularly difficult to catch it in the early stages of dissemination because there are no symptoms in the early stages. Using specific image processing ideas on computed tomography (CT), we can identify the tumor state in the early phases of spread and diagnose this at an early level. The early detection is crucial for curing and restraining the spread of uncontrolled malignant cells. The best outcomes for accurately identifying malignant tumors in their early stages come from combining the effects of morphological filtering and a contour-based picture segmentation technique. The segmented lung CT scan pictures that were malignant were separated from the rest of the testing dataset by a support vector machine (SVM) classifier in the subsequent analysis phase. Various image quality and performance metrics, such as accuracy, sensitivity, precision and specificity are used to validate the proposed technique. [ABSTRACT FROM AUTHOR]

Breast cancer remains a prevalent and serious health issue, leading to high mortality rates among women worldwide. Early detection of breast cancer is pivotal in improving patient outcomes. This study introduces an innovative approach for breast cancer segmentation by integrating Support Vector Machine (SVM) with Harris Hawks Optimization (HHO) and Cuckoo Search (CS) algorithms. HHO, a metaheuristic optimization algorithm inspired by the cooperative behavior of Harris Hawks, is employed for effective exploration and exploitation within the search space, thereby enhancing the accuracy of image segmentation. The CS algorithm, incorporating Cuckoo Search principles, ensures a balanced exploration of local and global search spaces, contributing to a comprehensive optimization strategy. The hybrid HHO-CS SVM algorithm is instrumental in fine-tuning hyperparameters, resulting in superior performance and improved segmentation outcomes for breast cancer detection. This innovative amalgamation of techniques significantly elevates the accuracy and efficiency of breast cancer detection through image segmentation. [ABSTRACT FROM AUTHOR]

In the world, cancer is listed as the second leading cause of death. Breast cancer is one of the types that affects women more often than men, and because it has a high mortality rate, the early detection for breast cancer is crucial. The demand for early breast cancer diagnosis and detection has led to a number of creative research avenues in recent years. But even if artificial intelligence techniques have improved in precision, their exactness still has to be increased to allow for their inevitable implementation in practical applications. This paper provides a Salp Swarm and Grey Wolf Optimization-based technique for diagnosing breast cancer that is inspired by nature. Data analysis for breast cancer was done using both SVM and KNN algorithms. For the purpose of diagnosis, we made use of the Wisconsin Breast Cancer Dataset (WBCD). The study also describes the proposed model's actual implementation in the field of computational biology, together with its characteristics, assessments, evaluations, and conclusions. Specificity, precision, F1-score, recall, and accuracy were some of the metrics used to evaluate how well the approach in question performed. When used on the WBCD-dataset, the proposed SSA-GWO model had an accuracy of 99.42%. The outcomes of the actual applications demonstrate the suggested hybrid algorithm's applicability to difficult situations involving unidentified search spaces. [ABSTRACT FROM AUTHOR]

Background: Breast cancer is the most common cancer-affecting women globally, with disproportionally high mortality rates in lower-income countries, including Ethiopia. The stage at diagnosis is a well-defined predictive system that determines the likelihood of breast cancer mortality. Early-stage breast cancer at diagnosis is associated with better treatment outcomes as compared with late stage. Although there are numerous primary studies on women with breast cancer with different proportions of early-stage breast cancer, there is currently no summary data on what proportion of breast cancer was diagnosed at early-stage in Ethiopia. This study focused on a pooled proportion of early-stage breast cancer at diagnosis in Ethiopia. Methods: By using key terms, Medline through Pub-Med, Google Scholar, Science Direct, HINARI and Medley were searched about breast cancer in Ethiopia, and a total of 288 articles were retrieved. After screening the articles and quality of each article was assessed using Newcastle–Ottawa Scale. Finally, 41 articles were used for the final pooled proportion. A random effects model was used to estimate the pooled prevalence and heterogeneity of included studies that were then assessed by using prediction interval. Results: Pooled proportion of early-stage breast cancer at diagnosis in Ethiopian hospitals was found to be 36% with a 95% confidence interval ranging from 31 to 41% and a 95% prediction interval ranging from 28 to 45%. Conclusion: Most breast cancer patients (64%) in Ethiopia are diagnosed at a late-stage. This contributes to the high mortality rates of breast cancer among women in Ethiopia. Therefore, in line with recommendations by the World Health Organization, we recommend that there should be an emphasis in Ethiopia to focus on early detection of breast cancer. [ABSTRACT FROM AUTHOR]

The second most common type of malignant tumor worldwide is colorectal cancer. Histopathology image analysis offers crucial data for the clinical diagnosis of colorectal cancer. Currently, deep learning techniques are applied to enhance cancer classification and tumor localization in histopathological image analysis. Moreover, traditional deep learning techniques might loss integrated information in the image while evaluating thousands of patches recovered from whole slide images (WSIs). This research proposes a novel colorectal cancer detection network (CCDNet) that combines coordinate attention transformer with atrous convolution. CCDNet first denoises the input histopathological image using a Wiener based Midpoint weighted non-local means filter (WMW-NLM) for guaranteeing precise diagnoses and maintain image features. Also, a novel atrous convolution with coordinate attention transformer (AConvCAT) is introduced, which successfully combines the advantages of two networks to classify colorectal tissue at various scales by capturing local and global information. Further, coordinate attention model is integrated with a Cross-shaped window (CrSWin) transformer for capturing tiny changes in colorectal tissue from multiple angles. The proposed CCDNet achieved accuracy rates of 98.61% and 98.96%, on the colorectal histological image and NCT-CRC-HE-100 K datasets correspondingly. The comparison analysis demonstrates that the suggested framework performed better than the most advanced methods already in use. In hospitals, clinicians can use the proposed CCDNet to verify the diagnosis. [ABSTRACT FROM AUTHOR]

Puncture biopsy is an important clinical technique to obtain diseased tissue for pathological diagnosis, where imaging guidance is critical. In this paper, we describe a metal reflector-enhanced microwave-induced thermoacoustic imaging (TAI) approach capable of guiding puncture biopsy for detection of breast cancer and joint diseases. Numerical experimentations simulating puncture guidance in breast cancer and knee gout models were first conducted using (CST STUDIO SUITE) (CST) software, and then ex-vivo experiments were performed followed by qualitative observations and semi-quantitative analysis. The results of both the simulations and ex-vivo experiments showed that our reflector-enhanced TAI could image the puncture needle in high resolution with a large depth of >12cm. [ABSTRACT FROM AUTHOR]

Micro-ultrasound has recently been introduced as a low-cost alternative to multi-parametric MRI for imaging prostate cancer. Early clinical studies have demonstrated promising results; however, robust validation via comparison with whole-mount pathology has yet to be achieved. Due to micro-ultrasound probe design and tissue deformation during scanning, it is difficult to accurately correlate micro-ultrasound imaging planes with ground truth whole-mount pathology slides. In this study, we developed a multi-step methodology to co-register micro-ultrasound and MRI to whole-mount pathology. The three-step process had a registration error of 3.90 ± 0.11 mm and consists of: (1) micro-ultrasound image reconstruction, (2) 3D landmark registration of micro-ultrasound to MRI, and (3) 2D capsule registration of MRI to whole-mount pathology. This process was then used in a preliminary reader study to compare the diagnostic accuracy of micro-ultrasound and MRI in 15 patients who underwent radical prostatectomy for prostate cancer. Micro-ultrasound was found to have equivalent performance to retrospective MRI review for index lesion detection (91.7% vs. 80%), while demonstrating an increased detection of tumor extent (52.5% vs. 36.7%) with similar false positive regions-of-interest (38.3% vs. 40.8%). Prospective MRI review had reduced detection of index lesions (73.3%) and tumor extent (18.9%) but improved false positive regions-of-interest (22.7%) relative to micro-ultrasound and retrospective MRI. Further evaluation is needed with a larger sample size. [ABSTRACT FROM AUTHOR]

Regular screening for colorectal cancer (CRC) is critical for early detection and long-term survival. Despite the current screening options available and advancements in therapies there will be around 53,000 CRC related deaths this year. There is great interest in non-invasive alternatives such as plasma cell-free RNA (cfRNA) for diagnostic, prognostic, and predictive applications. In the current study, our aim was to identify and validate potential cfRNA candidates to improve early CRC diagnosis. In phase 1 (n = 49; 25 controls, 24 cancers), discovery total RNA sequencing was performed. Select exons underwent validation in phase 2 (n = 73; 35 controls, 29 cancers, 9 adenomas) using targeted capture sequencing (n = 10,371 probes). In phase 3 (n = 57; 30 controls, 27 cancers), RT-qPCR was performed on previously identified candidates (n = 99). There were 895 exons that were differentially expressed (325 upregulated, 570 downregulated) among cancers versus controls. In phases 2 and 3, fewer markers were validated than expected in independent sets of patients, most of which were from previously published literature (FGA, FGB, GPR107, CDH3, and RP23AP7). In summary, we optimized laboratory processes and data analysis strategies which can serve as methodological framework for future plasma RNA studies beyond just the scope of CRC detection. Additionally, further exploration is needed in order to determine if the few cfRNA candidates identified in this study have clinical utility for early CRC detection. Over time, advancements in technologies, data analysis, and RNA preservation methods at time of collection may improve the biological and technical reproducibility of cfRNA biomarkers and enhance the feasibility of RNA-based liquid biopsies. [ABSTRACT FROM AUTHOR]

Background: Workplace cancer screening programs are determined as part of an employee's benefits package and health checkups are perceived positively. However, the current status of workplace cancer screening programs in Japan is unavailable. This study aimed to assess the adherence to national guidelines for colorectal, breast, and cervical cancer screenings in the workplace among Japanese enterprises and identify factors associated with excessive or inadequate screenings. Methods: A cross-sectional study design was employed. Data were obtained from a survey conducted by the "Corporate Action to Promote Cancer Control" between November and December 2022 among registered partner enterprises in Japan. The survey included questions on background characteristics, cancer screening practices, and intervention approaches. The analysis included 432 enterprises that provided complete responses regarding colorectal, breast, and cervical cancer screenings. Results: The guideline-adherence rates for colorectal, breast, and cervical cancer screenings in the workplace were 12.7%, 3.0%, and 8.8%, respectively. Enterprises had lower adherence to screening guidelines than local governments. Colorectal (70.8%) and breast (67.1%) cancer screenings were predominantly categorized as "overscreening" and cervical (60.6%) cancer screening, as "underscreening." Factors such as enterprise scale, health insurance associations, and the number of interventional approaches were significantly associated with increased "overscreening" (101–1000: β = 0.13, p = 0.01; ≥ 1000: β = 0.17, p < 0.01; health insurance association: β = 0.23, p < 0.01; and approaches: β = 0.42, p < 0.01) and reduced "underscreening" (101–1000: β = -0.13, p = 0.01; ≥ 1000: β = -0.17, p < 0.01; health insurance association: β = -0.18, p < 0.01; and approaches: β = -0.48, p < 0.01). Conclusion: Adherence to national guidelines for colorectal, breast, and cervical cancer screenings in the workplace was suboptimal among Japanese enterprises. Therefore, appropriate cancer screening measures and interventions to ensure guideline adherence and optimization of screening benefits while minimizing potential harms should be expeditiously implemented. [ABSTRACT FROM AUTHOR]

Background: Organized breast cancer screening (BCS) programs are effective measures among women aged 50–69 for preventing the sixth cause of death in Germany. Although the implementation of the national screening program started in 2005, participation rates have not yet reached EU standards. It is unclear which and how sociodemographic factors are related to BCS attendance. This scoping review aims to identify sociodemographic inequalities in BCS attendance among 50-69-year-old women following the implementation of the Organized Screening Program in Germany. Methods: Following PRISMA guidelines, we searched the Web of Science, Scopus, MEDLINE, PsycINFO, and CINAHL following the PCC (Population, Concept and Context) criteria. We included primary studies with a quantitative study design and reviews examining BCS attendance among women aged 50–69 with data from 2005 onwards in Germany. Harvest plots depicting effect size direction for the different identified sociodemographic inequalities and last two years or less BCS attendance and lifetime BCS attendance were developed. Results: We screened 476 titles and abstracts and 33 full texts. In total, 27 records were analysed, 14 were national reports, and 13 peer-reviewed articles. Eight sociodemographic variables were identified and summarised in harvest plots: age, education, income, migration status, type of district, employment status, partnership cohabitation and health insurance. Older women with lower incomes and migration backgrounds who live in rural areas and lack private insurance respond more favourably to BCS invitations. However, from a lifetime perspective, these associations only hold for migration background, are reversed for income and urban residency, and are complemented by partner cohabitation. Finally, women living in the former East German states of Saxony, Mecklenburg-Western Pomerania, Saxony-Anhalt, and Thuringia, as well as in the former West German state of Lower Saxony, showed higher BCS attendance rates in the last two years. Conclusion: High-quality research is needed to identify women at higher risk of not attending BCS in Germany to address the existing research's high heterogeneity, particularly since the overall attendance rate still falls below European standards. Protocol registration: https://osf.io/x79tq/. [ABSTRACT FROM AUTHOR]

Background: Screening participation remains suboptimal in cervical cancer (CC) and colorectal cancer (CRC) screening despite their effectiveness in reducing cancer-related morbidity and mortality. We investigated the effectiveness of an intervention by leveraging the high participation rate in breast cancer (BC) screening as an opportunity to offer self-sampling kits to nonparticipants in CC and CRC screening. Methods and findings: A pragmatic, unblinded, cluster-randomised, multiple period, crossover trial was conducted in 5 BC screening units in the Central Denmark Region (CDR) between September 1, 2021 and May 25, 2022. On each of 100 selected weekdays, 1 BC screening unit was randomly allocated as the intervention unit while the remaining units served as controls. Women aged 50 to 69 years attending BC screening at the intervention unit were offered administrative check-up on their CC screening status (ages 50 to 64 years) and CRC screening status (aged 50 to 69), and women with overdue screening were offered self-sampling. Women in the control group received only standard screening offers according to the organised programmes. The primary outcomes were differences between the intervention group and the control group in the total screening coverage for the 2 programmes and in screening participation among women with overdue screening, measured 6 months after the intervention. These were assessed using intention-to-treat analysis, reporting risk differences with 95% confidence intervals (CIs). A total of 27,116 women were included in the trial, with 5,618 (20.7%) in the intervention group and 21,498 (79.3%) in the control group. Six months after the intervention, total coverage was higher in the intervention group as compared with the control group in CC screening (88.3 versus 83.5, difference 4.8 percentage points, 95% CI [3.6, 6.0]; p < 0.001) and in CRC screening (79.8 versus 76.0, difference 3.8 percentage points, 95% CI [2.6, 5.1]; p < 0.001). Among women overdue with CC screening, participation in the intervention group was 32.0% compared with 6.1% in the control group (difference 25.8 percentage points, 95% CI [22.0, 29.6]; p < 0.001). In CRC screening, participation among women overdue with screening in the intervention group was 23.8% compared with 8.9% in the control group (difference 14.9 percentage points, 95% CI [12.3, 17.5]; p < 0.001). Women who did not participate in BC screening were not included in this study. Conclusions: Offering self-sampling to women overdue with CC and CRC screening when they attend BC screening was a feasible intervention, resulting in an increase in participation and total coverage. Other interventions are required to reach women who are not participating in BC screening. Trial registration: ClinicalTrials.govNCT05022511. The record of processing activities for research projects in the Central Denmark Region (R. No.: 1-16-02-217-21). Anne Dorte Lerche Helgestad and team investigate the effectiveness of an intervention by leveraging the high participation rate in breast cancer screening as an opportunity to engage non-participants in in cervical cancer and colorectal cancer screening. Author summary: Why was this study done?: Participation rates in cervical cancer (CC) and colorectal cancer (CRC) screening lag significantly behind those of breast cancer (BC) screening in Denmark, despite the proven preventive benefits in reducing cancer-related morbidity and mortality. Previous research has identified numerous barriers to nonparticipation across different screening programmes, prompting suggestions for combined screening services as a potential solution. Considering that women attending BC screening fall within the age range eligible for CC and CRC screening, leveraging the BC screening visit could serve as an opportune moment to engage in the other screening programmes. What did the researchers do and find?: We conducted a randomised controlled trial including 27,116 women aged 50 to 69 years attending BC screening, of whom 5,618 women received an intervention offering self-sampled CC and/or CRC screening if overdue for screening and within the eligible screening age range. The intervention proved effective in increasing coverage with 4.8 percentage points in CC screening and 3.8 percentage points in CRC screening compared to the control group. The intervention was feasible and well received by the women, without affecting their high satisfaction with BC screening. What do these findings mean?: This study suggests that combining preventive services may offer a pragmatic strategy to enhancing the effectiveness of public health interventions in various settings. The intervention strategy can be easily expanded and could increase screening participation if implemented on a larger scale. The main limitation of the study is that the intervention focuses solely on women attending BC screening, and a different approach is required for women not participating in this screening. [ABSTRACT FROM AUTHOR]

Introduction: Primary Human Papilloma Virus (HPV) testing offers higher sensitivity and specificity over Visual Inspection using Acetic acid (VIA) in cervical cancer screening. Self-sampling is a promising strategy to boost participation and reduce disparities. However, concerns about the initial costs hinder HPV testing adoption in low and middle-income countries. This study assesses the cost-utility of home-based HPV self-sampling versus VIA for cervical cancer screening in India. Methods: A cross-sectional study was conducted in East district, Sikkim, India, comparing the costs and utility outcomes of population-based cervical cancer screening through VIA and primary HPV screening through self-sampling. Cost-related data were collected from April 2021 to March 2022 using the bottom-up micro-costing method, while utility measures were collected prospectively using the EuroQoL-5D-5L questionnaire. The utility values were converted into quality-adjusted life days (QALDs) for an 8-day period. The willingness to pay threshold (WTP) was based on per capita GDP for 2022. If the calculated Incremental Cost-Effectiveness Ratio (ICER) value is lower than the WTP threshold, it signifies that the intervention is cost-effective. Results: The study included 95 women in each group of cervical cancer screening with VIA & HPV self-sampling. For eight days, the QALD was found to be 7.977 for the VIA group and 8.0 for the HPV group. The unit cost per woman screened by VIA and HPV self-testing was ₹1,597 (US$ 19.2) and ₹1,271(US$ 15.3), respectively. The ICER was ₹-14,459 (US$ -173.6), which was much below the WTP threshold for eight QALDs, i.e. ₹ 4,193 (US$ 50.4). Conclusion: The findings support HPV self-sampling as a cost-effective alternative to VIA. This informs policymakers and healthcare providers for better resource allocation in cervical cancer screening in Sikkim. [ABSTRACT FROM AUTHOR]

Background: Cervical cancer remains a significant public health concern in Europe. Effective introduction and scaling up of human papillomavirus (HPV) detection-based cervical cancer screening (CCS) requires a systematic assessment of health systems capacity. However, there is no validated capacity assessment methodology for CCS programmes, especially in European contexts. Addressing this gap, our study introduces an innovative and adaptable protocol for evaluating the capacity of CCS programmes across varying European health system settings. Methods: Our research team developed a three-step capacity assessment framework, incorporating a health policy review checklist, a facility visit survey, and key informants' interview guide followed by a strengths, weaknesses, opportunities and threats (SWOT) analysis. Piloting this comprehensive approach, we explored the CCS capacity in three countries: Estonia, Portugal and Romania. These countries were selected due to their contrasting healthcare structures and resources, providing a diverse overview of the European context. Results: Conducted over a period of 9 months, the capacity assessment covered multiple resources, 27 screening centres, 16 colposcopy and treatment centres and 15 key informant interviews. Our analysis highlighted both shared and country-specific challenges. A key common issue was ensuring high compliance to follow-up and management of screen-positive women. We identified considerable heterogeneity in resources and organization across the three countries, underscoring the need for tailored, rather than one-size-fits-all, solutions. Conclusions: Our study's novelty lies in the successful development of this capacity assessment methodology implementable within a relatively short time frame, proving its feasibility for use in various contexts and countries. The resulting set of materials, adaptable to different cancer types, is a ready-to-use toolkit to improve cancer screening processes and outcomes. This research marks a significant stride towards comprehensive capacity assessment for CCS programmes in Europe. Future directions include deploying these tools in other countries and cancer types, thereby contributing to the global fight against cancer. [ABSTRACT FROM AUTHOR]

Background: Breast and cervical cancer are the most common cancers in women, and are associated with high morbidity and mortality rates. Cancer screening can facilitate early diagnosis, reduce mortality, and ease the burden of cancer. Social support and self-efficacy are strongly associated with cancer screening behavior. The present study aimed to explore the mediating effect of self-efficacy on social support and cancer screening behavior. Methods: In this cross-sectional survey study conducted from June to October 2023, 312 women aged 35–65 years were recruited from the East Coast area of China. A general information questionnaire, cancer screening behavior questionnaire, social support scale and self-efficacy scale were used to collect data. Descriptive statistics were used to analyze the general characteristics of participants; one-way analysis of variance was used to test for differences in the measured variables; and Pearson's correlation analyses were used to describe the relationship among social support, self-efficacy, and cancer screening behavior. A mediation model was constructed and analyzed using the PROCESS macro for SPSS. Results: The mean (standard deviation) screening behavior score for breast cancer and cervical cancer was 3.98 (2.79), representing an intermediate level. Self-efficacy was closely related to social support and cancer screening behavior. Social support showed a significant positive correlation with self-efficacy (r = 0.37, p < 0.01) and cancer screening behavior (r = 0.18, p < 0.01). Self-efficacy was also significantly positively correlated with cancer screening behavior (r = 0.19, p < 0.05). Self-efficacy showed a full mediating effect between social support and cancer screening behavior, with an explanatory power of 32%. Conclusions: The findings emphasize the need to increase women's level of social support and self-efficacy, which in turn can increase women's participation in breast and cervical cancer screening. [ABSTRACT FROM AUTHOR]

Background: Multiple myeloma often presents with vague and non-specific symptoms. Many patients are diagnosed in unplanned rather than elective (planned) diagnostic pathways. This study investigates the diagnosis of multiple myeloma in unplanned pathways and the association with patient characteristics, disease profile, and survival. Methods: We conducted a nationwide register-based study, including all patients diagnosed with multiple myeloma in Denmark in 2014–2018. Patients were categorised as diagnosed in an unplanned pathway if registered with an acute admission within 30 days prior to the multiple myeloma diagnosis and no other previously registered pathway to this diagnosis. Unplanned pathways were compared to all other pathways combined. Results: We included 2,213 patients diagnosed with multiple myeloma, hereof 32% diagnosed in an unplanned pathway. Comorbidity, no prior cancer diagnosis, a history of few visits to the general practitioner (GP), multiple myeloma complications at diagnosis, high-risk cytogenetics, and advanced cancer stage were associated with a higher probability of being diagnosed in an unplanned pathway. For example, 24.4% (95% confidence interval (CI): 21.8–27.0) of patients with low comorbidity (Charlson Comorbidity Index (CCI) score 0) were diagnosed in an unplanned pathway as were 50.9% (95% CI: 45.6–56.1) of patients with high comorbidity (CCI score 3+). For patients with dialysis need at the time of diagnosis the probability was 66.0% (95% CI 54.2–77.8) and 30.9% (95% CI: 28.9–32.9) for patients with no dialysis need. Patients diagnosed in an unplanned pathway had inferior survival (hazard ratio 1.44 (95% CI: 1.26–1.64)). However, this association was not seen in analyses restricted to patients surviving for more than three years. Conclusions: High comorbidity level, few usual GP visits, advanced disease status at diagnosis, and complications were associated with diagnosis in an unplanned pathway. Further, patients diagnosed in an unplanned pathway had inferior survival. Promoting earlier diagnosis and preventing unplanned pathways may help improve survival in multiple myeloma. [ABSTRACT FROM AUTHOR]