Screening Tool For Cancer Research Articles

Mixed-methods systematic review of shared decision-making tools for cancer screening

Abstract Shared decision-making (SDM) tools hold promise for guiding informed choices in cancer screening. However, their effectiveness among underserved people, as well as the specific characteristics of these tools preferred by this group and clinicians, remains unclear. This review aimed to synthesize evidence on the effectiveness of SDM tools for cancer screening and explored the preferences of underserved people and clinicians regarding the specific characteristics of the SDM tools. A mixed-method convergent segregated approach was employed, which involved an independent synthesis of quantitative and qualitative data. Articles were systematically selected and screened, resulting in the inclusion and critical appraisal of 55 studies. Results from the meta-analyses showed that SDM tools for cancer screening are effective in reducing decisional conflict for both the general population and the underserved, and in increasing cancer screening knowledge and intention for underserved people only. Subgroup analyses showed minimal heterogeneity for decisional conflict outcomes, measured over a six-month period. Insights from the qualitative findings revealed that underserved people highly preferred SDM tools with relevant information about cancer risk, culturally tailored content, and high accessibility, both during clinical encounters and beyond. Meanwhile, clinicians highly preferred tools that can be easily integrated into medical systems, and can effectively guide SDM, while considering their patients’ values and the limited time for consultation. There is strong evidence on the effectiveness of SDM tools in facilitating informed choice in cancer screening, especially among underserved people. However, evidence on long-term outcomes remains insufficient. Additionally, considering the difference in preferences of key stakeholders in terms of tool characteristics, fostering collaboration with them during the creation of an SDM tool for cancer screening is essential. Key messages • Shared decision-making tools are effective in increasing screening knowledge and intention among underserved people. • Considering the difference in preferences of key stakeholders in terms of tool characteristics, fostering collaboration with them during the creation of an SDM tool for cancer screening is essential.

Development of a risk-stratified shared decision-making tool for colorectal cancer screening

Abstract European guidelines stress the importance of informed decision-making in colorectal cancer (CRC) screening. However, tailored tools that facilitate decision-making for underserved people and general practitioners (GPs) in Flanders are lacking. This study aimed to develop a tailored shared decision-making (SDM) tool for CRC screening, specifically a video decision aid, using a co-creative process. The development involved two rounds of focus group discussions with underserved people and five local quality group meetings with GPs in various parts of Flanders, Belgium. Qualitative data were analyzed using a Modified-Grounded Theory Analytical (M-GTA) approach to identify key themes. Findings revealed four core themes. The first theme, ‘Recognizing the Barriers to Screening’, identifies challenges such as a lack of time, staff, and tools for GPs, as well as language and literacy barriers for underserved people. The second theme, ‘Learning from Existing Tools’, highlights successful elements like visuals and simple language and limitations such as low accessibility and poor navigation. The third theme, ‘Determining the Content and Design,’ reveals that GPs seek user-friendly tools for at-home viewing, while underserved people value personalized and clear information about CRC risk factors and screening costs. The final theme, ‘Identifying Strategies for Integration,’ stresses the importance of a structured, collaborative care approach for the successful integration of the tool. The proposed modifications for the SDM tool include enhancing its accessibility with multiple language options, using simple and relatable visuals, and providing personalized risk discussions for underserved people and GPs. Nonetheless, further testing is needed to confirm the effectiveness of the SDM tool in supporting preventive talks and informed decision-making in CRC screening among these target groups. Key messages • A structured, collaborative care approach is needed for successful SDM tool integration during preventive talks with underserved people. • Further testing is needed to confirm the tool’s effectiveness in supporting informed decision-making in CRC screening for underserved people.

Metabolic Response to Small Molecule Therapy in Colorectal Cancer Tracked with Raman Spectroscopy and Metabolomics.

Despite numerous screening tools for colorectal cancer (CRC), 25 % of patients are diagnosed with advanced disease. Novel diagnostic technologies that are early, accurate, and rapid are imperative to assess the therapeutic efficacy of clinical drugs and identify new biomarkers of treatment response. Here Raman spectroscopy (RS) was used to track metabolic reprogramming in KRAS-mutant HCT116 and SW837 cells, and KRAS wild-type CC cells. RS combined with multivariate analysis methods distinguished nonresponsive, partially responsive, and responsive cells treated with cetuximab, a monoclonal antibody for EGFR inhibition, sotorasib, a clinically approved KRAS inhibitor, and various doses of trametinib, an inhibitor of the MAPK pathway. Cells treated with a combination of subtoxic doses of trametinib and BKM120, an inhibitor of the PI3K pathway, showed a synergistic response between the two pathways. Using a supervised machine learning regression model, we established a scoring methodology trained to a priori predict therapeutic response to new treatment combinations. RS metabolites were verified with mass spectrometry, and enrichment pathways were identified, including amino acid, purine, and nicotinate and nicotinamide metabolism that differentiated monotherapy from combination therapy. Our approach may ultimately be applicable to patient-derived primary cells and cultures of patient tumors to predict effective drugs for individualized care.

Integrating Multi-Cancer Early Detection (MCED) Tests with Standard Cancer Screening: System Dynamics Model Development and Feasibility Testing.

Cancer screening plays a critical role in early disease detection and improving outcomes. In Australia, established screening protocols for colorectal, breast and cervical cancer have significantly contributed to timely cancer detection. However, the recent introduction of multi-cancer early detection (MCED) tests arguably can disrupt current screening, yet the extent to which these tests provide additional benefits remains uncertain. We present the development and initial validation of a system dynamics (SD) model that estimates the additional cancer detections and costs associated with MCED tests. This article describes the development of a simulation model built to evaluate the additional patient diagnoses and the economic impact of incorporating MCED testing alongside Australia's well-established standard of care (SOC) screening programs for colorectal, breast, cervical and lung cancers. The model was designed to estimate the additional number of patients diagnosed at each cancer stage (stage I, II, III, IV, or unknown) and the associated costs. This simulation model allows for the analysis of multiple scenarios under a plausible set of assumptions regarding population-level participation rates. An SD model was developed to represent the existing SOC national cancer screening pathways and to integrate potential clinical pathways that could be introduced by MCED tests. The SD model was built to investigate three scenarios for the use of MCED testing: firstly, to explore the viability of MCED testing as a substitute among individuals who are not opting for SOC screening for any reason; secondly, to implement MCED testing exclusively for individuals ineligible for SOC screening, yet have high-risk characteristics; and thirdly, to employ MCED testing after SOC screening to serve as a triaging/confirmatory tool for individuals receiving inconclusive test results. The three primary scenarios were constructed by varying diagnostic accuracy and uptake rates of MCED tests. The clinical utility and outcomes of MCED testing for screening and early detection still lack comprehensive evidence. Nonetheless, this simulation model facilitates a thorough analysis of MCED tests within the Australian healthcare context, providing insights into potential additional detections and costs to the healthcare system, which may help prioritise future evidence development. The adaptable yet novel SD model presented herein is anticipated to be of considerable interest to industry, policymakers, consumers and clinicians involved in informing clinical and economic decisions regarding integrating MCED tests as cancer screening and early detection tools. The expected results of applying this SD model will determine whether using MCED testing in conjunction with SOC screening offers any potential benefits, possibly guiding policy decisions and clinical practices towards the adoption of MCED tests.

Future implications of artificial intelligence in lung cancer screening: a systematic review.

The aim of this study was to systematically review the literature to assess the application of AI-based interventions in lung cancer screening, and its future implications. Relevant published literature was screened using PRISMA guidelines across three databases: PubMed, Scopus, and Web of Science. Search terms for article selection included "artificial intelligence," "radiology," "lung cancer," "screening," and "diagnostic." Included studies evaluated the use of AI in lung cancer screening and diagnosis. Twelve studies met the inclusion criteria. All studies concerned the role of AI in lung cancer screening and diagnosis. The AIs demonstrated promising ability across four domains: (1) detection, (2) characterization and differentiation, (3) augmentation of the work of human radiologists, (4) AI implementation of the LUNG-RADS framework and its ability to augment this framework. All studies reported positive results, demonstrating in some cases AI's ability to perform these tasks to a level close to that of human radiologists. The AI systems included in this review were found to be effective screening tools for lung cancer. These findings hold important implications for the future use of AI in lung cancer screening programmes as they may see use as an adjunctive tool for lung cancer screening that would aid in making early and accurate diagnosis. AI-based systems appear to be powerful tools that can assist radiologists with lung cancer screening and diagnosis.

COMPARATIVE EVALUATION OF PAP SMEAR WITH HISTOPATHOLOGY IN CERVICAL LESION ACCORDING TO THE 2014 BETHESDA SYSTEM: AN INSTITUTIONAL STUDY

Objectives: The objective of this study is to evaluate the efficacy of a pap smear using The 2014 Bethesda System (TBS) for the diagnosis of premalignant and malignant lesions of the uterine cervix. Methods: A prospective study was conducted in the Department of Pathology at the institution from November 2015 to October 2017. Fifty patients with an unhealthy cervix have undergone conventional Pap smears and histopathological biopsies with the suspicion of cervical malignancy or premalignancy attending the Obstetrics and Gynecology Outpatient Department. The obtained smears were arranged according to TBS. The tissue biopsies have been processed routinely and they are stained with hematoxylin and eosin for histopathological diagnosis. Furthermore, cases such as non-neoplastic, metastatic lesions, and recurrent cases were excluded from this study. Results: The common age group has been identified as between 41 and 60 years and patients had low educational levels. Sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy observed in this study were 89.28%, 63.63%, 64.1%, 72.72%, and 72% respectively. Conclusion: Pap smear is a simple, effective, inexpensive procedure that can be routinely used as a screening tool for screening cervical cancer. TBSs also provide a standard approach for cytological evaluation that helps in the early detection of premalignant and malignant cervical lesions.

P2.04B.15 Co-Design of Decision Support Tools for Lung Cancer Screening in Australia

P2.04B.15 Co-Design of Decision Support Tools for Lung Cancer Screening in Australia

FP1.12 - How many Colorectal cancer patients had negative Faecal Immunochemical Testing (FIT) within the previous 1 year?

Abstract Introduction Colorectal cancer (CRC) accounts for approximately 10% of all cancer diagnoses and 9.4% of all cancer deaths worldwide. Since its introduction, quantitative faecal immunochemical testing (qFIT) has become a vital tool in bowel cancer screening and triaging of symptomatic patients. Our trust has seen a 20% increase in lower gastrointestinal referrals over a 12-month period. The aim of this investigation was to identify how many patients with a negative qFIT were diagnosed with CRC within 12 months and if there is potential to downgrade referrals with negative qFIT. Methods This retrospective study reviewed new CRC diagnoses in one hospital trust, diagnosed from January to December 2022, who were referred as symptomatic red flag referrals. All patients in this timeframe had records reviewed for qFIT performed within the 12 months prior to their diagnosis. A negative qFIT test was defined as lab result of <7ugHb/g. Results Two hundred and forty-seven patients were diagnosed with CRC from January to December 2022. One hundred and three patients did not have a documented qFIT within the timeframe and therefore were excluded from analysis. One hundred and forty-four cases were further reviewed, of which 14 (9.7%) had a negative qFIT within the 12 months before diagnosis. Conclusions This audit does not support the downgrading of Red Flag referrals based on a negative qFIT result. Further analysis is needed to ascertain how best to triage symptomatic referrals for colorectal cancer with a negative qFIT to help cope with an increasing burden of Red Flag referrals.

FP3.3 - Sensitivity of Faecal Immunochemical Testing

Abstract Aim The use of faecal immunochemical testing (FIT) in the diagnosis of colorectal cancers (CRC) has become a routinely utilised and reliable investigation. In the symptomatic population, FIT may identify those patients who require urgent colorectal investigation. It is also commonly used as a triaging tool in bowel cancer screening. In this study we sought to assess the sensitivity of FIT in detecting CRC in our centre. Method Patients with histologically confirmed CRC were identified from a data set gathered from the hospital colorectal specialist services between January 2021 to January 2022. Thereafter, the hospital electronic systems were used to retrospectively gather the value of FIT tests for each CRC patient found. Results From 407 patients with CRC identified, only 256 patients who we successfully managed to obtain their pre diagnosis FIT result were included. From those, 235 patients were FIT positive and 21 patients had a false negative result. Therefore, this suggests a FIT sensitivity of 91.79%. Furthermore, we identified 14 patients who had a repeat FIT preformed. From which, one patient who was originally fit negative had a positive result on the repeat test. Conclusion While faecal immunochemical testing is highly sensitive and a useful screening tool, it's important to remember that it is not always accurate. Therefore if a patient has convincing history or symptoms, we should keep a high index of suspicion and investigate further. It also remains to be seen if the use of double FIT will help increase the sensitivity of detecting CRC.

Metabolic Response to Small Molecule Therapy in Colorectal Cancer Tracked with Raman Spectroscopy and Metabolomics

AbstractDespite numerous screening tools for colorectal cancer (CRC), 25 % of patients are diagnosed with advanced disease. Novel diagnostic technologies that are early, accurate, and rapid are imperative to assess the therapeutic efficacy of clinical drugs and identify new biomarkers of treatment response. Here Raman spectroscopy (RS) was used to track metabolic reprogramming in KRAS‐mutant HCT116 and SW837 cells, and KRAS wild‐type CC cells. RS combined with multivariate analysis methods distinguished nonresponsive, partially responsive, and responsive cells treated with cetuximab, a monoclonal antibody for EGFR inhibition, sotorasib, a clinically approved KRAS inhibitor, and various doses of trametinib, an inhibitor of the MAPK pathway. Cells treated with a combination of subtoxic doses of trametinib and BKM120, an inhibitor of the PI3K pathway, showed a synergistic response between the two pathways. Using a supervised machine learning regression model, we established a scoring methodology trained to a priori predict therapeutic response to new treatment combinations. RS metabolites were verified with mass spectrometry, and enrichment pathways were identified, including amino acid, purine, and nicotinate and nicotinamide metabolism that differentiated monotherapy from combination therapy. Our approach may ultimately be applicable to patient‐derived primary cells and cultures of patient tumors to predict effective drugs for individualized care.

Breathomics: may it become an affordable, new tool for early diagnosis of non-small-cell lung cancer? An exploratory study on a cohort of 60 patients.

Analysis of breath, specifically the patterns of volatile organic compounds (VOCs), has shown the potential to distinguish between patients with lung cancer (LC) and healthy individuals (HC). However, the current technology relies on complex, expensive and low throughput analytical platforms, which provide an offline response, making it unsuitable for mass screening. A new portable device has been developed to enable fast and on-site LC diagnosis, and its reliability is being tested. Breath samples were collected from patients with histologically proven non-small-cell lung cancer (NSCLC) and healthy controls using Tedlar bags and a Nafion filter attached to a one-way mouthpiece. These samples were then analysed using an automated micro portable gas chromatography device that was developed in-house. The device consisted of a thermal desorption tube, thermal injector, separation column, photoionization detector, as well as other accessories such as pumps, valves and a helium cartridge. The resulting chromatograms were analysed using both chemometrics and machine learning techniques. Thirty NSCLC patients and 30 HC entered the study. After a training set (20 NSCLC and 20 HC) and a testing set (10 NSCLC and 10 HC), an overall specificity of 83.3%, a sensitivity of 86.7% and an accuracy of 85.0% to identify NSCLC patients were found based on 3 VOCs. These results are a significant step towards creating a low-cost, user-friendly and accessible tool for rapid on-site LC screening. ClinicalTrials.gov Identifier: NCT06034730.

Benefits and Risks of Mammography Screening in Women Ages 40 to 49 Years

Mammography is a widely used screening tool for breast cancer. While it has been shown to reduce mortality from breast cancer, its benefits and risks vary depending on the age group being screened. This paper aims to provide a comprehensive review of the benefits and risks of mammography screening specifically in women aged 40 to 49 years. The analysis includes statistical data, benefits in terms of early detection and mortality reduction, as well as the potential risks such as false positives, overdiagnosis, and radiation exposure.

Application of artificial intelligence in lung cancer screening: A real-world study in a Chinese physical examination population.

With the rapid increase of chest computed tomography (CT) images, the workload faced by radiologists has increased dramatically. It is undeniable that the use of artificial intelligence (AI) image-assisted diagnosis system in clinical treatment is a major trend in medical development. Therefore, in order to explore the value and diagnostic accuracy of the current AI system in clinical application, we aim to compare the detection and differentiation of benign and malignant pulmonary nodules between AI system and physicians, so as to provide a theoretical basis for clinical application. Our study encompassed a cohort of 23 336 patients who underwent chest low-dose spiral CT screening for lung cancer at the Health Management Center of West China Hospital. We conducted a comparative analysis between AI-assisted reading and manual interpretation, focusing on the detection and differentiation of benign and malignant pulmonary nodules. The AI-assisted reading exhibited a significantly higher screening positive rate and probability of diagnosing malignant pulmonary nodules compared with manual interpretation (p < 0.001). Moreover, AI scanning demonstrated a markedly superior detection rate of malignant pulmonary nodules compared with manual scanning (97.2% vs. 86.4%, p < 0.001). Additionally, the lung cancer detection rate was substantially higher in the AI reading group compared with the manual reading group (98.9% vs. 90.3%, p < 0.001). Our findings underscore the superior screening positive rate and lung cancer detection rate achieved through AI-assisted reading compared with manual interpretation. Thus, AI exhibits considerable potential as an adjunctive tool in lung cancer screening within clinical practice settings.

Novel Hybrid Quantum Architecture-Based Lung Cancer Detection Using Chest Radiograph and Computerized Tomography Images.

Lung cancer, the second most common type of cancer worldwide, presents significant health challenges. Detecting this disease early is essential for improving patient outcomes and simplifying treatment. In this study, we propose a hybrid framework that combines deep learning (DL) with quantum computing to enhance the accuracy of lung cancer detection using chest radiographs (CXR) and computerized tomography (CT) images. Our system utilizes pre-trained models for feature extraction and quantum circuits for classification, achieving state-of-the-art performance in various metrics. Not only does our system achieve an overall accuracy of 92.12%, it also excels in other crucial performance measures, such as sensitivity (94%), specificity (90%), F1-score (93%), and precision (92%). These results demonstrate that our hybrid approach can more accurately identify lung cancer signatures compared to traditional methods. Moreover, the incorporation of quantum computing enhances processing speed and scalability, making our system a promising tool for early lung cancer screening and diagnosis. By leveraging the strengths of quantum computing, our approach surpasses traditional methods in terms of speed, accuracy, and efficiency. This study highlights the potential of hybrid computational technologies to transform early cancer detection, paving the way for wider clinical applications and improved patient care outcomes.

PSA screening for prostate cancer in the United States: 30years of controversy.

In 1994, the United States approved the Prostate-Specific Antigen (PSA) test as a screening tool for prostate cancer. It did so despite the test's inherent weakness: not being prostate cancer specific. Subsequent randomized trials yielded conflicting results as to its benefits. Medical guideline organizations are concerned that PSA screening results in the diagnosis and treatment of clinically indolent prostate cancer. Nevertheless, PSA screening is prevalent in North America and Europe with PSA screening increasing in other regions. We provide a critical review of the major factors that led to the prevalence of PSA screening in the United States despite the debate about its benefits. Public advocacy in favor of the test and failure of the medical community to appreciate its inherent weakness led to widespread adoption. These factors persist today. Other countries need to carefully analyze the utility of the PSA test before adopting it.

Soluble CD44 in oral rinses for the early detection of cancer: a prospective cohort study in high-risk individuals

BackgroundThere are 54,000 new cases of oral cavity and oropharyngeal cancer in the United States and more than 476,000 worldwide each year. Oral cavity and oropharyngeal squamous cell carcinoma make up most tumors with five-year survival rates of 50% due to prevalence of late-stage diagnoses. Improved methods of early detection in high-risk individuals are urgently needed. We aimed to assess the tumorigenic biomarkers soluble CD44 (solCD44) and total protein (TP) measured using oral rinses as affordable convenient screening tools for cancer detection.MethodsIn this prospective cohort study, we recruited 150 healthy current or former smokers through a community screening program. Baseline and four annual visits were conducted from March 2011-January 2016 with records followed until August 2020. Participants provided oral rinses, received head and neck exams, and completed questionnaires. SolCD44 and TP levels were measured and compared across groups and time. Participants were placed in the cancer group if malignancy developed in the study period, the suspicious group if physical exams were concerning for premalignant disease or cancer in the head and neck, and the healthy group if there were no suspicious findings. This analysis used two-sample t-test for comparison of means and two-sample Wilcoxon Test for comparison of medians. For subjects with follow-ups, estimated means of biomarkers were obtained from a fitted Repeated Measures Analysis of Variance (RANOVA) model including group, visit, and their interaction. Pairwise comparisons of mean solCD44 were made, including intergroup and intragroup comparison of values at different years.ResultsMost participants were males (58.7%), < 60 years of age. (90.7%), and Black (100%). Baseline mean solCD44 was elevated (2.781 ng/ml) in the cancer group compared to the suspicious group (1.849 ng/ml) and healthy group (1.779 ng/ml).ConclusionThis study supports the feasibility of a CD44-based oral rinse test as an affordable and convenient adjunctive tool for early detection of aerodigestive tract and other cancers in high-risk populations.

SERS biosensors based on catalytic hairpin self-assembly and hybridization chain reaction cascade signal amplification strategies for ultrasensitive microRNA-21 detection.

A highly sensitive surface-enhanced Raman scattering (SERS) biosensor has been developedfor the detection of microRNA-21 (miR-21) using an isothermal enzyme-free cascade amplification method involving catalytic hairpin assembly (CHA) and hybridization chain reaction (HCR). The CHA reaction is triggered by the target miR-21, which causes hairpin DNA (C1 and C2) to self-assemble into CHA products. After AgNPs@Capture captures the resulting CHA product, the HCR reaction is started, forming long-stranded DNA on the surface of AgNPs. A strong SERS signal is generated due to the presence of a large amount of the Raman reporter methylene blue (MB) in the vicinity of the SERS "hot spot" on the surface of AgNPs. The monitoring of the SERS signal changes of MB allows for the highly sensitive and specific detection of miR-21. In optimal conditions, the biosensor exhibits a satisfactory linear range and a low detection limit for miR-21 of 42.3 fM. Additionally, this SERS biosensor shows outstanding selectivity and reproducibility. The application of this methodology to clinical blood samples allows for the differentiation of cancer patients from healthy controls. As a result, the CHA-HCR amplification strategy used in this SERS biosensor could be a useful tool for miRNA detection and early cancer screening.

Patient Perspectives on a Patient-Facing Tool for Lung Cancer Screening.

Individuals with high risk for lung cancer may benefit from lung cancer screening, but there are associated risks as well as benefits. Shared decision-making (SDM) tools with personalized information may provide key support for patients. Understanding patient perspectives on educational tools to facilitate SDM for lung cancer screening may support tool development. This study aimed to explore patient perspectives related to a SDM tool for lung cancer screening using a qualitative approach. We elicited patient perspectives by showing a provider-facing SDM tool. Focus group interviews that ranged in duration from 1.5 to 2 h were conducted with 23 individuals with high risk for lung cancer. Data were interpreted inductively using thematic analysis to identify patients' thoughts on and desires for a patient-facing SDM tool. The findings highlight that patients would like to have educational information related to lung cancer screening. We identified several key themes to be considered in the future development of patient-facing tools: barriers to acceptance, preference against screening and seeking empowerment. One further theme illustrated effects of patient-provider relationship as a limitation to meeting lung cancer screening information needs. Participants also noted several suggestions for the design of technology decision aids. These findings suggest that patients desire additional information on lung cancer screening in advance of clinical visits. However, there are several issues that must be considered in the design and development of technology to meet the information needs of patients for lung cancer screening decisions. Patients, service users, caregivers or members of the public were not involved in the study design, conduct, analysis or interpretation of the data. However, clinical experts in health communication provided detailed feedback on the study protocol, including the focus group approach. The study findings contribute to a better understanding of patient expectations for lung cancer screening decisions and may inform future development of tools for SDM.

Acceptability of artificial intelligence for cervical cancer screening in Dschang, Cameroon: a qualitative study on patient perspectives

BackgroundCervical cancer is the fourth most frequent cancer among women, with 90% of cervical cancer-related deaths occurring in low- and middle-income countries like Cameroon. Visual inspection with acetic acid is often used in low-resource settings to screen for cervical cancer; however, its accuracy can be limited. To address this issue, the Swiss Federal Institute of Technology Lausanne and the University Hospitals of Geneva are collaborating to develop an automated smartphone-based image classifier that serves as a computer aided diagnosis tool for cancerous lesions. The primary objective of this study is to explore the acceptability and perspectives of women in Dschang regarding the usage of a screening tool for cervical cancer relying on artificial intelligence. A secondary objective is to understand the preferred form and type of information women would like to receive regarding this artificial intelligence-based screening tool.MethodsA qualitative methodology was employed to gain better insight into the women’s perspectives. Participants, aged between 30 and 49 were invited from both rural and urban regions and semi-structured interviews using a pre-tested interview guide were conducted. The focus groups were divided on the basis of level of education, as well as HPV status. The interviews were audio-recorded, transcribed, and coded using the ATLAS.ti software.ResultsA total of 32 participants took part in the six focus groups, and 38% of participants had a primary level of education. The perspectives identified were classified using an adapted version of the Technology Acceptance Model. Key factors influencing the acceptability of artificial intelligence include privacy concerns, perceived usefulness, and trust in the competence of providers, accuracy of the tool as well as the potential negative impact of smartphones.ConclusionThe results suggest that an artificial intelligence-based screening tool for cervical cancer is mostly acceptable to the women in Dschang. By ensuring patient confidentiality and by providing clear explanations, acceptance can be fostered in the community and uptake of cervical cancer screening can be improved.Trial registrationEthical Cantonal Board of Geneva, Switzerland (CCER, N°2017–0110 and CER-amendment n°4) and Cameroonian National Ethics Committee for Human Health Research (N°2022/12/1518/CE/CNERSH/SP). NCT: 03757299.

Highly Sensitive 3D‐Nanoplasmonic‐Based Epidermal Growth Factor Receptor Mutation Multiplex Assay Chip for Liquid Biopsy

Economical mutation detection method with high analytical and clinical sensitivity is necessary for early cancer diagnosis and screening. In this study, a novel 3D‐nanoplasmonic‐based multiplex mutation assay chip is developed to detect epidermal growth factor receptor (EGFR) mutations. This assay kit comprises a 3D‐nanoplasmonic substrate immobilized with capture probes and primer–probe sets for recombinase polymerase amplification, wild‐type inhibition, and fluorescence detection, enabling multiplex detection of EGFR exon 19 deletions, exon 20 insertions, and exon 21 L858R point mutations. The strategy facilitates the detection of all deletions and insertions within the target region with extremely high analytical sensitivity, detecting as low as 1 × 10−9% mutation frequency, implying three copies/reactions and 100 zM. The synergistic effects of plasmon‐enhanced fluorescence from the 3D‐nanoplasmonic substrate and wild‐type inhibitor contribute to this high analytical sensitivity. Moreover, the developed chip exhibits 100% accuracy in the clinical testing of plasma samples from normal individuals and patients with benign lung tumor and malignant lung tumor. With high sensitivity and multiplexing capabilities, this assay operates at a low reaction temperature (around 37 °C) and requires a short processing time, ≈70 min post‐cell‐free DNA extraction. These features make the chip a valuable tool for easy and widespread cancer screening.