Screening Of High-risk Individuals Research Articles

Screening high-risk individuals for primary gastric adenocarcinoma: evaluating progression-free survival probability score in the presence and absence of Rictor expression after gastrectomy

ObjectiveDeveloping nomogram-based risk stratification model to determine 3-year and 5-year progression-free survival (PFS) and to identify high-risk patients with gastric adenocarcinoma based on different Rictor statuses.Methods1366 individuals who underwent radical gastric surgery to treat gastric adenocarcinoma at Shanxi Cancer Hospital from May 2002 to December 2020 were analyzed. Cox regression analysis was employed to create the nomograms. The nomograms’ performance was assessed using C-index, time receiver operating characteristic (t-ROC) curves, calibration curves, and decision curve analysis (DCA) curves in training and validation cohorts. Subsequently, patients were categorized into high-risk and low-risk groups based on the nomogram’s risk scores.ResultsThe Rictor (-) nomogram for predicting PFS included variables such as age, number of positive lymph nodes, vascular invasion, maximum diameter of the tumor, omentum metastasis, and expression of MSH2. In the internal validation, the C-index of the Rictor (-) nomogram was 0.760 (95%CI: 0.720-0.799), which was superior to the C-index of the American Joint Committee on Cancer (AJCC) 8th edition TNM staging (0.683, 95%CI: 0.646-0.721). Similarly, the Rictor (+) nomogram for predicting PFS included variables such as gender, age, pT stage, number of positive lymph nodes, neural invasion, maximum diameter of the tumor, omentum metastasis, Clavien-Dindo classification for complications, and CGA expression. The C-index of the Rictor (+) nomogram was 0.795 (95%CI: 0.764-0.825), which outperformed the C-index of the AJCC 8th edition TNM staging (0.693, 95%CI: 0.662-0.723). The calibration curves, t-ROC curves, and decision curve analysis for both nomogram models demonstrated their excellent prediction ability.ConclusionThis study presents the first risk stratification for Rictor status in gastric adenocarcinoma. Our model identifies low-risk patients who may not require additional postoperative treatment, while high-risk patients should consider targeted therapies that specifically target Rictor-positive indicators.

Elevated Urinary Levels of Fungal and Environmental Toxins in Patients with Pancreatic Ductal Adenocarcinoma

BackgroundRisk factors for pancreatic ductal adenocarcinoma (PDAC) include tobacco/alcohol abuse, genetic predisposition, insulin resistance, and pancreatic cysts. Despite these well-established risk factors and the screening of high-risk individuals, some people still develop PDAC. This study aims to explore a potential risk factor for PDAC by investigating the association between fungal toxins (FT) and environmental toxins (ET) and the disease. We predicted that individuals with PDAC would have higher levels of these toxins compared to healthy controls. The rationale behind this hypothesis is that exposure to FT and ET might contribute to the development of PDAC by elevating cancer risk.MethodsA pilot retrospective cohort study was conducted at Moffitt Cancer Center from 2022 to 2023. This study compared FT and ET levels, demographic data, and PDAC features between subjects with PDAC and healthy controls.ResultsForty subjects were enrolled in the study, comprising 20 with pancreatic ductal adenocarcinoma (PDAC) and 20 healthy controls. Baseline demographics were similar between the two groups. Among the PDAC subjects, the most common tumor location was the head of the pancreas (55%); 30% had locally advanced disease, 45% were borderline resectable, and 10% had metastatic disease.Compared to the controls, subjects with PDAC had significantly higher levels of fungal toxins (FTs) including ochratoxin, gliotoxin, and citrinin (p < 0.05). Additionally, PDAC patients had significantly elevated levels of environmental toxins (ETs) such as methyl tert-butyl ether (MTBE), xylene, styrene, acrylonitrile, perchlorate, diphenyl phosphate, bromopropane, organophosphates, acrolein, tiglylglycine, and diethylphosphate (p < 0.05).ConclusionOur study demonstrates that subjects with PDAC, without other risk factors, have higher FT and ET levels than controls. Further studies are needed to evaluate whether ET and FT exposure can be clinically utilized as a risk factor for PDAC development.

Pancreatic cancer screening in high-risk individuals.

The incidence of pancreatic cancer is increasing, although globally it represents less than 3% of all cancers. Despite advances in medical and surgical management, survival rates have not significantly improved in recent years. Consequently, pancreatic cancer, though relatively uncommon, is the third leading cause of cancer-related deaths. This is primarily due to the disease´s late detection. Symptoms appear late and are nonspecific, and over 80% of cases are diagnosed at an advanced stage and unsuitable for curative surgery, resulting in a five-year survival rate below 10%. However, the exceptional cases that are diagnosed early show five-year survival rates exceeding 80%. Therefore, one of the keys to improving pancreatic cancer prognosis lies in early detection, making screening in high-risk individuals a potentially crucial strategy.

Diagnostic accuracy of Cardiochek® PA point-of-care testing (POCT) analyser with a 3-in-1 lipid panel for epidemiological surveys

BackgroundPoint-of-care testing (POCT) is commonly used in epidemiological surveys due to its various advantages, such as portability and immediate test results. The CardioChek® PA analyser 3-in-1 lipid panel measures total cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL) cholesterol and low-density lipoprotein (LDL) cholesterol. This study tested the reliability and diagnostic accuracy of the CardioChek® PA analyser using a 3-in-1 lipid panel.MethodsA cross-sectional study design with quota sampling was used. A total of 203 respondents aged 18 years and above from a research centre in the Ministry of Health, Malaysia, were recruited. Venous blood was sent to the laboratory and tested with Siemens Atellica CH, while a POCT analyser was used for capillary blood measurements. Intraclass coefficient correlation (ICC) analysis was employed to determine the agreement between capillary and venous blood parameters. The diagnostic performance of the evaluated tests was evaluated using STATA version 12.ResultsThe agreement between capillary and laboratory venous blood was moderate (0.64–0.67) for TC and HDL, good (0.75) for LDL and excellent (0.91) for TG). The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were as follows: TC, 57.1%, 94.3%, 92.3% and 64.8%; TG, 76.0%, 100%, 100%, and 96.6%; HDL, 96.2%, 83.2%, 47.2% and 99.3%; and LDL, 81.0%, 100%, 100% and 68.3%, respectively.ConclusionsThe CardioChek® PA analyser showed acceptable diagnostic accuracy for screening high-risk individuals more often in places where laboratories are inaccessible. It could also be used in clinical settings where patients would benefit from swift treatment decisions.

Increasing the reach: optimizing screening for atrial fibrillation-the STROKESTOP III study.

Atrial fibrillation (AF) is the most common type of cardiac arrythmia and is an important risk factor for ischaemic stroke. Many cases of AF remain undiagnosed due to its paroxysmal, intermittent, and often asymptomatic nature. Early detection of AF through screening and initiation of treatment with oral anticoagulants can prevent stroke, increase life expectancy, and decrease the cost of healthcare for the society. However, participation has been low in previous AF screening studies employing population screening. The aim of this study is to determine whether opportunistic screening is a superior method to increase participation in comparison to population screening. We hypothesize that opportunistic screening will significantly increase participation. In our study, STROKESTOP III, a randomized prospective cohort study, we compare two different methods of AF screening in high-risk individuals: population screening vs. opportunistic screening. Sixteen different primary clinics in Värmland, Sweden, serving 75-76-year-old individuals (n = 2954), will be randomized to either population screening or opportunistic screening. The individuals will be instructed to record electrocardiogram (ECG) for 30 s, 3 times daily for 2 weeks, using a handheld one-lead ECG device. Patients with detected AF will be referred to their primary healthcare physician and offered treatment. The main objective of the study is to determine the rate of participation in opportunistic screening in comparison to population screening. The STROKESTOP III study will provide valuable information on which screening method to use for improved participation in atrial fibrillation screening.

Screening high-risk individuals for primary gastric carcinoma: evaluating overall survival probability score in the presence and absence of lymphatic metastasis post-gastrectomy

ObjectiveThe aim of this study was to develop and validate prognostic models for predicting overall survival in individuals with gastric carcinoma, specifically focusing on both negative and positive lymphatic metastasis.MethodsA total of 1650 patients who underwent radical gastric surgery at Shanxi Cancer Hospital between May 2002 and December 2020 were included in the analysis. Multiple Cox Proportional Hazards analysis was performed to identify key variables associated with overall survival in both negative and positive lymphatic metastasis cases. Internal validation was conducted using bootstrapping to assess the prediction accuracy of the models. Calibration curves were used to demonstrate the accuracy and consistency of the predictions. The discriminative abilities of the prognostic models were evaluated and compared with the 8th edition of AJCC-TNM staging using Harrell’s Concordance index, decision curve analysis, and time-dependent receiver operating characteristic curves.ResultsThe nomogram for node-negative lymphatic metastasis included variables such as age, pT stage, and maximum tumor diameter. The C-index for this model in internal validation was 0.719, indicating better performance compared to the AJCC 8th edition TNM staging. The nomogram for node-positive lymphatic metastasis included variables such as gender, age, maximum tumor diameter, neural invasion, Lauren classification, and expression of Her-2, CK7, and CD56. The C-index for this model was 0.674, also outperforming the AJCC 8th edition TNM staging. Calibration curves, time-dependent receiver operating characteristic curves, and decision curve analysis for both nomograms demonstrated excellent prediction ability. Furthermore, significant differences in prognosis between low- and high-risk groups supported the models’ strong risk stratification performance.ConclusionThis study provides valuable risk stratification models for lymphatic metastasis in gastric carcinoma, encompassing both node-positive and negative cases. These models can help identify low-risk individuals who may not require further intervention, while high-risk individuals can benefit from targeted therapies aimed at addressing lymphatic metastasis.

Clinical Application of Exhaled Breath Condensate in Diagnosis of Diseases.

Respiratory diseases are highly prevalent in the general population, and the morbidity, mortality, and healthcare burden on society at large have been on the rise worldwide. For example, lung cancer is a major contributor to cancer-related mortality around the globe, and identifying clinically relevant biomarkers for lung cancer detection at both early and metastatic stages has been a pressing need. Human metabolism is complicated and may vary with different individuals. Despite advances in the treatment and the early screening of respiratory diseases, most diagnoses are established at a late stage, i.e., when genetic and epigenetic changes have developed. A promising source of biomarkers indicative of the pathogenesis of respiratory diseases is exhaled breath condensate (EBC), a biological fluid and a natural matrix of the respiratory tract. Molecules, such as DNAs, RNAs, proteins, metabolites, and others, are found in EBC, and their presence/absence or changes in concentrations can serve as biomarkers. This review discusses the exhaled breath composition, candidate EBC biomarkers, and the potential to use EBC for diagnosing diseases, therapeutic monitoring, and screening high-risk individuals.

Clinical performance of a prefabricated immunofluorescence assay for nasopharyngeal cancer screening.

Epstein-Barr virus (EBV) IgA serology for viral capsid antigen (VCA) and early antigen (EA) aids early detection of nasopharyngeal cancer (NPC), resulting in improved survival. We evaluated the diagnostic performance of a prefabricated immunofluorescent assay (IFA) for NPC screening in high-risk individuals. Sera from 96 biopsy-proven patients with NPC diagnosed at the outpatient clinic and 96 healthy family members were tested for EBV-VCA IgA and EBV-EA IgA using the prefabricated IFA from EUROIMMUN (EI) and the traditional immunofluorescence method. The AUC of EI EBV-VCA IgA and EBV-EA IgA was 0.907 (95% confidence interval [CI]: 0.894-0.965) and 0.898 (95% CI: 0.848-0.947), respectively. Combined testing with the prefabricated assay at a threshold of VCA ≥1:320 or EA ≥1:10 showed 92.7% sensitivity and 81.2% specificity. Overall, the traditional EBV-EA IgA assay demonstrated the best accuracy (sensitivity 91.7% and specificity 96.9%) at a threshold of ≥1:5. While the traditional IFA method was more accurate, the prefabricated IFA test kit can be a useful tool for NPC screening in high-risk populations.

Identification of patients' smoking status using an explainable AI approach: a Danish electronic health records case study.

Smoking is a critical risk factor responsible for over eight million annual deaths worldwide. It is essential to obtain information on smoking habits to advance research and implement preventive measures such as screening of high-risk individuals. In most countries, including Denmark, smoking habits are not systematically recorded and at best documented within unstructured free-text segments of electronic health records (EHRs). This would require researchers and clinicians to manually navigate through extensive amounts of unstructured data, which is one of the main reasons that smoking habits are rarely integrated into larger studies. Our aim is to develop machine learning models to classify patients' smoking status from their EHRs. This study proposes an efficient natural language processing (NLP) pipeline capable of classifying patients' smoking status and providing explanations for the decisions. The proposed NLP pipeline comprises four distinct components, which are; (1) considering preprocessing techniques to address abbreviations, punctuation, and other textual irregularities, (2) four cutting-edge feature extraction techniques, i.e. Embedding, BERT, Word2Vec, and Count Vectorizer, employed to extract the optimal features, (3) utilization of a Stacking-based Ensemble (SE) model and a Convolutional Long Short-Term Memory Neural Network (CNN-LSTM) for the identification of smoking status, and (4) application of a local interpretable model-agnostic explanation to explain the decisions rendered by the detection models. The EHRs of 23,132 patients with suspected lung cancer were collected from the Region of Southern Denmark during the period 1/1/2009-31/12/2018. A medical professional annotated the data into 'Smoker' and 'Non-Smoker' with further classifications as 'Active-Smoker', 'Former-Smoker', and 'Never-Smoker'. Subsequently, the annotated dataset was used for the development of binary and multiclass classification models. An extensive comparison was conducted of the detection performance across various model architectures. The results of experimental validation confirm the consistency among the models. However, for binary classification, BERT method with CNN-LSTM architecture outperformed other models by achieving precision, recall, and F1-scores between 97% and 99% for both Never-Smokers and Active-Smokers. In multiclass classification, the Embedding technique with CNN-LSTM architecture yielded the most favorable results in class-specific evaluations, with equal performance measures of 97% for Never-Smoker and measures in the range of 86 to 89% for Active-Smoker and 91-92% for Never-Smoker. Our proposed NLP pipeline achieved a high level of classification performance. In addition, we presented the explanation of the decision made by the best performing detection model. Future work will expand the model's capabilities to analyze longer notes and a broader range of categories to maximize its utility in further research and screening applications.

Development of the Acute Coronary Syndrome Predictive Scale

Introduction: The use of a predictive scale for acute coronary syndrome (ACS) can play an essential role in screening high-risk individuals. This study aimed to develop the ACS predictive scale (ACS-PS) and investigate its construct validity, reliability, sensitivity and specificity. Methods: This was a retrospective methodological study with the aim of developing a predictive scale for ACS in Iran in 2019. In this study, the content validity (content validity index [CVI] and content validity ratio [CVR]), construct validity, sensitivity, specificity, cutoff point and internal consistency of the 13-item scale for predicting ACS (in Persian) were investigated. Participants included patients with a definite diagnosis of ACS (n=150) and a healthy group without ACS (n=143). Results: The score range of the 13-item scale was 0-130, and with a cutoff point of 11.5, both the sensitivity and specificity of the scale were 0.75. Cronbach’s alpha coefficient was 0.80. Conclusion: The present study introduced a sensitive and specific scale for predicting ACS. The ACS-PS is a partially short-form scale and requires less time to complete.

A311 EFFICACY OF PANCREATIC CANCER SCREENING IN HIGH RISK INDIVIDUALS

Abstract Background Pancreatic cancer (PC) is the 11th most prevalent cancer in Canada with about 6900 new cases in 2021. Due to late diagnosis, it is the 4th largest cause of cancer related mortality in Canada. Despite advances in diagnosis and treatment over the past decade, the 5-year survival remains ampersand:003C10%, making pancreatic cancer one of the most lethal malignancies worldwide. However, if detected early, the 5-year survival increases to 80%. The incidence of pancreatic cancer remains low. Therefore, the International Cancer of the Pancreas Screening (CAPS) consortium do not recommend screening everyone. Selective screening in high-risk individuals may be effective in early detection and treatment of pancreatic cancer. Aims 1. To determine the characteristics of patients undergoing PC screening at a single tertiary care center in Vancouver. 2. To determine the frequency of disease progression and outcomes in patients diagnosed with high-risk lesions during screening. Methods Retrospective chart review was performed for patients who were screened between January 1, 2005 to June 30, 2023. As per consensus from the CAPS Consortium, patients with at least 2 close relatives with PC, and those with predisposing genetic mutations screened using endoscopic ultrasound (EUS) and/or magnetic resonance imaging (MRI) were included in the study. Clinical data, such as age, tobacco use, genetic risk, endoscopic findings, and outcomes, such as disease progression, were collected. Statistical analysis was performed using Rstudio and Microsoft Excel. Results 73 patients were included, with 42 included due to pathogenic germline mutations, and 31 with familial pancreatic cancer. Most were female (52, 71.2%). Median age in the study was 54 years (range 24-74 years) at initial screening. 66 patients (90.4%) received an EUS and 7 patients (9.6%) received MRI for initial screening. At the time of initial screening. 74.6% of patients had a normal pancreas. 6 patients (8.2%) were found to have neoplastic lesions, e.g. ampulloma, neuroendocrine tumour or adenocarcinoma at initial screening and referred for surgery. In the median follow up time of 67.9 months (range 0-168.1 months), 6 patients were noted to have disease progression, 4 of which had increase in cyst size without any other worrisome features. 2 patients had progression to malignancy. 1 of those patients received chemotherapy and surgical resection and remains alive; the other patient was lost of follow up due to geographical move. Conclusions Pancreatic cancer screening in high risk individuals is effective in early detection and treatment. Given lower incidence of pancreatic cancer, we likely need additional patient enrolment to observe a significant improvement in patient outcomes. Funding Agencies None

Examination of Diagnostic Performance of New IgG4 Rapid Test Compared with IgG- and IgG4-ELISAs to Investigate Epidemiology of Strongyloidiasis in Northeast Thailand.

Strongyloidiasis, caused by Strongyloides stercoralis, is a neglected tropical disease with a global distribution. The infection can be fatal in immunocompromised individuals, and accurate diagnosis leading to timely treatment can save lives. Serodiagnosis is a sensitive method for diagnosis and is recommended for screening high-risk individuals. A point-of-care rapid test will facilitate the screening activities, especially in low-resource settings. This study aims to apply a new IgG4 immunochromatographic test using S. stercoralis recombinant antigen (SsRapid® cassette test) and to compare it with in-house IgG and IgG4 enzyme-linked immunosorbent assays (IgG- and IgG4-ELISAs) using native Strongyloides ratti antigen to investigate the epidemiology of strongyloidiasis in northeast Thailand. A total of 300 people participated, with 136 males and 164 females of a similar mean age. The reference tests were fecal examinations using the formalin-ethyl acetate concentration technique and an agar plate culture technique. The prevalence of S. stercoralis determined by SsRapid (81.7%) was significantly higher than that by fecal examinations (43.3%) or by antibody detection by IgG-ELISA (53.0%) or IgG4-ELISA (44.0%). The diagnostic sensitivities of SsRapid, IgG-ELISA, and IgG4-ELISA were found to be 93.9%, 77.7%, and 63.1%, respectively. The rate of positive tests by the SsRapid was significantly correlated to the levels of Strongyloides-specific IgG4 and IgG antibodies. By all diagnostic methods, male participants had a significantly higher prevalence of strongyloidiasis than females. Age was significantly associated with the concentration of specific serum IgG but not with the SsRapid grading score. In conclusion, SsRapid was shown to be a sensitive and valuable diagnostic test for the epidemiology study of strongyloidiasis.

Pancreatic cancer screening in high-risk individuals: look, but maybe not that hard

Pancreatic cancer screening in high-risk individuals: look, but maybe not that hard

Reducing the Burden of Diabetes Mellitus: Is it Achievable?

Diabetes mellitus is rapidly on the rise globally, particularly in low- and middle-income countries. Pakistan has emerged with the highest prevalence of diabetes by percentage according to recent estimates. Evidence is available for different strategies to reduce this burden. Screening high-risk individuals can reduce burden of undiagnosed diabetes and improve outcomes. Although prediabetes can progress to type 2 diabetes, it has the potential to regress to normoglycaemia as well. Interventions like lifestyle modifications and metformin in high-risk individuals can reduce the risk of progression to diabetes. Furthermore, there is a potential to reverse diabetes in some individuals in the early years after diagnosis with a low-calorie diet, carbohydrate restriction or bariatric surgery.

Knowledge, perception, and risk scoring of diabetes among rural nondiabetics in southern coastal Karnataka, India

ABSTRACT Background: Diabetes is one of the top 10 contributors to death globally. It is affecting more and more younger populations due to lifestyle changes in India. Tools like the Indian Diabetic Risk Score (IDRS) help in screening high-risk individuals for diabetes. Early diagnosis and prompt treatment help in avoiding complications and disabilities due to diabetes. Hence, this study was conducted to calculate the risk of diabetes using IDRS and to determine the knowledge and risk perception of diabetes among the nondiabetics residing in the rural field practice area of a medical college. Methodology: A descriptive cross-sectional study was conducted in the rural field practice area of a medical college. A total of 885 people participated in our study. All nondiabetics above 18 years of age were involved. The data were collected using a questionnaire and the IDRS questionnaire was used to determine the risk of diabetes. Data were analyzed using IBM SPSS 20th version. Results: Majority of the participants were between the age of 18 and 50 years. About 65.8% of the study population had medium risk according to IDRS. There was a significant relationship between gender, body mass index, and IDRS. A majority had good knowledge about diabetes. Only 31.5% knew that diabetes can cause complications in other organs of the body. Conclusion: Compared to prior research on rural Indians, this study’s population knew more about diabetes. To encourage people to adhere to their medication and treatment, further health education sessions should concentrate on minimizing the risk factors and complications of diabetes.

Co-designing a recruitment strategy for lung cancer screening in high-risk individuals: protocol for a mixed-methods study.

Lung cancer is a significant cause of cancer-related mortality globally, with early detection through screening critical to improving patient outcomes. However, recruiting high-risk individuals, particularly in deprived populations, for screening remains a considerable challenge. This study aims to co-design a targeted recruitment strategy for lung cancer screening, tailored to the specific needs and experiences of high-risk individuals, in collaboration with a Patient and Public Involvement (PPI) panel and expert stakeholders in Ireland. We will employ a mixed-methods design guided by the Medical Research Council (MRC) framework for developing complex interventions. Our approach will integrate systematic review findings on screening participation interventions, evaluation of the recruitment strategy's feasibility in an Irish context, and the application of behavioural science frameworks. The target population includes individuals over 55 years, either current smokers or those who quit within the last year, who reside in highly deprived areas. This co-designed recruitment strategy will combine evidence-based research, local context understanding, and stakeholder input to develop a solution that is both scientifically robust and tailored to the target population's needs. This patient-centred approach aims to increase the potential for successful implementation of lung cancer screening programs, thereby improving early detection and patient outcomes.

Exploring the relationship between baseline health-related quality of life (AQoL-4D utility values) and mortality during long-term follow-up for people living with a psychotic disorder

Holistic summary measures of health-related quality of life (HRQoL) could provide useful information for screening and/or monitoring high-risk individuals. This study explores the association of baseline HRQoL (AQoL-4D values) with death from natural and external causes (such as suicide, overdose, or accident) in a prevalent cohort over a mean follow-up of 6.9-years. Baseline data were obtained from the 2010 National Survey of High Impact Psychosis (SHIP) and its 2012 sister survey, the North-Metro Survey of High Impact Psychosis. Follow-up data were obtained from the National Deaths Index (to January 18, 2018). Associations between baseline HRQoL (and the 12 individual items of the AQoL-4D) and deaths by cause, stratified by sex were investigated using multivariable Cox Proportional Hazards models, with age used as the time scale. Overall, 7.6 % of the cohort (137 of 1805 people meeting ICD-10 criteria for a psychotic disorder and agreeing to linkage) died, 4.2 % from natural causes (primarily heart disease and cancer) and 3.4 % from external causes. There was an association between low HRQoL (AQoL-4D ≤ 0.20) and mortality due to natural causes, primarily driven by difficulties with mobility and vision in men, and difficulty with household tasks in women. No significant associations were obtained between AQoL-4D utilities and death from external causes. Sleep problems were associated with death from external causes for men only. As people with psychotic disorders experience multiple causes of death with complex associations which are difficult to quantify, monitoring for low HRQoL using the AQoL-4D could be a useful indicator of increased mortality risk in this population. TwitterMonitoring for low HRQoL (AQoL-4D ≤ 0.20) could be a useful indicator of increased mortality risk from natural causes in people living with psychotic disorders, with differing but specific items of relevance to men and women.

Association of Complete Blood Cell Count-Derived Inflammatory Biomarkers with Psoriasis and Mortality.

Psoriasis is a persistent inflammatory disorder that affects 3% of the population and is associated with cardiovascular diseases. Therefore, this study aimed to investigate the correlations between complete blood cell count (CBC)-derived inflammatory biomarkers, psoriasis prevalence, and all-cause mortality. Data were obtained from the National Health and Nutrition Examination Survey (NHANES) spanning 2003-2006 and 2009-2014. Mortality data up to December 31, 2019 were obtained using the National Death Index. The following CBC-derived inflammatory biomarkers were examined: neutrophil/lymphocyte ratio (NLR), neutrophil/(white blood cells - neutrophils) ratio (dNLR), monocyte count/lymphocyte ratio (MLR), (neutrophil + monocyte)/lymphocyte ratio (NMLR), platelet/lymphocyte ratio (PLR), and systemic inflammatory response index (SIRI). Weighted logistic and Cox regression analyses were used to calculate odds ratios, hazard ratios, and the corresponding 95% confidence intervals. Additionally, the prognostic value of the inflammatory indicators was assessed and ranked using the random survival forest approach. In total, data from 21,431 participants with average age of 45.02 ± 0.27 years (49.51% male) were included in the study, among which 600 participants were positive for psoriasis (prevalence rate, 2.80%). Additionally, 79 all-cause deaths were recorded during a median follow-up period of 8.83 (6.67-11.00) years. Moreover, NLR, dNLR, NMLR, PLR, and SIRI were positively associated with the prevalence of psoriasis. Furthermore, MLR, NMLR, and SIRI were positively correlated with all-cause mortality in patients with psoriasis, with NMLR being the most valuable predictor of all-cause mortality. CBC-derived inflammatory biomarkers were associated with psoriasis prevalence, NMLR, SIRI, and MLR values were associated with all-cause mortality in patients with psoriasis. Overall, assessment of these CBC-derived indicators may serve as a simple method for screening high-risk individuals among patients with psoriasis.

Development, validation, and visualization of a novel nomogram to predict stroke risk in patients.

Stroke is the second leading cause of death worldwide and a major cause of long-term neurological disability, imposing an enormous financial burden on families and society. This study aimed to identify the predictors in stroke patients and construct a nomogram prediction model based on these predictors. This retrospective study included 11,435 participants aged >20 years who were selected from the NHANES 2011-2018. Randomly selected subjects (n = 8531; 75%) and the remaining subjects comprised the development and validation groups, respectively. The least absolute shrinkage and selection operator (LASSO) binomial and logistic regression models were used to select the optimal predictive variables. The stroke probability was calculated using a predictor-based nomogram. Nomogram performance was assessed by the area under the receiver operating characteristic curve (AUC) and the calibration curve with 1000 bootstrap resample validations. Decision curve analysis (DCA) was performed to evaluate the clinical utility of the nomogram. According to the minimum criteria of non-zero coefficients of Lasso and logistic regression screening, older age, lower education level, lower family income, hypertension, depression status, diabetes, heavy smoking, heavy drinking, trouble sleeping, congestive heart failure (CHF), coronary heart disease (CHD), angina pectoris and myocardial infarction were independently associated with a higher stroke risk. A nomogram model for stroke patient risk was established based on these predictors. The AUC (C statistic) of the nomogram was 0.843 (95% CI: 0.8186-0.8430) in the development group and 0.826 (95% CI: 0.7811, 0.8716) in the validation group. The calibration curves after 1000 bootstraps displayed a good fit between the actual and predicted probabilities in both the development and validation groups. DCA showed that the model in the development and validation groups had a net benefit when the risk thresholds were 0-0.2 and 0-0.25, respectively. This study effectively established a nomogram including demographic characteristics, vascular risk factors, emotional factors and lifestyle behaviors to predict stroke risk. This nomogram is helpful for screening high-risk stroke individuals and could assist physicians in making better treatment decisions to reduce stroke occurrence.

Integrating Smoking Cessation Into Low-Dose Computed Tomography Lung Cancer Screening: Results of the Ontario, Canada Pilot

IntroductionLow-dose computed tomography screening in high-risk individuals reduces lung cancer mortality. To inform the implementation of a provincial lung cancer screening program, Ontario Health undertook a Pilot study, which integrated smoking cessation (SC). MethodsThe impact of integrating SC into the Pilot was assessed by the following: rate of acceptance of a SC referral; proportion of individuals who were currently smoking cigarettes and attended a SC session; the quit rate at 1 year; change in the number of quit attempts; change in Heaviness of Smoking Index; and relapse rate in those who previously smoked. ResultsA total of 7768 individuals were recruited predominantly through primary care physician referral. Of these, 4463 were currently smoking and were risk assessed and referred to SC services, irrespective of screening eligibility: 3114 (69.8%) accepted referral to an in-hospital SC program, 431 (9.7%) to telephone quit lines, and 50 (1.1%) to other programs. In addition, 4.4% reported no intention to quit and 8.5% were not interested in participating in a SC program. Of the 3063 screen-eligible individuals who were smoking at baseline low-dose computed tomography scan, 2736 (89.3%) attended in-hospital SC counseling. The quit rate at 1 year was 15.5% (95% confidence interval: 13.4%–17.7%; range: 10.5%–20.0%). Improvements were also observed in Heaviness of Smoking Index (p < 0.0001), number of cigarettes smoked per day (p < 0.0001), time to first cigarette (p < 0.0001), and number of quit attempts (p < 0.001). Of those who reported having quit within the previous 6 months, 6.3% had resumed smoking at 1 year. Furthermore, 92.7% of the respondents reported satisfaction with the hospital-based SC program. ConclusionsOn the basis of these observations, the Ontario Lung Screening Program continues to recruit through primary care providers, to assess risk for eligibility using trained navigators, and to use an opt-out approach to referral for cessation services. In addition, initial in-hospital SC support and intensive follow-on cessation interventions will be provided to the extent possible.