Targeted Screening Strategies Research Articles

Blood cell indices and inflammation-related markers with kidney cancer risk: a large-population prospective analysis in UK Biobank

BackgroundKidney cancer is a prevalent malignancy with an increasing incidence worldwide. Blood cell indices and inflammation-related markers have shown huge potential as biomarkers for predicting cancer incidences, but that is not clear in kidney cancer. Our study aims to investigate the correlations of blood cell indices and inflammation-related markers with kidney cancer risk.MethodsWe performed a population-based cohort prospective analysis using data from the UK Biobank. A total of 466,994 participants, free of kidney cancer at baseline, were included in the analysis. The hazard ratios (HRs) and 95% confidence intervals (CIs) for kidney cancer risk were calculated using Cox proportional hazards regression models. Restricted cubic spline models were used to investigate nonlinear longitudinal associations. Stratified analyses were used to identify high-risk populations. The results were validated through sensitivity analyses.ResultsDuring a mean follow-up of 12.4 years, 1,710 of 466,994 participants developed kidney cancer. The Cox regression models showed that 13 blood cell indices and four inflammation-related markers were associated with kidney cancer incidence. The restricted cubic spline models showed non-linear relationships with kidney cancer. Finally, combined with stratified and sensitivity analyses, we found that the mean corpuscular hemoglobin concentration (MCHC), red blood cell distribution width (RDW), platelet distribution width (PDW), systemic immune-inflammation index (SII), and product of platelet count and neutrophil count (PPN) were related to enhanced kidney cancer risk with stable results.ConclusionOur findings identified that three blood cell indices (MCHC, RDW, and PDW) and two inflammation-related markers (SII and PPN) were independent risk factors for the incidence of kidney cancer. These indexes may serve as potential predictors for kidney cancer and aid in the development of targeted screening strategies for at-risk individuals.

Primary care prescribing prior to lung cancer diagnosis (PPP-Lung): protocol for a systematic review

Background Lung cancer is the second most common cancer and the leading cause of cancer death worldwide. A significant reason for its high mortality is delayed diagnosis, with lung cancer typically diagnosed at an advanced stage. Previous research has shown that prescribing rates of certain medications increase in the 24 months preceding a cancer diagnosis. This suggests a potential opportunity for early diagnosis of lung cancer by the identification of high-risk patients based on the prescribing of medications associated with a subsequent lung cancer diagnosis. Our aim is to identify all prescribing events associated within an increased incidence of primary lung cancer in the subsequent 24 months. Methods We will conduct a systematic review, and, where possible, a meta-analysis, reporting the findings in accordance with the PRISMA reporting guideline. All peer-reviewed studies in the English language that quantitatively describe an association between prescribing data and lung cancer diagnosis using a control group will be eligible. Details regarding prescribing rate in the lung cancer group versus the control group will be extracted with study characteristics. Quality appraisal of studies, using ROBINS-E will be used for assessing risk of bias. For each drug studied, we will report prescribing rate ratios (PRRs) with 95% confidence intervals (CIs). A meta-analysis using a pooled estimate of PRRs, either by fixed or random-effect models, will be performed if possible. Conclusions This systematic review will summarise the evidence on drugs that, when prescribed, suggest the possibility of an as-yet-undiagnosed lung cancer. This research has the potential to impact clinical practice by informing targeted screening strategies and refining early detection protocols for this harmful disease. If achieved, this could increase the numbers of lung cancers diagnosed at an earlier stage, with consequent improvements to patients in terms of survival, treatment tolerability and quality of life.

Targeted Screening for Viral Hepatitis Among Various Ethnic Groups in Amsterdam, the Netherlands

Background: A significant portion of individuals with hepatitis B virus (HBV) or hepatitis C virus (HCV) in the Netherlands remain undiagnosed, with a majority from migrant backgrounds. Objectives: This study explored whether targeting HBV/HCV screening among individuals with metabolic risk factors enhances screening efficacy within a diverse ethnic cohort. Methods: Participants from six ethnic backgrounds were enlisted from the population-based, prospective HELIUS study in the Netherlands. Included were participants at elevated risk for non-alcoholic fatty liver disease (NAFLD), identified by elevated non-invasive tests (NITs) and/or metabolic risk factors, who were then tested for HBV/HCV. We evaluated screening efficiency, defined as the prevalence of HBV/HCV, by implementing two targeted screening strategies: (1) Testing individuals with elevated NITs; and (2) those with metabolic risk factors. These strategies were compared to a generic testing approach previously utilized in a subset of HELIUS participants. For non-Dutch origin participants, analyses were stratified based on the HBsAg-prevalence in their region of origin: Low (< 2%) and intermediate (2 - 8%). Results: The study included 346 participants at risk for NAFLD, predominantly of Surinamese (n = 180; 45%), Dutch (n = 103; 26%), or Ghanaian (n = 63; 16%) origin. The generic testing approach encompassed 3,050 individuals. Among individuals from low and intermediate HBV-endemic countries, HBsAg-prevalence was 4.7% and 5.3% for those with elevated NITs, 3.9%, and 3.5% for those with metabolic risk factors, and 0.8% and 3.7% for generic testing, respectively. Regarding HCV, two individuals were anti-HCV-positive, with none being HCV-RNA-positive. Conclusions: Targeted screening based on metabolic risk factors or elevated NITs may be more efficient than generic screening among migrants from regions with low HBV prevalence.

Abstract 1024: Differential gene expression of colorectal cancer biomarkers in Hispanic individuals

Abstract Colorectal cancer (CRC) is a leading cause of cancer death among men and women in Puerto Rico and the United States. About 60-70% of CRC cases are found at advanced stages (III/IV), suggesting limited adherence to available screening methods. Several molecular biomarkers have been identified as discriminatory for CRC (e.g., KRAS, NRAS, MSI), improving CRC management and patient outcomes. This study evaluates the differential expression patterns of DKK3, PKM2, IGFBP2, and SEPT9 genes between matched CRC tumors and adjacent mucosa samples. The secondary outcome was to examine the association between the presence of the selected biomarkers in tissue compared to blood samples. Using a retrospective study design, we examined 112 tissue samples of Hispanic individuals with a pathology-confirmed CRC diagnosis recruited throughout the Puerto Rico Familial Colorectal Cancer Registry (PURIFICAR). We quantified expression levels of target genes by RT-qPCR normalized with endogenous control GAPDH, using TaqMan Gene Expression Assay in the QuantStudio 3 (Applied Biosystems). Wilcoxon signed-rank test was used to calculate differences between gene expression from tumor and adjacent mucosal tissue samples. Additionally, 39 paired blood and tissue samples were analyzed to explore the association between biomarkers in these two types of samples. Protein biomarkers were measured using a commercially available ELISA kit according to manufacturer protocols (Thermo Scientific Federick, MD and Biosource San Diego, CA). mSEPT9 was measured using the Epi proColon® 2.0 CE test. The association between biomarker presence in tissue and blood samples was assessed using the Chi-square test of independence, with biomarker concentrations dichotomized at the median value. Statistical analyses were performed using Stata 17 and R version 4.3.1. DKK3 and IGFBP2 expression levels were higher among CRC tumor samples. However, expression levels of PKM2 and SEPT9 genes were slightly lower. DKK3 was the only target gene significantly different (p<0.05) when comparing overall gene expression between the matched samples. Upon comparison between early and advanced CRC stages, DKK3 expression levels were higher in advanced-stage tumor samples when compared to adjacent mucosal tissue samples (p<0.05). Moreover, a significant association between IGFBG2 presence in tissue compared to blood was detected at a 90% confidence level (p-value<0.10). This association was evident in early-stage CRC cases; there is a relationship between IGFBG2 biomarker presence in tissue and IGFBG2 biomarker presence in blood (p<0.05). Our findings indicate DKK3 and IGFBP2 as potential biomarkers for CRC progression and early detection. The study’s insights into the differential expression patterns of these biomarkers can inform targeted screening strategies. Further research is needed to assess their potential to enhance early tumor detection in Hispanics. Citation Format: Elba V. Caraballo-Rivera, Hilmaris Centeno-Girona, Gabriel De Jesus-Astacio, Camille Zenon-Melendez, Brenda Torres-Velasquez, Madeline Martir-Ocasio, Marcia R. Cruz-Correa. Differential gene expression of colorectal cancer biomarkers in Hispanic individuals [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1024.

Machine learning prediction of adolescent HIV testing services in Ethiopia.

Despite endeavors to achieve the Joint United Nations Programme on HIV/AIDS 95-95-95 fast track targets established in 2014 for HIV prevention, progress has fallen short. Hence, it is imperative to identify factors that can serve as predictors of an adolescent's HIV status. This identification would enable the implementation of targeted screening interventions and the enhancement of healthcare services. Our primary objective was to identify these predictors to facilitate the improvement of HIV testing services for adolescents in Ethiopia. A study was conducted by utilizing eight different machine learning techniques to develop models using demographic and health data from 4,502 adolescent respondents. The dataset consisted of 31 variables and variable selection was done using different selection methods. To train and validate the models, the data was randomly split into 80% for training and validation, and 20% for testing. The algorithms were evaluated, and the one with the highest accuracy and mean f1 score was selected for further training using the most predictive variables. The J48 decision tree algorithm has proven to be remarkably successful in accurately detecting HIV positivity, outperforming seven other algorithms with an impressive accuracy rate of 81.29% and a Receiver Operating Characteristic (ROC) curve of 86.3%. The algorithm owes its success to its remarkable capability to identify crucial predictor features, with the top five being age, knowledge of HIV testing locations, age at first sexual encounter, recent sexual activity, and exposure to family planning. Interestingly, the model's performance witnessed a significant improvement when utilizing only twenty variables as opposed to including all variables. Our research findings indicate that the J48 decision tree algorithm, when combined with demographic and health-related data, is a highly effective tool for identifying potential predictors of HIV testing. This approach allows us to accurately predict which adolescents are at a high risk of infection, enabling the implementation of targeted screening strategies for early detection and intervention. To improve the testing status of adolescents in the country, we recommend considering demographic factors such as age, age at first sexual encounter, exposure to family planning, recent sexual activity, and other identified predictors.

Emergent approach to small bowel tumors: diagnosis and treatment.

This study presents the diagnosis and treatment of rare small bowel tumors through clinical cases. Patients treated between 2000 and 2023 were included in the study. The clinical records of the patients were analyzed retrospectively. A total of 34 patients were included in the study. Of these patients, 26 (75.5%) were male and eight (23.5%) were female. The mean age of the patients was 62.1 years. The most common symptoms and signs were abdominal pain (76.4%), bloating (38.2%), and nausea and vomiting (17.6%). Diagnostic methods included computed tomography (CT) (82.3%), upper gastrointestinal double balloon enteroscopy (35.2%), and capsule endoscopy (5.8%). Diagnoses included adenocarcinoma in 13 cases, gastrointestinal stromal tumors (GISTs) in 12 cases, and neuroendocrine tumors (NETs) in two cases. Small bowel tumors frequently present with abdominal pain, bloating, and nausea and vomiting. CT and endoscopic procedures are the primary diagnostic tools. Small bowel cancers are often diagnosed late due to subtle clinical findings and the limitations of endoscopic imaging. Targeted screening strategies may be beneficial for certain at-risk and symptomatic patient groups. Early surgical intervention offers significant advantages for diagnosed patients.

A polygenic risk score predicts atrial fibrillation in patients with coronary artery disease without severe systolic dysfunction

Abstract Background Genome-wide polygenic risk scores (GPS) comprised of multiple common variants can identify individuals within the general population at significantly higher risk for developing atrial fibrillation AF; however, the clinical utility in general populations is limited by the low absolute risk of AF. Purpose To determine whether a genome-wide polygenic score for AF (GPSAF) can be utilized to identify a patient population at high absolute risk for the development of AF among older patients with established coronary artery disease (CAD) and left ventricular ejection fraction (LVEF) > 30-35%. Methods Participants in the PREDETERMINE study without a prior history of AF who had claims data available in Centers for Medicare and Medicaid Services (CMS) database were followed for incident AF defined as International Classification of Diseases codes 427.3 and I48. A recently validated GPSAF comprised of 1.1 million variants was generated and participants were divided into quintiles based upon the distribution of the GPSAF in the general population. The population was separated into 3 categories of genetic risk, with the top quintile classified as high risk, the second through fourth quintiles classified as intermediate risk, and the bottom quintile classified as low risk. Cumulative incidence curves for incident AF were plotted stratified by the GPSAF categories and the association between GPSAF and incident AF were estimated using Cox proportional hazard models with and without adjusting for established AF risk factors and biomarkers (N-terminal pro-B-type natriuretic peptide, high-sensitivity Troponin I, high sensitivity c-reactive protein). Results Over a median follow-up of 8.0 years, there were 482 incident AF events among 2272 study participants. Overall, median age was 67 [62,73] years and 73.5% were men. Baseline AF risk factors and biomarkers did not differ across GPSAF risk categories. The unadjusted cumulative incidence of AF over the course of the study was 39.2% (29.2%-47.8%) in the high GPSAF risk group, 32.5% (25.8%-38.5%) in the intermediate GPSAF risk group, and 21.6% (13.4%-29.9%) in the low GPSAF risk group (Figure 1). Compared with the participants with low GPSAF risk, participants with high and intermediate GPSAF risk had respectively t 2.32-fold (95% CI, 1.71-3.14; p=0.001) and 1.64-fold (95% CI, 1.27-2.10; p=0.001) increased risk for incident AF, adjusted for age and sex. Both remained significantly elevated after controlling for clinical factors, and biomarkers (Table 1). Conclusion A polygenic risk score for AF is strongly associated with incident AF risk among patients with CAD without severe systolic dysfunction, and clinically meaningful elevations in absolute risk of developing AF were observed in those in the highest quintile of risk. Future research is needed to determine if genetic risk assessment and targeted screening strategies will result in reduce morbidity from AF in this high-risk population.

An explainable artificial intelligence framework for risk prediction of COPD in smokers

BackgroundSince the inconspicuous nature of early signs associated with Chronic Obstructive Pulmonary Disease (COPD), individuals often remain unidentified, leading to suboptimal opportunities for timely prevention and treatment. The purpose of this study was to create an explainable artificial intelligence framework combining data preprocessing methods, machine learning methods, and model interpretability methods to identify people at high risk of COPD in the smoking population and to provide a reasonable interpretation of model predictions.MethodsThe data comprised questionnaire information, physical examination data and results of pulmonary function tests before and after bronchodilatation. First, the factorial analysis for mixed data (FAMD), Boruta and NRSBoundary-SMOTE resampling methods were used to solve the missing data, high dimensionality and category imbalance problems. Then, seven classification models (CatBoost, NGBoost, XGBoost, LightGBM, random forest, SVM and logistic regression) were applied to model the risk level, and the best machine learning (ML) model’s decisions were explained using the Shapley additive explanations (SHAP) method and partial dependence plot (PDP).ResultsIn the smoking population, age and 14 other variables were significant factors for predicting COPD. The CatBoost, random forest, and logistic regression models performed reasonably well in unbalanced datasets. CatBoost with NRSBoundary-SMOTE had the best classification performance in balanced datasets when composite indicators (the AUC, F1-score, and G-mean) were used as model comparison criteria. Age, COPD Assessment Test (CAT) score, gross annual income, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), anhelation, respiratory disease, central obesity, use of polluting fuel for household heating, region, use of polluting fuel for household cooking, and wheezing were important factors for predicting COPD in the smoking population.ConclusionThis study combined feature screening methods, unbalanced data processing methods, and advanced machine learning methods to enable early identification of COPD risk groups in the smoking population. COPD risk factors in the smoking population were identified using SHAP and PDP, with the goal of providing theoretical support for targeted screening strategies and smoking population self-management strategies.

Influence of metabolic syndrome and lifestyle factors on thyroid nodules in Chinese adult men: a cross-sectional study.

Given the high prevalence of thyroid nodules and the potential for malignancy, it is imperative to understand the various factors that contribute to their development. This study aimed to explore the relationship between metabolic syndrome, lifestyle, and thyroid nodules in adult men in southern China. This study enrolled a total of 183,990 subjects at a medical examination center in a general hospital in southern China between January 1, 2015, and December 31, 2020. Multivariate logistic regression analysis was utilized to evaluate the relationship between metabolic syndrome, lifestyle factors, and thyroid nodules. Furthermore, structural equation modeling elucidated the intricate relationships among these variables. The prevalence of thyroid nodules among Chinese adult males was 14.9%. Several factors were identified as risk factors for thyroid nodules, including advanced age, irregular meal time, smoking or quitting smoking, quitting drinking, heavy manual labor, hypertension, diabetes, dyslipidemia and centripetal obesity, and those belonging to ethnic minorities and drinking alcohol were found to be protective factors against thyroid nodules. Structural equation modeling highlighted metabolic syndrome's mediating role amidst lifestyle influences on thyroid nodules. The prevalence of thyroid nodules in Chinese adult males is relatively moderate to low. The factors identified in this study can help clinicians identify high-risk patients and develop targeted screening strategies for the timely detection of thyroid nodules. However, further mechanistic research and longitudinal studies are necessary to explore the underlying causes and establish causal relationships.

Optimising Population Based AAA Screening of 65 Year Old Men By Exploring Risk Factor Based Targeted Screening Strategies: In Light of Declining Prevalence

Objective: The prevalence of AAA has declined over the past decades and contemporary studies demonstrate prevalence rates of 1.3 – 1.5% 1,2 among 65 year old men, in contrast to historical rates of 4.9 – 7.2% 3,4 in the large scale screening RCTs conducted in the 1990s and early 2000s. Cost efficiency 5 can be demonstrated for screening programmes with even lower rates, but the clinical legitimacy of general AAA screening of 65 year old men can be questioned with falling prevalence rates. This study analyses risk factor data among large cohorts of 65 year old men screened in the Swedish population based general AAA screening programme – with the aim of exploring selective targeting screening strategies to reach men with the highest risk of having an AAA.

Usefulness of screening for Candida auris colonisation in international patients admitted to a large university hospital.

Candida auris is an emerging pathogen in health care-associated infections. In contrast to many other countries with rising numbers of C.auris, only seven cases have been reported in Germany from 2015 to 2017, mostly from patients who received prior medical treatment abroad. We therefore established a mandatory screening for C.auris colonisation at our tertiary care centre for all patients who were admitted as international patients or previously hospitalised in a foreign country within the past 6 months. Colonisation of patients was assessed using a previously established screening protocol for multidrug resistant bacteria. Since 2017, all screening samples were additionally analysed for C.auris using CHROMagar Candida (CHROMagar, Paris, France). Yeast isolates were identified using matrix-assisted laser ionisation time-of-flight (MALDI TOF), except for C.albicans (identified by the typical green colour on chromogenic agar). Data were analysed retrospectively. Our study cohort included 655 patients and an overall number of 1399 samples. Fifty-three patients were colonised with Candida species (C.albicans, n =37; C.glabrata, n =14; others n =9). No case of C.auris was detected. Candida spp. were mainly detected from respiratory samples (5.4% positive) and gastrointestinal specimen (5.2%). Laboratory costs were 14,689 € and analyses resulted in 98.7 h of additional technician's work. No colonisation with C.auris was detected among patients with previous hospitalisation abroad. Universal C.auris screening of patients with any contact to foreign health care does not seem to be cost-effective in our setting and more targeted screening strategies have to be developed.

Emotions and lung cancer screening: Prioritising a humanistic approach to care.

Low-dose computed tomography lung cancer screening has mortality benefits. Yet, uptake has been low. To inform strategies to better deliver and promote screening, in 2018, we interviewed 27 long-term smokers immediately following lung cancer screening in Australia, prior to receiving scan results. Existing lung screening studies employ the Health Belief Model. Reflecting growing acknowledgement of the centrality of emotions to screening uptake, we draw on psychological and sociological theories on emotions to thematically and abductively analyse the emotional dimensions of lung cancer screening, with implications for screening promotion and delivery. As smokers, interviewees described feeling stigmatised, with female participants internalising and male participants resisting stigma. Guilt and fear related to lung cancer were described as screening motivators. The screening itself elicited mild positive emotions. Notably, interviewees expressed gratitude for the care implicitly shown through lung screening to smokers. More than individual risk assessment, findings suggest lung screening campaigns should prioritise emotions. Peer workers have been found to increase cancer screening uptake in marginalised communities, however the risk to confidentiality-especially for female smokers-limits its feasibility in lung cancer screening. Instead, we suggest involving peer consultants in developing targeted screening strategies that foreground emotions. Furthermore, findings suggest prioritising humanistic care in lung screening delivery. Such an approach may be especially important for smokers from low socioeconomic backgrounds, who perceive lung cancer screening and smoking as sources of stigma and face a higher risk of dying from lung cancer and lower engagement with screening.

Pathology of Tumors Associated With Pathogenic Germline Variants in 9 Breast Cancer Susceptibility Genes

Rare germline genetic variants in several genes are associated with increased breast cancer (BC) risk, but their precise contributions to different disease subtypes are unclear. This information is relevant to guidelines for gene panel testing and risk prediction. To characterize tumors associated with BC susceptibility genes in large-scale population- or hospital-based studies. The multicenter, international case-control analysis of the BRIDGES study included 42 680 patients and 46 387 control participants, comprising women aged 18 to 79 years who were sampled independently of family history from 38 studies. Studies were conducted between 1991 and 2016. Sequencing and analysis took place between 2016 and 2021. Protein-truncating variants and likely pathogenic missense variants in ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, RAD51D, and TP53. The intrinsic-like BC subtypes as defined by estrogen receptor, progesterone receptor, and ERBB2 (formerly known as HER2) status, and tumor grade; morphology; size; stage; lymph node involvement; subtype-specific odds ratios (ORs) for carrying protein-truncating variants and pathogenic missense variants in the 9 BC susceptibility genes. The mean (SD) ages at interview (control participants) and diagnosis (cases) were 55.1 (11.9) and 55.8 (10.6) years, respectively; all participants were of European or East Asian ethnicity. There was substantial heterogeneity in the distribution of intrinsic subtypes by gene. RAD51C, RAD51D, and BARD1 variants were associated mainly with triple-negative disease (OR, 6.19 [95% CI, 3.17-12.12]; OR, 6.19 [95% CI, 2.99-12.79]; and OR, 10.05 [95% CI, 5.27-19.19], respectively). CHEK2 variants were associated with all subtypes (with ORs ranging from 2.21-3.17) except for triple-negative disease. For ATM variants, the association was strongest for the hormone receptor (HR)+ERBB2- high-grade subtype (OR, 4.99; 95% CI, 3.68-6.76). BRCA1 was associated with increased risk of all subtypes, but the ORs varied widely, being highest for triple-negative disease (OR, 55.32; 95% CI, 40.51-75.55). BRCA2 and PALB2 variants were also associated with triple-negative disease. TP53 variants were most strongly associated with HR+ERBB2+ and HR-ERBB2+ subtypes. Tumors occurring in pathogenic variant carriers were of higher grade. For most genes and subtypes, a decline in ORs was observed with increasing age. Together, the 9 genes were associated with 27.3% of all triple-negative tumors in women 40 years or younger. The results of this case-control study suggest that variants in the 9 BC risk genes differ substantially in their associated pathology but are generally associated with triple-negative and/or high-grade disease. Knowing the age and tumor subtype distributions associated with individual BC genes can potentially aid guidelines for gene panel testing, risk prediction, and variant classification and guide targeted screening strategies.

Age cohort screening for hepatocellular carcinoma in an African population

Background: Hepatocellular carcinoma (HCC) is a disease of global and public health significance. In Africa, HCC is the fourth most common cancer and sub-Saharan Africa is a hotbed for HCC due to high prevalence of hepatitis B (HBV) and hepatitis C (HCV) virus infections. The late presentation in African patients has been well documented with attendant bad prognosis. We undertook this study to determine if there is an age-related clustering of HCC based on etiology. Methods: This was a retrospective hospital-based study from records of 425 adult patients (18 years and above) with triphasic computed tomography confirmed HCC at the Jos university teaching hospital, Jos, Nigeria. Relevant data were extracted from the database into an Excel spreadsheet with subsequent analysis based on age and risk factors of HCC. Results: Of 425 patients included in this study, 323 (76%) were male. The overall mean (± standard deviation) age for the studied population was 48.8 ± 14.6 years: 48.8 + 14.5 years for females and 48.9 + 14.6 years for males. 44.7% had HBV and 28% had HCV. There was a significant difference in the mean age of those with HBV as against HCV (43.0 ± 12.5 years vs. 54.3 ± 14.2 years; P < 0.001). Among those who had HCV as a risk factor for HCC, the majority (31.9%) were in the age group of 51–60 years while most of those with HBV (32.1%) were in the 31–40 years of age group. Conclusion: In this African cohort, HBV-related HCC presented a decade earlier than HCV-related HCC. Targeted screening strategies for HCC may take this into account.

Healthcare Voucher Scheme for Screening of Cardiovascular Risk Factors: A Population-Based Study.

The present study aimed to evaluate the factors associated with unwillingness to join a healthcare voucher scheme for screening of cardiovascular risk factors in a Chinese population. We conducted a telephone survey by random selection of 1200 subjects who were aged 45 years or above in Hong Kong. We collected data on their attitude, perception, and perceived feasibility of a healthcare voucher scheme. The overall rates of having received at least one type, two types, and all three types of screening tests are 81.1%, 80.7%, and 79.3%, respectively. Younger individuals (aOR = 0.338, p = 0.004), those of a higher educational level (aOR = 1.825, p = 0.006), being employed (aOR = 3.030, p = 0.037), and lower perception of screening as beneficial (aOR = 0.495, p < 0.001) were significantly associated with no regular screening for at least one medical condition. The overall rate of willingness to join the voucher scheme (among those aged ≥ 45) is 83.7%. Male sex (aOR = 2.049, p = 0.010) and absence of family history of cardiovascular disease (aOR = 0.362, p = 0.002) are independent predictors of unwillingness to join. Our findings highlighted the significance of sex and family history on screening of cardiovascular factors. These constructs and independent predictors identified provide evidence-based formulation and implementation targeted screening strategies that enhance the screening rate of the three cardiovascular risk factors.

Prevalence and associated metabolic factors for thyroid nodules: a cross-sectional study in Southwest of China with more than 120 thousand populations

ObjectiveTo explore the prevalence and its associated metabolic factors of thyroid nodules (TNs) among subjects who participated in the physical examinations in Chongqing, China.MethodsThe participants from the Health Management Center of JinShan Hospital of Chongqing Medical University, between September 2015 and May 2020, were included in this study. All of the participants underwent thyroid ultrasonography, anthropometric measurements, and serum examinations. Differences in the TNs prevalence were compared with the chi-square test or Wilcoxon rang-sum test. Multivariable logistic regression analyses were used to estimate the metabolic factors associated with TNs and multiple thyroid nodules (MTNs).ResultsOf the included 121,702 participants, 41,547 had TNs, and 20,899 had MTNs, with the prevalence of 34.1 and 17.0 %, respectively. Women had a significantly higher prevalence of TNs than men (40.6 % vs. 29.8 %; χ2 = 1517.33, P < 0.001), and TNs prevalence was gradually increased with age (P for trend < 0.001). Female gender, advanced age, and metabolic factors including central obesity, hypertension, diabetes and fatty liver were positively associated with TNs; BMI, hyperlipoidemia and hyperuricemia were not independent risk factors of TNs. While female gender, advanced age, central obesity, hypertension and diabetes were independent risk factors of MTNs.ConclusionsThe prevalence of thyroid nodules was relatively high. The associated factors identified in this study could help the clinicians to detect the high-risk patients and make targeted screening strategies for the preventing of the occurrence of TNs.

Implementation of a Machine-Learning Algorithm in the Electronic Health Record for Targeted Screening for Familial Hypercholesterolemia: A Quality Improvement Study.

Implementation of a Machine-Learning Algorithm in the Electronic Health Record for Targeted Screening for Familial Hypercholesterolemia: A Quality Improvement Study.

Prevalence of Familial Plasma Cell Disorders in Patients with Multiple Myeloma

Prevalence of Familial Plasma Cell Disorders in Patients with Multiple Myeloma

Strong associations and moderate predictive value of early symptoms for SARS-CoV-2 test positivity among healthcare workers, the Netherlands, March 2020.

Healthcare workers (n = 803) with mild symptoms were tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (n = 90 positive) and asked to complete a symptom questionnaire. Anosmia, muscle ache, ocular pain, general malaise, headache, extreme tiredness and fever were associated with positivity. A predictive model based on these symptoms showed moderate discriminative value (sensitivity: 91.2%; specificity: 55.6%). While our models would not justify presumptive SARS-CoV-2 diagnosis without molecular confirmation, it can contribute to targeted screening strategies.

Using country of origin to inform targeted tuberculosis screening in asylum seekers: a modelling study of screening data in a German federal state, 2002\u20132015

BackgroundScreening programmes for tuberculosis (TB) among immigrants rarely consider the heterogeneity of risk related to migrants’ country of origin. We assess the performance of a large screening programme in asylum seekers by analysing (i) the difference in yield and numbers needed to screen (NNS) by country and WHO-reported TB burden, (ii) the possible impact of screening thresholds on sensitivity, and (iii) the value of WHO-estimated TB burden to improve the prediction accuracy of screening yield.MethodsWe combined individual data of 119,037 asylum seekers screened for TB in Germany (2002–2015) with TB estimates of the World Health Organization (WHO) (1990–2014) for their 81 countries of origin. Adjusted rate ratios (aRR) and 95% credible intervals (CrI) of the observed yield of screening were calculated in Bayesian Poisson regression models by categories of WHO-estimated TB incidence. We assessed changes in sensitivity depending on screening thresholds, used WHO TB estimates as prior information to predict TB in asylum seekers, and modelled country-specific probabilities of numbers needed to screen (NNS) conditional on different screening thresholds.ResultsThe overall yield was 82 per 100,000 and the annual yield ranged from 44.1 to 279.7 per 100,000. Country-specific yields ranged from 10 (95%- CrI: 1–47) to 683 (95%-CrI: 306–1336) per 100,000 in Iraqi and Somali asylum seekers, respectively. The observed yield was higher in asylum seekers from countries with a WHO-estimated TB incidence > 50 relative to those from countries ≤50 per 100,000 (aRR: 4.17, 95%-CrI: 2.86–6.59). Introducing a threshold in the range of a WHO-estimated TB incidence of 50 and 100 per 100,000 resulted in the lowest “loss” in sensitivity. WHO’s TB prevalence estimates improved prediction accuracy for eight of the 11 countries, and allowed modelling country-specific probabilities of NNS.ConclusionsWHO’s TB data can inform the estimation of screening yield and thus be used to improve screening efficiency in asylum seekers. This may help to develop more targeted screening strategies by reducing uncertainty in estimates of expected country-specific yield, and identify thresholds with lowest loss in sensitivity. Further modelling studies are needed which combine clinical, diagnostic and country-specific parameters.