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Identifying high-risk individuals for lung cancer screening: Going beyond NLST criteria.

ABSTRACT: There are two main types of strategies to identify target population for lung cancer screening: 1) strategies based on age and cumulative smoking criteria, 2) risk prediction models allowing the calculation of an individual risk. The objective of this study was to compare different strategies to identify the proportion of the Spanish population at high risk of developing lung cancer, susceptible to be included in a lung cancer screening programme.Cross-sectional study. We used the data of the Spanish National Interview Health Survey (ENSE) of 2011-2012 (21,006 individuals) to estimate the proportion of participants at high risk of developing lung cancer. This estimation was performed using the U.S. national lung screening trial (NLST) criteria and a 6-year prediction model (PLCOm2012), both independently and in combination.The prevalence of individuals at high risk of developing lung cancer according to the NLST criteria was 4.9% (7.9% for men, 2.4% for women). Among the 1,034 subjects who met the NLST criteria, 533 (427 men and 106 women) had a 6-year lung cancer risk ?2.0%. The combination of these two selection strategies showed that 2.5% of the Spanish population had a high risk of developing lung cancer. However, this selection process did not take into account different groups of subjects <75 years old having an individual risk of lung cancer ?2%, such as heavy smokers <55 years old who were long-time former smokers, and ever-smokers having smoked <30 pack-years with other risk factors.Further research is needed to determine which selection strategy achieves a higher benefit/harm ratio and to assess other prevention strategies for individuals with elevated risk for lung cancer but who do not meet the screening eligibility criteria.

SUBMITTER: Fu M

PROVIDER: S-EPMC5886563 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Identifying high-risk individuals for lung cancer screening: Going beyond NLST criteria.

Fu Marcela M Travier Noémie N Martín-Sánchez Juan Carlos JC Martínez-Sánchez Jose M JM Vidal Carmen C Garcia Montse M

PloS one 20180405 4

<h4>Background</h4>There are two main types of strategies to identify target population for lung cancer screening: 1) strategies based on age and cumulative smoking criteria, 2) risk prediction models allowing the calculation of an individual risk. The objective of this study was to compare different strategies to identify the proportion of the Spanish population at high risk of developing lung cancer, susceptible to be included in a lung cancer screening programme.<h4>Methods</h4>Cross-sectiona ...[more]

PMID: 29621354

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

Project description:BackgroundAltered right ventricular structure is an important feature of Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC), but is challenging to quantify objectively. The aim of this study was to go beyond ventricular volumes and diameters and to explore if the shape of the right and left ventricles could be assessed and related to clinical measures. We used quantifiable computational methods to automatically identify and analyse malformations in ARVC patients from Cardiovascular Magnetic Resonance (CMR) images. Furthermore, we investigated how automatically extracted structural features were related to arrhythmic events.MethodsA retrospective cross-sectional feasibility study was performed on CMR short axis cine images of 27 ARVC patients and 21 ageing asymptomatic control subjects. All images were segmented at the end-diastolic (ED) and end-systolic (ES) phases of the cardiac cycle to create three-dimensional (3D) bi-ventricle shape models for each subject. The most common components to single- and bi-ventricular shape in the ARVC population were identified and compared to those obtained from the control group. The correlations were calculated between identified ARVC shapes and parameters from the 2010 Task Force Criteria, in addition to clinical outcomes such as ventricular arrhythmias.ResultsBi-ventricle shape for the ARVC population showed, as ordered by prevalence with the percent of total variance in the population explained by each shape: global dilation/shrinking of both ventricles (44 %), elongation/shortening at the right ventricle (RV) outflow tract (15 %), tilting at the septum (10 %), shortening/lengthening of both ventricles (7 %), and bulging/shortening at both the RV inflow and outflow (5 %). Bi-ventricle shapes were significantly correlated to several clinical diagnostic parameters and outcomes, including (but not limited to) correlations between global dilation and electrocardiography (ECG) major criteria (p = 0.002), and base-to-apex lengthening and history of arrhythmias (p = 0.003). Classification of ARVC vs. control using shape modes yielded high sensitivity (96 %) and moderate specificity (81 %).ConclusionWe presented for the first time an automatic method for quantifying and analysing ventricular shapes in ARVC patients from CMR images. Specific ventricular shape features were highly correlated with diagnostic indices in ARVC patients and yielded high classification sensitivity. Ventricular shape analysis may be a novel approach to classify ARVC disease, and may be used in diagnosis and in risk stratification for ventricular arrhythmias.

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Identifying high-risk individuals for lung cancer screening: Going beyond NLST criteria.

Publications

Identifying high-risk individuals for lung cancer screening: Going beyond NLST criteria.

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