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Open AccessJournal ArticleDOI

Evaluation of the Lung Cancer Risks at Which to Screen Ever- and Never-Smokers: Screening Rules Applied to the PLCO and NLST Cohorts

TLDR
Martin Tammemägi and colleagues evaluate which risk groups of individuals, including nonsmokers and high-risk individuals from 65 to 80 years of age, should be screened for lung cancer using computed tomography.
Abstract
BACKGROUND Lung cancer risks at which individuals should be screened with computed tomography (CT) for lung cancer are undecided. This study's objectives are to identify a risk threshold for selecting individuals for screening, to compare its efficiency with the U.S. Preventive Services Task Force (USPSTF) criteria for identifying screenees, and to determine whether never-smokers should be screened. Lung cancer risks are compared between smokers aged 55-64 and ≥ 65-80 y. METHODS AND FINDINGS Applying the PLCO(m2012) model, a model based on 6-y lung cancer incidence, we identified the risk threshold above which National Lung Screening Trial (NLST, n = 53,452) CT arm lung cancer mortality rates were consistently lower than rates in the chest X-ray (CXR) arm. We evaluated the USPSTF and PLCO(m2012) risk criteria in intervention arm (CXR) smokers (n = 37,327) of the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO). The numbers of smokers selected for screening, and the sensitivities, specificities, and positive predictive values (PPVs) for identifying lung cancers were assessed. A modified model (PLCOall2014) evaluated risks in never-smokers. At PLCO(m2012) risk ≥ 0.0151, the 65th percentile of risk, the NLST CT arm mortality rates are consistently below the CXR arm's rates. The number needed to screen to prevent one lung cancer death in the 65th to 100th percentile risk group is 255 (95% CI 143 to 1,184), and in the 30th to 15 y, 8.5% had PLCO(m2012) risk ≥ 0.0151. None of 65,711 PLCO never-smokers had PLCO(m2012) risk ≥ 0.0151. Risks and lung cancers were significantly greater in PLCO smokers aged ≥ 65-80 y than in those aged 55-64 y. This study omitted cost-effectiveness analysis. CONCLUSIONS The USPSTF criteria for CT screening include some low-risk individuals and exclude some high-risk individuals. Use of the PLCO(m2012) risk ≥ 0.0151 criterion can improve screening efficiency. Currently, never-smokers should not be screened. Smokers aged ≥ 65-80 y are a high-risk group who may benefit from screening. Please see later in the article for the Editors' Summary.

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Journal ArticleDOI

Progress and prospects of early detection in lung cancer

TL;DR: Despite significant developments in the oncological management of late stage lung cancer over recent years, survival remains poor and the UK Office for National Statistics reported that patients diagnosed with distant metastatic disease had a 1-year survival rate of just 15–19% compared with 81–85% for stage I.
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Lung Cancer Screening, Version 3.2018, NCCN Clinical Practice Guidelines in Oncology.

TL;DR: This manuscript focuses on identifying patients at high risk for lung cancer who are candidates for low-dose computed tomography of the chest and on evaluating initial screening findings.
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Cancer Progress and Priorities: Lung Cancer

TL;DR: In the United States, lung cancer is the second most common diagnosed cancer and the leading cause of cancer-related death and the major risk factor is tobacco smoking.
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Screening for Lung Cancer: CHEST Guideline and Expert Panel Report

TL;DR: The updated evidence base is used to provide recommendations where the evidence allows, and statements based on experience and expert consensus where it does not, and to optimize the approach to low‐dose CT screening.
Journal ArticleDOI

Development and Validation of Risk Models to Select Ever-Smokers for CT Lung Cancer Screening

TL;DR: Application of a risk-based model for CT screening for lung cancer compared with a model based on USPSTF recommendations was estimated to be associated with a greater number of lung cancer deaths prevented over 5 years, along with a lower NNS to prevent 1 lung cancer death.
References
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Density estimation for statistics and data analysis

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Reduced lung-cancer mortality with low-dose computed tomographic screening.

TL;DR: Screening with the use of low-dose CT reduces mortality from lung cancer, as compared with the radiography group, and the rate of death from any cause was reduced.
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Regression modeling strategies : with applications to linear models, logistic regression, and survival analysis

TL;DR: In this article, the authors present a case study in least squares fitting and interpretation of a linear model, where they use nonparametric transformations of X and Y to fit a linear regression model.
Journal ArticleDOI

Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis

TL;DR: The basic Bayesian framework must be constrained, use of the step function in computing the probability that a team would rank best or worst in a league, and implementation of a Dirichlet process prior are presented.
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