Journal of thoracic imaging
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Lung cancer is the leading cause of cancer-related death worldwide. In 2011, the largest lung cancer screening trial worldwide, the US National Lung Screening Trial, published a 20% decrease in lung cancer-specific mortality in the computed tomography (CT)-screened group, compared with the group screened by chest x-ray. On the basis of this trial, different US guidelines recently have recommended CT lung cancer screening. ⋯ In Europe, several lung cancer screening trials are ongoing. It is planned to pool the results of the lung cancer screening trials in European randomized lung cancer CT screening (EUCT). By pooling of the data, EUCT hopes to be able to provide additional information for the discussion of some important issues regarding the implementation of lung cancer screening by low-dose CT, including: the determination of the optimal screen population, the comparison between a volume-based and diameter-based nodule management protocol, and the determination of optimal screen intervals.
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The National Lung Screening Trial (NLST) demonstrated that screening with low-dose CT versus chest radiography reduced lung cancer mortality by 16% to 20%. More recently, a cost-effectiveness analysis (CEA) of CT screening for lung cancer versus no screening in the NLST was performed. ⋯ In this paper, I review the methods and assumptions used to obtain the base case estimate of $81,000 per quality-adjusted life-year gained. In addition, I show how this estimate varied widely among different subsets and when some of the base case assumptions were changed and speculate on the cost-effectiveness of CT screening for lung cancer outside the NLST.
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Pulmonary nodules are commonly detected in computed tomography (CT) chest screening of a high-risk population. The specific visual or quantitative features on CT or other modalities can be used to characterize the likelihood that a nodule is benign or malignant. Visual features on CT such as size, attenuation, location, morphology, edge characteristics, and other distinctive "signs" can be highly suggestive of a specific diagnosis and, in general, be used to determine the probability that a specific nodule is benign or malignant. ⋯ Imaging analytics can objectively and reproducibly quantify nodule features on CT, nuclear medicine, and magnetic resonance imaging. Some quantitative techniques show great promise in helping to differentiate benign from malignant lesions or to stratify the risk of aggressive versus indolent neoplasm. In this article, we (1) summarize the visual characteristics, descriptors, and signs that may be helpful in management of nodules identified on screening CT, (2) discuss current quantitative and multimodality techniques that aid in the differentiation of nodules, and (3) highlight the power, pitfalls, and limitations of these various techniques.
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Globally, lung cancer is the leading cause of cancer death and is a major public health problem. Because lung cancer is usually diagnosed at an advanced stage, survival is generally poor. In recent decades, clinical advances have not led to marked improvements in outcomes. ⋯ Compared with NLST/USPSTF criteria, selection of individuals for screening using high-quality risk models should lead to fewer individuals being screened, more cancers being detected, and fewer false positives. More lives will be saved with greater cost-effectiveness. In this paper, we review methodological background for prediction modeling, existing lung cancer risk prediction models and some of their findings, and current issues in lung cancer risk prediction modeling and discuss future research.