Reshad Hassannezhad

Undergraduate

Tabriz University of Medical Sciences

Student

NLST (Learn more about this study)

NLST-210

Apr 13, 2016

Positive Predictive Value (PPV) trends of lung screening with Low Dose Computed Tomography (LDCT) in next rounds and a prediction model of nodules with higher probability of being true positive

Lung cancer is the leading cause of cancer-related death in United States. The National Lung Screening Trial (NLST) was a powerful trial to compare effectiveness of screening with Low Dose Computed Tomography (LDCT) with that of Chest X-Ray (CXR) in high risk population. The primary results of NLST showed 20 percent and 6.7 percent reduction in lung cancer deaths and overall mortality in LDCT arm, respectively. Mainly based on NLST results and some other published data in literature, many organizations in US started recommending screening for lung cancer in high risk population. Among them is US Prevent Services Task Force (USPSTF), which in 2013 recommended annual screening for lung cancer with LDCT in adults aged 55 to 80 years who have a 30 pack-year smoking history and currently smoke or have quit within the past 15 years. However, several studies have mentioned that implementation of screening with LDCT nationwide, faces with several major drawbacks; among them maybe the most important one is the costs.
One strategy to lower the expenses is to increase the predictive value of screening with LDCT; since each individual with a positive result should be followed up and more diagnostic procedures will be needed to determine whether it was a true positive or not. Some studies have suggested that Positive Predictive Value (PPV) of screening with LDCT has relation with the screening implementation program(1).
The goal of this study, however, is not to include analyses related to costs. In this study, we aim to assess the correlation between PPV and predictors like nodule size, location of tumor, margin characters (speculated, poorly defined, intermittent), density attenuation(soft tissue, ground glass, mixed, fluid), tumor stage, tumor type, and also we will assess the impact of choosing 4 mm cutoff on PPV. First, based on these data, we will build a prediction model of nodules with higher probability of being true positive. This is important, since it can help clinicians when interpreting the images. Second, we will use a statistical approach to predict how PPV will change in next rounds.
References
1. McMahon PM, Kong CY, Weinstein MC, Tramontano AC, Cipriano LE, Johnson BE, et al. Adopting helical CT screening for lung cancer: potential health consequences during a 15-year period. Cancer. 2008;113(12):3440-9.