Related Experiment Video
Updated: Nov 12, 2025

Using Micro-computed Tomography for the Assessment of Tumor Development and Follow-up of Response to Treatment in a Mouse Model of Lung Cancer
Published on: May 20, 2016
Low-dose CT lung cancer screening uptake: A rural-urban comparison
Anja Zgodic1,2, Whitney E Zahnd2, Shailesh Advani3,4
1Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.
Purpose:
The US Preventive Services Task Force recommends lung cancer screening with Low-Dose Computed Tomography (LDCT) in high-risk individuals. Our objective was to identify demographic, health, and financial factors associated with screening uptake, with a focus on urban-rural differences.
Methods:
We analyzed data from the 2018 and 2019 Behavioral Risk Factor Surveillance System and its optional Lung Cancer Screening Module to examine factors associated with screening uptake among 20 states that administered the optional module. We compared differences in factors associated with uptake overall and by geographical regions and conducted multivariable logistic mixed-effects regression, accounting for participant clustering by state to assess the impact of these factors on uptake.
Findings:
Overall 1,268 participants underwent LDCT screening with no significant differences observed between rural (16.3%) and urban residents (17.7%, p = 0.67). In multivariable models, rural residents did not differ significantly in their LDCT screening uptake (OR = 0.85; 95% CI: 0.67-1.09, p = 0.20), but uptake was significantly higher for participants with underlying chronic respiratory conditions, veterans, those with higher pack-year history, and those with poor/fair general health and prior history of cancer. Uptake declined with age, higher education level, concerns about paying for medical care, and lack of primary care.
Conclusions:
Modifiable targets can be leveraged to increase LDCT screening. Based on significant predictors of screening uptake, clinicians should prioritize interventions that effectively consider smoking history as well as those identified as effective in veterans' health settings. Additionally, reducing structural barriers to care related to insurance and income will be key to reducing disparities.
More Related Videos
08:05Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
Published on: December 19, 2020
06:51Utilizing 18F-FDG PET/CT Imaging and Quantitative Histology to Measure Dynamic Changes in the Glucose Metabolism in Mouse Models of Lung Cancer
Published on: July 21, 2018