Development and validation of prognostic models of lung cancer following low-dose computed tomographic screening

Principal Investigator

Name
Fergus Imrie

Degrees
D.Phil., M.Math.

Institution
University of Cambridge

Position Title
Visiting Researcher

Email
fi249@cam.ac.uk

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-1132

Initial CDAS Request Approval
Oct 3, 2023

Title
Development and validation of prognostic models of lung cancer following low-dose computed tomographic screening

Summary
Lung cancer remains the foremost cause of death from cancer worldwide. Studies have shown that low-dose computed tomographic (LDCT) screening can reduce lung-cancer-specific mortality by around 20%. However, many individuals do not have lung cancer when screened, although they could remain at high risk of developing lung cancer. Furthermore, even for individuals with lung nodules, finding a nodule without a verified cancer by the 1-year follow up is relatively common, with studies reporting that this was the case for 23% of NLST screens. Consequently, screening at less frequent intervals than annually (e.g. biennially) may be safe for those at sufficiently low risk. This approach has several benefits, such as enhanced efficiency, lower costs, and reduced potential harms from screening. Identifying such individuals remains a challenge. The purpose of this project is to develop and validate prognostic models of lung cancer to inform follow-up screening. The project will investigate both image-based prognostic models and approaches that combine LDCT images with risk factors such as age and cumulative smoking exposure.

Aims

1. To develop and validate prognostic models of lung cancer following LDCT screening.

Collaborators

Professor Mihaela van der Schaar
Dr Thomas Callender