Improving Lung Cancer Risk Prediction & Application

Principal Investigator: Martin Tammemagi

Affiliation: Brock University

Start Year: 2021

Lung cancer is the leading cause of cancer death in Canada and the World. Lung screening with computed tomography (CT) can identify lung cancers early, when they are still treatable, and can significantly reduce lung cancer deaths. Lung cancer screening works best when applied to high-risk individuals. The best way to identify high-risk individuals is by applying accurate lung cancer risk prediction models to estimate risk. One of the most widely validated and used models is the PLCOm2012 model. We plan to use CanPath and CANUE data to improvePLCOm2012 risk prediction and make it more appropriate for application in the Canadian population by answering the following: Can adding (1) outdoor air pollution or lung cancer associated (2) occupational exposures improve risk prediction? Can we produce a model that will accurately predict lung cancer in (3) never smokers? We plan to produce and evaluate mathematical models including relevant CanPath and CANUE data to answer these questions, and successful results should lead to improving selection of individuals for screening and reduce lung cancer deaths.