Lung Cancer Risk and Life-Expectancy-Based Models for Lung Cancer Screening Selection

Abstract

Lung cancer is the leading cause of death globally. There have been subsequently several lung cancer screening trials that have shown early detection can significantly improve lung cancer outcomes. However, screening everyone would be costly and unnecessary for certain individuals. Lung cancer screening through low dose computed tomography scans also exposes people to radiation and can lead to high rates of false positives. Lung cancer risk- models can reduce the number needed to screen, improve cancer detection rates and offer a more targeted screening approach. However, these models may preferentially select individuals who are not likely to benefit from screening, such as those who are older and have more comorbidities. A US life expectancy model was recently created to maximize screening efficiency by predicting the number of life years to be gained if they were screened for lung cancer.
In my presentation, I will briefly discuss the economic evidence for lung cancer screening. I will explain my research project that applied the life expectancy model and a risk model to a Canadian sample. I will present the results of my analysis of the selected subgroup of individuals with a low life expectancy and low risk for lung cancer. An analysis of this subgroup’s demographics, short term outcomes, as well as lung cancer incidence was also conducted. Finally, I will end with a discussion on how these results may improve the lung cancer screening programs in the future.