Grant: Project Grant

Goal: To improve Canadian lung cancer (LC) screening efficiency by exploiting predictive information on the screening CT scan. Background: LC is the leading cause of cancer death in Canada. CT screening lowers LC mortality but is associated with false-positive screens, unnecessary procedure-related complications, radiation exposure and healthcare costs. LC screening efficiency is related to the risk of LC in the population screened, and LC screening programs rely on a baseline LC risk calculator to determine eligibility. We believe LC efficiency can be improved greatly by incorporating information contained within the baseline CT scan. The airway tree is our first line of defence against cigarette smoke and is the main site of LC. Variation in airway tree caliber is common in the general population and this variation is strongly associated with higher risk of LC death among smokers (5.31-fold higher LC death rate)! Whether this airway tree risk classifier can improve LC risk prediction in the LC screening setting is uncertain, as is the potential for the airway tree risk classifier to improve screening efficiency when applied in Canadian LC screening setting. Aim 1: To quantify the improvement in LC risk prediction when incorporating a baseline CT airway tree risk classifier. Aim 2: Perform a cost-effectiveness analysis to determine whether incorporating the baseline CT airway tree risk classifier improves LC screening efficiency in Canada. Methods: We will use trial data to evaluate LC risk prediction, and supplement these data with 'real-world' Canadian screening data for cost-effectiveness analyses. Expertise: Our team brings proven expertise in epidemiology, lung cancer, CT imaging and health economics. Expected Outcomes: This study will provide pivotal evidence that a baseline CT airway tree risk classifier can improve LC screening efficiency in Canada, including decision modelling estimates to inform subsequent economic analyses and guide policy makers.