Endometrial Cancer Risk Modelling

Current screening strategies for endometrial cancer (EC) are effective, but they are not feasible or cost-effective to provide to everyone in the general population. Targeting those at higher risk for EC and its precursors in the general population is a promising way of providing screening and prevention strategies to those who need it. Given that over 40% of EC cases are due to modifiable risk factors, predictive risk models are one method that can be used to target high risk individuals in a general population and direct them to appropriate screening methods.

We are using the Canadian Partnership for Tomorrow’s Health (CanPath) cohort to validate pre-existing models in a Canadian population across British Columbia, Alberta, and Ontario. We will assess our models’ abilities to predict cases by comparing our predicted risk scores to the actual number of individuals in the dataset that were diagnosed with EC or its precursors. This information will be obtained by linking the CanPath dataset to administrative datasets, which we are in the process of ascertaining. This will be the first validated EC risk model in a Canadian cohort.