Prediction models for CVD prevention

Project Summary

While cardiovascular disease (CVD) remains the leading cause of death globally, over 50% of new cases are potentially preventable. Worldwide, practice guidelines recommend using prediction models to identify individuals most likely to benefit from preventative therapies. These models use demographic and clinical factors to predict the long‐term risk of developing CVD. Since 2012, Canadian guidelines have recommended using the Framingham Risk Score, despite a lack of Canadian‐based validation studies to determine its accuracy for long‐term predictions. Furthermore, in the last decade, new models have been developed in Canada, Europe, and the United States that may have better accuracy than the Framingham Risk Score. Accordingly, it is unclear which prediction model is best suited for primary prevention in Canada.

The objectives of this project include:

To determine the association between sociodemographic and clinical factors with the long-term risk of developing CVD in Ontario, Canada.

To develop new and validate existing risk prediction models for long-term CVD in Ontario, Canada.

To test the impact of guideline decision-making using models from objective 2 in Ontario, Canada.