A systematic review on the application of cardiovascular risk prediction models in pharmacoeconomics,with a focus on primary prevention

Background: Long-term trials on the effectiveness of pharmacological treatment for primary cardiovascular disease prevention are scant. For that reason risk prediction models are used as a tool to project changes in cardiovascular disease incidence due to changes in risk factor levels observed in short-term randomized clinical trials. In this article, we summarize the literature on the application of these risk models in pharmacoeconomic studies for primary cardiovascular disease prevention interventions in high-income countries.

Methods and results: We systematically reviewed the available literature on the application of cardiovascular disease risk models in pharmacoeconomic studies and assessed the quality of incorporation of risk models in these studies. Quality assessment indicated the distance between the characteristics of populations of the risk model and the studies reviewed, the frequent disagreement between risk model and study time horizons and the lack of proper consideration of the uncertainty surrounding risk predictions.

Conclusion: Given that utilizing a risk model to project the effect of a pharmacological intervention to cardiovascular events provides an estimate of the intervention's clinical and economical impact, consideration should be paid to the agreement between the study and risk model populations as well as the level of uncertainty that these predictions add to the outcome of a decision-analytic model. In the absence of hard endpoint trials, the value of risk models to model pharmacological efficacy in primary cardiovascular disease prevention remains high, although their limitations should be acknowledged.