Stratified Cost-Effectiveness Analysis To Guide Genetic Screening For Cancer Risk.

ƒ In each study, we used a simulation model to identify a subpopulation based on age and clinical risk, for whom we used genetic testing to find intensified prevention measures, which was optimally costeffective. ƒ As more genetic tests become available, this method can be used to identify screening strategies that maximize cost-effectiveness. ƒ We develop a framework for stratified costeffectiveness analysis using individual-based discrete-event simulations that allow for the representation of heterogeneous patient populations, and which can be used to evaluate the cost-effectiveness of genetic testing in different patient groups.