Predictive genetic testing for the identification of high-risk groups: a simulation study on the impact of predictive ability.

ABSTRACT:

Background

Genetic risk models could potentially be useful in identifying high-risk groups for the prevention of complex diseases. We investigated the performance of this risk stratification strategy by examining epidemiological parameters that impact the predictive ability of risk models.

Methods

We assessed sensitivity, specificity, and positive and negative predictive value for all possible risk thresholds that can define high-risk groups and investigated how these measures depend on the frequency of disease in the population, the frequency of the high-risk group, and the discriminative accuracy of the risk model, as assessed by the area under the receiver-operating characteristic curve (AUC). In a simulation study, we modeled genetic risk scores of 50 genes with equal od

SUBMITTER: Mihaescu R 

PROVIDER: S-EPMC3221548 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature