Correction of phenotype misclassification based on high-discrimination genetic predictive risk models.

ABSTRACT: Misclassification of phenotype status can seriously affect accuracy in association studies, including studies of genetic risk factors. A common problem is the classification of participants as nondiseased because of insufficient diagnostic workup or because participants have not been followed up long enough to develop disease. Some validated predictive models may have high discrimination in predicting disease. We suggest that information from such models can be used to predict the risk that a nondiseased participant will eventually develop disease and to recode the status of participants predicted to be at highest risk. We evaluate conditions under which recoding results in a maximal net improvement in the accuracy of phenotype classification. Net improvement is expected only when the posi

SUBMITTER: Ioannidis JP 

PROVIDER: S-EPMC12124723 | biostudies-literature | 2012 Nov

REPOSITORIES: biostudies-literature