Evaluating classification performance of biomarkers in two-phase case-control studies.

ABSTRACT: Biomarkers are playing an increasingly important role in disease screening, early detection, and risk prediction. The two-phase case-control sampling study design is widely used for the evaluation of candidate biomarkers. The sampling probabilities for cases and controls in the second phase can often depend on other covariates (sampling strata). This biased sampling can lead to invalid inference on a biomarker's classification accuracy if not properly accounted for. In this paper, we adopt the idea of inverse probability weighting and develop inverse probability weighting-based estimators for various measures of a biomarker's classification performance, including the points on the receiver operating characteristics (ROCs) curve, the area under the ROC curve (area under the curve), and the

SUBMITTER: Wang L 

PROVIDER: S-EPMC6317859 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature