title: Evaluating prognostic accuracy of biomarkers in nested case-control studies.
abstract: Nested case-control (NCC) design is used frequently in epidemiological studies as a cost-effective subcohort sampling strategy to conduct biomarker research. Sampling strategy, on the other hoand, creates challenges for data analysis because of outcome-dependent missingness in biomarker measurements. In this paper, we propose inverse probability weighted (IPW) methods for making inference about the prognostic accuracy of a novel biomarker for predicting future events with data from NCC studies. The consistency and asymptotic normality of these estimators are derived using the empirical process theory and convergence theorems for sequences of weakly dependent random variables. Simulation and analysis using Framingham Offspring Study data suggest that the proposed methods perform well in finite samples.
authors.affiliation: Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA.
authors.forename: Tianxi
authors.initials: T
authors.lastname: Cai
authors.forename: Yingye
authors.initials: Y
authors.lastname: Zheng
mesh_terms: D015415:Biomarkers / Q000032:analysis*; D056808:Biostatistics; D002097:C-Reactive Protein / Q000032:analysis; D002318:Cardiovascular Diseases / Q000097:blood; D016022:Case-Control Studies; D015331:Cohort Studies; D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D011336:Probability; D011379:Prognosis; D012307:Risk Factors
chemical_list: D015415:Biomarkers; D002097:C-Reactive Protein