Evaluating prognostic accuracy of biomarkers in nested case-control studies

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...

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Bibliographic Details
Published in:Biostatistics (Oxford, England) England), 2012-01, Vol.13 (1), p.89-100
Main Authors: Cai, Tianxi, Zheng, Yingye
Format: Article
Language:English
Subjects:
Accuracy
Biomarkers
Biomarkers - analysis
Biostatistics
C-Reactive Protein - analysis
Cardiovascular Diseases - blood
Case-Control Studies
Cohort Studies
Convergence
Data Interpretation, Statistical
Epidemiology
Humans
Models, Statistical
Probability
Prognosis
Risk Factors
Simulation
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Summary: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.
ISSN:1465-4644
1468-4357
DOI:10.1093/biostatistics/kxr021