Evaluating prognostic accuracy of biomarkers in nested case-control studies

Biostatistics. 2012 Jan;13(1):89-100. doi: 10.1093/biostatistics/kxr021. Epub 2011 Aug 19.

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.

Publication types

  • Evaluation Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers / analysis*
  • Biostatistics
  • C-Reactive Protein / analysis
  • Cardiovascular Diseases / blood
  • Case-Control Studies
  • Cohort Studies
  • Data Interpretation, Statistical
  • Humans
  • Models, Statistical
  • Probability
  • Prognosis
  • Risk Factors

Substances

  • Biomarkers
  • C-Reactive Protein