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American Journal of Epidemiology Advance Access originally published online on May 13, 2008
American Journal of Epidemiology 2008 168(1):89-97; doi:10.1093/aje/kwn099
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American Journal of Epidemiology © The Author 2008. Published by the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

PRACTICE OF EPIDEMIOLOGY

Adjusting for Covariates in Studies of Diagnostic, Screening, or Prognostic Markers: An Old Concept in a New Setting

Holly Janes1 and Margaret S. Pepe1,2

1 Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
2 Department of Biostatistics, University of Washington, Seattle, WA

Correspondence to Dr. Holly Janes, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, M2-C200, Seattle, WA 98109 (e-mail: hjanes{at}scharp.org)

Received for publication May 4, 2007. Accepted for publication March 21, 2008.

The concept of covariate adjustment is well established in therapeutic and etiologic studies. However, it has received little attention in the growing area of medical research devoted to the development of markers for disease diagnosis, screening, or prognosis, where classification accuracy, rather than association, is of primary interest. In this paper, the authors demonstrate the need for covariate adjustment in studies of classification accuracy, discuss methods for adjusting for covariates, and distinguish covariate adjustment from several other related, but fundamentally different, uses for covariates. They draw analogies and contrasts throughout with studies of association.

covariance adjustment; ROC curve; sensitivity; specificity

Abbreviations: AROC, covariate-adjusted ROC curve; PSA, prostate-specific antigen; ROC, receiver operating characteristic


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