The Youden index and the optimal cut-point corrected for measurement error

Neil J. Perkins, Enrique F. Schisterman

Research output: Contribution to journalArticlepeer-review

124 Scopus citations


Random measurement error can attenuate a biomarker's ability to discriminate between diseased and non-diseased populations. A global measure of biomarker effectiveness is the Youden index, the maximum difference between sensitivity, the probability of correctly classifying diseased individuals, and 1-specificity, the probability of incorrectly classifying health individuals. We present an approach for estimating the Youden index and associated optimal cut-point for a normally distributed biomarker that corrects for normally distributed random measurement error. We also provide confidence intervals for these corrected estimates using the delta method and coverage probability through simulation over a variety of situations. Applying these techniques to the biomarker thiobarbituric acid reaction substance (TBARS), a measure of sub-products of lipid peroxidation that has been proposed as a discriminating measurement for cardiovascular disease, yields a 50% increase in diagnostic effectiveness at the optimal cut-point. This result may lead to biomarkers that were once naively considered ineffective becoming useful diagnostic devices.

Original languageEnglish (US)
Pages (from-to)428-441
Number of pages14
JournalBiometrical Journal
Issue number4
StatePublished - Aug 2005
Externally publishedYes


  • Measurement error
  • Optimal cut-point
  • ROC curve
  • Sensitivity and specificity
  • Youden index

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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