Determining cut-points for Alzheimer's disease biomarkers: statistical issues, methods and challenges

Jonathan W Bartlett, Chris Frost, Niklas Mattsson, Tobias Skillbäck, Kaj Blennow, Henrik Zetterberg, Jonathan M Schott

Research output: Contribution to journalReview articlepeer-review

42 Citations (SciVal)


New proposed criteria for the clinical diagnosis of Alzheimer's disease increasingly incorporate biomarkers, most of which are normally measured on a continuous scale. Operationalizing such criteria thus requires continuous biomarkers to be dichotomized, which in turns requires the selection of a cut-point at which to dichotomize. In this article, we review the statistical principles underlying the choice of cut-points, describe some of the most commonly adopted statistical approaches used to estimate cut-points, highlight potential pitfalls in some of the approaches and characterize in what sense the estimated cut-point from each approach is optimal. We also emphasize that how a cut-point is selected must be made in reference to how the resulting dichotomized biomarker is to be used, and in particular what actions will follow from a positive or negative test result.

Original languageEnglish
Pages (from-to)391-400
Number of pages10
JournalBiomarkers in Medicine
Issue number4
Early online date23 Aug 2012
Publication statusPublished - Aug 2012


  • Alzheimer Disease/diagnosis
  • Amyloid beta-Peptides/cerebrospinal fluid
  • Biomarkers/cerebrospinal fluid
  • Humans
  • Likelihood Functions
  • Magnetic Resonance Imaging
  • Peptide Fragments/cerebrospinal fluid
  • Positron-Emission Tomography
  • ROC Curve
  • Uncertainty


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