Biomarker validation: Common data analysis concerns

Joe E. Ensor

Research output: Contribution to journalArticle

14 Scopus citations

Abstract

Biomarker validation, like any other confirmatory process based on statistical methodology, must discern associations that occur by chance from those reflecting true biological relationships. Validity of a biomarker is established by authenticating its correlation with clinical outcome. Validated biomarkers can lead to targeted therapy, improve clinical diagnosis, and serve as useful prognostic and predictive factors of clinical outcome. Statistical concerns such as confounding and multiplicity are common in biomarker validation studies. This article discusses four major areas of concern in the biomarker validation process and some of the proposed solutions. Because present-day statistical packages enable the researcher to address these common concerns, the purpose of this discussion is to raise awareness of these statistical issues in the hope of improving the reproducibility of validation study findings.

Original languageEnglish (US)
Pages (from-to)886-891
Number of pages6
JournalOncologist
Volume19
Issue number8
DOIs
StatePublished - 2014

Keywords

  • Biomarker
  • Confounding factors
  • Selection bias
  • Validation studies

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Fingerprint Dive into the research topics of 'Biomarker validation: Common data analysis concerns'. Together they form a unique fingerprint.

Cite this