Study designs and statistical analyses for biomarker research

Sensors (Basel). 2012;12(7):8966-86. doi: 10.3390/s120708966. Epub 2012 Jun 29.


Biomarkers are becoming increasingly important for streamlining drug discovery and development. In addition, biomarkers are widely expected to be used as a tool for disease diagnosis, personalized medication, and surrogate endpoints in clinical research. In this paper, we highlight several important aspects related to study design and statistical analysis for clinical research incorporating biomarkers. We describe the typical and current study designs for exploring, detecting, and utilizing biomarkers. Furthermore, we introduce statistical issues such as confounding and multiplicity for statistical tests in biomarker research.

Keywords: biomarker adaptive design; confounding; multiplicity; predictive factor; statistical test.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Biomarkers / metabolism*
  • Humans
  • Neoplasms / diagnosis
  • Neoplasms / metabolism
  • Precision Medicine
  • Predictive Value of Tests
  • Prognosis
  • Research Design*


  • Biomarkers