Study Designs and statistical analyses for biomarker research

Masahiko Gosho, Kengo Nagashima, Yasunori Sato

Research output: Contribution to journalReview articlepeer-review

64 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)8966-8986
Number of pages21
JournalSensors (Switzerland)
Issue number7
Publication statusPublished - 2012 Jul
Externally publishedYes


  • Biomarker adaptive design
  • Confounding
  • Multiplicity
  • Predictive factor
  • Statistical test

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering


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