Genomic biomarkers for a binary clinical outcome in early drug development microarray experiments

J Biopharm Stat. 2012;22(1):72-92. doi: 10.1080/10543406.2010.504906.


In this article, we discuss methods to select three different types of genes (treatment related, response related, or both) and investigate whether they can serve as biomarkers for a binary outcome variable. We consider an extension of the joint model introduced by Lin et al. (2010) and Tilahun et al. (2010) for a continuous response. As the model has certain drawbacks in a binary setting, we also present a way to use classical selection methods to identify subgroups of genes, which are treatment and/or response related. We evaluate their potential to serve as biomarkers by applying DLDA to predict the response level.

Publication types

  • Comparative Study

MeSH terms

  • Animals
  • Biomarkers
  • Drug Discovery / methods*
  • Genetic Markers / genetics*
  • Genomics / methods*
  • Humans
  • Oligonucleotide Array Sequence Analysis / methods*
  • Time Factors
  • Treatment Outcome


  • Biomarkers
  • Genetic Markers