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|Title: ||GENOMIC BIOMARKERS FOR A BINARY CLINICAL OUTCOME IN EARLY DRUG DEVELOPMENT MICROARRAY EXPERIMENTS|
|Authors: ||VAN SANDEN, Suzy|
Gohlmann, Hinrich W. H.
|Issue Date: ||2012|
|Publisher: ||TAYLOR & FRANCIS INC|
|Citation: ||JOURNAL OF BIOPHARMACEUTICAL STATISTICS, 22 (1), p. 72-92|
|Abstract: ||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.|
|Notes: ||[Van Sanden, Suzy; Shkedy, Ziv; Burzykowski, Tomasz] Univ Hasselt, Interuniv Inst Biostat & Stat Bioinformat, B-3590 Diepenbeek, Belgium. [Shkedy, Ziv; Burzykowski, Tomasz] Katholieke Univ Leuven, Louvain, Belgium. [Van Sanden, Suzy; Gohlmann, Hinrich W. H.; Talloen, Willem; Bijnens, Luc] Johnson & Johnson, PRD, Beerse, Belgium.
|ISI #: ||000302064800006|
|Type: ||Journal Contribution|
|Validation: ||ecoom, 2013|
|Appears in Collections: ||Research publications|
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