Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/13629
Title: GENOMIC BIOMARKERS FOR A BINARY CLINICAL OUTCOME IN EARLY DRUG DEVELOPMENT MICROARRAY EXPERIMENTS
Authors: VAN SANDEN, Suzy 
SHKEDY, Ziv 
BURZYKOWSKI, Tomasz 
Gohlmann, Hinrich W. H.
TALLOEN, Willem 
BIJNENS, Luc 
Issue Date: 2012
Publisher: TAYLOR & FRANCIS INC
Source: 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. svsande1@its.jnj.com
Keywords: Pharmacology & Pharmacy; Statistics & Probability; Biomarkers; BW ratio; Categorical data; Joint Modeling; Microarrays;Biomarkers; BW ratio; Categorical data; Joint modeling; Microarrays
Document URI: http://hdl.handle.net/1942/13629
ISSN: 1054-3406
e-ISSN: 1520-5711
DOI: 10.1080/10543406.2010.504906
ISI #: 000302064800006
Category: A1
Type: Journal Contribution
Validations: ecoom 2013
Appears in Collections:Research publications

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