Comparative optimism in models involving both classical clinical and gene expression information

Background: In cancer research, most clinical variables have already been investigated and are now well established. The use of transcriptomic variables has raised two problems: restricting their number and validating their significance. Thus, their contribution to prognosis is currently thought to be overestimated. The aim of this study was to determine to what extent optimism concerning current transcriptomic models may lead to overestimation of the contribution of transcriptomic variables to survival prognosis. Results: To achieve this goal, Cox proportional hazards models that adjust for clinical and transcriptomic variables were built. As the relevance of the clinical variables had already been established, they were not submitted to selection. As for genes, they were selected using both univariate and multivariate methods. Optimism and the contribution of clinical and transcriptomic variables to prognosis were compared through simulations and by using the Kent and O'Quigley...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Caroline Truntzer, Delphine Maucort-Boulch, Pascal Roy
• Keywords: BMCBI 2008, Clinical Variables, Current Transcriptomic Models, Transcriptomic Variables