Survival prediction using gene expression: a review and comparison

W.N. van Wieringen; D. Kun; R. Hampel; A.-L. Boulesteix

doi:10.1016/j.csda.2008.05.021

Survival prediction using gene expression: a review and comparison

W.N. van Wieringen, D. Kun, R. Hampel, A.-L. Boulesteix

Mathematics

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Abstract

Knowledge of transcription of the human genome might greatly enhance our understanding of cancer. In particular, gene expression may be used to predict the survival of cancer patients. Microarray data are characterized by their high-dimensionality: the number of covariates (p ∼ 1000) greatly exceeds the number of samples (n ∼ 100), which is a considerable challenge in the context of survival prediction. An inventory of methods that have been used to model survival using gene expression is given. These methods are critically reviewed and compared in a qualitative way. Next, these methods are applied to three real-life data sets for a quantitative comparison. The choice of the evaluation measure of predictive performance is crucial for the selection of the best method. Depending on the evaluation measure, either the L

Original language	English
Pages (from-to)	1590-1603
Journal	Computational Statistics and Data Analysis
Volume	53
Issue number	5
DOIs	https://doi.org/10.1016/j.csda.2008.05.021
Publication status	Published - 2009

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10.1016/j.csda.2008.05.021

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AU - Boulesteix, A.-L.

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Survival prediction using gene expression: a review and comparison

Abstract

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