Survival prediction using gene expression: a review and comparison

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

Research output: Contribution to JournalArticleAcademicpeer-review


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 languageEnglish
Pages (from-to)1590-1603
JournalComputational Statistics and Data Analysis
Issue number5
Publication statusPublished - 2009


Dive into the research topics of 'Survival prediction using gene expression: a review and comparison'. Together they form a unique fingerprint.

Cite this