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Bioinformatics Advance Access originally published online on February 25, 2009
Bioinformatics 2009 25(7):890-896; doi:10.1093/bioinformatics/btp088
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© The Author 2009. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Boosting for high-dimensional time-to-event data with competing risks

Harald Binder 1,2,*, Arthur Allignol 1,2, Martin Schumacher 2 and Jan Beyersmann 1,2

1Freiburg Center for Data Analysis and Modeling, University of Freiburg, Eckerstr. 1 and 2Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Stefan-Meier-Str. 26, 79104 Freiburg, Germany

*To whom correspondence should be addressed.


  Abstract

Motivation: For analyzing high-dimensional time-to-event data with competing risks, tailored modeling techniques are required that consider the event of interest and the competing events at the same time, while also dealing with censoring. For low-dimensional settings, proportional hazards models for the subdistribution hazard have been proposed, but an adaptation for high-dimensional settings is missing. In addition, tools for judging the prediction performance of fitted models have to be provided.

Results: We propose a boosting approach for fitting proportional subdistribution hazards models for high-dimensional data, that can e.g. incorporate a large number of microarray features, while also taking clinical covariates into account. Prediction performance is evaluated using bootstrap.632+ estimates of prediction error curves, adapted for the competing risks setting. This is illustrated with bladder cancer microarray data, where simultaneous consideration of both, the event of interest and competing events, allows for judging the additional predictive power gained from incorporating microarray measurements.

Availability: The proposed boosting approach is implemented in the R package CoxBoost and prediction error estimation in the package peperr, both available from CRAN.

Contact: binderh{at}fdm.uni-freiburg.de

Associate Editor: Joaquin Dopazo

Received on October 16, 2008; revised on January 19, 2009; accepted on February 12, 2009

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