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Activity Number: 530
Type: Contributed
Date/Time: Wednesday, August 7, 2013 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #309406
Title: Recursively Imputed Survival Trees for Predicting Colorectal Cancer Survival
Author(s): Jenny Häggström*+
Companies: Umeå University
Keywords:
Abstract:

Recursively Imputed Survival Tree (RIST) regression has recently been proposed for analysis of right-censored data and seems to be a promising method for predicting survival of colorectal cancer (CRC) patients. In simulation studies, with continuous covariates and low to moderate censoring rate, it has been shown that RIST regression performs better than several other methods. In this paper, simulation studies are performed to evaluate the performance of RIST regression when a majority of the covariates are categorical and the censoring rate is moderate to high and, finally, in order to predict survival and learn about prognostic features of CRC, RIST regression is applied to CRC data containing a mix of molecular and clinico-pathological covariates.


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