Volume 8, Issue 2 (20 2012)
irje 2012, 8(2): 13-19 |
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Saki Malehi A, Hajizadeh E, Fatemi R. Evaluation of Prognostic Variables for Classifying the Survival In Colorectal Patients using The Decision Tree. irje 2012; 8 (2) :13-19
URL: http://irje.tums.ac.ir/article-1-4-en.html
URL: http://irje.tums.ac.ir/article-1-4-en.html
1- , hajizadeh@modares.ac.ir
Abstract: (12790 Views)
Background
& Objectives: Identifying
the important influential factors is a great challenge in oncology studies.
Decision tree is one of methods that could be used to evaluate the prognostic
factors and classifying the patients' homogeneously. This method identifies the
main prognostic factors and then determines the subgroups of patients based on
those prognostic factors. The aim of this study was to assess the prognostic
factors and homogeneous subgroups of colorectal patient through survival tree.
Methods: Data collected from an observational of 739 colorectal patients registered in the cancer registry affiliated to the center of Research Center of Gastroenterology and Liver Disease (RCGLD), Shahid Beheshti Medical University, Tehran, Iran. Death was the interested event and the survival time was calculated from date of diagnosis until occurrence of event (or censoring) in months. Finally we used decision tree based method for classifying and analyzing the data.
Results: Based on our result, decision tree identified four covariates as important prognostic factors in 0.05 significant levels: general stage of cancer, age of diagnosis, histology of tumor and morphology type of tumor. Also patients based on these prognostic factors divided into five homogeneous subgroups. The greater values of measure of separation (SEP) criterion support the appropriateness of this model for such the data.
Conclusion: Decision tree is powerful and intuitive method. It has a key feature that is in addition to evaluate the prognostic factors, provides the homogeneous subgroups for future analysis.
Methods: Data collected from an observational of 739 colorectal patients registered in the cancer registry affiliated to the center of Research Center of Gastroenterology and Liver Disease (RCGLD), Shahid Beheshti Medical University, Tehran, Iran. Death was the interested event and the survival time was calculated from date of diagnosis until occurrence of event (or censoring) in months. Finally we used decision tree based method for classifying and analyzing the data.
Results: Based on our result, decision tree identified four covariates as important prognostic factors in 0.05 significant levels: general stage of cancer, age of diagnosis, histology of tumor and morphology type of tumor. Also patients based on these prognostic factors divided into five homogeneous subgroups. The greater values of measure of separation (SEP) criterion support the appropriateness of this model for such the data.
Conclusion: Decision tree is powerful and intuitive method. It has a key feature that is in addition to evaluate the prognostic factors, provides the homogeneous subgroups for future analysis.
Keywords: Decision tree, Survival analysis, Prognostic factors, Homogeneous subgroups, Colorectal cancer
Type of Study: Research |
Subject:
General
Received: 2011/09/6 | Accepted: 2012/01/28 | Published: 2013/08/18
Received: 2011/09/6 | Accepted: 2012/01/28 | Published: 2013/08/18
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