Cargando…

An Ensemble Prognostic Model for Colorectal Cancer

Colorectal cancer can be grouped into Dukes A, B, C, and D stages based on its developments. Generally speaking, more advanced patients have poorer prognosis. To integrate progression stage prediction systems with recurrence prediction systems, we proposed an ensemble prognostic model for colorectal...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Bi-Qing, Huang, Tao, Zhang, Jian, Zhang, Ning, Huang, Guo-Hua, Liu, Lei, Cai, Yu-Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3642113/
https://www.ncbi.nlm.nih.gov/pubmed/23658834
http://dx.doi.org/10.1371/journal.pone.0063494
_version_ 1782268102840418304
author Li, Bi-Qing
Huang, Tao
Zhang, Jian
Zhang, Ning
Huang, Guo-Hua
Liu, Lei
Cai, Yu-Dong
author_facet Li, Bi-Qing
Huang, Tao
Zhang, Jian
Zhang, Ning
Huang, Guo-Hua
Liu, Lei
Cai, Yu-Dong
author_sort Li, Bi-Qing
collection PubMed
description Colorectal cancer can be grouped into Dukes A, B, C, and D stages based on its developments. Generally speaking, more advanced patients have poorer prognosis. To integrate progression stage prediction systems with recurrence prediction systems, we proposed an ensemble prognostic model for colorectal cancer. In this model, each patient was assigned a most possible stage and a most possible recurrence status. If a patient was predicted to be recurrence patient in advanced stage, he would be classified into high risk group. The ensemble model considered both progression stages and recurrence status. High risk patients and low risk patients predicted by the ensemble model had a significant different disease free survival (log-rank test p-value, 0.0016) and disease specific survival (log-rank test p-value, 0.0041). The ensemble model can better distinguish the high risk and low risk patients than the stage prediction model and the recurrence prediction model alone. This method could be applied to the studies of other diseases and it could significantly improve the prediction performance by ensembling heterogeneous information.
format Online
Article
Text
id pubmed-3642113
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-36421132013-05-08 An Ensemble Prognostic Model for Colorectal Cancer Li, Bi-Qing Huang, Tao Zhang, Jian Zhang, Ning Huang, Guo-Hua Liu, Lei Cai, Yu-Dong PLoS One Research Article Colorectal cancer can be grouped into Dukes A, B, C, and D stages based on its developments. Generally speaking, more advanced patients have poorer prognosis. To integrate progression stage prediction systems with recurrence prediction systems, we proposed an ensemble prognostic model for colorectal cancer. In this model, each patient was assigned a most possible stage and a most possible recurrence status. If a patient was predicted to be recurrence patient in advanced stage, he would be classified into high risk group. The ensemble model considered both progression stages and recurrence status. High risk patients and low risk patients predicted by the ensemble model had a significant different disease free survival (log-rank test p-value, 0.0016) and disease specific survival (log-rank test p-value, 0.0041). The ensemble model can better distinguish the high risk and low risk patients than the stage prediction model and the recurrence prediction model alone. This method could be applied to the studies of other diseases and it could significantly improve the prediction performance by ensembling heterogeneous information. Public Library of Science 2013-05-02 /pmc/articles/PMC3642113/ /pubmed/23658834 http://dx.doi.org/10.1371/journal.pone.0063494 Text en © 2013 Li et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Li, Bi-Qing
Huang, Tao
Zhang, Jian
Zhang, Ning
Huang, Guo-Hua
Liu, Lei
Cai, Yu-Dong
An Ensemble Prognostic Model for Colorectal Cancer
title An Ensemble Prognostic Model for Colorectal Cancer
title_full An Ensemble Prognostic Model for Colorectal Cancer
title_fullStr An Ensemble Prognostic Model for Colorectal Cancer
title_full_unstemmed An Ensemble Prognostic Model for Colorectal Cancer
title_short An Ensemble Prognostic Model for Colorectal Cancer
title_sort ensemble prognostic model for colorectal cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3642113/
https://www.ncbi.nlm.nih.gov/pubmed/23658834
http://dx.doi.org/10.1371/journal.pone.0063494
work_keys_str_mv AT libiqing anensembleprognosticmodelforcolorectalcancer
AT huangtao anensembleprognosticmodelforcolorectalcancer
AT zhangjian anensembleprognosticmodelforcolorectalcancer
AT zhangning anensembleprognosticmodelforcolorectalcancer
AT huangguohua anensembleprognosticmodelforcolorectalcancer
AT liulei anensembleprognosticmodelforcolorectalcancer
AT caiyudong anensembleprognosticmodelforcolorectalcancer
AT libiqing ensembleprognosticmodelforcolorectalcancer
AT huangtao ensembleprognosticmodelforcolorectalcancer
AT zhangjian ensembleprognosticmodelforcolorectalcancer
AT zhangning ensembleprognosticmodelforcolorectalcancer
AT huangguohua ensembleprognosticmodelforcolorectalcancer
AT liulei ensembleprognosticmodelforcolorectalcancer
AT caiyudong ensembleprognosticmodelforcolorectalcancer