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Prognostic classification index in Iranian colorectal cancer patients: Survival tree analysis

AIMS: The aim of this study was to determine the prognostic index for separating homogenous subgroups in colorectal cancer (CRC) patients based on clinicopathological characteristics using survival tree analysis. METHODS: The current study was conducted at the Research Center of Gastroenterology and...

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Autores principales: Malehi, Amal Saki, Rahim, Fakher
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4845603/
https://www.ncbi.nlm.nih.gov/pubmed/27169118
http://dx.doi.org/10.4103/2278-330X.179703
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author Malehi, Amal Saki
Rahim, Fakher
author_facet Malehi, Amal Saki
Rahim, Fakher
author_sort Malehi, Amal Saki
collection PubMed
description AIMS: The aim of this study was to determine the prognostic index for separating homogenous subgroups in colorectal cancer (CRC) patients based on clinicopathological characteristics using survival tree analysis. METHODS: The current study was conducted at the Research Center of Gastroenterology and Liver Disease, Shahid Beheshti Medical University in Tehran, between January 2004 and January 2009. A total of 739 patients who already have been diagnosed with CRC based on pathologic report were enrolled. The data included demographic and clinical-pathological characteristic of patients. Tree-structured survival analysis based on a recursive partitioning algorithm was implemented to evaluate prognostic factors. The probability curves were calculated according to the Kaplan-Meier method, and the hazard ratio was estimated as an interest effect size. RESULT: There were 526 males (71.2%) of these patients. The mean survival time (from diagnosis time) was 42.46± (3.4). Survival tree identified three variables as main prognostic factors and based on their four prognostic subgroups was constructed. The log-rank test showed good separation of survival curves. Patients with Stage I-IIIA and treated with surgery as the first treatment showed low risk (median = 34 months) whereas patients with stage IIIB, IV, and more than 68 years have the worse survival outcome (median = 9.5 months). CONCLUSION: Constructing the prognostic classification index via survival tree can aid the researchers to assess interaction between clinical variables and determining the cumulative effect of these variables on survival outcome.
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spelling pubmed-48456032016-05-10 Prognostic classification index in Iranian colorectal cancer patients: Survival tree analysis Malehi, Amal Saki Rahim, Fakher South Asian J Cancer GI CANCER: Original Article AIMS: The aim of this study was to determine the prognostic index for separating homogenous subgroups in colorectal cancer (CRC) patients based on clinicopathological characteristics using survival tree analysis. METHODS: The current study was conducted at the Research Center of Gastroenterology and Liver Disease, Shahid Beheshti Medical University in Tehran, between January 2004 and January 2009. A total of 739 patients who already have been diagnosed with CRC based on pathologic report were enrolled. The data included demographic and clinical-pathological characteristic of patients. Tree-structured survival analysis based on a recursive partitioning algorithm was implemented to evaluate prognostic factors. The probability curves were calculated according to the Kaplan-Meier method, and the hazard ratio was estimated as an interest effect size. RESULT: There were 526 males (71.2%) of these patients. The mean survival time (from diagnosis time) was 42.46± (3.4). Survival tree identified three variables as main prognostic factors and based on their four prognostic subgroups was constructed. The log-rank test showed good separation of survival curves. Patients with Stage I-IIIA and treated with surgery as the first treatment showed low risk (median = 34 months) whereas patients with stage IIIB, IV, and more than 68 years have the worse survival outcome (median = 9.5 months). CONCLUSION: Constructing the prognostic classification index via survival tree can aid the researchers to assess interaction between clinical variables and determining the cumulative effect of these variables on survival outcome. Medknow Publications & Media Pvt Ltd 2016 /pmc/articles/PMC4845603/ /pubmed/27169118 http://dx.doi.org/10.4103/2278-330X.179703 Text en Copyright: © South Asian Journal of Cancer http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.
spellingShingle GI CANCER: Original Article
Malehi, Amal Saki
Rahim, Fakher
Prognostic classification index in Iranian colorectal cancer patients: Survival tree analysis
title Prognostic classification index in Iranian colorectal cancer patients: Survival tree analysis
title_full Prognostic classification index in Iranian colorectal cancer patients: Survival tree analysis
title_fullStr Prognostic classification index in Iranian colorectal cancer patients: Survival tree analysis
title_full_unstemmed Prognostic classification index in Iranian colorectal cancer patients: Survival tree analysis
title_short Prognostic classification index in Iranian colorectal cancer patients: Survival tree analysis
title_sort prognostic classification index in iranian colorectal cancer patients: survival tree analysis
topic GI CANCER: Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4845603/
https://www.ncbi.nlm.nih.gov/pubmed/27169118
http://dx.doi.org/10.4103/2278-330X.179703
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