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Prognostic Factors for Survival in Patients with Gastric Cancer using a Random Survival Forest
BACKGROUND: Gastric cancer is the fifth most common cancer and the third top cause of cancer related death with about 1 million new cases and 700,000 deaths in 2012. The aim of this investigation was to identify important factors for outcome using a random survival forest (RSF) approach. MATERIALS A...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
West Asia Organization for Cancer Prevention
2017
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5563089/ https://www.ncbi.nlm.nih.gov/pubmed/28240020 http://dx.doi.org/10.22034/APJCP.2017.18.1.129 |
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author | Adham, Davoud Abbasgholizadeh, Nategh Abazari, Malek |
author_facet | Adham, Davoud Abbasgholizadeh, Nategh Abazari, Malek |
author_sort | Adham, Davoud |
collection | PubMed |
description | BACKGROUND: Gastric cancer is the fifth most common cancer and the third top cause of cancer related death with about 1 million new cases and 700,000 deaths in 2012. The aim of this investigation was to identify important factors for outcome using a random survival forest (RSF) approach. MATERIALS AND METHODS: Data were collected from 128 gastric cancer patients through a historical cohort study in Hamedan-Iran from 2007 to 2013. The event under consideration was death due to gastric cancer. The random survival forest model in R software was applied to determine the key factors affecting survival. Four split criteria were used to determine importance of the variables in the model including log-rank, conversation?? of events, log-rank score, and randomization. Efficiency of the model was confirmed in terms of Harrell’s concordance index. RESULTS: The mean age of diagnosis was 63 ±12.57 and mean and median survival times were 15.2 (95%CI: 13.3, 17.0) and 12.3 (95%CI: 11.0, 13.4) months, respectively. The one-year, two-year, and three-year rates for survival were 51%, 13%, and 5%, respectively. Each RSF approach showed a slightly different ranking order. Very important covariates in nearly all the 4 RSF approaches were metastatic status, age at diagnosis and tumor size. The performance of each RSF approach was in the range of 0.29-0.32 and the best error rate was obtained by the log-rank splitting rule; second, third, and fourth ranks were log-rank score, conservation of events, and the random splitting rule, respectively. CONCLUSION: Low survival rate of gastric cancer patients is an indication of absence of a screening program for early diagnosis of the disease. Timely diagnosis in early phases increases survival and decreases mortality. |
format | Online Article Text |
id | pubmed-5563089 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | West Asia Organization for Cancer Prevention |
record_format | MEDLINE/PubMed |
spelling | pubmed-55630892017-08-28 Prognostic Factors for Survival in Patients with Gastric Cancer using a Random Survival Forest Adham, Davoud Abbasgholizadeh, Nategh Abazari, Malek Asian Pac J Cancer Prev Research Article BACKGROUND: Gastric cancer is the fifth most common cancer and the third top cause of cancer related death with about 1 million new cases and 700,000 deaths in 2012. The aim of this investigation was to identify important factors for outcome using a random survival forest (RSF) approach. MATERIALS AND METHODS: Data were collected from 128 gastric cancer patients through a historical cohort study in Hamedan-Iran from 2007 to 2013. The event under consideration was death due to gastric cancer. The random survival forest model in R software was applied to determine the key factors affecting survival. Four split criteria were used to determine importance of the variables in the model including log-rank, conversation?? of events, log-rank score, and randomization. Efficiency of the model was confirmed in terms of Harrell’s concordance index. RESULTS: The mean age of diagnosis was 63 ±12.57 and mean and median survival times were 15.2 (95%CI: 13.3, 17.0) and 12.3 (95%CI: 11.0, 13.4) months, respectively. The one-year, two-year, and three-year rates for survival were 51%, 13%, and 5%, respectively. Each RSF approach showed a slightly different ranking order. Very important covariates in nearly all the 4 RSF approaches were metastatic status, age at diagnosis and tumor size. The performance of each RSF approach was in the range of 0.29-0.32 and the best error rate was obtained by the log-rank splitting rule; second, third, and fourth ranks were log-rank score, conservation of events, and the random splitting rule, respectively. CONCLUSION: Low survival rate of gastric cancer patients is an indication of absence of a screening program for early diagnosis of the disease. Timely diagnosis in early phases increases survival and decreases mortality. West Asia Organization for Cancer Prevention 2017 /pmc/articles/PMC5563089/ /pubmed/28240020 http://dx.doi.org/10.22034/APJCP.2017.18.1.129 Text en Copyright: © Asian Pacific Journal of Cancer Prevention http://creativecommons.org/licenses/BY-SA/4.0 This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License |
spellingShingle | Research Article Adham, Davoud Abbasgholizadeh, Nategh Abazari, Malek Prognostic Factors for Survival in Patients with Gastric Cancer using a Random Survival Forest |
title | Prognostic Factors for Survival in Patients with Gastric Cancer using a Random Survival Forest |
title_full | Prognostic Factors for Survival in Patients with Gastric Cancer using a Random Survival Forest |
title_fullStr | Prognostic Factors for Survival in Patients with Gastric Cancer using a Random Survival Forest |
title_full_unstemmed | Prognostic Factors for Survival in Patients with Gastric Cancer using a Random Survival Forest |
title_short | Prognostic Factors for Survival in Patients with Gastric Cancer using a Random Survival Forest |
title_sort | prognostic factors for survival in patients with gastric cancer using a random survival forest |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5563089/ https://www.ncbi.nlm.nih.gov/pubmed/28240020 http://dx.doi.org/10.22034/APJCP.2017.18.1.129 |
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