Colorectal cancer (CRC) is a tumour of the colon and rectum. Most cases of CRC are sporadic; meaning there are no known hereditary (genetic) components, and it develops slowly over several years through adenomatous polyps. Changes in bowel habits, blood in the stool, and anaemia are cardinal symptoms and sings of CRC. In later stages, fatigue, anorexia, weight loss, pain, jaundice, and other signs and symptoms of locally advanced and metastatic disease occur. The aim of this study is to estimate the population based colorectal cancer survival analysis using cox Proportional Hazards model, in order to fits colorectal cancer data in population-based research. This research was a five-year retrospective study on data from a record of colorectal cancer patients that received treatments from 2013 to 2017 in Radiotherapy Department of Usmanu Danfodiyo University Teaching Hospital, Sokoto, being it one of the cancer registries in Nigeria. 9 covariates were selected to fit colorectal cancer data using Cox Regression Models. The 5-year median survival was found to be 121 days. From the results, it was concluded that the predictor variables could significantly predict the survival of colorectal cancer patients using Cox proportional model. Also the results show that the data met Cox Proportional Hazards Assumptions.
| Published in | Biomedical Statistics and Informatics (Volume 5, Issue 1) |
| DOI | 10.11648/j.bsi.20200501.13 |
| Page(s) | 14-19 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Colorectal, Cancer, Cox, Hazards, Assumptions
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APA Style
Marafa Haliru Muhammad, Usman Umar. (2020). Estimation of Population Based Colorectal Cancer Survival Analysis Using Cox Proportional Hazards Model. Biomedical Statistics and Informatics, 5(1), 14-19. https://doi.org/10.11648/j.bsi.20200501.13
ACS Style
Marafa Haliru Muhammad; Usman Umar. Estimation of Population Based Colorectal Cancer Survival Analysis Using Cox Proportional Hazards Model. Biomed. Stat. Inform. 2020, 5(1), 14-19. doi: 10.11648/j.bsi.20200501.13
AMA Style
Marafa Haliru Muhammad, Usman Umar. Estimation of Population Based Colorectal Cancer Survival Analysis Using Cox Proportional Hazards Model. Biomed Stat Inform. 2020;5(1):14-19. doi: 10.11648/j.bsi.20200501.13
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Download@article{10.11648/j.bsi.20200501.13,
author = {Marafa Haliru Muhammad and Usman Umar},
title = {Estimation of Population Based Colorectal Cancer Survival Analysis Using Cox Proportional Hazards Model},
journal = {Biomedical Statistics and Informatics},
volume = {5},
number = {1},
pages = {14-19},
doi = {10.11648/j.bsi.20200501.13},
url = {https://doi.org/10.11648/j.bsi.20200501.13},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.bsi.20200501.13},
abstract = {Colorectal cancer (CRC) is a tumour of the colon and rectum. Most cases of CRC are sporadic; meaning there are no known hereditary (genetic) components, and it develops slowly over several years through adenomatous polyps. Changes in bowel habits, blood in the stool, and anaemia are cardinal symptoms and sings of CRC. In later stages, fatigue, anorexia, weight loss, pain, jaundice, and other signs and symptoms of locally advanced and metastatic disease occur. The aim of this study is to estimate the population based colorectal cancer survival analysis using cox Proportional Hazards model, in order to fits colorectal cancer data in population-based research. This research was a five-year retrospective study on data from a record of colorectal cancer patients that received treatments from 2013 to 2017 in Radiotherapy Department of Usmanu Danfodiyo University Teaching Hospital, Sokoto, being it one of the cancer registries in Nigeria. 9 covariates were selected to fit colorectal cancer data using Cox Regression Models. The 5-year median survival was found to be 121 days. From the results, it was concluded that the predictor variables could significantly predict the survival of colorectal cancer patients using Cox proportional model. Also the results show that the data met Cox Proportional Hazards Assumptions.},
year = {2020}
}
TY - JOUR T1 - Estimation of Population Based Colorectal Cancer Survival Analysis Using Cox Proportional Hazards Model AU - Marafa Haliru Muhammad AU - Usman Umar Y1 - 2020/02/04 PY - 2020 N1 - https://doi.org/10.11648/j.bsi.20200501.13 DO - 10.11648/j.bsi.20200501.13 T2 - Biomedical Statistics and Informatics JF - Biomedical Statistics and Informatics JO - Biomedical Statistics and Informatics SP - 14 EP - 19 PB - Science Publishing Group SN - 2578-8728 UR - https://doi.org/10.11648/j.bsi.20200501.13 AB - Colorectal cancer (CRC) is a tumour of the colon and rectum. Most cases of CRC are sporadic; meaning there are no known hereditary (genetic) components, and it develops slowly over several years through adenomatous polyps. Changes in bowel habits, blood in the stool, and anaemia are cardinal symptoms and sings of CRC. In later stages, fatigue, anorexia, weight loss, pain, jaundice, and other signs and symptoms of locally advanced and metastatic disease occur. The aim of this study is to estimate the population based colorectal cancer survival analysis using cox Proportional Hazards model, in order to fits colorectal cancer data in population-based research. This research was a five-year retrospective study on data from a record of colorectal cancer patients that received treatments from 2013 to 2017 in Radiotherapy Department of Usmanu Danfodiyo University Teaching Hospital, Sokoto, being it one of the cancer registries in Nigeria. 9 covariates were selected to fit colorectal cancer data using Cox Regression Models. The 5-year median survival was found to be 121 days. From the results, it was concluded that the predictor variables could significantly predict the survival of colorectal cancer patients using Cox proportional model. Also the results show that the data met Cox Proportional Hazards Assumptions. VL - 5 IS - 1 ER -
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