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Assessing survival time of outpatients with cervical cancer: at the university of Gondar referral hospital using the Bayesian approach
BACKGROUND: Cervical cancer is the 4th most common cancer in women worldwide. as well as the 4th most common cause of cancer-related death. The main objective of this study was to identify factors that affect the survival time of outpatients with cervical cancer. METHODS: A retrolective study includ...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9921662/ https://www.ncbi.nlm.nih.gov/pubmed/36765315 http://dx.doi.org/10.1186/s12905-023-02202-9 |
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author | Gashu, Chalachew Tasfa, Buzuneh Alemu, Chekol Kassa, Yoseph |
author_facet | Gashu, Chalachew Tasfa, Buzuneh Alemu, Chekol Kassa, Yoseph |
author_sort | Gashu, Chalachew |
collection | PubMed |
description | BACKGROUND: Cervical cancer is the 4th most common cancer in women worldwide. as well as the 4th most common cause of cancer-related death. The main objective of this study was to identify factors that affect the survival time of outpatients with cervical cancer. METHODS: A retrolective study including outpatients with cervical cancer was carried out in a hospital. To achieve the aim, 322 outpatients with cervical cancer were included in the study based on the data taken from the medical records of patients enrolled from May 15, 2018, to May 15, 2022, at the University of Gondar referral hospital, Gondar, Ethiopia. The Kaplan–Meier plots and log-rank test were used for the comparison of survival functions; the Cox-PH model and Bayesian parametric survival models were used to analyze the survival times of outpatients with cervical cancer. Integrated nested Laplace approximation methods have been applied. RESULTS: Out of a total of 322 patients, 118 (36.6%) died as outpatients. The estimated median survival time for patients was 42 months. Using model selection criteria, the Bayesian log-normal accelerated failure time model was found to be appropriate. According to the results of this model, oral contraceptive use, HIV, stage, grade, co-morbid disease, history of abortion, weight, histology type, FIGO stage, radiation, chemotherapy, LVSI, metastatic number, regional nodes examined, and tumor size all have a significant impact on the survival time of outpatients with cervical cancer. The Bayesian log-normal accelerated failure time model accurately predicted the survival time of cervical cancer outpatients. CONCLUSIONS: The findings of this study suggested that reductions in weight, treatment, the presence of comorbid disease, the presence of HIV, squamous cell histology type, having a history of abortion, oral contraceptive use, a large tumor size, an increase in the International Federation of Gynecologists and Obstetricians stage, an increase in metastasis number, an increase in grade, positive regional nodes, lymphatic vascular space invasion, and late stages of cancer all shortened the survival time of cervical cancer outpatients. |
format | Online Article Text |
id | pubmed-9921662 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-99216622023-02-12 Assessing survival time of outpatients with cervical cancer: at the university of Gondar referral hospital using the Bayesian approach Gashu, Chalachew Tasfa, Buzuneh Alemu, Chekol Kassa, Yoseph BMC Womens Health Research BACKGROUND: Cervical cancer is the 4th most common cancer in women worldwide. as well as the 4th most common cause of cancer-related death. The main objective of this study was to identify factors that affect the survival time of outpatients with cervical cancer. METHODS: A retrolective study including outpatients with cervical cancer was carried out in a hospital. To achieve the aim, 322 outpatients with cervical cancer were included in the study based on the data taken from the medical records of patients enrolled from May 15, 2018, to May 15, 2022, at the University of Gondar referral hospital, Gondar, Ethiopia. The Kaplan–Meier plots and log-rank test were used for the comparison of survival functions; the Cox-PH model and Bayesian parametric survival models were used to analyze the survival times of outpatients with cervical cancer. Integrated nested Laplace approximation methods have been applied. RESULTS: Out of a total of 322 patients, 118 (36.6%) died as outpatients. The estimated median survival time for patients was 42 months. Using model selection criteria, the Bayesian log-normal accelerated failure time model was found to be appropriate. According to the results of this model, oral contraceptive use, HIV, stage, grade, co-morbid disease, history of abortion, weight, histology type, FIGO stage, radiation, chemotherapy, LVSI, metastatic number, regional nodes examined, and tumor size all have a significant impact on the survival time of outpatients with cervical cancer. The Bayesian log-normal accelerated failure time model accurately predicted the survival time of cervical cancer outpatients. CONCLUSIONS: The findings of this study suggested that reductions in weight, treatment, the presence of comorbid disease, the presence of HIV, squamous cell histology type, having a history of abortion, oral contraceptive use, a large tumor size, an increase in the International Federation of Gynecologists and Obstetricians stage, an increase in metastasis number, an increase in grade, positive regional nodes, lymphatic vascular space invasion, and late stages of cancer all shortened the survival time of cervical cancer outpatients. BioMed Central 2023-02-10 /pmc/articles/PMC9921662/ /pubmed/36765315 http://dx.doi.org/10.1186/s12905-023-02202-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Gashu, Chalachew Tasfa, Buzuneh Alemu, Chekol Kassa, Yoseph Assessing survival time of outpatients with cervical cancer: at the university of Gondar referral hospital using the Bayesian approach |
title | Assessing survival time of outpatients with cervical cancer: at the university of Gondar referral hospital using the Bayesian approach |
title_full | Assessing survival time of outpatients with cervical cancer: at the university of Gondar referral hospital using the Bayesian approach |
title_fullStr | Assessing survival time of outpatients with cervical cancer: at the university of Gondar referral hospital using the Bayesian approach |
title_full_unstemmed | Assessing survival time of outpatients with cervical cancer: at the university of Gondar referral hospital using the Bayesian approach |
title_short | Assessing survival time of outpatients with cervical cancer: at the university of Gondar referral hospital using the Bayesian approach |
title_sort | assessing survival time of outpatients with cervical cancer: at the university of gondar referral hospital using the bayesian approach |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9921662/ https://www.ncbi.nlm.nih.gov/pubmed/36765315 http://dx.doi.org/10.1186/s12905-023-02202-9 |
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