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A Population-Based Study on Liver Metastases in Women With Newly Diagnosed Ovarian Cancer

Aim: The purpose of this study was to analyze the incidence, clinical characteristics, prognostic factors and survival of ovarian cancer patients with liver metastases upon initial diagnosis. Methods: Patients with ovarian cancer liver metastases upon initial diagnosis between 2010 and 2016 were ide...

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Autores principales: Zhao, Haiyun, Xu, Fei, Li, Jiajia, Ni, Mengdong, Wu, Xiaohua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7545579/
https://www.ncbi.nlm.nih.gov/pubmed/33102229
http://dx.doi.org/10.3389/fonc.2020.571671
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author Zhao, Haiyun
Xu, Fei
Li, Jiajia
Ni, Mengdong
Wu, Xiaohua
author_facet Zhao, Haiyun
Xu, Fei
Li, Jiajia
Ni, Mengdong
Wu, Xiaohua
author_sort Zhao, Haiyun
collection PubMed
description Aim: The purpose of this study was to analyze the incidence, clinical characteristics, prognostic factors and survival of ovarian cancer patients with liver metastases upon initial diagnosis. Methods: Patients with ovarian cancer liver metastases upon initial diagnosis between 2010 and 2016 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate logistic regression was performed to identify the predictors of the presence of liver metastases in newly diagnosed ovarian cancer patients. Overall survival (OS) was assessed using the Kaplan-Meier method and log-rank test. Univariate and multivariate Cox regression was conducted to determine the independent prognostic factors for OS. Results: A total of 1,744 ovarian cancer patients with liver metastases was identified from the SEER database, accounting for 6.7% of the entire ovarian cancer patients. As to the unique distant organ provided by SEER, liver was the most common metastatic site of ovarian cancer (4.65%). Age, race, laterality, histology, pathological grade, extrahepatic sites, stage of tumor were the predictors of the presence with liver metastases revealed by multivariable logistic regression model. Median OS for the patients with liver metastases at initial diagnosis of ovarian cancer was 16.0 months. Multivariate Cox regression model confirmed race, histology, extrahepatic metastatic sites, surgery and marital status were independent prognostic factors for OS. Conclusion: The study provided population-based estimates of the incidence and prognosis of newly diagnosed ovary cancer patients with liver metastases, which could be potentially used for the risk assessment and individualized treatment.
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spelling pubmed-75455792020-10-22 A Population-Based Study on Liver Metastases in Women With Newly Diagnosed Ovarian Cancer Zhao, Haiyun Xu, Fei Li, Jiajia Ni, Mengdong Wu, Xiaohua Front Oncol Oncology Aim: The purpose of this study was to analyze the incidence, clinical characteristics, prognostic factors and survival of ovarian cancer patients with liver metastases upon initial diagnosis. Methods: Patients with ovarian cancer liver metastases upon initial diagnosis between 2010 and 2016 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate logistic regression was performed to identify the predictors of the presence of liver metastases in newly diagnosed ovarian cancer patients. Overall survival (OS) was assessed using the Kaplan-Meier method and log-rank test. Univariate and multivariate Cox regression was conducted to determine the independent prognostic factors for OS. Results: A total of 1,744 ovarian cancer patients with liver metastases was identified from the SEER database, accounting for 6.7% of the entire ovarian cancer patients. As to the unique distant organ provided by SEER, liver was the most common metastatic site of ovarian cancer (4.65%). Age, race, laterality, histology, pathological grade, extrahepatic sites, stage of tumor were the predictors of the presence with liver metastases revealed by multivariable logistic regression model. Median OS for the patients with liver metastases at initial diagnosis of ovarian cancer was 16.0 months. Multivariate Cox regression model confirmed race, histology, extrahepatic metastatic sites, surgery and marital status were independent prognostic factors for OS. Conclusion: The study provided population-based estimates of the incidence and prognosis of newly diagnosed ovary cancer patients with liver metastases, which could be potentially used for the risk assessment and individualized treatment. Frontiers Media S.A. 2020-09-25 /pmc/articles/PMC7545579/ /pubmed/33102229 http://dx.doi.org/10.3389/fonc.2020.571671 Text en Copyright © 2020 Zhao, Xu, Li, Ni and Wu. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Zhao, Haiyun
Xu, Fei
Li, Jiajia
Ni, Mengdong
Wu, Xiaohua
A Population-Based Study on Liver Metastases in Women With Newly Diagnosed Ovarian Cancer
title A Population-Based Study on Liver Metastases in Women With Newly Diagnosed Ovarian Cancer
title_full A Population-Based Study on Liver Metastases in Women With Newly Diagnosed Ovarian Cancer
title_fullStr A Population-Based Study on Liver Metastases in Women With Newly Diagnosed Ovarian Cancer
title_full_unstemmed A Population-Based Study on Liver Metastases in Women With Newly Diagnosed Ovarian Cancer
title_short A Population-Based Study on Liver Metastases in Women With Newly Diagnosed Ovarian Cancer
title_sort population-based study on liver metastases in women with newly diagnosed ovarian cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7545579/
https://www.ncbi.nlm.nih.gov/pubmed/33102229
http://dx.doi.org/10.3389/fonc.2020.571671
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