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A Practical Nomogram to Predict Early Death in Advanced Epithelial Ovarian Cancer

Background: Ovarian cancer is a common gynecological malignancy, most of which is epithelial ovarian cancer (EOC). Advanced EOC is linked with a higher incidence of premature death. To date, no effective prognostic tools are available to evaluate the possibility of early death in patients with advan...

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Autores principales: Song, Zixuan, Zhou, Yangzi, Bai, Xue, Zhang, Dandan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8017286/
https://www.ncbi.nlm.nih.gov/pubmed/33816311
http://dx.doi.org/10.3389/fonc.2021.655826
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author Song, Zixuan
Zhou, Yangzi
Bai, Xue
Zhang, Dandan
author_facet Song, Zixuan
Zhou, Yangzi
Bai, Xue
Zhang, Dandan
author_sort Song, Zixuan
collection PubMed
description Background: Ovarian cancer is a common gynecological malignancy, most of which is epithelial ovarian cancer (EOC). Advanced EOC is linked with a higher incidence of premature death. To date, no effective prognostic tools are available to evaluate the possibility of early death in patients with advanced EOC. Methods: Advanced (FIGO stage III and IV) EOC patients who were enrolled in the Surveillance, Epidemiology, and End Results database between 2004 and 2015 were regarded as subjects and studied. We aimed to construct a nomogram that can deliver early death prognosis in patients with advanced EOC by identifying crucial independent factors using univariate and multivariate logistic regression analyses to help deliver accurate prognoses. Results: In total, 13,403 patients with advanced EOC were included in this study. Three hundred ninety-seven out of a total of 9,379 FIGO stage III patients died early. There were 4,024 patients with FIGO stage IV, 414 of whom died early. Nomograms based on independent prognostic factors have the satisfactory predictive capability and clinical pragmatism. The internal validation feature of the nomogram demonstrated a high level of accuracy of the predicted death. Conclusions: By analyzing data from a large cohort, a clinically convenient nomogram was established to predict premature death in advanced EOC. This tool can aid clinicians in screening patients who are at higher risk for tailoring treatment plans.
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spelling pubmed-80172862021-04-03 A Practical Nomogram to Predict Early Death in Advanced Epithelial Ovarian Cancer Song, Zixuan Zhou, Yangzi Bai, Xue Zhang, Dandan Front Oncol Oncology Background: Ovarian cancer is a common gynecological malignancy, most of which is epithelial ovarian cancer (EOC). Advanced EOC is linked with a higher incidence of premature death. To date, no effective prognostic tools are available to evaluate the possibility of early death in patients with advanced EOC. Methods: Advanced (FIGO stage III and IV) EOC patients who were enrolled in the Surveillance, Epidemiology, and End Results database between 2004 and 2015 were regarded as subjects and studied. We aimed to construct a nomogram that can deliver early death prognosis in patients with advanced EOC by identifying crucial independent factors using univariate and multivariate logistic regression analyses to help deliver accurate prognoses. Results: In total, 13,403 patients with advanced EOC were included in this study. Three hundred ninety-seven out of a total of 9,379 FIGO stage III patients died early. There were 4,024 patients with FIGO stage IV, 414 of whom died early. Nomograms based on independent prognostic factors have the satisfactory predictive capability and clinical pragmatism. The internal validation feature of the nomogram demonstrated a high level of accuracy of the predicted death. Conclusions: By analyzing data from a large cohort, a clinically convenient nomogram was established to predict premature death in advanced EOC. This tool can aid clinicians in screening patients who are at higher risk for tailoring treatment plans. Frontiers Media S.A. 2021-03-19 /pmc/articles/PMC8017286/ /pubmed/33816311 http://dx.doi.org/10.3389/fonc.2021.655826 Text en Copyright © 2021 Song, Zhou, Bai and Zhang. 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
Song, Zixuan
Zhou, Yangzi
Bai, Xue
Zhang, Dandan
A Practical Nomogram to Predict Early Death in Advanced Epithelial Ovarian Cancer
title A Practical Nomogram to Predict Early Death in Advanced Epithelial Ovarian Cancer
title_full A Practical Nomogram to Predict Early Death in Advanced Epithelial Ovarian Cancer
title_fullStr A Practical Nomogram to Predict Early Death in Advanced Epithelial Ovarian Cancer
title_full_unstemmed A Practical Nomogram to Predict Early Death in Advanced Epithelial Ovarian Cancer
title_short A Practical Nomogram to Predict Early Death in Advanced Epithelial Ovarian Cancer
title_sort practical nomogram to predict early death in advanced epithelial ovarian cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8017286/
https://www.ncbi.nlm.nih.gov/pubmed/33816311
http://dx.doi.org/10.3389/fonc.2021.655826
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