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Nomograms to predict the prognosis in malignant ovarian germ cell tumors: a large cohort study

BACKGROUND: Malignant ovarian germ cell tumors (MOGCTs) are rare gynecologic neoplasms. The use of nomograms that are based on various clinical indicators to predict the prognosis of MOGCTs are currently lacking. METHODS: Clinical and demographic information of patients with MOGCT recorded between 2...

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Autores principales: Song, Zixuan, Wang, Yizi, Zhou, Yangzi, Zhang, Dandan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8908578/
https://www.ncbi.nlm.nih.gov/pubmed/35272629
http://dx.doi.org/10.1186/s12885-022-09324-7
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author Song, Zixuan
Wang, Yizi
Zhou, Yangzi
Zhang, Dandan
author_facet Song, Zixuan
Wang, Yizi
Zhou, Yangzi
Zhang, Dandan
author_sort Song, Zixuan
collection PubMed
description BACKGROUND: Malignant ovarian germ cell tumors (MOGCTs) are rare gynecologic neoplasms. The use of nomograms that are based on various clinical indicators to predict the prognosis of MOGCTs are currently lacking. METHODS: Clinical and demographic information of patients with MOGCT recorded between 2004 and 2015 were obtained from the Surveillance, Epidemiology, and End Results database, and Cox regression analysis was performed to screen for important independent prognostic factors. Prognostic factors were used to construct predictive calculational charts for 1-year, 3-year, and 5-year overall survival (OS). The externally validated case cohort included a total of 121 MOGCT patients whose data were recorded from 2008 to 2019 from the database of the Shengjing Hospital of China Medical University. RESULTS: A total of 1401 patients with MOGCT were recruited for the study. A nomogram was used to forecast the 1-year, 3-year, and 5-year OS using data pertaining to age, International Federation of Gynecology and Obstetrics (FIGO) staging, histological subtype and grade, and surgical type. Nomograms have a more accurate predictive ability and clinical utility than FIGO staging alone. Internal and external validation also demonstrated satisfactory consistency between projected and actual OS. CONCLUSIONS: A nomogram constructed using multiple clinical indicators provided a more accurate prognosis than FIGO staging alone. This nomogram may assist clinicians in identifying patients who are at increased risk, thus implementing individualized treatment regimens.
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spelling pubmed-89085782022-03-18 Nomograms to predict the prognosis in malignant ovarian germ cell tumors: a large cohort study Song, Zixuan Wang, Yizi Zhou, Yangzi Zhang, Dandan BMC Cancer Research BACKGROUND: Malignant ovarian germ cell tumors (MOGCTs) are rare gynecologic neoplasms. The use of nomograms that are based on various clinical indicators to predict the prognosis of MOGCTs are currently lacking. METHODS: Clinical and demographic information of patients with MOGCT recorded between 2004 and 2015 were obtained from the Surveillance, Epidemiology, and End Results database, and Cox regression analysis was performed to screen for important independent prognostic factors. Prognostic factors were used to construct predictive calculational charts for 1-year, 3-year, and 5-year overall survival (OS). The externally validated case cohort included a total of 121 MOGCT patients whose data were recorded from 2008 to 2019 from the database of the Shengjing Hospital of China Medical University. RESULTS: A total of 1401 patients with MOGCT were recruited for the study. A nomogram was used to forecast the 1-year, 3-year, and 5-year OS using data pertaining to age, International Federation of Gynecology and Obstetrics (FIGO) staging, histological subtype and grade, and surgical type. Nomograms have a more accurate predictive ability and clinical utility than FIGO staging alone. Internal and external validation also demonstrated satisfactory consistency between projected and actual OS. CONCLUSIONS: A nomogram constructed using multiple clinical indicators provided a more accurate prognosis than FIGO staging alone. This nomogram may assist clinicians in identifying patients who are at increased risk, thus implementing individualized treatment regimens. BioMed Central 2022-03-10 /pmc/articles/PMC8908578/ /pubmed/35272629 http://dx.doi.org/10.1186/s12885-022-09324-7 Text en © The Author(s) 2022 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
Song, Zixuan
Wang, Yizi
Zhou, Yangzi
Zhang, Dandan
Nomograms to predict the prognosis in malignant ovarian germ cell tumors: a large cohort study
title Nomograms to predict the prognosis in malignant ovarian germ cell tumors: a large cohort study
title_full Nomograms to predict the prognosis in malignant ovarian germ cell tumors: a large cohort study
title_fullStr Nomograms to predict the prognosis in malignant ovarian germ cell tumors: a large cohort study
title_full_unstemmed Nomograms to predict the prognosis in malignant ovarian germ cell tumors: a large cohort study
title_short Nomograms to predict the prognosis in malignant ovarian germ cell tumors: a large cohort study
title_sort nomograms to predict the prognosis in malignant ovarian germ cell tumors: a large cohort study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8908578/
https://www.ncbi.nlm.nih.gov/pubmed/35272629
http://dx.doi.org/10.1186/s12885-022-09324-7
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