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Women With Ovarian Cancer and With Fertility Preservation: A Survival Analysis Using the Surveillance, Epidemiology, and End Results Database and Construction of Nomograms to Predict Cancer-Specific Survival

OBJECTIVE: This study aimed to determine the risk and prognostic factors of ovarian cancer (OC) in women having fertility-sparing surgery, as well as survival outcomes of those with stage I epithelial ovarian cancer (EOC). We also determined the effect of chemotherapy in OC treatment and used multip...

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Autores principales: Hou, Yue-min, Yu, Hui, Hao, Jia-tao, Feng, Fang, An, Rui-fang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035747/
https://www.ncbi.nlm.nih.gov/pubmed/35480098
http://dx.doi.org/10.3389/fonc.2022.860046
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author Hou, Yue-min
Yu, Hui
Hao, Jia-tao
Feng, Fang
An, Rui-fang
author_facet Hou, Yue-min
Yu, Hui
Hao, Jia-tao
Feng, Fang
An, Rui-fang
author_sort Hou, Yue-min
collection PubMed
description OBJECTIVE: This study aimed to determine the risk and prognostic factors of ovarian cancer (OC) in women having fertility-sparing surgery, as well as survival outcomes of those with stage I epithelial ovarian cancer (EOC). We also determined the effect of chemotherapy in OC treatment and used multiple independent risk factors to establish a prognostic nomogram model for patients with stage I EOC. PATIENTS AND METHODS: Individuals with OC and with fertility-sparing surgery (FSS) between 1998 and 2016 were identified in the SEER database. Univariate and multivariate logistic regression was performed to identify the distributions of patient characteristics according to chemotherapy. Cancer-specific survival (CSS) was assessed using Kaplan–Meier curves and log-rank tests. Univariate and multivariate Cox regression was conducted to determine the independent prognostic factors for CSS. Cox analysis was used to construct a nomogram model. The C-index and calibration plots showed the performance evaluation results. RESULTS: A total of 1,839 women with OC with FSS were identified in the SEER database. Factors associated with significantly higher odds of undergoing chemotherapy included younger age, being unmarried, having grades 2–4, stages II–III, or clear cell and non-epithelial histologic type following a multivariate logistic regression analysis. Multivariate Cox regression analysis confirmed that age, marital status, chemotherapy, histologic type, grade, and the International Federation of Gynecology and Obstetrics (FIGO) stage were independent prognostic factors for CSS. In stage I EOC, the prognosis in patients with stage IA/IB-grade 3 (5-year CSS 85.3%) or stage IC (5-year CSS 80.6%) was worse than that in those with stage IA/IB-grade 1 (5-year CSS 95.2%), or stage IA/IB-grade 2 (5-year CSS 94.7%). However, chemotherapy improved the survival of patients with stage IA/IB-grade 3 (5-year CSS 78.1% vs. 94.6%, p = 0.024) or stage IC (5-year CSS 75.1% vs. 86.7%, p = 0.170). DISCUSSION: The study provided population-based estimates of risk factors and prognoses in patients with OC and with FSS as well as the survival outcomes of patients with stage I EOC and the effect of chemotherapy. The constructed nomograms exhibited superior prognostic discrimination and survival prediction for patients with stage I EOC.
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spelling pubmed-90357472022-04-26 Women With Ovarian Cancer and With Fertility Preservation: A Survival Analysis Using the Surveillance, Epidemiology, and End Results Database and Construction of Nomograms to Predict Cancer-Specific Survival Hou, Yue-min Yu, Hui Hao, Jia-tao Feng, Fang An, Rui-fang Front Oncol Oncology OBJECTIVE: This study aimed to determine the risk and prognostic factors of ovarian cancer (OC) in women having fertility-sparing surgery, as well as survival outcomes of those with stage I epithelial ovarian cancer (EOC). We also determined the effect of chemotherapy in OC treatment and used multiple independent risk factors to establish a prognostic nomogram model for patients with stage I EOC. PATIENTS AND METHODS: Individuals with OC and with fertility-sparing surgery (FSS) between 1998 and 2016 were identified in the SEER database. Univariate and multivariate logistic regression was performed to identify the distributions of patient characteristics according to chemotherapy. Cancer-specific survival (CSS) was assessed using Kaplan–Meier curves and log-rank tests. Univariate and multivariate Cox regression was conducted to determine the independent prognostic factors for CSS. Cox analysis was used to construct a nomogram model. The C-index and calibration plots showed the performance evaluation results. RESULTS: A total of 1,839 women with OC with FSS were identified in the SEER database. Factors associated with significantly higher odds of undergoing chemotherapy included younger age, being unmarried, having grades 2–4, stages II–III, or clear cell and non-epithelial histologic type following a multivariate logistic regression analysis. Multivariate Cox regression analysis confirmed that age, marital status, chemotherapy, histologic type, grade, and the International Federation of Gynecology and Obstetrics (FIGO) stage were independent prognostic factors for CSS. In stage I EOC, the prognosis in patients with stage IA/IB-grade 3 (5-year CSS 85.3%) or stage IC (5-year CSS 80.6%) was worse than that in those with stage IA/IB-grade 1 (5-year CSS 95.2%), or stage IA/IB-grade 2 (5-year CSS 94.7%). However, chemotherapy improved the survival of patients with stage IA/IB-grade 3 (5-year CSS 78.1% vs. 94.6%, p = 0.024) or stage IC (5-year CSS 75.1% vs. 86.7%, p = 0.170). DISCUSSION: The study provided population-based estimates of risk factors and prognoses in patients with OC and with FSS as well as the survival outcomes of patients with stage I EOC and the effect of chemotherapy. The constructed nomograms exhibited superior prognostic discrimination and survival prediction for patients with stage I EOC. Frontiers Media S.A. 2022-04-11 /pmc/articles/PMC9035747/ /pubmed/35480098 http://dx.doi.org/10.3389/fonc.2022.860046 Text en Copyright © 2022 Hou, Yu, Hao, Feng and An https://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
Hou, Yue-min
Yu, Hui
Hao, Jia-tao
Feng, Fang
An, Rui-fang
Women With Ovarian Cancer and With Fertility Preservation: A Survival Analysis Using the Surveillance, Epidemiology, and End Results Database and Construction of Nomograms to Predict Cancer-Specific Survival
title Women With Ovarian Cancer and With Fertility Preservation: A Survival Analysis Using the Surveillance, Epidemiology, and End Results Database and Construction of Nomograms to Predict Cancer-Specific Survival
title_full Women With Ovarian Cancer and With Fertility Preservation: A Survival Analysis Using the Surveillance, Epidemiology, and End Results Database and Construction of Nomograms to Predict Cancer-Specific Survival
title_fullStr Women With Ovarian Cancer and With Fertility Preservation: A Survival Analysis Using the Surveillance, Epidemiology, and End Results Database and Construction of Nomograms to Predict Cancer-Specific Survival
title_full_unstemmed Women With Ovarian Cancer and With Fertility Preservation: A Survival Analysis Using the Surveillance, Epidemiology, and End Results Database and Construction of Nomograms to Predict Cancer-Specific Survival
title_short Women With Ovarian Cancer and With Fertility Preservation: A Survival Analysis Using the Surveillance, Epidemiology, and End Results Database and Construction of Nomograms to Predict Cancer-Specific Survival
title_sort women with ovarian cancer and with fertility preservation: a survival analysis using the surveillance, epidemiology, and end results database and construction of nomograms to predict cancer-specific survival
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035747/
https://www.ncbi.nlm.nih.gov/pubmed/35480098
http://dx.doi.org/10.3389/fonc.2022.860046
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