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Predictive Nomogram and Risk Factors for Lymph Node Metastasis in Bladder Cancer
Lymph node metastasis (LNM) is an important prognostic factor for bladder cancer (BCA) and determines the treatment strategy. This study aimed to determine related clinicopathological factors of LNM and analyze the prognosis of BCA. A total of 10,653 eligible patients with BCA were randomly divided...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8242250/ https://www.ncbi.nlm.nih.gov/pubmed/34222019 http://dx.doi.org/10.3389/fonc.2021.690324 |
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author | Tian, Zijian Meng, Lingfeng Wang, Xin Diao, Tongxiang Hu, Maolin Wang, Miao Zhang, Yaqun Liu, Ming |
author_facet | Tian, Zijian Meng, Lingfeng Wang, Xin Diao, Tongxiang Hu, Maolin Wang, Miao Zhang, Yaqun Liu, Ming |
author_sort | Tian, Zijian |
collection | PubMed |
description | Lymph node metastasis (LNM) is an important prognostic factor for bladder cancer (BCA) and determines the treatment strategy. This study aimed to determine related clinicopathological factors of LNM and analyze the prognosis of BCA. A total of 10,653 eligible patients with BCA were randomly divided into training or verification sets using the 2004–2015 data of the Surveillance, Epidemiology, and End Results database. To identify prognostic factors for the overall survival of BCA, we utilized the Cox proportional hazard model. Independent risk factors for LNM were evaluated via logistic regression analysis. T-stage, tumor grade, patient age and tumor size were identified as independent risk factors for LNM and were used to develop the LNM nomogram. The Kaplan-Meier method and competitive risk analyses were applied to establish the influence of lymph node status on BCA prognosis. The accuracy of LNM nomogram was evaluated in the training and verification sets. The areas under the receiver operating characteristic curve (AUC) showed an effective predictive accuracy of the nomogram in both the training (AUC: 0.690) and verification (AUC: 0.704) sets. In addition, the calibration curve indicated good consistency between the prediction of deviation correction and the ideal reference line. The decision curve analysis showed that the nomogram had a high clinical application value. In conclusion, our nomogram displayed high accuracy and reliability in predicting LNM. This could assist the selection of the optimal treatment for patients. |
format | Online Article Text |
id | pubmed-8242250 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82422502021-07-01 Predictive Nomogram and Risk Factors for Lymph Node Metastasis in Bladder Cancer Tian, Zijian Meng, Lingfeng Wang, Xin Diao, Tongxiang Hu, Maolin Wang, Miao Zhang, Yaqun Liu, Ming Front Oncol Oncology Lymph node metastasis (LNM) is an important prognostic factor for bladder cancer (BCA) and determines the treatment strategy. This study aimed to determine related clinicopathological factors of LNM and analyze the prognosis of BCA. A total of 10,653 eligible patients with BCA were randomly divided into training or verification sets using the 2004–2015 data of the Surveillance, Epidemiology, and End Results database. To identify prognostic factors for the overall survival of BCA, we utilized the Cox proportional hazard model. Independent risk factors for LNM were evaluated via logistic regression analysis. T-stage, tumor grade, patient age and tumor size were identified as independent risk factors for LNM and were used to develop the LNM nomogram. The Kaplan-Meier method and competitive risk analyses were applied to establish the influence of lymph node status on BCA prognosis. The accuracy of LNM nomogram was evaluated in the training and verification sets. The areas under the receiver operating characteristic curve (AUC) showed an effective predictive accuracy of the nomogram in both the training (AUC: 0.690) and verification (AUC: 0.704) sets. In addition, the calibration curve indicated good consistency between the prediction of deviation correction and the ideal reference line. The decision curve analysis showed that the nomogram had a high clinical application value. In conclusion, our nomogram displayed high accuracy and reliability in predicting LNM. This could assist the selection of the optimal treatment for patients. Frontiers Media S.A. 2021-06-16 /pmc/articles/PMC8242250/ /pubmed/34222019 http://dx.doi.org/10.3389/fonc.2021.690324 Text en Copyright © 2021 Tian, Meng, Wang, Diao, Hu, Wang, Zhang and Liu 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 Tian, Zijian Meng, Lingfeng Wang, Xin Diao, Tongxiang Hu, Maolin Wang, Miao Zhang, Yaqun Liu, Ming Predictive Nomogram and Risk Factors for Lymph Node Metastasis in Bladder Cancer |
title | Predictive Nomogram and Risk Factors for Lymph Node Metastasis in Bladder Cancer |
title_full | Predictive Nomogram and Risk Factors for Lymph Node Metastasis in Bladder Cancer |
title_fullStr | Predictive Nomogram and Risk Factors for Lymph Node Metastasis in Bladder Cancer |
title_full_unstemmed | Predictive Nomogram and Risk Factors for Lymph Node Metastasis in Bladder Cancer |
title_short | Predictive Nomogram and Risk Factors for Lymph Node Metastasis in Bladder Cancer |
title_sort | predictive nomogram and risk factors for lymph node metastasis in bladder cancer |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8242250/ https://www.ncbi.nlm.nih.gov/pubmed/34222019 http://dx.doi.org/10.3389/fonc.2021.690324 |
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