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A model for predicting overall survival in bladder cancer patients with signet ring cell carcinoma: a population-based study

INTRODUCTION: This study is to examine the predictors of survival and to construct a nomogram for predicting the overall survival (OS) of primary bladder signet ring cell carcinoma (SRCC) patients based on the analysis of the Surveillance, Epidemiology, and End Results (SEER) database. METHODS: A to...

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Autores principales: Liu, Liang, Li, Chuangui, Wang, Qiang, Yuan, Haibo, Wang, Yuanyuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9893594/
https://www.ncbi.nlm.nih.gov/pubmed/36732873
http://dx.doi.org/10.1186/s40001-022-00970-y
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author Liu, Liang
Li, Chuangui
Wang, Qiang
Yuan, Haibo
Wang, Yuanyuan
author_facet Liu, Liang
Li, Chuangui
Wang, Qiang
Yuan, Haibo
Wang, Yuanyuan
author_sort Liu, Liang
collection PubMed
description INTRODUCTION: This study is to examine the predictors of survival and to construct a nomogram for predicting the overall survival (OS) of primary bladder signet ring cell carcinoma (SRCC) patients based on the analysis of the Surveillance, Epidemiology, and End Results (SEER) database. METHODS: A total of 219 eligible patients diagnosed with SRCC were analyzed using the 2004–2015 data from SEER database. Univariate and multivariate Cox regression were used to determine independent prognostic factors, followed by development of a nomogram based on the multivariate Cox regression models. The consistency index (C-index), receiver operating characteristic (ROC) curve, and calibration curve were used to validate the prognostic nomogram. RESULTS: The nomograms indicated appreciable accuracy in predicting the OS, with C-index of 0.771 and 0.715, respectively. The area under the curve (AUC) of the nomogram was 0.713 for 1 year, 0.742 for 3 years, and 0.776 for 5 years in the training set, while was 0.730 for 1 year, 0.727 for 3 years, and 0.697 for 5 years in the validation set. The calibration curves revealed satisfactory consistency between the prediction of deviation correction and ideal reference line. CONCLUSIONS: The prognostic nomogram developed in the analytical data of SEER it provided high accuracy and reliability in predicting the survival outcomes of primary bladder SRCC patients and could be used to comprehensively assess the risk of SRCC. Moreover, they could enable clinicians to make more precise treatment decisions for primary bladder SRCC patients.
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spelling pubmed-98935942023-02-03 A model for predicting overall survival in bladder cancer patients with signet ring cell carcinoma: a population-based study Liu, Liang Li, Chuangui Wang, Qiang Yuan, Haibo Wang, Yuanyuan Eur J Med Res Research INTRODUCTION: This study is to examine the predictors of survival and to construct a nomogram for predicting the overall survival (OS) of primary bladder signet ring cell carcinoma (SRCC) patients based on the analysis of the Surveillance, Epidemiology, and End Results (SEER) database. METHODS: A total of 219 eligible patients diagnosed with SRCC were analyzed using the 2004–2015 data from SEER database. Univariate and multivariate Cox regression were used to determine independent prognostic factors, followed by development of a nomogram based on the multivariate Cox regression models. The consistency index (C-index), receiver operating characteristic (ROC) curve, and calibration curve were used to validate the prognostic nomogram. RESULTS: The nomograms indicated appreciable accuracy in predicting the OS, with C-index of 0.771 and 0.715, respectively. The area under the curve (AUC) of the nomogram was 0.713 for 1 year, 0.742 for 3 years, and 0.776 for 5 years in the training set, while was 0.730 for 1 year, 0.727 for 3 years, and 0.697 for 5 years in the validation set. The calibration curves revealed satisfactory consistency between the prediction of deviation correction and ideal reference line. CONCLUSIONS: The prognostic nomogram developed in the analytical data of SEER it provided high accuracy and reliability in predicting the survival outcomes of primary bladder SRCC patients and could be used to comprehensively assess the risk of SRCC. Moreover, they could enable clinicians to make more precise treatment decisions for primary bladder SRCC patients. BioMed Central 2023-02-02 /pmc/articles/PMC9893594/ /pubmed/36732873 http://dx.doi.org/10.1186/s40001-022-00970-y Text en © The Author(s) 2023 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
Liu, Liang
Li, Chuangui
Wang, Qiang
Yuan, Haibo
Wang, Yuanyuan
A model for predicting overall survival in bladder cancer patients with signet ring cell carcinoma: a population-based study
title A model for predicting overall survival in bladder cancer patients with signet ring cell carcinoma: a population-based study
title_full A model for predicting overall survival in bladder cancer patients with signet ring cell carcinoma: a population-based study
title_fullStr A model for predicting overall survival in bladder cancer patients with signet ring cell carcinoma: a population-based study
title_full_unstemmed A model for predicting overall survival in bladder cancer patients with signet ring cell carcinoma: a population-based study
title_short A model for predicting overall survival in bladder cancer patients with signet ring cell carcinoma: a population-based study
title_sort model for predicting overall survival in bladder cancer patients with signet ring cell carcinoma: a population-based study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9893594/
https://www.ncbi.nlm.nih.gov/pubmed/36732873
http://dx.doi.org/10.1186/s40001-022-00970-y
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