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Nomogram for predicting preoperative regional lymph nodes metastasis in patients with metaplastic breast cancer: a SEER population-based study
BACKGROUND: Metaplastic breast cancer (MBC) is a rare subtype of breast cancer, and generally associated with poor outcomes. Lymph nodes metastasis (LNM) is confirmed as a critical independent prognostic factor and determine the optimal treatment strategies in MBC patients. We aimed to develop and v...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8130108/ https://www.ncbi.nlm.nih.gov/pubmed/34001061 http://dx.doi.org/10.1186/s12885-021-08313-6 |
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author | Zhang, Mi Wang, Biyuan Liu, Na Wang, Hui Zhang, Juan Wu, Lei Zhao, Andi Wang, Le Zhao, Xiaoai Yang, Jin |
author_facet | Zhang, Mi Wang, Biyuan Liu, Na Wang, Hui Zhang, Juan Wu, Lei Zhao, Andi Wang, Le Zhao, Xiaoai Yang, Jin |
author_sort | Zhang, Mi |
collection | PubMed |
description | BACKGROUND: Metaplastic breast cancer (MBC) is a rare subtype of breast cancer, and generally associated with poor outcomes. Lymph nodes metastasis (LNM) is confirmed as a critical independent prognostic factor and determine the optimal treatment strategies in MBC patients. We aimed to develop and validate a nomogram to predict the possibility of preoperative regional LNM in MBC patients. METHODS: MBC patients diagnosed between 1990 and 2016 in the Surveillance, Epidemiology, and End Results (SEER) database were included and stochastically divided into a training set and validation set at a ratio of 7:3. The risk variables of regional LNM in the training set were determined by univariate and multivariate logistic regression analyses. And then we integrated those risk factors to construct the nomogram. The prediction nomogram was further verified in the verification set. The discrimination, calibration and clinical utility of the nomogram were evaluated by the area under the receiver operating characteristic (ROC) curve (AUC), calibration plots and decision curve analysis (DCA), respectively. RESULTS: A total of 2205 female MBC patients were included in the study. Among the 2205 patients, 24.8% (546/2205) had positive regional lymph nodes. The nomogram for predicting the risk of regional LNM contained predictors of grade, estrogen receptor (ER) status and tumor size, with AUC of 0.683 (95% confidence interval (CI): 0.653–0.713) and 0.667 (95% CI: 0.621–0.712) in the training and validation sets, respectively. Calibration plots showed perfect agreement between actual and predicted regional LNM risks. At the same time, DCA of the nomogram demonstrated good clinical utilities. CONCLUSIONS: The nomogram established in this study showed excellent prediction ability, and could be used to preoperatively estimate the regional LNM risk in MBC. |
format | Online Article Text |
id | pubmed-8130108 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-81301082021-05-18 Nomogram for predicting preoperative regional lymph nodes metastasis in patients with metaplastic breast cancer: a SEER population-based study Zhang, Mi Wang, Biyuan Liu, Na Wang, Hui Zhang, Juan Wu, Lei Zhao, Andi Wang, Le Zhao, Xiaoai Yang, Jin BMC Cancer Research Article BACKGROUND: Metaplastic breast cancer (MBC) is a rare subtype of breast cancer, and generally associated with poor outcomes. Lymph nodes metastasis (LNM) is confirmed as a critical independent prognostic factor and determine the optimal treatment strategies in MBC patients. We aimed to develop and validate a nomogram to predict the possibility of preoperative regional LNM in MBC patients. METHODS: MBC patients diagnosed between 1990 and 2016 in the Surveillance, Epidemiology, and End Results (SEER) database were included and stochastically divided into a training set and validation set at a ratio of 7:3. The risk variables of regional LNM in the training set were determined by univariate and multivariate logistic regression analyses. And then we integrated those risk factors to construct the nomogram. The prediction nomogram was further verified in the verification set. The discrimination, calibration and clinical utility of the nomogram were evaluated by the area under the receiver operating characteristic (ROC) curve (AUC), calibration plots and decision curve analysis (DCA), respectively. RESULTS: A total of 2205 female MBC patients were included in the study. Among the 2205 patients, 24.8% (546/2205) had positive regional lymph nodes. The nomogram for predicting the risk of regional LNM contained predictors of grade, estrogen receptor (ER) status and tumor size, with AUC of 0.683 (95% confidence interval (CI): 0.653–0.713) and 0.667 (95% CI: 0.621–0.712) in the training and validation sets, respectively. Calibration plots showed perfect agreement between actual and predicted regional LNM risks. At the same time, DCA of the nomogram demonstrated good clinical utilities. CONCLUSIONS: The nomogram established in this study showed excellent prediction ability, and could be used to preoperatively estimate the regional LNM risk in MBC. BioMed Central 2021-05-17 /pmc/articles/PMC8130108/ /pubmed/34001061 http://dx.doi.org/10.1186/s12885-021-08313-6 Text en © The Author(s) 2021 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 Article Zhang, Mi Wang, Biyuan Liu, Na Wang, Hui Zhang, Juan Wu, Lei Zhao, Andi Wang, Le Zhao, Xiaoai Yang, Jin Nomogram for predicting preoperative regional lymph nodes metastasis in patients with metaplastic breast cancer: a SEER population-based study |
title | Nomogram for predicting preoperative regional lymph nodes metastasis in patients with metaplastic breast cancer: a SEER population-based study |
title_full | Nomogram for predicting preoperative regional lymph nodes metastasis in patients with metaplastic breast cancer: a SEER population-based study |
title_fullStr | Nomogram for predicting preoperative regional lymph nodes metastasis in patients with metaplastic breast cancer: a SEER population-based study |
title_full_unstemmed | Nomogram for predicting preoperative regional lymph nodes metastasis in patients with metaplastic breast cancer: a SEER population-based study |
title_short | Nomogram for predicting preoperative regional lymph nodes metastasis in patients with metaplastic breast cancer: a SEER population-based study |
title_sort | nomogram for predicting preoperative regional lymph nodes metastasis in patients with metaplastic breast cancer: a seer population-based study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8130108/ https://www.ncbi.nlm.nih.gov/pubmed/34001061 http://dx.doi.org/10.1186/s12885-021-08313-6 |
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