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Nomogram predict relapse-free survival of patients with thymic epithelial tumors after surgery
BACKGROUND: Hematological indicators and clinical characteristics play an important role in the evaluation of the progression and prognosis of thymic epithelial tumors. Therefore, we aimed to combine these potential indicators to establish a prognostic nomogram to determine the relapse-free survival...
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/PMC8299634/ https://www.ncbi.nlm.nih.gov/pubmed/34294070 http://dx.doi.org/10.1186/s12885-021-08585-y |
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author | Huang, Yang-Yu Wu, Lei-Lei Liu, Xuan Liang, Shen-Hua Ma, Guo-Wei |
author_facet | Huang, Yang-Yu Wu, Lei-Lei Liu, Xuan Liang, Shen-Hua Ma, Guo-Wei |
author_sort | Huang, Yang-Yu |
collection | PubMed |
description | BACKGROUND: Hematological indicators and clinical characteristics play an important role in the evaluation of the progression and prognosis of thymic epithelial tumors. Therefore, we aimed to combine these potential indicators to establish a prognostic nomogram to determine the relapse-free survival (RFS) of patients with thymic epithelial tumors undergoing thymectomy. METHODS: This retrospective study was conducted on 156 patients who underwent thymectomy between May 2004 and August 2015. Cox regression analysis were performed to determine the potential indicators related to prognosis and combine these indicators to create a nomogram for visual prediction. The prognostic predictive ability of the nomogram was evaluated using the consistency index (C-index), receiver operating characteristic (ROC) curve, and risk stratification. Decision curve analysis was used to evaluate the net benefits of the model. RESULTS: Preoperative albumin levels, neutrophil-to-lymphocyte ratio (NLR), T stage, and WHO histologic types were included in the nomogram. In the training cohort, the nomogram showed well prognostic ability (C index: 0.902). Calibration curves for the relapse-free survival (RFS) were in good agreement with the standard lines in training and validation cohorts. CONCLUSIONS: Combining clinical and hematologic factors, the nomogram performed well in predicting the prognosis and the relapse-free survival of this patient population. And it has potential to identify high-risk patients at an early stage. This is a relatively novel approach for the prediction of RFS in this patient population. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-08585-y. |
format | Online Article Text |
id | pubmed-8299634 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-82996342021-07-28 Nomogram predict relapse-free survival of patients with thymic epithelial tumors after surgery Huang, Yang-Yu Wu, Lei-Lei Liu, Xuan Liang, Shen-Hua Ma, Guo-Wei BMC Cancer Research BACKGROUND: Hematological indicators and clinical characteristics play an important role in the evaluation of the progression and prognosis of thymic epithelial tumors. Therefore, we aimed to combine these potential indicators to establish a prognostic nomogram to determine the relapse-free survival (RFS) of patients with thymic epithelial tumors undergoing thymectomy. METHODS: This retrospective study was conducted on 156 patients who underwent thymectomy between May 2004 and August 2015. Cox regression analysis were performed to determine the potential indicators related to prognosis and combine these indicators to create a nomogram for visual prediction. The prognostic predictive ability of the nomogram was evaluated using the consistency index (C-index), receiver operating characteristic (ROC) curve, and risk stratification. Decision curve analysis was used to evaluate the net benefits of the model. RESULTS: Preoperative albumin levels, neutrophil-to-lymphocyte ratio (NLR), T stage, and WHO histologic types were included in the nomogram. In the training cohort, the nomogram showed well prognostic ability (C index: 0.902). Calibration curves for the relapse-free survival (RFS) were in good agreement with the standard lines in training and validation cohorts. CONCLUSIONS: Combining clinical and hematologic factors, the nomogram performed well in predicting the prognosis and the relapse-free survival of this patient population. And it has potential to identify high-risk patients at an early stage. This is a relatively novel approach for the prediction of RFS in this patient population. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-08585-y. BioMed Central 2021-07-22 /pmc/articles/PMC8299634/ /pubmed/34294070 http://dx.doi.org/10.1186/s12885-021-08585-y 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 Huang, Yang-Yu Wu, Lei-Lei Liu, Xuan Liang, Shen-Hua Ma, Guo-Wei Nomogram predict relapse-free survival of patients with thymic epithelial tumors after surgery |
title | Nomogram predict relapse-free survival of patients with thymic epithelial tumors after surgery |
title_full | Nomogram predict relapse-free survival of patients with thymic epithelial tumors after surgery |
title_fullStr | Nomogram predict relapse-free survival of patients with thymic epithelial tumors after surgery |
title_full_unstemmed | Nomogram predict relapse-free survival of patients with thymic epithelial tumors after surgery |
title_short | Nomogram predict relapse-free survival of patients with thymic epithelial tumors after surgery |
title_sort | nomogram predict relapse-free survival of patients with thymic epithelial tumors after surgery |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8299634/ https://www.ncbi.nlm.nih.gov/pubmed/34294070 http://dx.doi.org/10.1186/s12885-021-08585-y |
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