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Novel Nomograms Based on Gamma-Glutamyl Transpeptidase-to-Lymphocyte Ratio Predict Prognosis of Hepatocellular Carcinoma Patients After Hepatectomy
BACKGROUND: The prediction of prognosis of hepatocellular carcinoma (HCC) is of great significance in improving disease outcome and optimizing clinical management, while reliable prognostic indicators are lacking. This study was conducted to develop readily-to-use nomograms for prognosis prediction...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925392/ https://www.ncbi.nlm.nih.gov/pubmed/36798739 http://dx.doi.org/10.2147/JHC.S391755 |
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author | Ma, Cheng Cao, Yin Zhang, Guang Qiu, Jiannan Zhou, Yan Wang, Peng Wang, Shuo Yan, Dongliang Ma, Ding Jiang, Chunping Wang, Zhongxia |
author_facet | Ma, Cheng Cao, Yin Zhang, Guang Qiu, Jiannan Zhou, Yan Wang, Peng Wang, Shuo Yan, Dongliang Ma, Ding Jiang, Chunping Wang, Zhongxia |
author_sort | Ma, Cheng |
collection | PubMed |
description | BACKGROUND: The prediction of prognosis of hepatocellular carcinoma (HCC) is of great significance in improving disease outcome and optimizing clinical management, while reliable prognostic indicators are lacking. This study was conducted to develop readily-to-use nomograms for prognosis prediction of HCC after hepatectomy. MATERIALS AND METHODS: Data of eligible patients were collected and analyzed retrospectively. Independent prognostic factors were identified by Cox regression, and nomograms for the prediction of disease-free survival (DFS) and overall survival (OS) were developed. The performance of the nomograms was evaluated by receiver operating characteristics (ROC) curves, C-indexes and calibration curves and was verified by the validation cohort. The predictive value of the nomograms was also compared with the 8th edition of American Joint Committee on Cancer (AJCC) Tumor-Node-Metastasis (TNM) and the Barcelona Clinic Liver Cancer (BCLC) staging systems. RESULTS: In total, 599 patients were enrolled in the analysis: 420 in the training cohort and 179 in the validation cohort. The optimal cut-off value of Gamma-Glutamyl Transpeptidase-to-Lymphocyte Ratio (GLR) was 19.5. GLR contributed significantly to the nomograms with good predictive power. In ROC analyses, the areas under curve (AUCs) of the nomograms for 1-, 3- and 5-year DFS and OS prediction were 0.758, 0.756, 0.734 and 0.810, 0.799, 0.758, respectively. The C-indexes of the DFS nomogram were 0.697 (95% CI 0.665–0.729) in the training cohort and 0.710 (95% CI 0.664–0.756) in the validation cohort. For OS prediction, the C-indexes were 0.741 (95% CI 0.704–0.778) and 0.758 (95% CI 0.705–0.811) in the training and validation cohorts, respectively. The calibration curves demonstrated satisfactory agreement between nomogram predictions and actual observations. The nomograms demonstrated superior predictive performance to the TNM and the BCLC staging systems. CONCLUSION: Our novel nomograms showed adequate performance in the prediction of HCC prognosis after hepatectomy, which may facilitate the risk stratification and individualized management of HCC patients. |
format | Online Article Text |
id | pubmed-9925392 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-99253922023-02-15 Novel Nomograms Based on Gamma-Glutamyl Transpeptidase-to-Lymphocyte Ratio Predict Prognosis of Hepatocellular Carcinoma Patients After Hepatectomy Ma, Cheng Cao, Yin Zhang, Guang Qiu, Jiannan Zhou, Yan Wang, Peng Wang, Shuo Yan, Dongliang Ma, Ding Jiang, Chunping Wang, Zhongxia J Hepatocell Carcinoma Original Research BACKGROUND: The prediction of prognosis of hepatocellular carcinoma (HCC) is of great significance in improving disease outcome and optimizing clinical management, while reliable prognostic indicators are lacking. This study was conducted to develop readily-to-use nomograms for prognosis prediction of HCC after hepatectomy. MATERIALS AND METHODS: Data of eligible patients were collected and analyzed retrospectively. Independent prognostic factors were identified by Cox regression, and nomograms for the prediction of disease-free survival (DFS) and overall survival (OS) were developed. The performance of the nomograms was evaluated by receiver operating characteristics (ROC) curves, C-indexes and calibration curves and was verified by the validation cohort. The predictive value of the nomograms was also compared with the 8th edition of American Joint Committee on Cancer (AJCC) Tumor-Node-Metastasis (TNM) and the Barcelona Clinic Liver Cancer (BCLC) staging systems. RESULTS: In total, 599 patients were enrolled in the analysis: 420 in the training cohort and 179 in the validation cohort. The optimal cut-off value of Gamma-Glutamyl Transpeptidase-to-Lymphocyte Ratio (GLR) was 19.5. GLR contributed significantly to the nomograms with good predictive power. In ROC analyses, the areas under curve (AUCs) of the nomograms for 1-, 3- and 5-year DFS and OS prediction were 0.758, 0.756, 0.734 and 0.810, 0.799, 0.758, respectively. The C-indexes of the DFS nomogram were 0.697 (95% CI 0.665–0.729) in the training cohort and 0.710 (95% CI 0.664–0.756) in the validation cohort. For OS prediction, the C-indexes were 0.741 (95% CI 0.704–0.778) and 0.758 (95% CI 0.705–0.811) in the training and validation cohorts, respectively. The calibration curves demonstrated satisfactory agreement between nomogram predictions and actual observations. The nomograms demonstrated superior predictive performance to the TNM and the BCLC staging systems. CONCLUSION: Our novel nomograms showed adequate performance in the prediction of HCC prognosis after hepatectomy, which may facilitate the risk stratification and individualized management of HCC patients. Dove 2023-02-09 /pmc/articles/PMC9925392/ /pubmed/36798739 http://dx.doi.org/10.2147/JHC.S391755 Text en © 2023 Ma et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Ma, Cheng Cao, Yin Zhang, Guang Qiu, Jiannan Zhou, Yan Wang, Peng Wang, Shuo Yan, Dongliang Ma, Ding Jiang, Chunping Wang, Zhongxia Novel Nomograms Based on Gamma-Glutamyl Transpeptidase-to-Lymphocyte Ratio Predict Prognosis of Hepatocellular Carcinoma Patients After Hepatectomy |
title | Novel Nomograms Based on Gamma-Glutamyl Transpeptidase-to-Lymphocyte Ratio Predict Prognosis of Hepatocellular Carcinoma Patients After Hepatectomy |
title_full | Novel Nomograms Based on Gamma-Glutamyl Transpeptidase-to-Lymphocyte Ratio Predict Prognosis of Hepatocellular Carcinoma Patients After Hepatectomy |
title_fullStr | Novel Nomograms Based on Gamma-Glutamyl Transpeptidase-to-Lymphocyte Ratio Predict Prognosis of Hepatocellular Carcinoma Patients After Hepatectomy |
title_full_unstemmed | Novel Nomograms Based on Gamma-Glutamyl Transpeptidase-to-Lymphocyte Ratio Predict Prognosis of Hepatocellular Carcinoma Patients After Hepatectomy |
title_short | Novel Nomograms Based on Gamma-Glutamyl Transpeptidase-to-Lymphocyte Ratio Predict Prognosis of Hepatocellular Carcinoma Patients After Hepatectomy |
title_sort | novel nomograms based on gamma-glutamyl transpeptidase-to-lymphocyte ratio predict prognosis of hepatocellular carcinoma patients after hepatectomy |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925392/ https://www.ncbi.nlm.nih.gov/pubmed/36798739 http://dx.doi.org/10.2147/JHC.S391755 |
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