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A Novel Prognostic Scoring Model Based on Albumin and γ-Glutamyltransferase for Hepatocellular Carcinoma Prognosis
AIM: To investigate the predictive value of albumin (ALB) and γ-glutamyltransferase (GGT) in hepatocellular carcinoma (HCC) patients undergoing curative resection. We sought to establish a new scoring model for predicting the prognosis of HCC patients undergoing curative resection. PATIENTS AND METH...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6934113/ https://www.ncbi.nlm.nih.gov/pubmed/31920379 http://dx.doi.org/10.2147/CMAR.S232073 |
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author | Wang, Liguang Li, Qun Zhang, Jie Lu, Jun |
author_facet | Wang, Liguang Li, Qun Zhang, Jie Lu, Jun |
author_sort | Wang, Liguang |
collection | PubMed |
description | AIM: To investigate the predictive value of albumin (ALB) and γ-glutamyltransferase (GGT) in hepatocellular carcinoma (HCC) patients undergoing curative resection. We sought to establish a new scoring model for predicting the prognosis of HCC patients undergoing curative resection. PATIENTS AND METHODS: A retrospective analysis was performed in 303 HCC patients who underwent curative resection. Preoperative risk factors for survival were investigated using univariate and multivariate analyses. On the basis of significant factors, a prognostic scoring model was established. The overall survival (OS) and recurrence-free survival (RFS) were compared between different groups. RESULTS: Multivariate Cox regression showed that preoperative decreased ALB levels and elevated GGT levels were significantly associated with poor OS and RFS. Multivariate analysis showed that ALB level, GGT level, portal vein tumor thrombus, and tumor number were independent prognostic factors for both OS and RFS. Thereafter, we established a preoperative prognostic scoring model combining the four risk factors. The results revealed that higher risk scores might mean worse OS and RFS. CONCLUSION: Preoperative ALB and GGT levels are potentially useful biomarkers for predicting the prognostic outcomes in HCC patients undergoing curative resection. Our new prognostic scoring model qualifies as a novel prognostic predictor for HCC patients after curative resection. |
format | Online Article Text |
id | pubmed-6934113 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-69341132020-01-09 A Novel Prognostic Scoring Model Based on Albumin and γ-Glutamyltransferase for Hepatocellular Carcinoma Prognosis Wang, Liguang Li, Qun Zhang, Jie Lu, Jun Cancer Manag Res Original Research AIM: To investigate the predictive value of albumin (ALB) and γ-glutamyltransferase (GGT) in hepatocellular carcinoma (HCC) patients undergoing curative resection. We sought to establish a new scoring model for predicting the prognosis of HCC patients undergoing curative resection. PATIENTS AND METHODS: A retrospective analysis was performed in 303 HCC patients who underwent curative resection. Preoperative risk factors for survival were investigated using univariate and multivariate analyses. On the basis of significant factors, a prognostic scoring model was established. The overall survival (OS) and recurrence-free survival (RFS) were compared between different groups. RESULTS: Multivariate Cox regression showed that preoperative decreased ALB levels and elevated GGT levels were significantly associated with poor OS and RFS. Multivariate analysis showed that ALB level, GGT level, portal vein tumor thrombus, and tumor number were independent prognostic factors for both OS and RFS. Thereafter, we established a preoperative prognostic scoring model combining the four risk factors. The results revealed that higher risk scores might mean worse OS and RFS. CONCLUSION: Preoperative ALB and GGT levels are potentially useful biomarkers for predicting the prognostic outcomes in HCC patients undergoing curative resection. Our new prognostic scoring model qualifies as a novel prognostic predictor for HCC patients after curative resection. Dove 2019-12-23 /pmc/articles/PMC6934113/ /pubmed/31920379 http://dx.doi.org/10.2147/CMAR.S232073 Text en © 2019 Wang et al. http://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/). 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 Wang, Liguang Li, Qun Zhang, Jie Lu, Jun A Novel Prognostic Scoring Model Based on Albumin and γ-Glutamyltransferase for Hepatocellular Carcinoma Prognosis |
title | A Novel Prognostic Scoring Model Based on Albumin and γ-Glutamyltransferase for Hepatocellular Carcinoma Prognosis |
title_full | A Novel Prognostic Scoring Model Based on Albumin and γ-Glutamyltransferase for Hepatocellular Carcinoma Prognosis |
title_fullStr | A Novel Prognostic Scoring Model Based on Albumin and γ-Glutamyltransferase for Hepatocellular Carcinoma Prognosis |
title_full_unstemmed | A Novel Prognostic Scoring Model Based on Albumin and γ-Glutamyltransferase for Hepatocellular Carcinoma Prognosis |
title_short | A Novel Prognostic Scoring Model Based on Albumin and γ-Glutamyltransferase for Hepatocellular Carcinoma Prognosis |
title_sort | novel prognostic scoring model based on albumin and γ-glutamyltransferase for hepatocellular carcinoma prognosis |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6934113/ https://www.ncbi.nlm.nih.gov/pubmed/31920379 http://dx.doi.org/10.2147/CMAR.S232073 |
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