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A sample model established by S-index predicting overall survival after curative resection of primary hepatocellular carcinoma

PURPOSE: Prognostic prediction after curative resection of primary hepatocellular carcinoma (PHCC) remains an arduous task. The S-index calculated from γ-glutamyl transpeptidase, albumin, and platelets is reported to predict the severity of liver fibrosis. We constructed a nomogram for predicting th...

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Autores principales: Chen, Lei, Cai, Bin-Bin, Zhou, Chao-Jun, Hou, Xiang-Qing, Hu, Si-Pin, Fang, Guan, Chen, Wen-Chao, Li, Lin-Hui, Yang, Wen-Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6338126/
https://www.ncbi.nlm.nih.gov/pubmed/30679923
http://dx.doi.org/10.2147/CMAR.S193593
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author Chen, Lei
Cai, Bin-Bin
Zhou, Chao-Jun
Hou, Xiang-Qing
Hu, Si-Pin
Fang, Guan
Chen, Wen-Chao
Li, Lin-Hui
Yang, Wen-Jun
author_facet Chen, Lei
Cai, Bin-Bin
Zhou, Chao-Jun
Hou, Xiang-Qing
Hu, Si-Pin
Fang, Guan
Chen, Wen-Chao
Li, Lin-Hui
Yang, Wen-Jun
author_sort Chen, Lei
collection PubMed
description PURPOSE: Prognostic prediction after curative resection of primary hepatocellular carcinoma (PHCC) remains an arduous task. The S-index calculated from γ-glutamyl transpeptidase, albumin, and platelets is reported to predict the severity of liver fibrosis. We constructed a nomogram for predicting the survival probability of PHCC based on a new indicator, the S-index, combined with other routine clinical parameters. PATIENTS AND METHODS: We selected 490 patients with PHCC postradical surgery at the First Affiliated Hospital of Wenzhou Medical University between January 2007 and January 2014. The subjects were randomly allocated into the training cohort and the validation cohort in the ratio 7:3 by the digital method. Important variables screened by univariate analysis were included in multivariate analysis to obtain independent risk factors for predicting the prognosis of PHCC. The construction of the nomogram was based on Cox proportional hazard regression models. The concordance index (C-index) was used in the nomogram for evaluating the model performance for prognosis. We drew time-dependent receiver operating characteristic curves to compare our model with other staging systems. RESULTS: The nomogram based on six independent risk factors after multivariate analyses had good predictive power after radical surgery of PHCC. In the training and validation groups, the C-index of the nomogram was highly consistent for evaluating survival from PHCC. Compared with the traditional scoring system, the areas under time-dependent receiver operating characteristic curves were 0.7382, 0.7293, and 0.7520 for 1-, 3-, and 5-year overall survival, respectively. In summary, the nomogram showed excellent results in terms of prognosis of PHCC. CONCLUSION: Based on the S-index and the other clinical indicators, we developed a precise nomogram that predicts the survival probability of patients with PHCC after radical surgery. This tool can provide effective information for surgeons and patients.
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spelling pubmed-63381262019-01-24 A sample model established by S-index predicting overall survival after curative resection of primary hepatocellular carcinoma Chen, Lei Cai, Bin-Bin Zhou, Chao-Jun Hou, Xiang-Qing Hu, Si-Pin Fang, Guan Chen, Wen-Chao Li, Lin-Hui Yang, Wen-Jun Cancer Manag Res Original Research PURPOSE: Prognostic prediction after curative resection of primary hepatocellular carcinoma (PHCC) remains an arduous task. The S-index calculated from γ-glutamyl transpeptidase, albumin, and platelets is reported to predict the severity of liver fibrosis. We constructed a nomogram for predicting the survival probability of PHCC based on a new indicator, the S-index, combined with other routine clinical parameters. PATIENTS AND METHODS: We selected 490 patients with PHCC postradical surgery at the First Affiliated Hospital of Wenzhou Medical University between January 2007 and January 2014. The subjects were randomly allocated into the training cohort and the validation cohort in the ratio 7:3 by the digital method. Important variables screened by univariate analysis were included in multivariate analysis to obtain independent risk factors for predicting the prognosis of PHCC. The construction of the nomogram was based on Cox proportional hazard regression models. The concordance index (C-index) was used in the nomogram for evaluating the model performance for prognosis. We drew time-dependent receiver operating characteristic curves to compare our model with other staging systems. RESULTS: The nomogram based on six independent risk factors after multivariate analyses had good predictive power after radical surgery of PHCC. In the training and validation groups, the C-index of the nomogram was highly consistent for evaluating survival from PHCC. Compared with the traditional scoring system, the areas under time-dependent receiver operating characteristic curves were 0.7382, 0.7293, and 0.7520 for 1-, 3-, and 5-year overall survival, respectively. In summary, the nomogram showed excellent results in terms of prognosis of PHCC. CONCLUSION: Based on the S-index and the other clinical indicators, we developed a precise nomogram that predicts the survival probability of patients with PHCC after radical surgery. This tool can provide effective information for surgeons and patients. Dove Medical Press 2019-01-14 /pmc/articles/PMC6338126/ /pubmed/30679923 http://dx.doi.org/10.2147/CMAR.S193593 Text en © 2019 Chen et al. 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.
spellingShingle Original Research
Chen, Lei
Cai, Bin-Bin
Zhou, Chao-Jun
Hou, Xiang-Qing
Hu, Si-Pin
Fang, Guan
Chen, Wen-Chao
Li, Lin-Hui
Yang, Wen-Jun
A sample model established by S-index predicting overall survival after curative resection of primary hepatocellular carcinoma
title A sample model established by S-index predicting overall survival after curative resection of primary hepatocellular carcinoma
title_full A sample model established by S-index predicting overall survival after curative resection of primary hepatocellular carcinoma
title_fullStr A sample model established by S-index predicting overall survival after curative resection of primary hepatocellular carcinoma
title_full_unstemmed A sample model established by S-index predicting overall survival after curative resection of primary hepatocellular carcinoma
title_short A sample model established by S-index predicting overall survival after curative resection of primary hepatocellular carcinoma
title_sort sample model established by s-index predicting overall survival after curative resection of primary hepatocellular carcinoma
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6338126/
https://www.ncbi.nlm.nih.gov/pubmed/30679923
http://dx.doi.org/10.2147/CMAR.S193593
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