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Prognostic nomograms for patients with resectable hepatocelluar carcinoma incorporating systemic inflammation and tumor characteristics
BACKGROUND: The model to predict the prognosis of resectable hepatocelluar carcinoma (HCC) has not been determined. METHODS: Predictors were selected using Cox model. Nomograms were generated in the training set and validated in the validation set. The predictive ability of the nomogram was determin...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5348354/ https://www.ncbi.nlm.nih.gov/pubmed/27811374 http://dx.doi.org/10.18632/oncotarget.13038 |
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author | Shen, Junyi He, Linye Li, Chuan Wen, Tianfu Chen, Weixia Lu, Changli Yan, Lvnan Li, Bo Yang, Jiayin |
author_facet | Shen, Junyi He, Linye Li, Chuan Wen, Tianfu Chen, Weixia Lu, Changli Yan, Lvnan Li, Bo Yang, Jiayin |
author_sort | Shen, Junyi |
collection | PubMed |
description | BACKGROUND: The model to predict the prognosis of resectable hepatocelluar carcinoma (HCC) has not been determined. METHODS: Predictors were selected using Cox model. Nomograms were generated in the training set and validated in the validation set. The predictive ability of the nomogram was determined by concordance index and calibration curve. RESULTS: Independent factors for overall survival including alpha-fetoprotein level (hazard ratio (HR):1.292), tumor size (HR:1.092), tumor number (HR:1.472), microvascular invasion (HR:1.660), neutrophil to lymphocyte count ratio (NLR) (HR:1.428), major vascular invasion (HR:2.485) and satellite lesions(HR:1.392) were selected into the nomogram for survival. The c-index in the training set and validation set were 0.767 and 0.719, respectively, which were statistically higher than those of the four conventional staging systems.(Barcelona Clinic Liver Cancer: 0.644 and 0.609; the seventh American Joint Committee on Cancer: 0.678 and 0.674; Cancer of the Liver Italian Program: 0.692 and 0.648; Hong Kong Liver Cancer: 0.689 and 0.639, p < 0.001 for all). A nomogram for predicting 3- and 5-year recurrence free survival was generated with the c-index of 0.746 for the training set and 0.718 for the validation set, respectively. CONCLUSIONS: We have generated nomograms predicting prognosis for HCC treated by hepatectomy with a higher predictive power. |
format | Online Article Text |
id | pubmed-5348354 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-53483542017-03-31 Prognostic nomograms for patients with resectable hepatocelluar carcinoma incorporating systemic inflammation and tumor characteristics Shen, Junyi He, Linye Li, Chuan Wen, Tianfu Chen, Weixia Lu, Changli Yan, Lvnan Li, Bo Yang, Jiayin Oncotarget Research Paper BACKGROUND: The model to predict the prognosis of resectable hepatocelluar carcinoma (HCC) has not been determined. METHODS: Predictors were selected using Cox model. Nomograms were generated in the training set and validated in the validation set. The predictive ability of the nomogram was determined by concordance index and calibration curve. RESULTS: Independent factors for overall survival including alpha-fetoprotein level (hazard ratio (HR):1.292), tumor size (HR:1.092), tumor number (HR:1.472), microvascular invasion (HR:1.660), neutrophil to lymphocyte count ratio (NLR) (HR:1.428), major vascular invasion (HR:2.485) and satellite lesions(HR:1.392) were selected into the nomogram for survival. The c-index in the training set and validation set were 0.767 and 0.719, respectively, which were statistically higher than those of the four conventional staging systems.(Barcelona Clinic Liver Cancer: 0.644 and 0.609; the seventh American Joint Committee on Cancer: 0.678 and 0.674; Cancer of the Liver Italian Program: 0.692 and 0.648; Hong Kong Liver Cancer: 0.689 and 0.639, p < 0.001 for all). A nomogram for predicting 3- and 5-year recurrence free survival was generated with the c-index of 0.746 for the training set and 0.718 for the validation set, respectively. CONCLUSIONS: We have generated nomograms predicting prognosis for HCC treated by hepatectomy with a higher predictive power. Impact Journals LLC 2016-11-03 /pmc/articles/PMC5348354/ /pubmed/27811374 http://dx.doi.org/10.18632/oncotarget.13038 Text en Copyright: © 2016 Shen et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Shen, Junyi He, Linye Li, Chuan Wen, Tianfu Chen, Weixia Lu, Changli Yan, Lvnan Li, Bo Yang, Jiayin Prognostic nomograms for patients with resectable hepatocelluar carcinoma incorporating systemic inflammation and tumor characteristics |
title | Prognostic nomograms for patients with resectable hepatocelluar carcinoma incorporating systemic inflammation and tumor characteristics |
title_full | Prognostic nomograms for patients with resectable hepatocelluar carcinoma incorporating systemic inflammation and tumor characteristics |
title_fullStr | Prognostic nomograms for patients with resectable hepatocelluar carcinoma incorporating systemic inflammation and tumor characteristics |
title_full_unstemmed | Prognostic nomograms for patients with resectable hepatocelluar carcinoma incorporating systemic inflammation and tumor characteristics |
title_short | Prognostic nomograms for patients with resectable hepatocelluar carcinoma incorporating systemic inflammation and tumor characteristics |
title_sort | prognostic nomograms for patients with resectable hepatocelluar carcinoma incorporating systemic inflammation and tumor characteristics |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5348354/ https://www.ncbi.nlm.nih.gov/pubmed/27811374 http://dx.doi.org/10.18632/oncotarget.13038 |
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