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Integrated nomograms to predict overall survival and recurrence-free survival in patients with combined hepatocellular cholangiocarcinoma (cHCC) after liver resection
The current clinical classification of primary liver cancer is unable to efficiently predict the prognosis of combined hepatocellular cholangiocarcinoma (cHCC). Accurate satellite nodules (SAT) and microvascular invasion (MVI) prediction in cHCC patients is very important for treatment decision maki...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7467372/ https://www.ncbi.nlm.nih.gov/pubmed/32788423 http://dx.doi.org/10.18632/aging.103577 |
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author | Wang, Tao Yang, Xianwei Tang, Huairong Kong, Junjie Shen, Shu Qiu, Haizhou Wang, Wentao |
author_facet | Wang, Tao Yang, Xianwei Tang, Huairong Kong, Junjie Shen, Shu Qiu, Haizhou Wang, Wentao |
author_sort | Wang, Tao |
collection | PubMed |
description | The current clinical classification of primary liver cancer is unable to efficiently predict the prognosis of combined hepatocellular cholangiocarcinoma (cHCC). Accurate satellite nodules (SAT) and microvascular invasion (MVI) prediction in cHCC patients is very important for treatment decision making and prognostic evaluation. The aim of this work was to explore important factors affecting the prognosis of cHCC patients after liver resection and to develop preoperative nomograms to predict SAT and MVI in cHCC patients. The nomogram was developed using the data from 148 patients who underwent liver resection for cHCC patients at our hospital between January 2006 and December 2014. Based on the results of the multivariate analysis, a nomogram integrating all significant independent factors affecting overall survival and recurrence-free survival was constructed to predict the prognosis of cHCC. Next, risk factors for SAT and MVI were evaluated with logistic regression. Blood signatures were established using the LASSO regression, and then, we combined the clinical risk factors and blood signatures of the patients to establish predictive models for SAT and MVI. The C-index of the nomogram for predicting survival was 0.685 (95% CI, 0.638 to 0.732), which was significantly higher than the C-index for other liver cancer classification systems. |
format | Online Article Text |
id | pubmed-7467372 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-74673722020-09-14 Integrated nomograms to predict overall survival and recurrence-free survival in patients with combined hepatocellular cholangiocarcinoma (cHCC) after liver resection Wang, Tao Yang, Xianwei Tang, Huairong Kong, Junjie Shen, Shu Qiu, Haizhou Wang, Wentao Aging (Albany NY) Research Paper The current clinical classification of primary liver cancer is unable to efficiently predict the prognosis of combined hepatocellular cholangiocarcinoma (cHCC). Accurate satellite nodules (SAT) and microvascular invasion (MVI) prediction in cHCC patients is very important for treatment decision making and prognostic evaluation. The aim of this work was to explore important factors affecting the prognosis of cHCC patients after liver resection and to develop preoperative nomograms to predict SAT and MVI in cHCC patients. The nomogram was developed using the data from 148 patients who underwent liver resection for cHCC patients at our hospital between January 2006 and December 2014. Based on the results of the multivariate analysis, a nomogram integrating all significant independent factors affecting overall survival and recurrence-free survival was constructed to predict the prognosis of cHCC. Next, risk factors for SAT and MVI were evaluated with logistic regression. Blood signatures were established using the LASSO regression, and then, we combined the clinical risk factors and blood signatures of the patients to establish predictive models for SAT and MVI. The C-index of the nomogram for predicting survival was 0.685 (95% CI, 0.638 to 0.732), which was significantly higher than the C-index for other liver cancer classification systems. Impact Journals 2020-08-13 /pmc/articles/PMC7467372/ /pubmed/32788423 http://dx.doi.org/10.18632/aging.103577 Text en Copyright © 2020 Wang 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 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Wang, Tao Yang, Xianwei Tang, Huairong Kong, Junjie Shen, Shu Qiu, Haizhou Wang, Wentao Integrated nomograms to predict overall survival and recurrence-free survival in patients with combined hepatocellular cholangiocarcinoma (cHCC) after liver resection |
title | Integrated nomograms to predict overall survival and recurrence-free survival in patients with combined hepatocellular cholangiocarcinoma (cHCC) after liver resection |
title_full | Integrated nomograms to predict overall survival and recurrence-free survival in patients with combined hepatocellular cholangiocarcinoma (cHCC) after liver resection |
title_fullStr | Integrated nomograms to predict overall survival and recurrence-free survival in patients with combined hepatocellular cholangiocarcinoma (cHCC) after liver resection |
title_full_unstemmed | Integrated nomograms to predict overall survival and recurrence-free survival in patients with combined hepatocellular cholangiocarcinoma (cHCC) after liver resection |
title_short | Integrated nomograms to predict overall survival and recurrence-free survival in patients with combined hepatocellular cholangiocarcinoma (cHCC) after liver resection |
title_sort | integrated nomograms to predict overall survival and recurrence-free survival in patients with combined hepatocellular cholangiocarcinoma (chcc) after liver resection |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7467372/ https://www.ncbi.nlm.nih.gov/pubmed/32788423 http://dx.doi.org/10.18632/aging.103577 |
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