Cargando…

A model combining TNM stage and tumor size shows utility in predicting recurrence among patients with hepatocellular carcinoma after resection

OBJECTIVE: Hepatocellular carcinoma (HCC) recurrence is a clinical challenge. An accurate prediction system for patients with HCC is needed, since the choice of HCC treatment strategies is very important. PATIENTS AND METHODS: A total of 804 patients with HCC who underwent curative resection at Sun...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Yu, Chen, Shu-wei, Liu, Li-li, Yang, Xia, Cai, Shao-hang, Yun, Jing-ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6159804/
https://www.ncbi.nlm.nih.gov/pubmed/30288102
http://dx.doi.org/10.2147/CMAR.S175303
_version_ 1783358660655710208
author Zhang, Yu
Chen, Shu-wei
Liu, Li-li
Yang, Xia
Cai, Shao-hang
Yun, Jing-ping
author_facet Zhang, Yu
Chen, Shu-wei
Liu, Li-li
Yang, Xia
Cai, Shao-hang
Yun, Jing-ping
author_sort Zhang, Yu
collection PubMed
description OBJECTIVE: Hepatocellular carcinoma (HCC) recurrence is a clinical challenge. An accurate prediction system for patients with HCC is needed, since the choice of HCC treatment strategies is very important. PATIENTS AND METHODS: A total of 804 patients with HCC who underwent curative resection at Sun Yat-sen University Cancer Center were included in this study. Demographics, clinicopathological data, and follow-up information were collected. RESULTS: A logistic regression analysis was conducted to investigate the relationships between clinical features and HCC recurrence. Tumor size (OR=1.454, 95% CI: 1.047–2.020, P=0.026) and TNM stage (OR=1.360, 95% CI: 1.021–1.813, P=0.036) were independent predictors of HCC recurrence after curative resection. Therefore, the following equation was established to predict HCC recurrence: 0.308×TNM+0.374×tumor size–0.639. The equation score was 0.53±0.23 in patients who experienced HCC recurrence compared with 0.47±0.24 in other patients. A similar trend was observed in patients who survived after the last follow-up, compared with those who did not, with scores of 0.37±0.26 vs 0.52±0.22, respectively (P<0.001). The Kaplan–Meier analysis showed that patients with HCC with equation values >0.5 had significantly worse outcomes than those with equation values ≤0.5 (P<0.001) for overall survival (OS) and recurrence (P=0.043). Multivariate Cox analyses showed that tumor multiplicity (P=0.039), involucrum (P=0.029), vascular invasion (P<0.001), and equation value (P<0.001) were independent prognostic variables for OS, whereas tumor multiplicity (P=0.01), tumor differentiation (P=0.007), vascular invasion (P<0.001), involucrum (P=0.01), and equation value (P<0.001) were independent prognostic variables for HCC recurrence. CONCLUSION: We established a novel and effective equation for predicting the probability of recurrence and OS after curative resection. Patients with a high recurrence score, based on this equation, should undergo additional high-end imaging examinations.
format Online
Article
Text
id pubmed-6159804
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Dove Medical Press
record_format MEDLINE/PubMed
spelling pubmed-61598042018-10-04 A model combining TNM stage and tumor size shows utility in predicting recurrence among patients with hepatocellular carcinoma after resection Zhang, Yu Chen, Shu-wei Liu, Li-li Yang, Xia Cai, Shao-hang Yun, Jing-ping Cancer Manag Res Original Research OBJECTIVE: Hepatocellular carcinoma (HCC) recurrence is a clinical challenge. An accurate prediction system for patients with HCC is needed, since the choice of HCC treatment strategies is very important. PATIENTS AND METHODS: A total of 804 patients with HCC who underwent curative resection at Sun Yat-sen University Cancer Center were included in this study. Demographics, clinicopathological data, and follow-up information were collected. RESULTS: A logistic regression analysis was conducted to investigate the relationships between clinical features and HCC recurrence. Tumor size (OR=1.454, 95% CI: 1.047–2.020, P=0.026) and TNM stage (OR=1.360, 95% CI: 1.021–1.813, P=0.036) were independent predictors of HCC recurrence after curative resection. Therefore, the following equation was established to predict HCC recurrence: 0.308×TNM+0.374×tumor size–0.639. The equation score was 0.53±0.23 in patients who experienced HCC recurrence compared with 0.47±0.24 in other patients. A similar trend was observed in patients who survived after the last follow-up, compared with those who did not, with scores of 0.37±0.26 vs 0.52±0.22, respectively (P<0.001). The Kaplan–Meier analysis showed that patients with HCC with equation values >0.5 had significantly worse outcomes than those with equation values ≤0.5 (P<0.001) for overall survival (OS) and recurrence (P=0.043). Multivariate Cox analyses showed that tumor multiplicity (P=0.039), involucrum (P=0.029), vascular invasion (P<0.001), and equation value (P<0.001) were independent prognostic variables for OS, whereas tumor multiplicity (P=0.01), tumor differentiation (P=0.007), vascular invasion (P<0.001), involucrum (P=0.01), and equation value (P<0.001) were independent prognostic variables for HCC recurrence. CONCLUSION: We established a novel and effective equation for predicting the probability of recurrence and OS after curative resection. Patients with a high recurrence score, based on this equation, should undergo additional high-end imaging examinations. Dove Medical Press 2018-09-20 /pmc/articles/PMC6159804/ /pubmed/30288102 http://dx.doi.org/10.2147/CMAR.S175303 Text en © 2018 Zhang 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
Zhang, Yu
Chen, Shu-wei
Liu, Li-li
Yang, Xia
Cai, Shao-hang
Yun, Jing-ping
A model combining TNM stage and tumor size shows utility in predicting recurrence among patients with hepatocellular carcinoma after resection
title A model combining TNM stage and tumor size shows utility in predicting recurrence among patients with hepatocellular carcinoma after resection
title_full A model combining TNM stage and tumor size shows utility in predicting recurrence among patients with hepatocellular carcinoma after resection
title_fullStr A model combining TNM stage and tumor size shows utility in predicting recurrence among patients with hepatocellular carcinoma after resection
title_full_unstemmed A model combining TNM stage and tumor size shows utility in predicting recurrence among patients with hepatocellular carcinoma after resection
title_short A model combining TNM stage and tumor size shows utility in predicting recurrence among patients with hepatocellular carcinoma after resection
title_sort model combining tnm stage and tumor size shows utility in predicting recurrence among patients with hepatocellular carcinoma after resection
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6159804/
https://www.ncbi.nlm.nih.gov/pubmed/30288102
http://dx.doi.org/10.2147/CMAR.S175303
work_keys_str_mv AT zhangyu amodelcombiningtnmstageandtumorsizeshowsutilityinpredictingrecurrenceamongpatientswithhepatocellularcarcinomaafterresection
AT chenshuwei amodelcombiningtnmstageandtumorsizeshowsutilityinpredictingrecurrenceamongpatientswithhepatocellularcarcinomaafterresection
AT liulili amodelcombiningtnmstageandtumorsizeshowsutilityinpredictingrecurrenceamongpatientswithhepatocellularcarcinomaafterresection
AT yangxia amodelcombiningtnmstageandtumorsizeshowsutilityinpredictingrecurrenceamongpatientswithhepatocellularcarcinomaafterresection
AT caishaohang amodelcombiningtnmstageandtumorsizeshowsutilityinpredictingrecurrenceamongpatientswithhepatocellularcarcinomaafterresection
AT yunjingping amodelcombiningtnmstageandtumorsizeshowsutilityinpredictingrecurrenceamongpatientswithhepatocellularcarcinomaafterresection
AT zhangyu modelcombiningtnmstageandtumorsizeshowsutilityinpredictingrecurrenceamongpatientswithhepatocellularcarcinomaafterresection
AT chenshuwei modelcombiningtnmstageandtumorsizeshowsutilityinpredictingrecurrenceamongpatientswithhepatocellularcarcinomaafterresection
AT liulili modelcombiningtnmstageandtumorsizeshowsutilityinpredictingrecurrenceamongpatientswithhepatocellularcarcinomaafterresection
AT yangxia modelcombiningtnmstageandtumorsizeshowsutilityinpredictingrecurrenceamongpatientswithhepatocellularcarcinomaafterresection
AT caishaohang modelcombiningtnmstageandtumorsizeshowsutilityinpredictingrecurrenceamongpatientswithhepatocellularcarcinomaafterresection
AT yunjingping modelcombiningtnmstageandtumorsizeshowsutilityinpredictingrecurrenceamongpatientswithhepatocellularcarcinomaafterresection