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Risk prediction models for hepatocellular carcinoma in different populations
Hepatocellular carcinoma (HCC) is a malignant disease with limited therapeutic options due to its aggressive progression. It places heavy burden on most low and middle income countries to treat HCC patients. Nowadays accurate HCC risk predictions can help making decisions on the need for HCC surveil...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4865607/ https://www.ncbi.nlm.nih.gov/pubmed/27199512 http://dx.doi.org/10.21147/j.issn.1000-9604.2016.02.02 |
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author | Ma, Xiao Yang, Yang Tu, Hong Gao, Jing Tan, Yu-Ting Zheng, Jia-Li Bray, Freddie Xiang, Yong-Bing |
author_facet | Ma, Xiao Yang, Yang Tu, Hong Gao, Jing Tan, Yu-Ting Zheng, Jia-Li Bray, Freddie Xiang, Yong-Bing |
author_sort | Ma, Xiao |
collection | PubMed |
description | Hepatocellular carcinoma (HCC) is a malignant disease with limited therapeutic options due to its aggressive progression. It places heavy burden on most low and middle income countries to treat HCC patients. Nowadays accurate HCC risk predictions can help making decisions on the need for HCC surveillance and antiviral therapy. HCC risk prediction models based on major risk factors of HCC are useful and helpful in providing adequate surveillance strategies to individuals who have different risk levels. Several risk prediction models among cohorts of different populations for estimating HCC incidence have been presented recently by using simple, efficient, and ready-to-use parameters. Moreover, using predictive scoring systems to assess HCC development can provide suggestions to improve clinical and public health approaches, making them more cost-effective and effort-effective, for inducing personalized surveillance programs according to risk stratification. In this review, the features of risk prediction models of HCC across different populations were summarized, and the perspectives of HCC risk prediction models were discussed as well. |
format | Online Article Text |
id | pubmed-4865607 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-48656072016-05-19 Risk prediction models for hepatocellular carcinoma in different populations Ma, Xiao Yang, Yang Tu, Hong Gao, Jing Tan, Yu-Ting Zheng, Jia-Li Bray, Freddie Xiang, Yong-Bing Chin J Cancer Res Review Article Hepatocellular carcinoma (HCC) is a malignant disease with limited therapeutic options due to its aggressive progression. It places heavy burden on most low and middle income countries to treat HCC patients. Nowadays accurate HCC risk predictions can help making decisions on the need for HCC surveillance and antiviral therapy. HCC risk prediction models based on major risk factors of HCC are useful and helpful in providing adequate surveillance strategies to individuals who have different risk levels. Several risk prediction models among cohorts of different populations for estimating HCC incidence have been presented recently by using simple, efficient, and ready-to-use parameters. Moreover, using predictive scoring systems to assess HCC development can provide suggestions to improve clinical and public health approaches, making them more cost-effective and effort-effective, for inducing personalized surveillance programs according to risk stratification. In this review, the features of risk prediction models of HCC across different populations were summarized, and the perspectives of HCC risk prediction models were discussed as well. AME Publishing Company 2016-04 /pmc/articles/PMC4865607/ /pubmed/27199512 http://dx.doi.org/10.21147/j.issn.1000-9604.2016.02.02 Text en Copyright 2016 Chinese Journal of Cancer Research http://creativecommons.org/licenses/by-nc-sa/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/ |
spellingShingle | Review Article Ma, Xiao Yang, Yang Tu, Hong Gao, Jing Tan, Yu-Ting Zheng, Jia-Li Bray, Freddie Xiang, Yong-Bing Risk prediction models for hepatocellular carcinoma in different populations |
title | Risk prediction models for hepatocellular carcinoma in different populations |
title_full | Risk prediction models for hepatocellular carcinoma in different populations |
title_fullStr | Risk prediction models for hepatocellular carcinoma in different populations |
title_full_unstemmed | Risk prediction models for hepatocellular carcinoma in different populations |
title_short | Risk prediction models for hepatocellular carcinoma in different populations |
title_sort | risk prediction models for hepatocellular carcinoma in different populations |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4865607/ https://www.ncbi.nlm.nih.gov/pubmed/27199512 http://dx.doi.org/10.21147/j.issn.1000-9604.2016.02.02 |
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