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Prediction models for development of hepatocellular carcinoma in chronic hepatitis B patients
Chronic hepatitis B (CHB)-related hepatocellular carcinoma (HCC) is a major health problem in Asian-Pacific regions. Antiviral therapy reduces, but does not completely prevent, HCC development. Thus, there is a need for accurate risk prediction to assist prognostication and decisions on the need for...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8107908/ https://www.ncbi.nlm.nih.gov/pubmed/34002133 http://dx.doi.org/10.12998/wjcc.v9.i14.3238 |
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author | Guo, Jiang Gao, Xue-Song |
author_facet | Guo, Jiang Gao, Xue-Song |
author_sort | Guo, Jiang |
collection | PubMed |
description | Chronic hepatitis B (CHB)-related hepatocellular carcinoma (HCC) is a major health problem in Asian-Pacific regions. Antiviral therapy reduces, but does not completely prevent, HCC development. Thus, there is a need for accurate risk prediction to assist prognostication and decisions on the need for antiviral therapy and HCC surveillance. A few risk scores have been developed to predict the occurrence of HCC in CHB patients. Initially, the scores were derived from untreated CHB patients. With the development and extensive clinical application of nucleos(t)ide analog(s) (NA), the number of risk scores based on treated CHB patients has increased gradually. The components included in risk scores may be categorized into host factors and hepatitis B virus factors. Hepatitis activities, hepatitis B virus factors, and even liver fibrosis or cirrhosis are relatively controlled by antiviral therapy. Therefore, variables that are more dynamic during antiviral therapy have since been included in risk scores. However, host factors are more difficult to modify. Most existing scores derived from Asian populations have been confirmed to be accurate in predicting HCC development in CHB patients from Asia, while these scores have not offered excellent predictability in Caucasian patients. These findings support that more relevant variables should be considered to provide individualized predictions that are easily applied to CHB patients of different ethnicities. CHB patients should receive different intensities of HCC surveillance according to their risk category. |
format | Online Article Text |
id | pubmed-8107908 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-81079082021-05-16 Prediction models for development of hepatocellular carcinoma in chronic hepatitis B patients Guo, Jiang Gao, Xue-Song World J Clin Cases Minireviews Chronic hepatitis B (CHB)-related hepatocellular carcinoma (HCC) is a major health problem in Asian-Pacific regions. Antiviral therapy reduces, but does not completely prevent, HCC development. Thus, there is a need for accurate risk prediction to assist prognostication and decisions on the need for antiviral therapy and HCC surveillance. A few risk scores have been developed to predict the occurrence of HCC in CHB patients. Initially, the scores were derived from untreated CHB patients. With the development and extensive clinical application of nucleos(t)ide analog(s) (NA), the number of risk scores based on treated CHB patients has increased gradually. The components included in risk scores may be categorized into host factors and hepatitis B virus factors. Hepatitis activities, hepatitis B virus factors, and even liver fibrosis or cirrhosis are relatively controlled by antiviral therapy. Therefore, variables that are more dynamic during antiviral therapy have since been included in risk scores. However, host factors are more difficult to modify. Most existing scores derived from Asian populations have been confirmed to be accurate in predicting HCC development in CHB patients from Asia, while these scores have not offered excellent predictability in Caucasian patients. These findings support that more relevant variables should be considered to provide individualized predictions that are easily applied to CHB patients of different ethnicities. CHB patients should receive different intensities of HCC surveillance according to their risk category. Baishideng Publishing Group Inc 2021-05-16 2021-05-16 /pmc/articles/PMC8107908/ /pubmed/34002133 http://dx.doi.org/10.12998/wjcc.v9.i14.3238 Text en ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) |
spellingShingle | Minireviews Guo, Jiang Gao, Xue-Song Prediction models for development of hepatocellular carcinoma in chronic hepatitis B patients |
title | Prediction models for development of hepatocellular carcinoma in chronic hepatitis B patients |
title_full | Prediction models for development of hepatocellular carcinoma in chronic hepatitis B patients |
title_fullStr | Prediction models for development of hepatocellular carcinoma in chronic hepatitis B patients |
title_full_unstemmed | Prediction models for development of hepatocellular carcinoma in chronic hepatitis B patients |
title_short | Prediction models for development of hepatocellular carcinoma in chronic hepatitis B patients |
title_sort | prediction models for development of hepatocellular carcinoma in chronic hepatitis b patients |
topic | Minireviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8107908/ https://www.ncbi.nlm.nih.gov/pubmed/34002133 http://dx.doi.org/10.12998/wjcc.v9.i14.3238 |
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