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A novel predictive model using routinely clinical parameters to predict liver fibrosis in patients with chronic hepatitis B
OBJECTIVES: Noninvasive models have been established for the assessment of liver fibrosis in patients with chronic hepatitis B(CHB). However, the predictive performance of these established models remains inconclusive. We aimed to develop a novel predictive model for liver fibrosis in CHB based on r...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5601730/ https://www.ncbi.nlm.nih.gov/pubmed/28938634 http://dx.doi.org/10.18632/oncotarget.19501 |
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author | Wang, Jian Yan, Xiaomin Yang, Yue Chang, Haiyan Jia, Bei Zhao, Xiang-An Chen, Guangmei Xia, Juan Liu, Yong Chen, Yuxin Wang, Guiyang Wang, Li Zhang, Zhaoping Ding, Weimao Huang, Rui Wu, Chao |
author_facet | Wang, Jian Yan, Xiaomin Yang, Yue Chang, Haiyan Jia, Bei Zhao, Xiang-An Chen, Guangmei Xia, Juan Liu, Yong Chen, Yuxin Wang, Guiyang Wang, Li Zhang, Zhaoping Ding, Weimao Huang, Rui Wu, Chao |
author_sort | Wang, Jian |
collection | PubMed |
description | OBJECTIVES: Noninvasive models have been established for the assessment of liver fibrosis in patients with chronic hepatitis B(CHB). However, the predictive performance of these established models remains inconclusive. We aimed to develop a novel predictive model for liver fibrosis in CHB based on routinely clinical parameters. RESULTS: Platelets(PLT), the standard deviation of red blood cell distribution width(RDW-SD), alkaline phosphatase(ALP) and globulin were independent predictors of significant fibrosis by multivariable analysis. Based on these parameters, a new predictive model namely APRG(ALP/PLT/RDW-SD/globulin) was proposed. The areas under the receiver-operating characteristic curves(AUROCs) of APRG index in predicting significant fibrosis(≥F2), advanced fibrosis(≥F3) and liver cirrhosis(≥F4) were 0.757(95%CI 0.699 to 0.816), 0.763(95%CI 0.711 to 0.816) and 0.781(95%CI 0.728 to 0.835), respectively. The AUROCs of the APRG were significantly higher than that of aspartate transaminase(AST) to PLT ratio index(APRI), RDW to PLT ratio(RPR) and AST to alanine aminotransferase ratio(AAR) to predict significant fibrosis, advanced fibrosis and cirrhosis. The AUROCs of the APRG were also significantly higher than fibrosis-4 score (FIB-4) (0.723, 95%CI 0.663 to 0.783) for cirrhosis(P=0.034) and better than gamma-glutamyl transpeptidase(GGT) to PLT ratio(GPR) (0.657, 95%CI 0.590 to 0.724) for significant fibrosis(P=0.001). MATERIALS AND METHODS: 308 CHB patients who underwent liver biopsy were enrolled. The diagnostic values of the APRG for liver fibrosis with other noninvasive models were compared. CONCLUSIONS: The APRG has a better diagnostic value than conventionally predictive models to assess liver fibrosis in CHB patients. The application of APRG may reduce the need for liver biopsy in CHB patients in clinical practice. |
format | Online Article Text |
id | pubmed-5601730 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-56017302017-09-21 A novel predictive model using routinely clinical parameters to predict liver fibrosis in patients with chronic hepatitis B Wang, Jian Yan, Xiaomin Yang, Yue Chang, Haiyan Jia, Bei Zhao, Xiang-An Chen, Guangmei Xia, Juan Liu, Yong Chen, Yuxin Wang, Guiyang Wang, Li Zhang, Zhaoping Ding, Weimao Huang, Rui Wu, Chao Oncotarget Research Paper OBJECTIVES: Noninvasive models have been established for the assessment of liver fibrosis in patients with chronic hepatitis B(CHB). However, the predictive performance of these established models remains inconclusive. We aimed to develop a novel predictive model for liver fibrosis in CHB based on routinely clinical parameters. RESULTS: Platelets(PLT), the standard deviation of red blood cell distribution width(RDW-SD), alkaline phosphatase(ALP) and globulin were independent predictors of significant fibrosis by multivariable analysis. Based on these parameters, a new predictive model namely APRG(ALP/PLT/RDW-SD/globulin) was proposed. The areas under the receiver-operating characteristic curves(AUROCs) of APRG index in predicting significant fibrosis(≥F2), advanced fibrosis(≥F3) and liver cirrhosis(≥F4) were 0.757(95%CI 0.699 to 0.816), 0.763(95%CI 0.711 to 0.816) and 0.781(95%CI 0.728 to 0.835), respectively. The AUROCs of the APRG were significantly higher than that of aspartate transaminase(AST) to PLT ratio index(APRI), RDW to PLT ratio(RPR) and AST to alanine aminotransferase ratio(AAR) to predict significant fibrosis, advanced fibrosis and cirrhosis. The AUROCs of the APRG were also significantly higher than fibrosis-4 score (FIB-4) (0.723, 95%CI 0.663 to 0.783) for cirrhosis(P=0.034) and better than gamma-glutamyl transpeptidase(GGT) to PLT ratio(GPR) (0.657, 95%CI 0.590 to 0.724) for significant fibrosis(P=0.001). MATERIALS AND METHODS: 308 CHB patients who underwent liver biopsy were enrolled. The diagnostic values of the APRG for liver fibrosis with other noninvasive models were compared. CONCLUSIONS: The APRG has a better diagnostic value than conventionally predictive models to assess liver fibrosis in CHB patients. The application of APRG may reduce the need for liver biopsy in CHB patients in clinical practice. Impact Journals LLC 2017-07-22 /pmc/articles/PMC5601730/ /pubmed/28938634 http://dx.doi.org/10.18632/oncotarget.19501 Text en Copyright: © 2017 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 3.0 (http://creativecommons.org/licenses/by/3.0/) (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, Jian Yan, Xiaomin Yang, Yue Chang, Haiyan Jia, Bei Zhao, Xiang-An Chen, Guangmei Xia, Juan Liu, Yong Chen, Yuxin Wang, Guiyang Wang, Li Zhang, Zhaoping Ding, Weimao Huang, Rui Wu, Chao A novel predictive model using routinely clinical parameters to predict liver fibrosis in patients with chronic hepatitis B |
title | A novel predictive model using routinely clinical parameters to predict liver fibrosis in patients with chronic hepatitis B |
title_full | A novel predictive model using routinely clinical parameters to predict liver fibrosis in patients with chronic hepatitis B |
title_fullStr | A novel predictive model using routinely clinical parameters to predict liver fibrosis in patients with chronic hepatitis B |
title_full_unstemmed | A novel predictive model using routinely clinical parameters to predict liver fibrosis in patients with chronic hepatitis B |
title_short | A novel predictive model using routinely clinical parameters to predict liver fibrosis in patients with chronic hepatitis B |
title_sort | novel predictive model using routinely clinical parameters to predict liver fibrosis in patients with chronic hepatitis b |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5601730/ https://www.ncbi.nlm.nih.gov/pubmed/28938634 http://dx.doi.org/10.18632/oncotarget.19501 |
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