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FibroBox: a novel noninvasive tool for predicting significant liver fibrosis and cirrhosis in HBV infected patients

BACKGROUND: China is a highly endemic area of chronic hepatitis B (CHB). The accuracy of existed noninvasive biomarkers including TE, APRI and FIB-4 for staging fibrosis is not high enough in Chinese cohort. METHODS: Using liver biopsy as a gold standard, a novel noninvasive indicator was developed...

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Autores principales: Lu, Xiao-Jie, Yang, Xiao-Jun, Sun, Jing-Yu, Zhang, Xin, Yuan, Zhao-Xin, Li, Xiu-Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7520974/
https://www.ncbi.nlm.nih.gov/pubmed/33005419
http://dx.doi.org/10.1186/s40364-020-00215-2
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author Lu, Xiao-Jie
Yang, Xiao-Jun
Sun, Jing-Yu
Zhang, Xin
Yuan, Zhao-Xin
Li, Xiu-Hui
author_facet Lu, Xiao-Jie
Yang, Xiao-Jun
Sun, Jing-Yu
Zhang, Xin
Yuan, Zhao-Xin
Li, Xiu-Hui
author_sort Lu, Xiao-Jie
collection PubMed
description BACKGROUND: China is a highly endemic area of chronic hepatitis B (CHB). The accuracy of existed noninvasive biomarkers including TE, APRI and FIB-4 for staging fibrosis is not high enough in Chinese cohort. METHODS: Using liver biopsy as a gold standard, a novel noninvasive indicator was developed using laboratory tests, ultrasound measurements and liver stiffness measurements with machine learning techniques to predict significant fibrosis and cirrhosis in CHB patients in north and east part of China. We retrospectively evaluated the diagnostic performance of the novel indicator named FibroBox, Fibroscan, aspartate transaminase-to-platelet ratio index (APRI), and fibrosis-4 index (FIB-4) in CHB patients from Jilin and Huai’an (training sets) and also in Anhui and Beijing cohorts (validation sets). RESULTS: Of 1289 eligible HBV patients who had liver histological data, 63.2% had significant fibrosis and 22.5% had cirrhosis. In LASSO logistic regression and filter methods, fibroscan results, platelet count, alanine transaminase (ALT), prothrombin time (PT), type III procollagen aminoterminal peptide (PIIINP), type IV collagen, laminin, hyaluronic acid (HA) and diameter of spleen vein were finally selected as input variables in FibroBox. Consequently, FibroBox was developed of which the area under the receiver operating characteristic curve (AUROC) was significantly higher than that of TE, APRI and FIB-4 to predicting significant fibrosis and cirrhosis. In the Anhui and Beijing cohort, the AUROC of FibroBox was 0.88 (95% CI, 0.72–0.82) and 0.87 (95% CI, 0.83–0.91) for significant fibrosis and 0.87 (95% CI, 0.82–0.92) and 0.90 (95% CI, 0.85–0.94) for cirrhosis. In the validation cohorts, FibroBox accurately diagnosed 81% of significant fibrosis and 84% of cirrhosis. CONCLUSIONS: FibroBox has a better performance in predicting liver fibrosis in Chinese cohorts with CHB, which may serve as a feasible alternative to liver biopsy.
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spelling pubmed-75209742020-09-30 FibroBox: a novel noninvasive tool for predicting significant liver fibrosis and cirrhosis in HBV infected patients Lu, Xiao-Jie Yang, Xiao-Jun Sun, Jing-Yu Zhang, Xin Yuan, Zhao-Xin Li, Xiu-Hui Biomark Res Research BACKGROUND: China is a highly endemic area of chronic hepatitis B (CHB). The accuracy of existed noninvasive biomarkers including TE, APRI and FIB-4 for staging fibrosis is not high enough in Chinese cohort. METHODS: Using liver biopsy as a gold standard, a novel noninvasive indicator was developed using laboratory tests, ultrasound measurements and liver stiffness measurements with machine learning techniques to predict significant fibrosis and cirrhosis in CHB patients in north and east part of China. We retrospectively evaluated the diagnostic performance of the novel indicator named FibroBox, Fibroscan, aspartate transaminase-to-platelet ratio index (APRI), and fibrosis-4 index (FIB-4) in CHB patients from Jilin and Huai’an (training sets) and also in Anhui and Beijing cohorts (validation sets). RESULTS: Of 1289 eligible HBV patients who had liver histological data, 63.2% had significant fibrosis and 22.5% had cirrhosis. In LASSO logistic regression and filter methods, fibroscan results, platelet count, alanine transaminase (ALT), prothrombin time (PT), type III procollagen aminoterminal peptide (PIIINP), type IV collagen, laminin, hyaluronic acid (HA) and diameter of spleen vein were finally selected as input variables in FibroBox. Consequently, FibroBox was developed of which the area under the receiver operating characteristic curve (AUROC) was significantly higher than that of TE, APRI and FIB-4 to predicting significant fibrosis and cirrhosis. In the Anhui and Beijing cohort, the AUROC of FibroBox was 0.88 (95% CI, 0.72–0.82) and 0.87 (95% CI, 0.83–0.91) for significant fibrosis and 0.87 (95% CI, 0.82–0.92) and 0.90 (95% CI, 0.85–0.94) for cirrhosis. In the validation cohorts, FibroBox accurately diagnosed 81% of significant fibrosis and 84% of cirrhosis. CONCLUSIONS: FibroBox has a better performance in predicting liver fibrosis in Chinese cohorts with CHB, which may serve as a feasible alternative to liver biopsy. BioMed Central 2020-09-25 /pmc/articles/PMC7520974/ /pubmed/33005419 http://dx.doi.org/10.1186/s40364-020-00215-2 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Lu, Xiao-Jie
Yang, Xiao-Jun
Sun, Jing-Yu
Zhang, Xin
Yuan, Zhao-Xin
Li, Xiu-Hui
FibroBox: a novel noninvasive tool for predicting significant liver fibrosis and cirrhosis in HBV infected patients
title FibroBox: a novel noninvasive tool for predicting significant liver fibrosis and cirrhosis in HBV infected patients
title_full FibroBox: a novel noninvasive tool for predicting significant liver fibrosis and cirrhosis in HBV infected patients
title_fullStr FibroBox: a novel noninvasive tool for predicting significant liver fibrosis and cirrhosis in HBV infected patients
title_full_unstemmed FibroBox: a novel noninvasive tool for predicting significant liver fibrosis and cirrhosis in HBV infected patients
title_short FibroBox: a novel noninvasive tool for predicting significant liver fibrosis and cirrhosis in HBV infected patients
title_sort fibrobox: a novel noninvasive tool for predicting significant liver fibrosis and cirrhosis in hbv infected patients
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7520974/
https://www.ncbi.nlm.nih.gov/pubmed/33005419
http://dx.doi.org/10.1186/s40364-020-00215-2
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