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LiveBoost: A GB-based prediction system for liver fibrosis in chronic hepatitis B patients in China - A multi-center retrospective study

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Pubmed体系：

收录情况： ◇ SCIE

作者：
Xie Guoxiang[1] * ; Xiao Huanming[2] * ; Liu Quan[1] ; Chen Tianlu[3] ; Chen Fengyan[1] ; Zhou Kejun[1] ; Wang Xiaoning[4] ; Liu Ping[4] ; Jia Zhifeng[5] ; Chen Lei[5] ; Deng Xin[6] ; Meng Fankun[7] ; Zhang Zhenhua[8] ; Chi Xiaoling[2] ; Jia Wei[1,9] ;
机构： [1]Human Metabolomics Institute Inc., Shenzhen, Guangdong, China. [2]Hepatology Department, Guangdong Provincial Hospital of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China. [3]Center for Translational Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China. [4]Institute of Interdisciplinary Integrative Medicine Research, Key Laboratory of Liver and Kidney Diseases (Ministry of Education), Institute of Liver Diseases, Shuguang Hospital, Department of Pharmacology, Shanghai University of Traditional Chinese Medicine, Shanghai, China. [5]Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong, China. [6]Hepatology Department, The Third People's Hospital of Shenzhen, Shenzhen, China. [7]Ultrasound and Functional Diagnosis Center, Beijing Youan Hospital affiliated to Capital Medical University, Beijing, China. [8]Department of Infectious Diseases and Institute of Clinical Virology, The Second Hospital of Anhui Medical University, Hefei, Anhui, China. [9]School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China.
出处：
DOI： 10.1016/j.heliyon.2024.e24161

关键词： Hepatic fibrosis FIB-4 APRI Chronic hepatitis B LiveBoost

摘要：
The aim of this study was to evaluate the accuracy of LiveBoost™, a gradient boosting (GB)-based prediction system based on standard biochemical values (AST, ALT, platelet count) and age, in Chinese patients with chronic hepatitis B (CHB) and compare its performance with FIB-4 (fibrosis-4 score) and APRI (the aspartate transaminase to platelet ratio index).This retrospective trial enrolled 454 participants, including 279 CHB patients who underwent liver biopsy and 175 normal controls from 3 centers in China. All participants underwent laboratory blood testing. LiveBoost was constructed using GB and FIB-4 and APRI were calculated from laboratory data.LiveBoost outperformed APRI and FIB-4 in predicting hepatic fibrosis and cirrhosis. The GB model had an AUROC of 0.977 for CHB diagnosis, 0.804 for early and advanced fibrosis, and 0.836 for non-cirrhosis and cirrhosis, compared to AUROC of 0.554, 0.673 and 0.720 for FIB-4, AUROC of 0.977, 0.652 and 0.654 for APRI.LiveBoost is a more reliable and cost-effective method than APRI and FIB-4 for assessing liver fibrosis in Chinese patients with CHB.© 2024 The Authors.

语种：
外文
WOS：
PubmedID：
中科院(CAS)分区：
出版当年[2023]版：
大类 | 3 区 综合性期刊
小类 | 3 区 综合性期刊
最新[2025]版：
大类 | 4 区 综合性期刊
小类 | 4 区 综合性期刊
JCR分区：
出版当年[2022]版：
Q2 MULTIDISCIPLINARY SCIENCES
最新[2023]版：
Q1 MULTIDISCIPLINARY SCIENCES

影响因子： 最新[2023版] 最新五年平均 出版当年[2022版] 出版当年五年平均 出版前一年[2021版] 出版后一年[2023版]

第一作者：
第一作者机构： [1]Human Metabolomics Institute Inc., Shenzhen, Guangdong, China.
共同第一作者：
通讯作者：
通讯机构： [1]Human Metabolomics Institute Inc., Shenzhen, Guangdong, China. [9]School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China.
推荐引用方式(GB/T 7714)：
Xie Guoxiang,Xiao Huanming,Liu Quan,et al.LiveBoost: A GB-based prediction system for liver fibrosis in chronic hepatitis B patients in China - A multi-center retrospective study[J].HELIYON.2024,10(2):e24161.doi:10.1016/j.heliyon.2024.e24161.
APA：
Xie Guoxiang,Xiao Huanming,Liu Quan,Chen Tianlu,Chen Fengyan...&Jia Wei.(2024).LiveBoost: A GB-based prediction system for liver fibrosis in chronic hepatitis B patients in China - A multi-center retrospective study.HELIYON,10,(2)
MLA：
Xie Guoxiang,et al."LiveBoost: A GB-based prediction system for liver fibrosis in chronic hepatitis B patients in China - A multi-center retrospective study".HELIYON 10..2(2024):e24161

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