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

Guoxiang Xie*, Huanming Xiao, Quan Liu, Tianlu Chen, Fengyan Chen, Kejun Zhou, Xiaoning Wang, Ping Liu, Zhifeng Jia, Lei Chen, Xin Deng, Fankun Meng, Zhenhua Zhang, Xiaoling Chi*, Wei Jia*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

Abstract

Background: 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).

Methods: 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.

Results: 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.

Conclusions: LiveBoost is a more reliable and cost-effective method than APRI and FIB-4 for assessing liver fibrosis in Chinese patients with CHB.

Original languageEnglish
Article numbere24161
Number of pages9
JournalHeliyon
Volume10
Issue number2
DOIs
Publication statusPublished - 30 Jan 2024

Scopus Subject Areas

  • General

User-Defined Keywords

  • APRI
  • Chronic hepatitis B
  • FIB-4
  • Hepatic fibrosis
  • LiveBoost

Fingerprint

Dive into the research topics of 'LiveBoost: A GB-based prediction system for liver fibrosis in chronic hepatitis B patients in China - A multi-center retrospective study'. Together they form a unique fingerprint.

Cite this