Performance of noninvasive tools for identification of minimal liver fibrosis in patients with hepatitis B virus infection

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

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.

Performance of noninvasive tools for identification of minimal liver fibrosis in patients with hepatitis B virus infection

Background

Various noninvasive liver fibrosis assessment tools are available. Here, we evaluated the performance of the asparagine aminotransferase‐to‐platelet ratio index (APRI), the fibrosis‐4 index (FIB‐4), transient elastography (TE), and the globulin–platelet (GP) ratio for identifying liver fibrosis in patients with hepatitis B virus (HBV) infection.

Methods

A total of 146 patients were assessed using TE, FIB‐4, APRI, the GP ratio, and liver biopsy. Three patient grouping methods were applied: any fibrosis (AF; F0 vs. F1/2/3/4); moderate fibrosis (MF; F0/1 vs. F2/3/4); and severe fibrosis (SF; F0/1/2 vs. F3/4). Receiver operating characteristic (ROC) curve analysis, univariate analyses, and multivariate logistic regression were conducted.

Results

Regardless of patient‐grouping method, the area under the curve (AUC) of TE and the GP ratio were similar. Using the AF grouping method, the GP ratio showed superior performance compared with APRI and FIB‐4: the AUCs for the GP ratio, TE, APRI, and FIB‐4 were 0.76, 0.75, 0.70, and 0.66, respectively. Using the MF grouping method, the GP ratio also showed superior performance compared with APRI and FIB‐4: the AUCs for the GP ratio, TE, APRI, and FIB‐4 were 0.66, 0.68, 0.57, and 0.53, respectively. Using the SF grouping method, the AUCs for the GP ratio, TE, APRI, and FIB‐4 were not significantly different.

Conclusion

Compared with FIB‐4 and APRI, the GP ratio had higher accuracy for identifying liver fibrosis, especially early‐stage fibrosis, in patients with HBV infection.