Development and evaluation of a novel noninvasive index for predicting significant fibrosis, advanced fibrosis, and cirrhosis in patients with chronic hepatitis B infection

Noninvasive Models to Assess Liver Inflammation and Fibrosis in Chronic HBV Infected Patients with Normal or Mildly Elevated Alanine Transaminase Levels: Which One Is Most Suitable?

The prevalence of substantial inflammation or fibrosis in treatment-naïve patients with chronic hepatitis B (CHB) and normal alanine transaminase (ALT) levels is high. A retrospective analysis was conducted on 559 consecutive patients with hepatitis B virus infection, who underwent liver biopsy, to investigate the value of noninvasive models based on routine serum markers for evaluating liver histology in CHB patients with normal or mildly elevated ALT levels and to provide treatment guidance. After comparing 55 models, we identified the top three models that exhibited excellent performance. The APGA model, based on the area under the receiver operating characteristic curve (AUROC), demonstrated a superior ability to evaluate significant (AUROC = 0.750) and advanced fibrosis (AUROC = 0.832) and demonstrated a good performance in assessing liver inflammation (AUROCs = 0.779 and 0.874 for stages G ≥ 2 and G ≥ 3, respectively). APGA also exhibited significant correlations with liver inflammation and fibrosis stage (correlation coefficients, 0.452 and 0.405, respectively (p < 0.001)). When the patients were stratified into groups based on HBeAg status and ALT level, APGA consistently outperformed the other 54 models. The other top two models, GAPI and XIE, also outperformed models based on other chronic hepatitis diseases. APGA may be the most suitable option for detecting liver fibrosis and inflammation in Chinese patients with CHB.

Fibrosis-4 index, a predictor for prognosis of hepatocellular carcinoma patients after curative hepatectomy even in hepatitis B virus dominant populations

Purpose

Liver fibrosis plays an important role in the development of hepatocellular carcinoma (HCC) and determining its prognosis. Although many staging systems and liver reserve models have been developed without the intention of predicting prognosis of HCC, some studies have investigated their prognostic values in HCC after curative liver resection (LR). The aim of this study is to evaluate prognostic value of non-invasive biomarkers after curative LR.

Methods

Between 2006 and 2013, HCC patients underwent LR were included and total 962 patients were enrolled. All non-invasive biomarkers (fibrosis 4 index (FIB-4), aspartate aminotransferase-to-platelet ratio index (APRI), aspartate aminotransferase-to-alanine aminotransferase ratio (AAR), AAR-to-platelet ratio index (AARPRI), and albumin-bilirubin (ALBI) score) were measured at the time of HCC diagnosis. To binarize each biomarker, an optimal cut-off value for fibrosis stage was selected using the value of minimum distance from the left-upper corner of the receiver operating characteristic curve with a specificity >60%. We performed Cox regression analysis on 2-year recurrence-free survival (RFS) and overall survival (OS).

Results

The area under curve values for FIB-4 and APRI were the largest for fibrosis stage compared to other biomarkers, 0.669 (95% confidential interval (CI), 0.610-0.719) and 0.748 (95% CI, 0.692-0.800), respectively. Between those two indices, FIB-4 is considered a statistically significant prognostic factor of RFS in HCC patients after LR. The HR for 2-year RFS and OS were 1.81 (95% CI, 1.18-2.77; P = 0.007) and 2.36 (95% CI, 0.99-5.65; P = 0.054), respectively.

Conclusion

FIB-4 is identified as a statistically significant predictor of HCC prognosis after curative LR even in HBV dominant populations.

A Novel Non-invasive Model Based on GPR for the Prediction of Liver Fibrosis in Patients With Chronic Hepatitis B

Background: Some controversy remains regarding conventional serum indices for the evaluation of liver fibrosis. Therefore, we aimed to combine the existing index with other serum parameters to discriminate liver fibrosis stages in patients with chronic hepatitis B (CHB). Methods: A total of 1,622 treatment-naïve CHB patients were divided into training (n = 1,211) and validation (n = 451) cohorts. Liver histology was assessed according to the Scheuer scoring scheme. All common demographic and clinical parameters were analyzed. Results: By utilizing the results of the logistic regression analysis, we developed a novel index, the product of GPR, international normalized ratio (INR), and type IV collagen (GIVPR), to discriminate liver fibrosis. In the training group, the areas under the ROCs (AUROCs) of GIVPR, APRI, FIB-4, and GPR for significant fibrosis were 0.81, 0.75, 0.72, and 0.77, respectively; the AUROCs of GIVPR, APRI, FIB-4, and GPR for advanced fibrosis were 0.82, 0.74, 0.74, and 0.78, respectively; and the AUROCs of GIVPR, APRI, FIB-4, and GPR for cirrhosis were 0.87, 0.78, 0.78, and 0.83, respectively. Similar results were also obtained in the validation group. Furthermore, the decision curve analysis suggested that GIVPR represented superior clinical benefits in both independent cohorts. Conclusion: The GIVPR constructed on GPR represents a superior predictive model for discriminating liver fibrosis in CHB patients.