The Age, Gamma-Glutamyl Transpeptidase and Platelet Index: A Novel Noninvasive Model for Predicting Hepatocellular Carcinoma in Patients with Hepatitis B Virus-Related Liver Cirrhosis

J Hepatocell Carcinoma. 2022 Oct 8:9:1057-1063. doi: 10.2147/JHC.S386977. eCollection 2022.

Abstract

Background and aims: High incidence of hepatocellular carcinoma (HCC) exists in patients with liver cirrhosis (LC), but the predictive accuracy of noninvasive scoring systems (NSSs) is yet to be elucidated. The present study aimed to evaluate the predictive ability of fibrosis-4 (FIB-4), aminotransferase-to-platelet ratio index (APRI), and gamma-glutamyl transpeptidase to platelet ratio (GPR) in patients with LC, and to establish a new model with more accuracy.

Methods: Data from 94 patients with compensated LC and 134 patients with decompensated cirrhosis (DC) were collected. The prediction accuracy of NSSs, including APRI, GPR, and FIB-4, was compared.

Results: During a median follow-up of 37.5 months, 9 patients in the compensated LC group and 38 in the DC group developed HCC. For 228 patients, the area under the receiver operating characteristic curve (AUROC) of APRI, GPR, and FIB-4 was 0.596, 0.625, and 0.654, respectively. Multivariable logistic analysis showed that age, gamma-glutamyl transpeptidase (GGT), and platelet (PLT) were independent risk factors for HCC development, and a new model encompassing age, GGT, and PLT was superior to NSSs (all P<0.05). With an optimal cutoff value of 0.216, Model (Age_GGT_PLT) achieved 68.09% sensitivity and 69.61% specificity.

Conclusion: NSSs, including APRI, GPR, and FIB-4, has a non-optimal accuracy in predicting HCC development in patients with HBV-related LC. Thus, the new model consisting of age, GGT, and PLT may be more accurate than NSSs.

Keywords: decompensated cirrhosis; gamma-glutamyl transpeptidase; hepatocellular carcinoma; liver cirrhosis; risk score.

Grants and funding

This study was supported by the 333 High-level Talents Project of Jiangsu Province (Grant No. LGY2020032), the Science and Technology Project of Changzhou (Grant No. CJ20200057), and the Project of Changzhou Health Commission (Grant No. QN202128).