A simple algorithm for non-invasive diagnosis of significant liver histological changes in patients with CHB and normal or mildly elevated alanine transaminase levels

Significant liver histological changes (SLHC) were defined as moderate to severe liver inflammation (A2 or higher) and/or fibrosis (F2 or higher) using the METAVIR scoring system. This study aimed to develop an algorithm for the non-invasive detection of SLHC in patients with chronic hepatitis B (CHB) and normal or mildly elevated alanine transaminase (ALT) levels. Using liver histology as gold standard, we developed a simple algorithm for the diagnosis of SLHC in a training set (504 patients), and then validated the diagnostic accuracy in a validation set (166 patients). A new algorithm (AAG) attributed to age, ALT, and gamma-glutamyl transpeptidase (GGT) was developed. In the training set, the area under ROC curve (AUROC) of AAG was significantly higher than that of ALT, aspartate transaminase (AST), GPR, and APRI for the diagnosis of SLHC (0.74, 0.68, 0.65, 0.56, and 0.53, respectively; all P < .05). In the validation set, the AUROC of AAG was also higher than that of ALT, AST, GPR, and APRI (0.73, 0.65, 0.62, 0.62, and 0.61, respectively; all P < .05). Using AAG ≥ 2, the sensitivity and negative predictive value was 84% to 98% and 75% to 94%, respectively, for the diagnosis of SLHC. Using AAG ≥ 6, the specificity and positive predictive value was 93% to 97% and 67% to 79%, respectively, for the diagnosis of SLHC. The AAG algorithm represents a novel noninvasive method for the diagnosis of SLHC in CHB patients with normal or mildly elevated ALT levels.