Performance of several simple, noninvasive models for assessing significant liver fibrosis in patients with chronic hepatitis B

Abstract

AimTo compare the performance of several simple, noninvasive models comprising various serum markers in diagnosing significant liver fibrosis in the same sample of patients with chronic hepatitis B (CHB) with the same judgment standard.MethodsA total of 308 patients with CHB who had undergone liver biopsy, laboratory tests, and liver stiffness measurement (LSM) at the Southwest Hospital, Chongqing, China between March 2010 and April 2014 were retrospectively studied. Receiver operating characteristic (ROC) curves and area under ROC curves (AUROCs) were used to analyze the results of the models, which incorporated age-platelet (PLT) index (API model), aspartate transaminase (AST) to alanine aminotransferase (ALT) ratio (AAR model), AST to PLT ratio index (APRI model), γ-glutamyl transpeptidase (GGT) to PLT ratio index (GPRI model), GGT-PLT-albumin index (S index model), age-AST-PLT-ALT index (FIB-4 model), and age-AST-PLT-ALT-international normalized ratio index (Fibro-Q model).ResultsThe AUROCs of the S index, GPRI, FIB-4, APRI, API, Fibro-Q, AAR, and LSM for predicting significant liver fibrosis were 0.726 (P < 0.001), 0.726 (P < 0.001), 0.621 (P = 0.001), 0.619 (P = 0.001), 0.580 (P = 0.033), 0.569 (P = 0.066), 0.495 (P = 0.886), and 0.757 (P < 0.001), respectively. The S index and GPRI had the highest correlation with histopathological scores (r = 0.373, P < 0.001; r = 0.372, P < 0.001, respectively) and LSM values (r = 0.516, P < 0.001; r = 0.513, P < 0.001, respectively). When LSM was combined with S index and GPRI, the AUROCs were 0.753 (P < 0.001) and 0.746 (P < 0.001), respectively.ConclusionS index and GPRI had the best diagnostic performance for significant liver fibrosis and were robust predictors of significant liver fibrosis in patients with CHB for whom transient elastography was unavailable.

SHFI: A Novel Noninvasive Predictive Model for Significant Fibrosis in Patients With Chronic Hepatitis B

“…Zeng et al showed that Fibro-Q had poor predictive value and was 0.569 of AUC (44). The current results showed that if Fibro-Q was above 2.26 for predicting significant fibrosis, AUC was 0.856.…”

“…Some researchers found that AUC of API was 0.680 and 0.580 (43,44). The other ones also showed that AUC of API was 0.767 and 0.529 for 3.5 and 5.5 cut off values, respectively (34,37).…”

Development of algorithms based on serum markers and transient elastography for detecting significant fibrosis and cirrhosis in chronic hepatitis B patients: Significant reduction in liver biopsy

“…These methods are economically inexpensive and convenient, but their diagnostic accuracy and sensitivity are not high . Although these non‐invasive markers were first used to assess fibrosis in chronic hepatitis C (CHC) patients, they have also been applied to patients with CHB . Several diagnostic algorithms combining different fibrosis models have been proposed to detect liver fibrosis in CHC patients, and showed excellent diagnostic performance compared with individual models.…”

“…22,23 Although these non-invasive markers were first used to assess fibrosis in chronic hepatitis C (CHC) patients, 12,17,22 they have also been applied to patients with CHB. [24][25][26][27][28][29][30] Several diagnostic algorithms combining different fibrosis models have been proposed to detect liver fibrosis in CHC patients, and showed excellent diagnostic performance compared with individual models. However, similar algorithms that can be applied to CHB patients are very rare.…”

Noninvasive Models to Predict Liver Fibrosis in Patients with Chronic Hepatitis B: A Study from Turkey

“…In liver damage, an increase in PT/INR ratio and a decrease in albumin level have been observed (31). In a study on the role of laboratory tests in the identification of fibrosis in CHB patients, platelet count, AST, ALT, GGT, ALP, total bilirubin, albumin, and INR were compared between patients with liver fibrosis stages 0 -1 and 2 -4; these parameters were found to be significantly different between the groups with respect to fibrosis stage (32). In another study, age, INR, AST, and GGT were associated with liver fibrosis stage (21).…”