Noninvasive tests (NITs) such as Fibrosis-4 index (FIB-4) and the aspartate aminotransferase to platelet ratio index (APRI), developed using classical statistical methods, are increasingly used for determining liver fibrosis stages and recommended in treatment guidelines replacing the liver biopsy. Application of conventional cutoffs of FIB-4 and APRI resulted in high rates of misclassification of fibrosis stages.

There is an unmet need for more accurate NIT that can overcome the limitations of FIB-4 and APRI.

Machine learning with random forests (RF) algorithm was used to develop a noninvasive index using retrospective data of 7238 biopsy-proven chronic hepatitis C (CHC) patients from two centers in Egypt; derivation dataset (n=1821) and validation set in the second center (n=5417). Receiver operator curve (ROC) analysis was used to define cutoffs for different stages of fibrosis. Performance of the new score was externally validated in cohorts from two other sites in Egypt (n=560) and seven different countries (n=1317). Fibrosis stages were determined using METAVIR score. Results were also compared with three established tools (FIB-4, APRI, and AAR).

Age in addition to readily available laboratory parameters as aspartate, and alanine aminotransferases, alkaline phosphatase, albumin (g/dL), and platelet count (/cm3) correlated with the biopsy-derived stage of liver fibrosis in the derivation cohort and were used to construct the model for predicting the fibrosis stage by applying RF algorithm, resulting in a FIB-6 index which can be calculated easily at (http://fib6.elriah.info). Application of the cutoff values derived from the derivation group on the validation groups yielded very good performance in ruling out cirrhosis (negative predictive value [NPV] = 97.7%), compensated advance liver disease (cACLD) (NPV = 90.2%), and significant fibrosis (NPV = 65.7%). In the external validation groups from different countries, FIB-6 demonstrated higher sensitivity and NPV than FIB-4, APRI, and AAR.

FIB-6 score is non-invasive, simple, and accurate test for ruling out liver cirrhosis and cACLD in chronic hepatitis C patients and performs better than APRI, FIB-4, and AAR.

This article is protected by copyright. All rights reserved.