Published online Feb 21, 2021. doi: 10.3748/wjg.v27.i7.641
Peer-review started: November 26, 2020
First decision: December 21, 2020
Revised: December 30, 2020
Accepted: January 13, 2021
Article in press: January 13, 2021
Published online: February 21, 2021
Transient elastography (FibroScan) is a new and non-invasive test, which can replace biopsy and has been widely recommended by the guidelines of chronic hepatitis B virus (HBV) management for assessing hepatic fibrosis staging. Liver stiffness measurement (LSM) by FibroScan is associated with the degree of hepatic fibrosis, but can also be confounded by liver necroinflammation, alanine aminotransferase (ALT), cholestasis, portal hypertension, hepatic congestion, and body mass index (BMI) and other factors, which may affect the diagnostic accuracy of the FibroScan device in fibrosis staging.
Many studies suggested that the cutoff value of LSM tends to increase with elevated ALT level, and its diagnostic accuracy tends to decrease with elevated ALT level, but it is not clear whether pathological hepatic inflammation would similarly affect LSM values and diagnostic accuracy of FibroScan assessing hepatic fibrosis.
We aimed to evaluate the diagnostic value of FibroScan and the effect of hepatic inflammation on the accuracy of FibroScan assessing liver fibrosis staging in patients with chronic HBV infection, and to develop a predictive model combining other related non-invasive confounders to predict the risk of FibroScan staging misdiagnosis.
The data of 416 patients with chronic HBV infection who accepted FibroScan, liver biopsy, clinical, and biological examination were retrospectively collected between January 2014 and December 2019 from two affiliated hospitals of Fujian Medical University. Receiver operating characteristic (ROC) curves were used to analyze the data. The diagnostic performance of FibroScan for the stage of liver fibrosis was analyzed using ROC curves. Any discordance in fibrosis staging by FibroScan and pathological scores was statistically analyzed. The accuracy of FibroScan in assessing the stage of fibrosis in patients with different degrees of liver inflammation was analyzed using Logistic regression and ROC curves. A non-invasive model was constructed to predict the risk of misdiagnosis of fibrosis stage using FibroScan.
We confirmed that LSM values obtained using FibroScan were positively correlated with hepatic fibrosis and demonstrated the good performance of FibroScan in predicting the stage of liver fibrosis. However, discordance between the fibrosis stage determined using FibroScan and that determined by pathological examination was observed in some patients. Furthermore, we found that liver inflammatory activity over 2 was an independent risk factor for misdiagnosis of fibrosis stage using FibroScan. Patients with liver inflammation activity ≥ 2 showed higher LSM values using FibroScan and higher rates of misdiagnosis of fibrosis stage, whereas the diagnostic performance of FibroScan for different fibrosis stages was significantly lower than that in patients with inflammation activity < 2. A non-invasive prediction model was established to assess the risk of misdiagnosis of fibrosis stage using FibroScan, and the area under the curve was 0.701, which was superior to that observed using other single related factors.
Liver inflammation was an independent risk factor affecting the diagnostic accuracy of FibroScan for HBV-related fibrosis staging. The combination of other related non-invasive factors can predict the risk of misdiagnosis of fibrosis staging using FibroScan, and may be helpful for making decisions on liver biopsy and guiding the diagnosis and therapy of chronic HBV infection.
This multi-center cross-sectional study developed and evaluated a noninvasive model to predict the risk of misdiagnosis of fibrosis staging using FibroScan, thus an extensive liver biopsy database should be established to comprehensively evaluate the reliable cut-off value of FibroScan for assessing the stage of liver fibrosis and further verify the diagnostic performance of this model in future prospective studies.