Assessment of liver fibrosis with the gamma-glutamyl transpeptidase to platelet ratio: a multicentre validation in patients with HBV infection

DGPRI, a new liver fibrosis assessment index, predicts recurrence of AFP-negative hepatocellular carcinoma after hepatic resection: a single-center retrospective study

Although patients with alpha-fetoprotein-negative hepatocellular carcinoma (AFPNHCC) have a favorable prognosis, a high risk of postoperative recurrence remains. We developed and validated a novel liver fibrosis assessment index, the direct bilirubin-gamma-glutamyl transpeptidase-to-platelet ratio (DGPRI). DGPRI was calculated for each of the 378 patients with AFPNHCC who underwent hepatic resection. The patients were divided into high- and low-score groups using the optimal cutoff value. The Lasso-Cox method was used to identify the characteristics of postoperative recurrence, followed by multivariate Cox regression analysis to determine the independent risk factors associated with recurrence. A nomogram model incorporating the DGPRI was developed and validated. High DGPRI was identified as an independent risk factor (hazard ratio = 2.086) for postoperative recurrence in patients with AFPNHCC. DGPRI exhibited better predictive ability for recurrence 1-5 years after surgery than direct bilirubin and the gamma-glutamyl transpeptidase-to-platelet ratio. The DGPRI-nomogram model demonstrated good predictive ability, with a C-index of 0.674 (95% CI 0.621-0.727). The calibration curves and clinical decision analysis demonstrated its clinical utility. The DGPRI nomogram model performed better than the TNM and BCLC staging systems for predicting recurrence-free survival. DGPRI is a novel and effective predictor of postoperative recurrence in patients with AFPNHCC and provides a superior assessment of preoperative liver fibrosis.

Review: Advances in the Pathogenesis and Treatment of Immune Thrombocytopenia Associated with Viral Hepatitis

Hepatitis B virus and hepatitis C virus are the hepatitis subtypes that most commonly induce immune thrombocytopenia (ITP). Although the pathogenesis of viral hepatitis-associated ITP remains unclear, it may involve antibody cross-reactivity due to molecular mimicry, the formation of virus-platelet immune complexes, and T cell-mediated suppression of bone marrow hematopoiesis. Moreover, there is significant correlation between platelet count and the severity of viral hepatitis, the risk of progression to liver cirrhosis, and clinical prognosis. However, treatment of viral hepatitis-associated ITP is hindered by some antiviral drugs. In this review, we summarize research progress to date on the pathogenesis and treatment of viral hepatitis-related ITP, hoping to provide a reference for clinical diagnosis and treatment.

Diagnostic accuracy of apparent diffusion coefficient values combined with γ-glutamyl transpeptidase-to-platelet ratio parameters for predicting hepatitis B-related fibrosis

OBJECTIVES

The accuracy of non-invasive liver fibrosis diagnosis based on the apparent diffusion coefficient (ADC) value combined with the γ-glutamyl transpeptidase-to-platelet ratio (GPR) model to predict the stage of hepatitis B-related fibrosis has not been reported. This study aimed to evaluate the diagnostic efficacy of ADC value combined with GPR for liver fibrosis grading.

METHODS

The data of 180 patients with chronic hepatitis B (CHB) diagnosed by liver biopsy were analyzed. The ADC value, GPR, and their combination were assessed in different cirrhosis stages using receiver operating characteristic curve analysis to evaluate their value in diagnosing liver fibrosis.

RESULTS

We observed that liver fibrosis stages were inversely associated with ADC values (r=-0.691, P<0.001), and positively associated with GPR (r=0.502, P<0.001). The area under the curve for diagnostic efficacy of ADC values, GPR, and their combination for F≥2 liver fibrosis was 0.831, 0.749, and 0.858, respectively, and for F≥3 was 0.872, 0.771, and 0.903, respectively. The diagnostic cutoffs of the combination for each stage were -7.07, -12.21 and -37.75, respectively.

CONCLUSIONS

The combined diagnostic tool of ADC and GPR may improve the accuracy of hepatitis B-related liver fibrosis diagnosis, especially for F≥3.

Optimized cutoffs of gamma-glutamyl transpeptidase-to-platelet ratio, aspartate aminotransferase-to-platelet ratio index, and fibrosis-4 scoring systems for exclusion of cirrhosis in patients with chronic hepatitis B

Accurate prediction of the extent of fibrosis is of great clinical importance in patients infected with chronic hepatitis B (CHB). This study aimed to compare the performance of gamma-glutamyl transpeptidase-to-platelet ratio (GPR), aspartate aminotransferase-to-platelet ratio index (APRI), and fibrosis-4 (FIB-4) in evaluating liver fibrosis stages and to identify optimized cutoffs to exclude cirrhosis. Consecutive patients with CHB with liver biopsies were enrolled and randomly divided into derivation and validation cohorts. Areas under the receiver operating characteristic curve were used to evaluate the diagnostic performance of APRI, FIB-4, and GPR to distinguish fibrosis stages. New cutoffs with a sensitivity of at least 90% and a negative predictive value (NPV) of more than 95% were identified. A total of 880 individuals were enrolled in this study. The derivation data set consisted of 617 patients, with 82 patients with cirrhosis. In the validation cohort (n = 263), 29 patients had cirrhosis. APRI, FIB-4, and GPR had comparable diagnostic performance for diagnosing significant fibrosis. GPR outperformed APRI (p < 0.05) in the prediction of cirrhosis. A newly identified GPR score of 0.35 had a sensitivity and NPV of 93.9% and 98.0%, respectively, and misclassified 5 of 82 (6.1%) patients with cirrhosis in the derivation group. All new cutoffs identified in this study also reached our goal in the validation cohort. The new GPR score could rule out a larger proportion of individuals without cirrhosis, and the subgroup analysis showed more stable performance. However, the lower cutoff dose increases the need for further testing compared to the conventional cutoff. Conclusion: A newly identified cutoff for GPR (<0.35) could rule out more patients without cirrhosis compared to APRI and FIB-4 and have low misclassification rates.

Radiomics analysis of contrast-enhanced CT for staging liver fibrosis: an update for image biomarker

BACKGROUND

To establish and validate a radiomics-based model for staging liver fibrosis at contrast-enhanced CT images.

MATERIALS AND METHODS

This retrospective study developed two radiomics-based models (R-score: radiomics signature; R-fibrosis: integrate radiomic and serum variables) in a training cohort of 332 patients (median age, 59 years; interquartile range, 51-67 years; 256 men) with biopsy-proven liver fibrosis who underwent contrast-enhanced CT between January 2017 and December 2020. Radiomic features were extracted from non-contrast, arterial and portal phase CT images and selected using the least absolute shrinkage and selection operator (LASSO) logistic regression to differentiate stage F3-F4 from stage F0-F2. Optimal cutoffs to diagnose significant fibrosis (stage F2-F4), advanced fibrosis (stage F3-F4) and cirrhosis (stage F4) were determined by receiver operating characteristic curve analysis. Diagnostic performance was evaluated by area under the curve, Obuchowski index, calibrations and decision curve analysis. An internal validation was conducted in 111 randomly assigned patients (median age, 58 years; interquartile range, 49-66 years; 89 men).

RESULTS

In the validation cohort, R-score and R-fibrosis (Obuchowski index, 0.843 and 0.846, respectively) significantly outperformed aspartate transaminase-to-platelet ratio (APRI) (Obuchowski index, 0.651; p < .001) and fibrosis-4 index (FIB-4) (Obuchowski index, 0.676; p < .001) for staging liver fibrosis. Using the cutoffs, R-fibrosis and R-score had a sensitivity range of 70-87%, specificity range of 71-97%, and accuracy range of 82-86% in diagnosing significant fibrosis, advanced fibrosis and cirrhosis.

CONCLUSION

Radiomic analysis of contrast-enhanced CT images can reach great diagnostic performance of liver fibrosis.

Asociación Mexicana de Hepatología A.C. Clinical guideline on hepatitis B

Hepatitis B virus (HBV) infection continues to be a worldwide public health problem. In Mexico, at least three million adults are estimated to have acquired hepatitis B (total hepatitis B core antibody [anti-HBc]-positive), and of those, 300,000 active carriers (hepatitis B surface antigen [HBsAg]-positive) could require treatment. Because HBV is preventable through vaccination, its universal application should be emphasized. HBV infection is a major risk factor for developing hepatocellular carcinoma. Semi-annual liver ultrasound and serum alpha-fetoprotein testing favor early detection of that cancer and should be carried out in all patients with chronic HBV infection, regardless of the presence of advanced fibrosis or cirrhosis. Currently, nucleoside/nucleotide analogues that have a high barrier to resistance are the first-line therapies.

Asociación Mexicana de Hepatología A.C. Clinical guideline on hepatitis B

Hepatitis B virus (HBV) infection continues to be a worldwide public health problem. In Mexico, at least three million adults are estimated to have acquired hepatitis B (total hepatitis B core antibody [anti-HBc]-positive), and of those, 300,000 active carriers (hepatitis B surface antigen [HBsAg]-positive) could require treatment. Because HBV is preventable through vaccination, its universal application should be emphasized. HBV infection is a major risk factor for developing hepatocellular carcinoma. Semi-annual liver ultrasound and serum alpha-fetoprotein testing favor early detection of that cancer and should be carried out in all patients with chronic HBV infection, regardless of the presence of advanced fibrosis or cirrhosis. Currently, nucleoside/nucleotide analogues that have a high barrier to resistance are the first-line therapies.

Application and Development of Artificial Intelligence and Intelligent Disease Diagnosis

With the continuous development of artificial intelligence (AI) technology, big data-supported AI technology with considerable computer and learning capacity has been applied in diagnosing different types of diseases. This study reviews the application of expert systems, neural networks, and deep learning used by AI technology in disease diagnosis. This paper also gives a glimpse of the intelligent diagnosis and treatment of digestive system diseases, respiratory system diseases, and osteoporosis by AI technology.

FibroBox: a novel noninvasive tool for predicting significant liver fibrosis and cirrhosis in HBV infected patients

Background

China is a highly endemic area of chronic hepatitis B (CHB). The accuracy of existed noninvasive biomarkers including TE, APRI and FIB-4 for staging fibrosis is not high enough in Chinese cohort.

Methods

Using liver biopsy as a gold standard, a novel noninvasive indicator was developed using laboratory tests, ultrasound measurements and liver stiffness measurements with machine learning techniques to predict significant fibrosis and cirrhosis in CHB patients in north and east part of China. We retrospectively evaluated the diagnostic performance of the novel indicator named FibroBox, Fibroscan, aspartate transaminase-to-platelet ratio index (APRI), and fibrosis-4 index (FIB-4) in CHB patients from Jilin and Huai’an (training sets) and also in Anhui and Beijing cohorts (validation sets).

Results

Of 1289 eligible HBV patients who had liver histological data, 63.2% had significant fibrosis and 22.5% had cirrhosis. In LASSO logistic regression and filter methods, fibroscan results, platelet count, alanine transaminase (ALT), prothrombin time (PT), type III procollagen aminoterminal peptide (PIIINP), type IV collagen, laminin, hyaluronic acid (HA) and diameter of spleen vein were finally selected as input variables in FibroBox. Consequently, FibroBox was developed of which the area under the receiver operating characteristic curve (AUROC) was significantly higher than that of TE, APRI and FIB-4 to predicting significant fibrosis and cirrhosis. In the Anhui and Beijing cohort, the AUROC of FibroBox was 0.88 (95% CI, 0.72–0.82) and 0.87 (95% CI, 0.83–0.91) for significant fibrosis and 0.87 (95% CI, 0.82–0.92) and 0.90 (95% CI, 0.85–0.94) for cirrhosis. In the validation cohorts, FibroBox accurately diagnosed 81% of significant fibrosis and 84% of cirrhosis.

Conclusions

FibroBox has a better performance in predicting liver fibrosis in Chinese cohorts with CHB, which may serve as a feasible alternative to liver biopsy.

Review of Serum Biomarkers and Models Derived from Them in HBV-Related Liver Diseases

A series of predictive scoring systems is available for stratifying the severity of conditions and assessing the prognosis in patients with HBV-related liver diseases. We show nine of the most popular serum biomarkers and their models (i.e., serum cystatin C, homocysteine, C-reactive protein, C-reactive protein to albumin ratio, aspartate aminotransferase to platelet ratio index, fibrosis index based on four factors, gamma-glutamyl transpeptidase to platelet ratio, albumin-bilirubin score, and gamma-glutamyl transpeptidase to albumin ratio) that have gained great interest from clinicians. Compared with traditional scoring systems, these serum biomarkers and their models are easily acquired, simple, and relatively inexpensive. In the present review, we summarize the latest studies focused on these serum biomarkers and their models as diagnostic and prognostic indexes in HBV-related liver diseases.

A Novel Prediction Model for Significant Liver Fibrosis in Patients with Chronic Hepatitis B

Background

Preventing liver fibrosis from progressing to cirrhosis and even liver cancer is a key step in the treatment of chronic hepatitis B (CHB). This study is aimed at constructing and validating a new nomogram for predicting significant liver fibrosis (S ≥ 2) in CHB patients.

Methods

The nomogram was based on a retrospective study of 252 CHB patients. The predictive accuracy and discriminative ability of the nomogram were evaluated by the area under receiver operating characteristic curve (AUROC), decision curves, and calibration curve compared with the fibrosis 4 score (FIB-4) and aspartate aminotransferase-to-platelet ratio index (APRI). The results were validated using bootstrap resampling and an external set of 168 CHB patients.

Results

A total of 420 CHB patients were enrolled based on liver biopsy results. Independent factors predicting significant liver fibrosis were laminin (LN), procollagen type III N-terminal peptide (PIIINP), and blood platelet count (PLT) in a multivariate analysis, and these factors were selected to construct the nomogram. The calibration curve for the probability of significant liver fibrosis showed optimal agreement between the prediction from the nomogram and actual observation. The prediction from the nomogram was more consistent with the results of liver biopsy than FIB-4 and APRI. The AUROC of the nomogram was higher than that of FIB-4 and APRI for predicting significant liver fibrosis. These results were confirmed in the validation set. Furthermore, the decision curve analysis suggested that the most net benefits were provided by the nomogram.

Conclusions

We found the proposed nomogram resulted in a more accurate prediction of significant liver fibrosis in CHB patients and could provide the most net benefits. We recommend this noninvasive assessment for patients with liver fibrosis to avoid the risk of liver biopsy and earlier intervention to prevent the development of cirrhosis or liver cancer.

The Delta-4 fibrosis score (D4FS): A novel fibrosis score in chronic hepatitis D

BACKGROUND

Chronic Hepatitis D virus (HDV) infection results in the most severe form of viral hepatitis with a rapid progression to cirrhosis. However, non-invasive fibrosis tests that can accurately predict cirrhosis have not been adequately validated. We aimed to develop a clinically useful non-invasive score that can accurately detect cirrhosis.

MATERIAL AND METHODS

Patients with chronic HDV diagnosed by liver histology or serum PCR were evaluated. Data regarding demographics, laboratory, imaging, vibration-controlled transient elastography (VCTE), and liver biopsy were collected. The total cohort was randomized into a training and validation cohort. The training cohort was used to develop a novel score, the Delta-4 fibrosis score (D4FS) which was then compared to other non-invasive tests in the validation cohort by area under receiver operating characteristics (AUROC).

RESULTS

77 patients with chronic HDV were evaluated: mean age 42.6 (SD:11.1) years, 59.7% male, and 57.1% Asian. The total cohort was then separated into a training (n = 45) and validation (n = 32) cohort with no significant differences in terms of clinical characteristics between the two. From the training cohort, the D4FS was derived from variables of statistical and clinical interest (gamma-glutamyl transpeptidase (GGT), platelet count, alanine aminotransferase (ALT), and liver stiffness measurement (LSM)). The D4FS demonstrated the best AUROC in the validation cohort (0.94) followed by VCTE (0.90), FIB-4 (0.86), APRI (0.81), and AAR (0.71).

DISCUSSION

The D4FS is a clinically useful non-invasive fibrosis score that can accurately detect cirrhosis in patients with chronic HDV infection. Further studies should be performed to further validate clinical utility.

Lnc-TCL6 is a potential biomarker for early diagnosis and grade in liver-cirrhosis patients

Background

Long non-coding RNAs (lncRNAs) have been applied as biomarkers in many diseases. However, scarce biomarkers are available in single lncRNA differential expression associated with different clinical stages of liver cirrhosis (LC). The aim of the study is to identify some lncRNAs that can serve as non-invasive sensitive biomarkers for early diagnosis and grade of LC.

Methods

Blood lncRNA expression was evaluated in three independent cohorts with 305 participants including healthy controls, hepatitis B virus (HBV) carriers, and patients with chronic hepatitis B (CHB) or LC. First, candidate lncRNAs were screened by CapitalBiotech microarray to diagnose cirrhosis. Quantitative reverse-transcriptase polymerase chain reaction was then used to investigate the expression of selected lncRNAs in the whole group of cirrhosis and different Child–Pugh classes. Ultimately, the diagnostic accuracy of the promising biomarker was examined and validated via Mann–Whitney test and receiver-operating characteristics analysis.

Results

Lnc-TCL6 was identified as a sensitive biomarker for early diagnosis of LC (Child–Pugh A) compared with healthy controls (area under the ROC curve [AUC] = 0.636), HBV carriers (AUC = 0.671), and CHB patients (AUC = 0.672). Furthermore, lnc-TCL6 showed a favourable capacity in discriminating among different Child–Pugh classes (AUC: 0.711–0.837). Compared with healthy controls, HBV carriers, and CHB patients, the expression of lnc-TCL6 was obviously up-regulated in Child–Pugh A patients and, conversely, significantly down-regulated in Child–Pugh C patients.

Conclusions

Lnc-TCL6 is a novel potential biomarker for early diagnosis of LC and is a possible predictor of disease progression.

Preoperative D-dimer and Gamma-Glutamyltranspeptidase Predict Major Complications and Survival in Colorectal Liver Metastases Patients After Resection

OBJECTIVES: To investigate the predictive value of the pre-operative D-dimer and gamma-glutamyltranspeptidase (GGT) for the prognosis in colorectal liver metastases (CRLM) patients after hepatic resection. METHODS: Two hundred and ninety-two patients between December 2008 and December 2016 and 101 patients at our center from January 2017 to December 2018 were selected as a training set and validation set, respectively. The combination of the pre-operative D-dimer and GGT status (CPDG score) was scored as follows: elevated D-dimer levels with elevated GGT levels was allocated a score of 2, decreased D-dimer levels with decreased GGT levels was allocated a score of 0, and all other combinations were allocated a score of 1. In the training set, a logistic regression was applied to explore potential predictors of major postoperative complications. A Cox proportional hazards analysis was used to analyze survival. We further verified our findings in the validation set. RESULTS: Major complications occurred in 43 (14.7%) and 25 (24.8%) patients in the training set and validation set, respectively. In the training set, multivariate analysis showed that elevated GGT levels and elevated D-dimer levels independently predicted major complications respectively. In the multivariate analyses, elevated pre-operative D-dimer levels remained independently associated with decreased overall survival (OS) (hazard ratio [HR] = 1.751, 95% confidence interval [CI]: 1.139-2.691, P = .01). The CPDG score was an independent prognostic factor for major complications and OS in the multivariate analyses. The predictive ability of the CPDG score was higher than either factor alone. A Kaplan-Meier survival analysis showed that compared with patients with CPDG score = 1 or CPDG score = 0, patients with a CPDG score = 2 had worsened OS. Furthermore, for OS comparisons, the differences between any two groups were significant. In the validation set, elevated GGT and D-dimer were also suggested to predict worse progression-free survival (PFS) and to be independently associated with major complications. CONCLUSIONS: The pre-operative D-dimer levels, GGT levels and CPDG score are reliable biomarkers to predict post-operative major complications or survival in CRLM patients after hepatic resection, which make it useful for CRLM patients in guiding surveillance approaches and prognosis assessments.

Diagnostic accuracy of γ-glutamyl transpeptidase-to-platelet ratio for predicting hepatitis B-related fibrosis: a meta-analysis

BACKGROUND AND AIM

Emerging published data on the accuracy of γ-glutamyl transpeptidase-to-platelet ratio (GPR) for diagnosing hepatitis B virus (HBV)-related fibrosis are inconsistent. The aim of this study was to systematically review the performance of GPR for diagnosing HBV-related significant fibrosis, severe fibrosis, and cirrhosis.

PATIENTS AND METHODS

A comprehensive literature search of PubMed, Web of Science, and EMBASE was conducted before July 2018. Study selection was performed according to inclusion and exclusion criteria. The relevant parameters of eligible studies were abstracted. The methodological quality was assessed according to the Quality Assessment of Diagnostic Accuracy Studies. Areas under summary receiver operating characteristic curves, sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratios were used to examine the GPR accuracy for the diagnosis of significant fibrosis, severe fibrosis, and cirrhosis.

RESULTS

A total of 10 studies including 5882 patients with HBV infection underwent liver biopsy were incorporated. The prevalence of significant fibrosis, severe fibrosis, and cirrhosis were 58% (range: 22-72%), 36% (range: 10-55%), and 19% (range: 2-33%), respectively. Areas under summary receiver operating characteristic curves of GPR for predicting significant fibrosis, severe fibrosis, and cirrhosis were 0.733, 0.777, and 0.796, respectively. Subgroup analysis was performed according to geographical region and histological scoring system with similar results.

CONCLUSION

GPR has moderate diagnostic accuracy for predicting HBV-related significant fibrosis, severe fibrosis, and cirrhosis, and further studies with large sample size, rigorous design, multicenter study population are urgently needed.

A Noninvasive Score to Predict Liver Fibrosis in HBeAg-Positive Hepatitis B Patients with Normal or Minimally Elevated Alanine Aminotransferase Levels

Noninvasive fibrosis tests are highly needed but have not been well studied in chronic hepatitis B patients with normal or minimally elevated alanine aminotransferase (ALT) levels. This study is aimed at developing a noninvasive score system to predict liver fibrosis in these patients. HBeAg-positive chronic hepatitis B patients with ALT levels of <80 IU/l and liver histology (n = 290) were assigned to training (n = 203) or validation (n = 87) groups. Training group patients were divided into nonsignificant (F0–1) and significant fibrosis (F2–4) according to METAVIR stages. Logistic regression was performed to identify factors for liver fibrosis and develop a score system. The capacity of the score to identify the severity of fibrosis was displayed by receiver operating characteristic curve (ROC) and area under ROC (AUROC) values. Multivariate logistic regression showed that HBeAg (ratios of the sample to the cutoff values (S/CO)) and liver stiffness measurement (LSM; kilopascals (kPa)) were independent factors of liver fibrosis. A score system composed of HBeAg and LSM by assigning a point of 1, 2, or 3 to different HBeAg and LSM levels, respectively, was developed. The scores 2-3, 4, and 5-6 of the sum of HBeAg and LSM points indicated nonsignificant, indeterminate, and significant fibrosis, respectively. The score system had an AUROC of 0.880 and showed similar performance in validation group patients. The accuracy for identifying significant and nonsignificant fibrosis was 77.14% in validation group patients and 71.26% in the entire group of patients. It is suggested that this noninvasive score system can accurately predict hepatic fibrosis and may reduce the need for liver biopsy in HBeAg-positive patients with normal or minimally elevated ALT levels.

Transient Elastography for Significant Liver Fibrosis and Cirrhosis in Chronic Hepatitis B: A Meta-Analysis

BACKGROUND

The hepatitis B virus infection is a global health issue and the stage of liver fibrosis affects the prognosis in patients with chronic hepatitis B (CHB). We performed the meta-analysis describing diagnostic accuracy of transient elastography (TE) for predicting CHB-related fibrosis.

METHODS

We performed an adequate literature search to identify studies that assessed the diagnostic accuracy of TE in CHB patients using biopsy as reference standard. Hierarchical summary receiver-operating curves model and the bivariate mixed-effects binary regression model were applied to generate summary receiver-operating characteristic curves and pooled estimates of sensitivity and specificity.

RESULTS

The area under the summary receiver-operating curve for significant fibrosis and cirrhosis was 0.86 (95% confidence interval (CI): 0.83-0.89) and 0.92 (95% CI: 0.90-0.94), respectively. The sensitivity, specificity, and diagnostic odds ratio of TE for significant fibrosis were 0.78 (95% CI: 0.73-0.81, p < 0.01; I² = 85.59%), 0.81 (95% CI: 0.77-0.84, p < 0.01; I² = 88.20%), and 14.44 (95% CI: 10.80-19.31, p < 0.01; I² = 100%) and for cirrhosis were 0.84 (95% CI: 0.80-0.88, p < 0.01; I² = 76.67%), 0.87 (95% CI: 0.84-0.90, p < 0.01; I² = 90.89%), and 36.63 (95% CI: 25.38-52.87, p < 0.01; I² = 100%), respectively. The optimal cut-off values of TE were 7.25 kPa for diagnosing significant fibrosis and 12.4 kPa for diagnosing cirrhosis, respectively.

CONCLUSION

TE is of great value in the detection of patients with CHB-related cirrhosis but has a suboptimal accuracy in the detection of significant fibrosis.