A novel predictive model using routinely clinical parameters to predict liver fibrosis in patients with chronic hepatitis B

Using blood routine indicators to establish a machine learning model for predicting liver fibrosis in patients with Schistosoma japonicum

This study intends to use the basic information and blood routine of schistosomiasis patients to establish a machine learning model for predicting liver fibrosis. We collected medical records of Schistosoma japonicum patients admitted to a hospital in China from June 2019 to June 2022. The method was to screen out the key variables and six different machine learning algorithms were used to establish prediction models. Finally, the optimal model was compared based on AUC, specificity, sensitivity and other indicators for further modeling. The interpretation of the model was shown by using the SHAP package. A total of 1049 patients' medical records were collected, and 10 key variables were screened for modeling using lasso method, including red cell distribution width-standard deviation (RDW-SD), Mean corpuscular hemoglobin concentration (MCHC), Mean corpuscular volume (MCV), hematocrit (HCT), Red blood cells, Eosinophils, Monocytes, Lymphocytes, Neutrophils, Age. Among the 6 different machine learning algorithms, LightGBM performed the best, and its AUCs in the training set and validation set were 1 and 0.818, respectively. This study established a machine learning model for predicting liver fibrosis in patients with Schistosoma japonicum. The model could help improve the early diagnosis and provide early intervention for schistosomiasis patients with liver fibrosis.

Noninvasive Models to Assess Liver Inflammation and Fibrosis in Chronic HBV Infected Patients with Normal or Mildly Elevated Alanine Transaminase Levels: Which One Is Most Suitable?

The prevalence of substantial inflammation or fibrosis in treatment-naïve patients with chronic hepatitis B (CHB) and normal alanine transaminase (ALT) levels is high. A retrospective analysis was conducted on 559 consecutive patients with hepatitis B virus infection, who underwent liver biopsy, to investigate the value of noninvasive models based on routine serum markers for evaluating liver histology in CHB patients with normal or mildly elevated ALT levels and to provide treatment guidance. After comparing 55 models, we identified the top three models that exhibited excellent performance. The APGA model, based on the area under the receiver operating characteristic curve (AUROC), demonstrated a superior ability to evaluate significant (AUROC = 0.750) and advanced fibrosis (AUROC = 0.832) and demonstrated a good performance in assessing liver inflammation (AUROCs = 0.779 and 0.874 for stages G ≥ 2 and G ≥ 3, respectively). APGA also exhibited significant correlations with liver inflammation and fibrosis stage (correlation coefficients, 0.452 and 0.405, respectively (p < 0.001)). When the patients were stratified into groups based on HBeAg status and ALT level, APGA consistently outperformed the other 54 models. The other top two models, GAPI and XIE, also outperformed models based on other chronic hepatitis diseases. APGA may be the most suitable option for detecting liver fibrosis and inflammation in Chinese patients with CHB.

Non-Invasive Serum Biomarkers for the Diagnosis of Cirrhosis in Patients with Autoimmune Hepatitis (AIH) and AIH-Primary Biliary Cholangitis Overlap Syndrome (AIH-PBC): Red Cell Distribution Width to Platelet Ratio (RPR) Yielded the Most Promising Result

Several serum biomarkers for fibrosis assessment have been proposed in various liver diseases, but in autoimmune hepatitis (AIH) or overlap with primary biliary cholangitis (PBC; AIH-PBC) patients, the data are scarce. This retrospective cross-sectional study was conducted to validate six non-invasive biomarkers in the diagnosis of cirrhosis (F4 fibrosis) in such patients. We included adult patients diagnosed with AIH or AIH-PBC overlap syndrome who underwent a liver biopsy between 2011 and 2021. Laboratory data were collected to calculate the following scores: red cell distribution width to platelet ratio (RPR), aspartate aminotransferase/platelet ratio index (APRI), Fibrosis-4 index (FIB-4), aspartate aminotransferase (AST) to alanine aminotransferase (ALT) ratio (AAR), neutrophil-to-lymphocyte ratio (NLR), and lymphocyte-to-platelet ratio (LPR). A total of 139 patients were eligible (111 AIH and 28 AIH-PBC). The prevalence of cirrhosis was 35.3% (36% in AIH and 32.1% in AIH-PBC). The AUROCs of the RPR, FIB-4, APRI, AAR, LPR, and NLR in all patients were 0.742, 0.724, 0.650, 0.640, 0.609, and 0.585, respectively. RPR was significantly superior to APRI, NLR, and LPR. Moreover, RPR showed the highest AUROC (0.915) in the overlap AIH-PBC subgroup. In conclusion, RPR yielded the highest diagnostic accuracy to predict cirrhosis in AIH and AIH-PBC overlap syndrome patients, while FIB-4 was considerably optimal.

A novel web-based online nomogram to predict advanced liver fibrosis in patients with autoimmune hepatitis-primary biliary cholangitis overlap syndrome

Background

Patients with autoimmune hepatitis-primary biliary cholangitis (AIH-PBC) overlap syndrome have a worse prognosis compared to AIH or PBC alone and accurately predicting the severity and dynamically monitoring the progression of disease are therefore essential. We aimed to develop a nomogram-based model to predict advanced liver fibrosis in patients with AIH-PBC overlap syndrome.

Methods

A total of 121 patients with AIH-PBC overlap syndrome were retrospectively included and randomly assigned to a development set and a validation set. Backward stepwise regression's best model with the lowest AIC was employed to create a nomogram. Diagnose accuracy was evaluated using the area under the receiver operator characteristic curve (AUROC), calibration analysis, and decision curve analysis (DCA) and was compared with aspartate aminotransferase-to-platelet ratio (APRI) and fibrosis index based on four factors-4 (FIB-4) score.

Results

The median age of patients was 53.0 years (IQR: 46.0-63.0), and female patients accounted for 95.0 %. Platelets, globulin, total bilirubin, and prothrombin time were associated with advanced fibrosis (≥S3) and used to construct an AIH-PBC overlap syndrome fibrosis (APOSF)-nomogram (available online at https://ndth-zzy.shinyapps.io/APOSF-nomogram/). The AUROCs of APOSF-nomogram were 0.845 (95 % CI: 0.754-0.936) and 0.843 (95 % CI: 0.705-0.982) in development set and validation set respectively, which was significantly better than APRI and FIB-4. Calibration revealed that the estimated risk fits well with biopsy-proven observation. DCA outperformed APRI and FIB4 in terms of net benefit, demonstrating clinical utility.

Conclusion

This novel non-invasive web-based online APOSF-nomogram provided a convenient tool for identifying advanced fibrosis in patients with AIH-PBC overlap syndrome. Further prospective, multicenter studies with large sample size are necessary to validate the applicability of APOSF-nomogram.

An easy-to-use AIHF-nomogram to predict advanced liver fibrosis in patients with autoimmune hepatitis

Background

The evaluation of liver fibrosis is essential in the management of patients with autoimmune hepatitis (AIH). We aimed to establish and validate an easy-to-use nomogram to identify AIH patients with advanced liver fibrosis.

Methods

AIH patients who underwent liver biopsies were included and randomly divided into a training set and a validation set. The least absolute shrinkage and selection operator (LASSO) regression was used to select independent predictors of advanced liver fibrosis from the training set, which were utilized to establish a nomogram. The performance of the nomogram was evaluated using the receiver characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).

Results

The median age of 235 patients with AIH was 54 years old, with 83.0% of them being female. Six independent factors associated with advanced fibrosis, including sex, age, red cell distribution width, platelets, alkaline phosphatase, and prothrombin time, were combined to construct a predictive AIH fibrosis (AIHF)-nomogram. The AIHF-nomogram showed good agreement with real observations in the training and validation sets, according to the calibration curve. The AIHF-nomogram performed significantly better than the fibrosis-4 and aminotransferase-to-platelet ratio scores in the training and validation sets, with an area under the ROCs for predicting advanced fibrosis of 0.804 in the training set and 0.781 in the validation set. DCA indicated that the AIHFI-nomogram was clinically useful. The nomogram will be available at http://ndth-zzy.shinyapps.io/AIHF-nomogram/as a web-based calculator.

Conclusions

The novel, easy-to-use web-based AIHF-nomogram model provides an insightful and applicable tool to identify AIH patients with advanced liver fibrosis.

Construction of a Lasso regression-based prediction model for development of cirrhosis in chronic hepatitis B

BACKGROUND

Chronic hepatitis B (CHB) is a global epidemic, and its progression to cirrhosis is often overlooked by patients. Noninvasive diagnostic models for cirrhosis, which are developed using common clinical indicators, can provide reference value for the early diagnosis and treatment of cirrhosis in CHB.

AIM

To construct a prediction model for cirrhosis based on common clinical indicators.

METHODS

Patients with CHB who underwent liver biopsy at the Department of Infectious Diseases, The First or Second Affiliated Hospital of Anhui Medical University from 2010 to 2018 were selected, and their laboratory test indicators were collected and compared between patients with and without cirrhosis. Lasso regression model was used to screen the variables with predictive value for cirrhosis, and multivariate logistic regression analysis was performed to establish a prediction model for cirrhosis. The area under the curve (AUC) was calculated to assess the discrimination performance of the model. Decision curve analysis (DCA) was performed to assess the benefit of the model, and calibration curve-based analysis (CA) was performed to assess the calibration of the model.

RESULTS

A total of 1087 CHB cases were included, of which 135 had cirrhosis. All indicators were statistically different between the two groups except for hepatitis B virus (HBV) DNA, alanine transaminase (ALT) (P < 0.05). Lasso regression analysi identified the predictive variables as age, alpha-fetoprotein (AFP), albumin (ALB), globulin (GLB), glutamyl transpeptidase (GGT), and platelet count (PLT). A prediction model for cirrhosis was developed by multifactorial logistic regression analysis: Logit P = 1.26 + 0.02 × age + 0.001 × AFP - 0.10 × ALB + 0.07 × GLB + 0.004 × GGT - 0.02 × PLT. The AUC of the model for predicting cirrhosis was 0.83 (95% confidence interval: 0.79-0.87). DCA suggested that the use of the developed prediction model resulted in an increased net benefit for the patients, and CA suggested that the predictive effect of the prediction model was in accordance with the actual outcome.

CONCLUSION

The present study has developed a prediction model for cirrhosis based on age, AFP, ALB, GLB, GGT, and PLT in patients with CHB, and it is useful for the early diagnosis of cirrhosis in CHB.

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.

Comparison of two-dimensional shear wave elastography, magnetic resonance elastography, and three serum markers for diagnosing fibrosis in patients with chronic hepatitis B: a meta-analysis

BACKGROUND

Two-dimensional shear wave elastography (2D-SWE), magnetic resonance elastography (MRE), aspartate transaminase-to-platelet ratio index (APRI), fibrosis index based on 4 factors (FIB-4), and King's score have been proposed for diagnosing fibrosis.

METHODS

Literature databases were searched until October 1st, 2020. The summary area under the receiver operating characteristic curve (AUROC), the summary diagnostic odds ratios, and the summary sensitivities and specificities were used to assess the performance of these noninvasive methods for staging fibrosis.

RESULTS

Our final data contained 72 studies. The prevalence of significant fibrosis, advanced fibrosis, and cirrhosis was 58.3%, 36.2%, and 20.5%, respectively, in chronic hepatitis B (CHB). For 2D-SWE and MRE, the summary AUROCs were 0.89 and 0.97, 0.95 and 0.97, and 0.94 and 0.97 for significant fibrosis, advanced fibrosis, and cirrhosis, respectively. The summary AUROCs using APRI and FIB-4 for detecting significant fibrosis, advanced fibrosis, and cirrhosis were 0.76 and 0.75, 0.74 and 0.77, and 0.77 and 0.82, respectively. The summary AUROCs of King's score for detecting significant fibrosis and cirrhosis were 0.77 and 0.83, respectively.

CONCLUSION

MRE and 2D-SWE may show the best diagnostic accuracy for predicting fibrosis in CHB. Among the three serum markers, King's score may be more useful for diagnosing 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.

A novel nomogram to predict evident histological liver injury in patients with HBeAg-positive chronic hepatitis B virus infection

Background

HBeAg-positive chronic infection is a unique phase of chronic hepatitis B virus (HBV) infection. Current guidelines advise against starting antiviral treatment for HBeAg-positive chronic hepatitis B virus (HBV) infection patients, some data suggest treating such patients may reduce the risk of hepatocellular carcinoma. We aimed to explore whether these patients can have evident histological liver injury (EHLI), and develop a non-invasive model for identifying EHLI in such patients.

Method

We assessed whether HBeAg-positive chronic HBV infection patients can have EHLI defined by Ishak fibrosis stage ≥3 and/or histologic activity index ≥ 9 in a prospective multicenter study. Logistic and Lasso regression was used to select the optimal predictors. We used Akaike information criterion, discrimination improvement, net reclassification improvement to develop and validate models predicting EHLI risk in training cohort and two external validation cohorts.

Findings

Of these 336 patients met the inclusion criteria, 181(54%) were HBeAg-positive chronic HBV infection, of whom 60 patients (33%) had EHLI, the proportion of significant fibrosis was higher than that of significant inflammation (33% vs. 8%, P < 0.001). Age, liver stiffness measurement, ALT, alkaline phosphatase, and albumin were identified as independent predictors for EHLI and used to develop a nomogram that have been demonstrated having a good performance in predicting EHLI with AUROCs of 0.92(95%CI: 0.86–0.99) in the training cohort (n = 233) and 0.90(95%CI: 0.84–0.95) in validation cohort 1(n = 103), significant correcting current guidelines recommendations overestimating insignificant or significant histological disease. After 72-weeks entecavir treatment for HBeAg-positive chronic HBV infection patients with EHLI identified by nomogram, histological improvement occurred in 40 of 49(82%), 38(78%) had fibrosis reversal, and 35(73%) no longer had EHLI.

Interpretation

In HBeAg-positive chronic HBV infection patients, 33% has EHLI. The nomogram developed in this study can accurately identify HBeAg-positive chronic HBV infection patients with EHLI, and that responded very well to antiviral therapy.

Funding

This study was funded by the State Key Projects Specialized on Infectious Disease, Chinese Ministry of science and technology (2013ZX10005002; 2018ZX10725506), National Natural Science Foundation of China (81970525) and Beijing Key Research Project of Special Clinical Application (Z151100004015221).

Artificial Neural Network Model for Liver Cirrhosis Diagnosis in Patients with Hepatitis B Virus-Related Hepatocellular Carcinoma

Background

Testing for the presence of liver cirrhosis (LC) is one of the most critical diagnostic and prognostic assessments for patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). More non-invasive tools are needed to diagnose LC but the predictive abilities of current models are still inconclusive. This study aimed to develop and validate a novel and non-invasive artificial neural network (ANN) model for diagnosing LC in patients with HBV-related HCC using routine laboratory serological indicators.

Methods

A total of 1152 HBV-related HCC patients who underwent hepatectomy were included and randomly divided into the training set (n = 864, 75%) and validation set (n = 288, 25%). The ANN model was constructed from the training set using multivariate Logistic regression analysis and then verified in the validation set.

Results

The morbidity of LC in the training and validation sets was 41.2% and 46.8%, respectively. Multivariate analysis showed that age, platelet count, prothrombin time and total bilirubin were independent risk factors for LC (P < 0.05). The area under the ROC curve (AUC) analyses revealed that the ANN model had higher predictive accuracy than the Logistic model (ANN: 0.757 vs Logistic: 0.721; P < 0.001), and other scoring systems (ANN: 0.757 vs CP: 0.532, MELD: 0.594, ALBI: 0.575, APRI: 0.621, FIB-4: 0.644, AAR: 0.491, and GPR: 0.604; P < 0.05 for all) in diagnosing LC. Similar results were obtained in the validation set.

Conclusion

The ANN model has better diagnostic capabilities than other commonly used models and scoring systems in assessing LC risk in patients with HBV-related HCC.

Diagnostic value of fibrinogen to prealbumin ratio and gamma-glutamyl transpeptidase to platelet ratio in the progression of AFP-negative hepatocellular carcinoma

Background

This study aimed to comprehensively assess the diagnostic value of fibrinogen to prealbumin ratio (FPR) and gamma-glutamyl transpeptidase to platelet ratio (GPR) as single markers or in combination in patients with alpha-fetoprotein-negative (AFP-negative) hepatocellular carcinoma (HCC).

Methods

A total of 199 healthy controls and 515 AFP-negative patients were enrolled in this study, including 180 HCC inpatients, 151 liver cirrhosis (LC) patients, and 184 chronic hepatitis (CH) cases. Mann-Whitney U or Kruskal-Wallis H test were used to analyze differences between groups in laboratory parameters and clinicopathological features. The diagnostic value of FPR and GPR, alone or in combination, in AFP-negative HCC (AFP-NHCC) patients was determined via a receiver operating characteristic (ROC) curve.

Results

The levels of FPR and GPR were gradually increased in the development of AFP-NHCC and positively correlated with the tumor size and Barcelona Clinic Liver Cancer (BCLC) stages. Moreover, GPR was associated with Edmondson-Steiner grades. After univariate logistic regression analysis, FPR and GPR remained independent predictors of adverse outcomes. The combination of FPR and GPR had a good ability to detect AFP-NHCC from the control group (area under curve [AUC] = 0.977), AFP-negative CH (AUC = 0.745), and AFP-negative LC (AUC = 0.666). FPR combined with GPR possessed a larger area (0.943, 0.971) and sensitivity (87.50%, 89.81%) than FPR or GPR alone for differentiating AFP-NHCC with tumor size < 3 cm or at the BCLC-A stage.

Conclusions

The pretreatment levels of FPR and GPR played vital roles in the development of AFP-NHCC, especially in patients with early or small AFP-NHCC.

Noninvasive inflammatory markers for assessing liver fibrosis stage in autoimmune hepatitis patients

OBJECTIVE

To examine the accuracy of noninvasive inflammatory markers in predicting liver fibrosis stage in patients with autoimmune hepatitis (AIH).

PATIENTS AND METHODS

We enrolled 55 patients with AIH and 60 healthy controls in this study, and divided them into three groups: F0 (control); F1-F3 (noncirrhotic fibrosis); and F4 (cirrhosis). The following markers were analyzed for all participants: lymphocyte-to-neutrophil ratio (LNR); lymphocyte-to-platelet ratio (LPR); lymphocyte-to-monocyte ratio (LMR); immunoglobulin-to-platelet ratio (IGPR); aminotransferase-to-platelet ratio index (APRI); aspartate aminotransferase-to-alanine aminotransferase ratio (AAR); and fibrosis-4 score (FIB-4). The predictive accuracy of these noninvasive markers was assessed using area under the receiver operating characteristic curve. Multivariate ordinal logistic regression models were used to analyze associations between the noninvasive markers and liver fibrosis stage.

RESULTS

AAR, LPR, LMR, IGPR, APRI, and FIB-4 were linked to liver fibrosis-stage (P < 0.05), with correlation indices of - 0.219, 0.258, - 0.149, 0.647, 0.841, and 0.704, respectively, but not LNR (P = 0.093). area under the receiver operating characteristic curves of LPR, IGPR, AAR, LMR, APRI, and FIB-4 for detecting cirrhosis (F4 vs. F0-F3) were 0.936 (95% confidence interval: 0.870-1.000, P < 0.001), 0.939 (0.875-1.000, P < 0.001), 0.528 (0.319-0.738, P = 0.768), 0.555 (0.409-0.700, P = 0.568), 0.798 (0.694-0.902, P = 0.002), and 0.881 (0.796-0.967, P < 0.001). Our multivariate ordinal regression analysis showed that LPR and IGPR were associated independently with liver fibrosis stage, with a coefficient of 0.385 (95% confidence interval: 0.103-0.667, P = 0.007) and 14.903 (2.091-27.786, P = 0.023), respectively.

CONCLUSION

LPR and IGPR were associated independently with liver fibrosis stage in treatment-naive AIH, and were superior to APRI and FIB-4 in detecting cirrhosis.

Noninvasive indicators predict advanced liver fibrosis in autoimmune hepatitis patients

BACKGROUND

Liver biopsy is the criterion standard for diagnosing liver fibrosis, but it is not widely used to monitor liver fibrosis because of the invasiveness, risk of complications, and sample errors. Therefore, it is necessary to involve other techniques to monitor liver fibrosis or cirrhosis during clinical practice. The objective was to explore noninvasive indicators to predict advanced liver fibrosis in autoimmune hepatitis (AIH) patients.

METHODS

A total of 45 AIH patients and 47 healthy controls were recruited to this retrospective study. Complete blood count and liver function tests were performed for all subjects. AIH patients were divided into "no/minimal fibrosis" group and "advanced fibrosis" group based on liver biopsy.

RESULTS

AIH patients demonstrated significantly higher monocytes, MCV, RDW-CV, RDW-SD, NLR, RDW-CV/PLT, RDW-SD/PLT, TBIL, DBIL, GLB, ALT, AST, GGT, ALP, and GPR and lower WBC, neutrophils, lymphocytes, RBC, HGB, HCT, LMR, TP, ALB, and AAR compared with healthy controls. Patients with advanced fibrosis showed remarkably higher RDW-CV, RDW-SD, RDW-CV/PLT, RDW-SD/PLT, AAR, and FIB-4 and lower RBC, PLT, PCT, and ALB compared with the no/minimal fibrosis group. Logistic regression analysis showed that RDW-SD/PLT was an independent risk factor for advanced fibrosis with an OR (95% CI) of 2.647 (1.383-5.170). Receiver operating characteristic (ROC) analysis revealed that RDW-SD, RDW-CV/PLT, RDW-SD/PLT, FIB-4, and AAR had an area under the ROC curve (AUC) above 0.700 and RDW-SD/PLT had the largest AUC of 0.785 with a cutoff value of 0.239.

CONCLUSION

RDW-SD, RDW-CV/PLT, RDW-SD/PLT, FIB-4, and AAR were excellent noninvasive biomarkers and RDW-SD/PLT was an independent risk factor for predicting advanced fibrosis in AIH patients.

Red cell distribution width to platelet ratio for liver fibrosis: a systematic review and meta-analysis of diagnostic accuracy

Introduction: Red cell distribution width to platelet ratio (RPR) may be a useful marker for the evaluation of liver fibrosis in chronic liver disease (CLD). We sought to investigate its value in fibrosis-related outcomes in a meta-analysis of diagnostic accuracy. Areas covered: We searched MEDLINE (1966-2019), Clinicaltrials.gov (2008-2019), Cochrane Central Register of Controlled Trials (CENTRAL) (1999-2019), Google Scholar (2004-2019) and WHO (International Clinical Trials Register Platform) databases using a structured algorithm. The articles were assessed by Quality Assessment of Diagnostic Accuracy Studies tool (QUADAS-2). In over 1,800 patients for each outcome, pooled sensitivity and specificity for a) significant fibrosis, b) advanced fibrosis and c) cirrhosis were: a) 0.635 and 0.769 with an AUC of 0.747, b) 0.607 and 0.783 with an AUC of 0.773, c) 0.739 and 0.768 with an AUC of 0.818 respectively. Similar results were found for chronic hepatitis B in all outcomes. Subgroup analysis indicated a high specificity for advanced fibrosis detection in primary biliary cirrhosis. Sensitivity analysis did not alter the results. Expert opinion: RPR is a good predictor of fibrosis, especially as severity of chronic liver disease progresses. Future research should elucidate its value in specific etiologies of chronic liver disease.

Performance of common imaging techniques vs serum biomarkers in assessing fibrosis in patients with chronic hepatitis B: A systematic review and meta-analysis

BACKGROUND

Noninvasive biomarkers have been developed to predict hepatitis B virus (HBV) related fibrosis owing to the significant limitations of liver biopsy. Both serum biomarkers and imaging techniques have shown promising results and may improve the evaluation of liver fibrosis. However, most of the previous studies focused on the diagnostic effects of various imaging techniques on fibrosis in all chronic liver diseases.

AIM

To compare the performance of common imaging methods and serum biomarkers for prediction of significant fibrosis caused only by HBV infection.

METHODS

A systematic review was conducted on the records available in PubMed, EMBASE, and the Cochrane Library electronic databases until December 2018. We systematically assessed the effectiveness of two serum biomarkers and three imagine techniques in predicting significant fibrosis solely caused by HBV infection. The serum biomarkers included aspartate aminotransferase-to-platelet ratio index (APRI) and fibrosis index based on the 4 factors (FIB-4). The three imaging techniques included acoustic radiation force impulse (ARFI), FibroScan, and magnetic resonance elastography (MRE). Three parameters, the area under the summary receiver operating characteristic curve (AUSROC), the summary diagnostic odds ratio, and the summary sensitivity and specificity, were used to examine the accuracy of all tests for liver fibrosis.

RESULTS

Out of 2831 articles evaluated for eligibility, 204 satisfied the predetermined inclusion criteria for this current meta-analysis. Eventually, our final data contained 81 studies. The AUSROCs of serum biomarkers of APRI and FIB-4 were both 0.75. For imaging techniques (ARFI, FibroScan, and MRE), the areas were 0.89, 0.83, and 0.97, respectively. The heterogeneities of ARFI and FibroScan were statistically significant (I² > 50%). The publication bias was not observed in any of the serum biomarkers or imaging methods.

CONCLUSION

These five methods have attained an acceptable level of diagnostic accuracy. Imaging techniques, MRE in particular, demonstrate significant advantages in accurately predicting HBV-related significant fibrosis, while serum biomarkers are admissible methods.

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.

The relationship between serum hepatitis B virus DNA level and liver histology in patients with chronic HBV infection

BACKGROUND

There is no consensus regarding the relationship between HBV DNA and liver fibrosis, and the relationship between HBV DNA and the degree of liver cirrhosis has not been reported in patients with chronic HBV infection.

METHODS

From January 2011 to December 2016, liver biopsies were performed on 396 patients with chronic hepatitis B and cirrhosis. Assessments of liver fibrosis and cirrhosis were based on the Laennec staging system.

RESULTS

Serum levels of HBV DNA were correlated with fibrosis and cirrhosis (KW = 73.946, P<0.001). Serum HBV DNA level was correlated with mild fibrosis, moderate to severe fibrosis and cirrhosis (P = 0.009, P<0.001, and P<0.001, respectively). The HBeAg-positive group and HBeAg-negative group showed significant differences in HBV DNA levels, and the rates of mild fibrosis, severe fibrosis and cirrhosis were significantly different between these two groups (F = 17.585, P<0.001 and F = 6.017, P = 0.003, respectively). The replication status of the serum HBV DNA affected fibrosis formation as well as cirrhosis (χ2 = 53.76, P<0.001). In the HBeAg-positive group, the sensitivity, specificity and AUC values of HBV DNA as a predictor for mild fibrosis and cirrhosis were 64.3%, 78.94% and 0.818, respectively, and 81.0%, 69.2%, and 0.871, respectively. In the HBeAg-negative group, the sensitivity, specificity and AUC values of HBV DNA for liver sclerosis prediction were 48%, 76.8% and 0.697, respectively.

CONCLUSIONS

Different HBV DNA levels had different effects on the formation of fibrosis and sclerosis in liver tissues. HBV DNA levels can predict mild fibrosis and cirrhosis in liver tissue, which is enhanced in HBeAg-positive patients.

How to improve access to therapy in hepatitis B patients

Despite the availability of a preventive vaccine and active antiviral treatments that stop disease progression and reduce the risk of hepatocellular carcinoma, hepatitis B is still a major public health problem. Only an estimated 10% of the 257 million people living with HBV have been diagnosed and as few as 1% are being adequately treated. Barriers to diagnosis and treatment include: (i) limited awareness and lack of knowledge about HBV infection and HBV-related diseases; (ii) under-diagnosis with insufficient screening and referral to care; (iii) limited treatment due to drug availability, costs, reimbursement policies and the need for long-term or life-long therapy. These barriers and the actions needed to improve access to treatment are strongly influenced by the prevalence of infection and affect middle-high vs low-middle income countries differently, where most HBV carriers are found. In high-prevalence regions and low-to middle-income countries, the main challenges are availability and cost while in low-prevalence regions and middle-to high-income countries low screening rates, public awareness, social stigma and discrimination play an important role. Overcoming these challenges on a global scale is a complex clinical and public health challenge and multilateral commitment from pharmaceutical companies, governments, funders and the research community is lacking. The new WHO 2016 Global Health Sector Strategy on viral hepatitis targets testing and treatment, suggesting that important but strong actions are needed from advocacy groups, scientific societies and funding agencies to foster awareness and access to cure.

Progress in non-invasive detection of liver fibrosis

Liver fibrosis is an important pathological precondition for hepatocellular carcinoma. The degree of hepatic fibrosis is positively correlated with liver cancer. Liver fibrosis is a series of pathological and physiological process related to liver cell necrosis and degeneration after chronic liver injury, which finally leads to extracellular matrix and collagen deposition. The early detection and precise staging of fibrosis and cirrhosis are very important for early diagnosis and timely initiation of appropriate therapeutic regimens. The risk of severe liver fibrosis finally progressing to liver carcinoma is >50%. It is known that biopsy is the gold standard for the diagnosis and staging of liver fibrosis. However, this method has some limitations, such as the potential for pain, sampling variability, and low patient acceptance. Furthermore, the necessity of obtaining a tissue diagnosis of liver fibrosis still remains controversial. An increasing number of reliable non-invasive approaches are now available that are widely applied in clinical practice, mostly in cases of viral hepatitis, resulting in a significantly decreased need for liver biopsy. In fact, the non-invasive detection and evaluation of liver cirrhosis now has good accuracy due to current serum markers, ultrasound imaging, and magnetic resonance imaging quantification techniques. A prominent advantage of the non-invasive detection and assessment of liver fibrosis is that liver fibrosis can be monitored repeatedly and easily in the same patient. Serum biomarkers have the advantages of high applicability (>95%) and good reproducibility. However, their results can be influenced by different patient conditions because none of these markers are liver-specific. The most promising techniques appear to be transient elastography and magnetic resonance elastography because they provide reliable results for the detection of fibrosis in the advanced stages, and future developments promise to increase the reliability and accuracy of the staging of hepatic fibrosis. This article aims to describe the recent progress in the development of non-invasive assessment methods for the staging of liver fibrosis, with a special emphasize on computer-aided quantitative and deep learning methods.

Aspartate transaminase to platelet ratio index and gamma-glutamyl transpeptidase-to-platelet ratio outweigh fibrosis index based on four factors and red cell distribution width-platelet ratio in diagnosing liver fibrosis and inflammation in chronic hepatitis B

BACKGROUND

The benefits of using serum markers to diagnose stages of liver disease in chronic hepatitis B (CHB) patients are controversial. We conducted a study to compare the clinical significance of four markers in evaluating liver inflammation and fibrosis in CHB patients.

METHODS

A total of 323 treatment-naive CHB patients who received a liver biopsy and routine laboratory testing were enrolled in our study. We used the Scheuer scoring system as a pathological standard for diagnosing liver inflammation and fibrosis. The diagnostic performance of the fibrosis index based on four factors (FIB-4), the aspartate transaminase to platelet ratio index (APRI), the gamma-glutamyl transpeptidase-to-platelet ratio (GPR), and the red cell distribution width-platelet ratio (RPR) were analyzed with receiver-operating characteristic curves (ROC).

RESULTS

No significant differences among the four indexes for diagnosing significant fibrosis (S ≥ 2) was found, while APRI and GPR were superior to FIB-4 and RPR in diagnosing moderate (G ≥ 2), severe (G ≥ 3) inflammation, and severe fibrosis (S ≥ 3). The AUROCs for diagnosing G ≥ 2 and G ≥ 3 were 0.732 and 0.861 for APRI, 0.726 and0.883 for GPR, 0.703 and0.705 for FIB-4, and 0.660 and 0.747 for RPR, respectively. The AUROCs for diagnosing S ≥ 2 and S ≥ 3 were0.724 and 0.799 for APRI, 0.714 and0.801 for GPR, 0.683 and0.730 for FIB-4, and 0.643 and 0.705 for RPR, respectively.

CONCLUSION

APRI and GPR were more effective than FIB-4 and RPR at diagnosing liver inflammation and fibrosis.