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

Chen, Yanping; Li, Yanping; Li, Na; Fan, Xiude; Li, Chunyan; Zhang, Pingping; Han, Qunying; Liu, Zhengwen

doi:https://doi.org/10.1155/2018/3924732

Disease Markers

On this page

Abstract Introduction Materials and Methods Results Discussion Data Availability Disclosure Conflicts of Interest Acknowledgments Supplementary Materials References Copyright Related Articles

Research Article | Open Access

Volume 2018 | Article ID 3924732 | https://doi.org/10.1155/2018/3924732

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

Yanping Chen,^1,2Yanping Li,²Na Li,¹Xiude Fan,¹Chunyan Li,^1,2Pingping Zhang,^1,2Qunying Han,¹and Zhengwen Liu¹

Academic Editor: Timo Sorsa

Received11 Aug 2018

Revised01 Sept 2018

Accepted09 Sept 2018

Published14 Oct 2018

Abstract

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 () were assigned to training () or validation () 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.

1. Introduction

Chronic hepatitis B virus (HBV) infection may induce chronic hepatitis, liver cirrhosis, and hepatocellular carcinoma (HCC) and affects nearly 250 million people worldwide [1]. The course of chronic HBV infection is a dynamic process in which the individuals with HBV infection may experience different clinical phases displaying variable levels of serum alanine aminotransferase (ALT), HBV DNA, and HBV antigens [2]. The levels of serum ALT and HBV DNA and the severity of hepatic fibrosis are important predictors of long-term outcome and indicators of treatment initiation and response assessment [2, 3].

The indication of fibrosis or inflammation in patients with highly elevated ALT levels or cirrhosis is relatively easier. However, in HBV-infected patients with persistent borderline normal or slightly elevated ALT levels, liver biopsy is recommended [2] since it remains the gold standard for the evaluation of liver fibrosis and inflammation in chronic liver disease [4]. Liver biopsy is an invasive examination with high cost and certain pitfalls such as discomfort in patients, association of complications, and sampling errors [5, 6]. It is particularly difficult for patients to undergo multiple liver biopsies in order to serially monitor disease progression or to guide treatment. As a result, noninvasive approaches using readily available and noninvasive parameters have been developed for assessing the extent of liver fibrosis [7–13]. However, most of these methods were developed and used for hepatic fibrosis in hepatitis C virus (HCV) infection and/or HCV/human immunodeficiency virus (HIV) coinfection. Validation and comparisons of these models for liver fibrosis in chronic HBV infection showed unideal or inconsistent findings or diminished accuracy [14–22].

Recently, a model, gamma-glutamyltranspeptidase- (GGT-) to-platelet ratio (GPR), was developed to predict significant liver fibrosis and cirrhosis in patients with chronic HBV infection [23]. Some studies indicated that GPR had better performance in comparison with aspartate aminotransferase- (AST-) to-platelet ratio index (APRI) and fibrosis index based on 4 factors (FIB-4) in predicting liver fibrosis of chronic hepatitis B [24] and in improving the sensitivity and specificity of hepatic fibrosis assessment in chronic hepatitis B when combined with APRI or FIB-4 [25]. However, a study comparing seventeen noninvasive models including GPR showed that the models evaluated were not appropriate for all situations of chronic HBV infection [21]. Other studies showed that GPR does not add any advantage over APRI and FIB-4 in identifying significant fibrosis, severe fibrosis, and cirrhosis in chronic hepatitis B patients [26–28].

Few studies have been conducted to develop or evaluate noninvasive approaches in identifying liver fibrosis in hepatitis B e-antigen- (HBeAg-) positive chronic hepatitis B patients with normal or minimally elevated ALT levels (usually ALT of <2 upper limit of normal value (ULN)). APRI and FIB-4 were not indicated to be ideal hepatic fibrosis markers in these patients [20]. A model, globulin-platelet model (GP), was shown to be a more accurate noninvasive fibrosis model than APRI and FIB-4 to diagnose significant fibrosis and cirrhosis in chronic hepatitis B patients with high HBV DNA and mildly elevated ALT levels [29], but it has not been validated. Notably, liver stiffness measurement (LSM) by transient elastography, a noninvasive technique, was shown to be superior to APRI and FIB-4 for indicating liver fibrosis in HBV-infected patients with persistently normal ALT levels [20]. LSM was also shown to be a reliable noninvasive examination for the diagnosis of liver fibrosis in HBeAg-positive patients with high HBV DNA and normal or mildly elevated ALT levels [30]. However, the value of other noninvasive demographic, clinical, and laboratory parameters, especially their combination with LSM, needs to be further clarified in identifying liver fibrosis in HBeAg-positive patients with ALT of <2× ULN. Therefore, this study is aimed at developing a noninvasive approach by including LSM and routinely available noninvasive parameters in the analysis for the evaluation of liver fibrosis in HBeAg-positive patients with ALT of <2× ULN based on the fibrosis staging by liver biopsy. The results were also compared with the most discussed models, APRI and FIB-4, and the newly developed GPR.

2. Materials and Methods

2.1. Patients

The data of 290 HBeAg-positive chronic hepatitis B patients undergoing liver biopsy were collected from the Affiliated Hospital of Yan’an University from October 2013 to February 2018. Chronic HBV infection was defined as the persistent positivity of hepatitis B surface antigen (HBsAg), HBeAg, and antibody to hepatitis B core antigen (anti-HBc) for more than 6 months [31].

Inclusion criteria of patients were age ≥ 18 years; HBsAg, HBeAg, and HBV DNA positive for more than 6 months; serum ALT of <2× ULN; and signed informed consent for liver biopsy. Exclusion criteria of patients were: coinfection with other hepatotropic viruses such as HCV, hepatitis A virus, hepatitis E virus, or other viruses such as HIV; existence of other liver diseases including alcoholic, nonalcoholic, drug-induced, autoimmune liver diseases, and decompensated liver cirrhosis or tumors; diseases causing extrahepatic organ fibrosis; a history of antiviral therapy (interferon or nucleos(t)ides); pregnancy; and use of anticoagulant 1 week before liver biopsy. This study was performed to conform to the Declaration of Helsinki and was approved by the Ethics Committee of the Affiliated Hospital of Yan’an University (No. 2016–30).

2.2. Laboratory Tests

Fasting vein blood was collected for laboratory tests within 1 week of liver biopsy. Hyaluronic acid (HA), laminin, type III procollagen (PCIII), and type IV collagen (IV-C) were determined using Autodesk Chemiluminescent Immunoassay Analyzer (Yantai, China) and reagents from Beijing Yuande Bio-Medical Engineering Co., Ltd. (Beijing, China). HBV DNA quantification was performed using Abbott RealTime HBV assay with the Abbott m2000 SystemDNA reagents (Abbott Molecular Inc., Des Plaines, IL, USA) and ABI7500 Quantitative Cycler (ABI, USA). HBsAg was quantitatively determined by chemiluminescent microparticle immunoassay (CMIA) of ARCHITECT HBsAg assay (Abbott Ireland, Sligo, Ireland). HBeAg and anti-HBc were determined by CMIA of ARCHITECT HBeAg assay (Abbott GmbH & Co. KG, Wiesbaden, Germany) and anti-HBc II assay (Abbott GmbH & Co. KG, Wiesbaden, Germany), respectively, and the ratios of the sample to the cutoff values (S/CO) were used as HBeAg and anti-HBc levels, respectively.

2.3. Imaging Examination and Liver Stiffness Measurement

The thickness of the spleen and the inner diameter of the portal vein were measured using a Toshiba Ultrasound (Toshiba, Japan). LSM (kilopascals (kPa)) was performed using a liver transient elastography FibroScan System (Echosens SAS, Paris, France). The operator was blinded to the clinical characteristics of the patients. The median value of LSM was used to represent liver stiffness.

2.4. Liver Biopsy and Pathological Diagnosis

Percutaneous liver biopsy was performed with local anesthesia under the guidance of ultrasonography. Liver samples of about 1.5–3 cm in length were fixed with 10% formaldehyde solution and embedded with paraffin for histological analysis. Liver histology was interpreted by two hepatology pathologists who were blinded to the clinical information and the results of noninvasive tests. According to the METAVIR scoring system [32], liver fibrosis was classified into five stages: F0, no fibrosis; F1, portal fibrosis without septa; F2, portal fibrosis with rare septa; F3, numerous septa without cirrhosis; and F4, cirrhosis.

2.5. Grouping of Training and Validation Patients

The study population was divided into a training group and a validation group according to the recruiting time. Patients recruited from October 2013 to October 2016 were included in the training group () and patients recruited from November 2016 to February 2018 () were included in the validation group. According to the METAVIR scoring system [32], liver fibrosis was classified as nonsignificant (F0–1) and significant fibrosis (F2–4).

2.6. Statistical Analysis

SPSS version 20.0 software (SPSS Inc., Chicago, IL, USA) was used for statistical analysis. Data with normal distribution were expressed as the mean ± standard deviation (SD), and comparison was performed by t-test. Data with nonnormal distribution was expressed as median and interquartile range (median (IQR)). Comparisons were performed using a nonparametric test (Mann–Whitney U test). The dichotomous data were expressed by composition ratio. The comparison was carried out by ² test. Liver pathological examination of fibrosis was used as the gold standard, and risk factors for liver fibrosis were analysed by logistic regression. A score system was derived from the independent factors. The diagnostic ability of the score system for liver fibrosis was evaluated using the receiver operating characteristic curve (ROC). The cutoff values were determined by the ROC at maximum Youden’s index with optimal sensitivity and specificity. The area under the ROC (AUROC) was compared using MedCalc Software. A two-tailed value of indicated a statistical significance.

3. Results

3.1. Patient Characteristics

Of the 290 HBeAg-positive chronic hepatitis B patients, 218 patients (75.2%) had nonsignificant hepatic fibrosis (F0–1) and 72 patients (24.8%) had significant hepatic fibrosis (F2–4) according to the liver pathological fibrosis stage.

The characteristics of patients in the training and validation groups and the differences between the two groups are shown in Table 1. Of note, the training group had a higher percent of patients with fibrosis F0–1 (80.79%, F0–1/F2–4 = 164/39) than the validation group (62.07%, F0–1/F2–4 = 54/33, , Table 1).

3.2. Noninvasive Parameters Associated with Hepatic Fibrosis in the Training Group

The fibrosis stages in the 203 training group patients were as follows: F0, 13 patients (6.4%); F1, 151 patients (74.4%); F2, 28 patients (13.8%); F3, 9 patients (4.4%); and F4, 2 patients (1.0%). Scilicet, 164 (80.8%) patients, had nonsignificant liver fibrosis (F0–1 group) and 39 patients (19.2%) had significant hepatic fibrosis (F2–4). The comparison of parameters between the patients with F0–1 and those with F2–4 fibrosis are shown in Supplementary Table 1. Compared with nonsignificant fibrosis patients (F0–1), patients with significant liver fibrosis (F2–4) had lower HBV DNA, HBsAg, HBeAg, and platelet count levels and higher anti-HBc, alpha-fetoprotein (AFP), AST, globulin, GGT, laminin, IV-C, LSM, and spleen thickness (Supplementary Table 1).

Multivariate logistic regression showed that lower HBeAg level (OR: 0.391, 95% CI: 0.241–0.632, ) and higher LSM (OR: 1.522, 95% CI: 1.274–1.819, ) were independent predictors of significant liver fibrosis (Table 2).

3.3. Development of a Score System and Performance in the Training Group

Based on multivariate logistic regression, a formula, , was derived, where . By compound function derivation and operation [33, 34], the formula was optimized as follows: . Because the coefficients of the variables HBeAg and LSM were almost equal and their ratio approximated 1, the formula was simplified as to facilitate calculation.

The lower and upper cutoff values for HBeAg were 1247.38 S/CO and 106.91 S/CO, respectively, and the values for LSM were 4.95 kPa and 8.50 kPa, respectively (Table 3). To develop a score system, HBeAg and LSM were, respectively, assigned to different points from 1 to 3 according to the cutoff values, and the sum of HBeAg and LSM points (score) was used for staging liver fibrosis (Table 4). The scores 3 and 5 corresponding to a sensitivity of 92.3% and a specificity of 98.8% were determined to be the cutoff values of the score system, namely, scores 2–3, 4, and 5–6 indicated nonsignificant hepatic fibrosis, indeterminate fibrosis, and significant fibrosis, respectively (Table 4). The 203 patients in the training group were scored according to this system, and the AUROC was 0.880 (95% CI: 0.827, 0.921) for differentiating significant and nonsignificant fibrosis (, Supplementary Figure 1).

According to the pathological diagnosis of the liver tissue, the score for classifying hepatic fibrosis had a sensitivity of 90.0% and a specificity of 85.7%. The accuracy was 86.5%, positive predictive value was 58.7%, and negative predictive value was 97.4%. The positive likelihood ratio and negative likelihood ratio were 6.30 and 0.12, respectively.

The AUROC of the score (0.880) was significantly higher than HBeAg (0.822), LSM (0.791), APRI (0.720), FIB-4 (0.671), and GPR (, , , , and , respectively, Table 5, Figure 1).

3.4. Validation of the Score System

The fibrosis stages in the 87 validation group patients were as follows: F0, 11 patients (12.6%); F1, 43 patients (49.4%); F2, 23 patients (26.4%); F3, 9 patients (10.3%), and F4, 1 patient (1.1%), in which 54 patients (62.1%) had nonsignificant fibrosis (F0–1) and 33 patients (37.9%) had significant fibrosis (F2–4).

The AUROC of the score for predicting liver fibrosis in this group patients was 0.727 (0.612, 0.842). Because there were differences between the validation group and the training group patients in the fibrosis stages and the validation group had a relatively small sample size (Table 1), the AUROC was standardized by the methods as described elsewhere [35]. The adjusted AUROC was calculated to be 0.835 (95% CI: 0.612, 0.842), which had no significant difference compared with the training group (0.880, 95% CI: 0.827, 0.921; , , Supplementary Table 2).

Of the 87 patients in the validation group, 53 patients were predicted to have scores 2 and 3, 17 patients have score 4, and 17 patients have scores 5 and 6, respectively, according to the score system. Of the patients with scores 2–3, 41/53 (77.36%) had nonsignificant fibrosis and 13/17 (76.47%) patients with scores 5–6 had significant fibrosis. The total diagnostic accuracy of scores 2–3 and scores 5–6 was 77.14%. In the 17 patients with score 4, 9 cases had nonsignificant fibrosis and 8 cases had significant fibrosis. In the validation group, 62.07% of the patients can be accurately predicted for the degree of hepatic fibrosis by the score system.

4. Discussion

Previous studies showed that in HBeAg-positive patients with ALT of ≤2× ULN, the presence of significant liver fibrosis (≥F2) was 30.2% [36]. In HBeAg-positive patients with persistently normal ALT and ALT 1–2× ULN, significant fibrosis was found in 49.4% and 69.8% of the patients, respectively [37]. In HBeAg-positive patients with persistently normal or intermittently elevated ALT, histologic fibrosis stage of ≥2 was found in 40.2% and 65.5% of the patients, respectively [38]. In the present study, 24.8% (72/218) of the patients with ALT of <2× ULN had significant hepatic fibrosis (F2–4). Although there are differences in the proportion of liver fibrosis stages between the studies which may be related to the age and the definition of ALT levels, it is clearly revealed that nearly more than 25% of HBeAg-positive patients with ALT of <80 IU/l had significant liver fibrosis.

Many factors have been examined for the role in evaluating liver fibrosis in chronic hepatitis B patients. In our study, various demographic, clinical, and laboratory parameters were included in the analysis in relation to liver fibrosis in HBeAg-positive chronic hepatitis B patients with ALT of <2× ULN. Patients with significant liver fibrosis (F2–4), in comparison with nonsignificant fibrosis (F0–1), had lower HBV DNA, HBsAg, HBeAg, and platelet count levels and higher anti-HBc, AFP, AST, globulin, GGT, laminin, IV-C, LSM, and spleen thickness. These results are mostly consistent with previous studies showing that lower serum HBsAg, HBV DNA, and platelet count [39–42] and higher AFP, AST, globulin, GGT, laminin, and IV-C levels [29, 42–45] are associated with significant fibrosis in chronic hepatitis B patients. Older age was suggested to be related to significant fibrosis in chronic hepatitis B patients in previous studies [39, 41, 42, 46, 47]. However, our study did not show a relationship between patient age and liver fibrosis. This may be related to the patient population included in our study because HBeAg-positive chronic hepatitis B patients with ALT of <2× ULN are usually younger and the age range of the patients has small deviations. Higher ALT levels were also indicated to be associated with increased risk of advanced liver fibrosis in some previous studies [47, 48]. In the present study, ALT levels were not indicated to be a factor associated with liver fibrosis. The inclusion of patients with ALT of <2× ULN in the study may be partly related to this result because the magnitude of ALT fluctuation is small in this subgroup of patients. A previous study also showed that an elevated ALT level was not predictive of significant fibrosis for HBeAg-positive disease [41]. Moreover, the degree of liver fibrosis in chronic HBV infection is determined by complex interaction of multiple factors. A recent study showed that, in patients with ALT of >20 but ≤40 IU/l, age, ALT, and GGT were independent predictors of significant liver histological changes including significant fibrosis, while in patients with ALT of ≤20 IU/l, age was the only independent predictor of significant liver histological changes [46]. Albumin levels had no significant difference between patients with significant and nonsignificant fibrosis in HBeAg-positive chronic hepatitis B patients with ALT of <2× ULN in the present study. This is consistent with most of previous investigations. Anti-HBc and spleen thickness were rarely evaluated previously, and higher level of anti-HBc and wider thickness of spleen were observed in patients with significant hepatic fibrosis in the present study. Further studies are required to confirm the role of anti-HBc and spleen thickness in assessing liver fibrosis in chronic HBV infection.

Multiple logistic regression analysis using liver pathological examination of fibrosis as the gold standard showed that HBeAg levels and LSM are independent predictors of the hepatic fibrosis, and a novel score system composed of HBeAg and LSM levels was derived in the present study. HBeAg quantitation has been shown to have a moderate predictive value for discriminating immune tolerant phase and immune clearance phase in chronic HBV infection [49]. Serum HBeAg levels were indicated to be negatively correlated with the severity of liver inflammation in HBeAg-positive chronic hepatitis B patients [50], and high serum HBeAg levels were suggested to accurately predict insignificant histology among HBeAg-positive patients with ALT of <2× ULN [51]. HBeAg has been found to induce the activation and proliferation of hepatic stellate cells [52] which are pivotal players in the development of hepatic fibrosis. Consistently, HBeAg levels showed a good predictive value for liver fibrosis in HBeAg-positive patients with ALT of <2× ULN in the present study. It is suggested that HBeAg is involved in the pathology of liver fibrosis in chronic HBV infection and its levels may indicate the degree of liver fibrosis.

LSM by transient elastography is widely used for the noninvasive evaluation of liver fibrosis. It is indicated to be a reliable noninvasive test for the diagnosis of liver fibrosis in chronic hepatitis B patients with ALT of ≤2× ULN [30]. It is superior to current serobiomarkers in chronic hepatitis B patients with various levels of ALT [53, 54]. It is also superior to APRI and FIB-4 in chronic hepatitis B patients with persistently normal ALT levels [20]. Moreover, LSM is superior to FibroTest in the noninvasive identification of fibrosis among HCV carriers with normal/near-normal aminotransferases [55]. LSM displayed a good predictive value for liver fibrosis in HBeAg-positive patients with ALT of <2× ULN in the present study. Of note, enhanced inflammatory activity as indicated by elevated ALT can lead to elevated LSM values unrelated to histological fibrosis stage and can result in the overestimation of fibrosis [20, 53]. Therefore, LSM appears to have an advantage in classifying liver fibrosis in hepatitis B patients with ALT of <2× ULN because of the avoidance of potential influence by significantly elevated ALT levels.

The inclusion of parameters that directly reflect HBV replication (HBeAg) and reflect liver fibrosis (LSM) can better reflect the involvement of factors associated with liver fibrosis in HBeAg-positive patients with normal or slightly elevated ALT levels. In fact, the score system developed in this study is superior to the most used models APRI and FIB-4 and the newly developed GPR for predicting liver fibrosis in HBeAg-positive chronic hepatitis B patients with ALT of <2× ULN.

The score system was validated in the validation group patients with similar performance as in the training group patients. In addition to high sensitivity and specificity with high diagnostic accuracy and reproducibility, the score system is easy to calculate and simple to use and has better patient acceptance and higher speed of result obtainability with the noninvasive nature. This score may be especially useful for dynamic evaluation of liver fibrosis and may reduce the need for liver biopsy, making clinical care safer and more convenient for HBeAg-positive patients with ALT of <2× ULN.

Although the score system developed has advantages in evaluating liver fibrosis in this particular subgroup of patients, it is not perfect, in that the system has not been validated in large patient population with various demographic, clinical, and laboratory variations. For example, the patients included in our study had normal body mass index (BMI) while technical failure of LSM was shown to be common in patients with BMI ≥ 28 kg/m² [56]. Therefore, additional studies evaluating the diagnostic accuracy of the score system are needed. In addition, the model may currently be unable to be adopted in some clinical practice settings, but it indicates an important direction toward more accurate evaluation of liver fibrosis with the increasing application of HBeAg determination and LSM usage.

In summary, the novel score system composed of noninvasive parameters, HBeAg and LSM, can accurately differentiate hepatic fibrosis and may reduce the need for liver biopsy in these subgroups of patients. Additional studies are needed to confirm the diagnostic accuracy of the score system and to evaluate the usefulness for identifying patients with significant fibrosis who might benefit from antiviral therapy.

Data Availability

The data underlying the findings of this study are all included in the manuscript and in the Supplementary Materials section of this manuscript.

Disclosure

The funders have no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Conflicts of Interest

The authors declare that they have no conflicts of interest related to this paper or the study it describes.

Acknowledgments

We thank Professor Guanghua Xu, Dr. Tai Wang, Dr. Haimei Wang, Dr. Ruiqin Zhang, and Dr. Yuan Li from the Department of Infectious Diseases, Affiliated Hospital of Yan’an University and Dr. Yan Li, Dr. Xiaoyan Zeng, Dr. Fan Gao, Dr. Yawen Wang, Dr. Guoyu Zhang, Dr. Man Li, and Dr. Zhu Li from the First Affiliated Hospital of Xi’an Jiaotong University for their help during this study. This study was supported by Key R&D Project of China Shaanxi Provincial Department of Science and Technology (2017 SF-269), Special Scientific Research Project of China, Education Department of Shaanxi Province (17JK0866), and National Natural Science Foundation of China (Grant number: 81371798).

Supplementary Materials

Supplementary 1. Table 1: comparison of patients with different liver fibrosis stages (F0–1 vs. F2–4) in the training group.

Supplementary 2. Table 2: comparison of AUC values of the score system for classifying liver fibrosis in training and validation group patients.

Supplementary 3. Figure 1: receiver operating characteristic curve of the score for identifying significant from insignificant liver fibrosis in the training group patients.

References

A. Schweitzer, J. Horn, R. T. Mikolajczyk, G. Krause, and J. J. Ott, “Estimations of worldwide prevalence of chronic hepatitis B virus infection: a systematic review of data published between 1965 and 2013,” The Lancet, vol. 386, no. 10003, pp. 1546–1555, 2015.
View at: Publisher Site | Google Scholar
N. A. Terrault, A. S. F. Lok, B. J. McMahon et al., “Update on prevention, diagnosis, and treatment of chronic hepatitis B: AASLD 2018 hepatitis B guidance,” Hepatology, vol. 67, no. 4, pp. 1560–1599, 2018.
View at: Publisher Site | Google Scholar
P. Lampertico, K. Agarwal, T. Berg et al., “EASL 2017 clinical practice guidelines on the management of hepatitis B virus infection,” Journal of Hepatology, vol. 67, no. 2, pp. 370–398, 2017.
View at: Publisher Site | Google Scholar
A. A. Bravo, S. G. Sheth, and S. Chopra, “Liver biopsy,” New England Journal of Medicine, vol. 344, no. 7, pp. 495–500, 2001.
View at: Publisher Site | Google Scholar
J. Perrault, D. B. McGill, B. J. Ott, and W. F. Taylor, “Liver biopsy: complications in 1000 inpatients and outpatients,” Gastroenterology, vol. 74, no. 1, pp. 103–106, 1978.
View at: Google Scholar
G. Colloredo, M. Guido, A. Sonzogni, and G. Leandro, “Impact of liver biopsy size on histological evaluation of chronic viral hepatitis: the smaller the sample, the milder the disease,” Journal of Hepatology, vol. 39, no. 2, pp. 239–244, 2003.
View at: Publisher Site | Google Scholar
F. Imbert-Bismut, V. Ratziu, L. Pieroni, F. Charlotte, Y. Benhamou, and T. Poynard, “Biochemical markers of liver fibrosis in patients with hepatitis C virus infection: a prospective study,” The Lancet, vol. 357, no. 9262, pp. 1069–1075, 2001.
View at: Publisher Site | Google Scholar
X. Forns, S. Ampurdanès, J. M. Llovet et al., “Identification of chronic hepatitis C patients without hepatic fibrosis by a simple predictive model,” Hepatology, vol. 36, no. 4, pp. 986–992, 2002.
View at: Publisher Site | Google Scholar
C. T. Wai, J. K. Greenson, R. J. Fontana et al., “A simple noninvasive index can predict both significant fibrosis and cirrhosis in patients with chronic hepatitis C,” Hepatology, vol. 38, no. 2, pp. 518–526, 2003.
View at: Publisher Site | Google Scholar
A. Sud, J. M. Hui, G. C. Farrell et al., “Improved prediction of fibrosis in chronic hepatitis C using measures of insulin resistance in a probability index,” Hepatology, vol. 39, no. 5, pp. 1239–1247, 2004.
View at: Publisher Site | Google Scholar
A. S. F. Lok, M. G. Ghany, Z. D. Goodman et al., “Predicting cirrhosis in patients with hepatitis C based on standard laboratory tests: results of the HALT-C cohort,” Hepatology, vol. 42, no. 2, pp. 282–292, 2005.
View at: Publisher Site | Google Scholar
R. K. Sterling, E. Lissen, N. Clumeck et al., “Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV coinfection,” Hepatology, vol. 43, no. 6, pp. 1317–1325, 2006.
View at: Publisher Site | Google Scholar
A. Vallet-Pichard, V. Mallet, B. Nalpas et al., “FIB-4: an inexpensive and accurate marker of fibrosis in HCV infection. Comparison with liver biopsy and fibrotest,” Hepatology, vol. 46, no. 1, pp. 32–36, 2007.
View at: Publisher Site | Google Scholar
F. Ucar, S. Sezer, Z. Ginis et al., “APRI, the FIB-4 score, and Forn’s index have noninvasive diagnostic value for liver fibrosis in patients with chronic hepatitis B,” European Journal of Gastroenterology & Hepatology, vol. 25, no. 9, pp. 1076–1081, 2013.
View at: Publisher Site | Google Scholar
J. Ma, Y. Jiang, and G. Gong, “Evaluation of seven noninvasive models in staging liver fibrosis in patients with chronic hepatitis B virus infection,” European Journal of Gastroenterology & Hepatology, vol. 25, no. 4, pp. 428–434, 2013.
View at: Publisher Site | Google Scholar
J. Cheng, J. Hou, H. Ding et al., “Validation of ten noninvasive diagnostic models for prediction of liver fibrosis in patients with chronic hepatitis B,” PLoS One, vol. 10, no. 12, article e0144425, 2015.
View at: Publisher Site | Google Scholar
G. Xiao, J. Yang, and L. Yan, “Comparison of diagnostic accuracy of aspartate aminotransferase to platelet ratio index and fibrosis-4 index for detecting liver fibrosis in adult patients with chronic hepatitis B virus infection: a systemic review and meta-analysis,” Hepatology, vol. 61, no. 1, pp. 292–302, 2015.
View at: Publisher Site | Google Scholar
Z. Zhang, G. Wang, K. Kang, G. Wu, and P. Wang, “The diagnostic accuracy and clinical utility of three noninvasive models for predicting liver fibrosis in patients with HBV infection,” PLoS One, vol. 11, no. 4, article e0152757, 2016.
View at: Publisher Site | Google Scholar
F. M. Sanai, T. Farah, K. Albeladi et al., “Diminished accuracy of biomarkers of fibrosis in low replicative chronic hepatitis B,” BMC Gastroenterology, vol. 17, no. 1, p. 101, 2017.
View at: Publisher Site | Google Scholar
Y. W. Tan, X. B. Zhou, Y. Ye, C. He, and G. H. Ge, “Diagnostic value of FIB-4, aspartate aminotransferase-to-platelet ratio index and liver stiffness measurement in hepatitis B virus-infected patients with persistently normal alanine aminotransferase,” World Journal of Gastroenterology, vol. 23, no. 31, pp. 5746–5754, 2017.
View at: Publisher Site | Google Scholar
M. Dong, J. Wu, X. Yu et al., “Validation and comparison of seventeen noninvasive models for evaluating liver fibrosis in Chinese hepatitis B patients,” Liver International, vol. 38, no. 9, pp. 1562–1570, 2018.
View at: Publisher Site | Google Scholar
M. Tag-Adeen, M. Z. Omar, F. M. Abd-Elsalam et al., “Assessment of liver fibrosis in Egyptian chronic hepatitis B patients: a comparative study including 5 noninvasive indexes,” Medicine, vol. 97, no. 6, article e9781, 2018.
View at: Publisher Site | Google Scholar
M. Lemoine, Y. Shimakawa, S. Nayagam et al., “The gamma-glutamyl transpeptidase to platelet ratio (GPR) predicts significant liver fibrosis and cirrhosis in patients with chronic HBV infection in West Africa,” Gut, vol. 65, no. 8, pp. 1369–1376, 2016.
View at: Publisher Site | Google Scholar
D. P. Liu, W. Lu, Z. Q. Zhang et al., “Comparative evaluation of GPR versus APRI and FIB-4 in predicting different levels of liver fibrosis of chronic hepatitis B,” Journal of Viral Hepatitis, vol. 25, no. 5, pp. 581–589, 2018.
View at: Publisher Site | Google Scholar
Y. C. Hu, H. Liu, X. Y. Liu et al., “Value of gamma-glutamyltranspeptidase-to-platelet ratio in diagnosis of hepatic fibrosis in patients with chronic hepatitis B,” World Journal of Gastroenterology, vol. 23, no. 41, pp. 7425–7432, 2017.
View at: Publisher Site | Google Scholar
Q. Li, J. Song, Y. Huang et al., “The gamma-glutamyl-transpeptidase to platelet ratio does not show advantages than APRI and fib-4 in diagnosing significant fibrosis and cirrhosis in patients with chronic hepatitis B,” Medicine, vol. 95, no. 16, article e3372, 2016.
View at: Publisher Site | Google Scholar
L. L. Schiavon, J. L. Narciso-Schiavon, M. L. G. Ferraz, A. E. B. Silva, and R. J. Carvalho-Filho, “The γ-glutamyl transpeptidase to platelet ratio (GPR) in HBV patients: just adding up?” Gut, vol. 66, no. 6, pp. 1169-1170, 2017.
View at: Publisher Site | Google Scholar
X. J. Lu, X. H. Li, Z. X. Yuan et al., “Assessment of liver fibrosis with the gamma-glutamyl transpeptidase to platelet ratio: a multicentre validation in patients with HBV infection,” Gut, vol. 67, no. 10, pp. 1903-1904, 2018.
View at: Publisher Site | Google Scholar
Q. Li, C. Lu, W. Li, Y. Huang, and L. Chen, “Globulin-platelet model predicts significant fibrosis and cirrhosis in CHB patients with high HBV DNA and mildly elevated alanine transaminase levels,” Clinical and Experimental Medicine, vol. 18, no. 1, pp. 71–78, 2018.
View at: Publisher Site | Google Scholar
Q. Li, L. Chen, and Y. Zhou, “Diagnostic accuracy of liver stiffness measurement in chronic hepatitis B patients with normal or mildly elevated alanine transaminase levels,” Scientific Reports, vol. 8, no. 1, p. 5224, 2018.
View at: Publisher Site | Google Scholar
S. K. Sarin, M. Kumar, G. K. Lau et al., “Asian-Pacific clinical practice guidelines on the management of hepatitis B: a 2015 update,” Hepatology International, vol. 10, no. 1, pp. 1–98, 2016.
View at: Publisher Site | Google Scholar
P. Bedossa and T. Poynard, “An algorithm for the grading of activity in chronic hepatitis C,” Hepatology, vol. 24, no. 2, pp. 289–293, 1996.
View at: Publisher Site | Google Scholar
W. Rudin, Principles of Mathematical Analysis, McGraw-Hill, New York, 3rd edition, 1976.
W. L. Winston and J. B. Goldberg, Operations Research: Applications and Algorithms, Brooks/Cole Publishing Company, Pacific Grove, CA, USA, 4th edition, 2003.
T. Poynard, P. Halfon, L. Castera et al., “Standardization of ROC curve areas for diagnostic evaluation of liver fibrosis markers based on prevalences of fibrosis stages,” Clinical Chemistry, vol. 53, no. 9, pp. 1615–1622, 2007.
View at: Publisher Site | Google Scholar
Q. Li, W. Li, Y. Huang, and L. Chen, “The gamma-glutamyl transpeptidase-to-platelet ratio predicts liver fibrosis and cirrhosis in HBeAg-positive chronic HBV infection patients with high HBV DNA and normal or mildly elevated alanine transaminase levels in China,” Journal of Viral Hepatitis, vol. 23, no. 11, pp. 912–919, 2016.
View at: Publisher Site | Google Scholar
B. Liao, Z. Wang, S. Lin et al., “Significant fibrosis is not rare in Chinese chronic hepatitis B patients with persistent normal ALT,” PLoS One, vol. 8, no. 10, article e78672, 2013.
View at: Publisher Site | Google Scholar
M. Kumar, S. K. Sarin, S. Hissar et al., “Virologic and histologic features of chronic hepatitis B virus-infected asymptomatic patients with persistently normal ALT,” Gastroenterology, vol. 134, no. 5, pp. 1376–1384, 2008.
View at: Publisher Site | Google Scholar
Q. Xie, X. Hu, Y. Zhang, X. Jiang, X. Li, and J. Li, “Decreasing hepatitis B viral load is associated with a risk of significant liver fibrosis in hepatitis B e antigen positive chronic hepatitis B,” Journal of Medical Virology, vol. 86, no. 11, pp. 1828–1837, 2014.
View at: Publisher Site | Google Scholar
S. K. Goyal, A. K. Jain, V. K. Dixit et al., “HBsAg level as predictor of liver fibrosis in HBeAg positive patients with chronic hepatitis B virus infection,” Journal of Clinical and Experimental Hepatology, vol. 5, no. 3, pp. 213–220, 2015.
View at: Publisher Site | Google Scholar
W.-K. Seto, C.-L. Lai, P. P. C. Ip et al., “A large population histology study showing the lack of association between ALT elevation and significant fibrosis in chronic hepatitis B,” PLoS One, vol. 7, no. 2, article e32622, 2012.
View at: Publisher Site | Google Scholar
L. Xiao, J. Xian, Y. Li et al., “Parameters associated with significant liver histological changes in patients with chronic hepatitis B,” ISRN Gastroenterology, vol. 2014, Article ID 913890, 6 pages, 2014.
View at: Publisher Site | Google Scholar
L. Feng, K. Sun, J. Zhang, G. Feng, and Y. Zhao, “A novel non-invasive index using AFP and APTT is associated with liver fibrosis in patients with chronic hepatitis B infection: a retrospective cohort study,” BMJ Open, vol. 5, no. 9, article e008032, 2015.
View at: Publisher Site | Google Scholar
H. Dong, C. Xu, W. Zhou et al., “The combination of 5 serum markers compared to FibroScan to predict significant liver fibrosis in patients with chronic hepatitis B virus,” Clinica Chimica Acta, vol. 483, pp. 145–150, 2018.
View at: Publisher Site | Google Scholar
Q. Han, S. Lou, Z. Liu et al., “Higher pretherapy and significant decrease during the first 12 months of therapy in serum laminin levels may associate with hepatitis B e antigen seroconversion in chronic hepatitis B patients treated with lamivudine,” Clinical and Experimental Medicine, vol. 10, no. 4, pp. 245–251, 2010.
View at: Publisher Site | Google Scholar
Q. Li, C. Lu, W. Li, Y. Huang, and L. Chen, “The independent predictors of significant liver histological changes in chronic hepatitis B virus infection patients with persistently high-normal or low-normal alanine transaminase levels,” Discovery Medicine, vol. 23, no. 124, pp. 19–25, 2017.
View at: Google Scholar
G. L. Wong, V. W. Wong, P. C. Choi et al., “Clinical factors associated with liver stiffness in hepatitis B e antigen-positive chronic hepatitis B patients,” Clinical Gastroenterology and Hepatology, vol. 7, no. 2, pp. 227–233, 2009.
View at: Publisher Site | Google Scholar
S. Alam, N. Ahmad, G. Mustafa, A. Shrestha, A. K. M. K. Alam, and M. Khan, “Evaluation of normal or minimally elevated alanine transaminase, age and DNA level in predicting liver histological changes in chronic hepatitis B,” Liver International, vol. 31, no. 6, pp. 824–830, 2011.
View at: Publisher Site | Google Scholar
L. Wang, Z. Q. Zou, K. Wang, J. G. Yu, and X. Z. Liu, “Role of serum hepatitis B virus marker quantitation to differentiate natural history phases of HBV infection,” Hepatology International, vol. 10, no. 1, pp. 133–138, 2016.
View at: Publisher Site | Google Scholar
L. Zhang, M. H. Li, W. H. Cao et al., “Negative correlation of serum hepatitis B surface antigen and hepatitis B e antigen levels with the severity of liver inflammation in treatment-naïve patients with chronic hepatitis B virus infection,” Chinese Medical Journal, vol. 130, no. 22, pp. 2697–2702, 2017.
View at: Publisher Site | Google Scholar
H. Wang, R. Yan, Y. Zhou, M. S. Wang, G. Q. Ruo, and M. J. Cheng, “Comparison of hepatitis B surface antigen and e antigen in predicting liver histology in hepatitis B e antigen-positive chronic hepatitis B patients,” Hepatology International, vol. 8, no. 2, pp. 216–223, 2014.
View at: Publisher Site | Google Scholar
Y. Zan, Y. Zhang, and P. Tien, “Hepatitis B virus e antigen induces activation of rat hepatic stellate cells,” Biochemical and Biophysical Research Communications, vol. 435, no. 3, pp. 391–396, 2013.
View at: Publisher Site | Google Scholar
J. Jia, J. Hou, H. Ding et al., “Transient elastography compared to serum markers to predict liver fibrosis in a cohort of Chinese patients with chronic hepatitis B,” Journal of Gastroenterology and Hepatology, vol. 30, no. 4, pp. 756–762, 2015.
View at: Publisher Site | Google Scholar
S. Singh, A. J. Muir, D. T. Dieterich, and Y. T. Falck-Ytter, “American Gastroenterological Association Institute technical review on the role of elastography in chronic liver diseases,” Gastroenterology, vol. 152, no. 6, pp. 1544–1577, 2017.
View at: Publisher Site | Google Scholar
C. Colletta, C. Smirne, C. Fabris et al., “Value of two noninvasive methods to detect progression of fibrosis among HCV carriers with normal aminotransferases,” Hepatology, vol. 42, no. 4, pp. 838–845, 2005.
View at: Publisher Site | Google Scholar
J. Jia, J. Hou, H. Ding et al., “Prevalence and factors associated with failure of liver stiffness measurement using FibroScan in a prospective study of 2114 examinations,” European Journal of Gastroenterology & Hepatology, vol. 18, no. 4, pp. 411-412, 2006.
View at: Publisher Site | Google Scholar

Copyright

Copyright © 2018 Yanping Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

PDF Download Citation

Download other formats

Order printed copies

Views

2170

Downloads

988

Citations