Noninvasive biomarkers have been developed to predict hepatitis B virus (HBV)-related fibrosis owing to the significant limitations of liver biopsy. Those biomarkers were initially derived from evaluation of hepatitis C virus (HCV)-related fibrosis, and their accuracy among HBV-infected patients was under constant debate. A systematic review was conducted on records in PubMed, EMBASE and the Cochrane Library electronic databases, up until April 1st, 2013, in order to systematically assess the effectiveness and accuracy of these biomarkers for predicting HBV-related fibrosis. The questionnaire for quality assessment of diagnostic accuracy studies (QUADAS) was used. Out of 115 articles evaluated for eligibility, 79 studies satisfied the pre-determined inclusion criteria for meta-analysis. Eventually, our final data set for the meta-analysis contained 30 studies. The areas under the SROC curve for APRI, FIB-4, and FibroTest of significant fibrosis were 0.77, 0.75, and 0.84, respectively. For cirrhosis, the areas under the SROC curve for APRI, FIB-4 and FibroTest were 0.75, 0.87, and 0.90, respectively. The heterogeneity of FIB-4 and FibroTest were not statistically significant. The heterogeneity of APRI for detecting significant fibrosis was affected by median age (P = 0.0211), and for cirrhosis was affected by etiology (P = 0.0159). Based on the analysis we claim that FibroTest has excellent diagnostic accuracy for identification of HBV-related significant fibrosis and cirrhosis. FIB-4 has modest benefits and may be suitable for wider scope implementation.
Citation: Xu X-Y, Kong H, Song R-X, Zhai Y-H, Wu X-F, Ai W-S, et al. (2014) The Effectiveness of Noninvasive Biomarkers to Predict Hepatitis B-Related Significant Fibrosis and Cirrhosis: A Systematic Review and Meta-Analysis of Diagnostic Test Accuracy. PLoS ONE 9(6): e100182. https://doi.org/10.1371/journal.pone.0100182
Editor: Anand S. Mehta, Drexel University College of Medicine, United States of America
Received: December 3, 2013; Accepted: May 22, 2014; Published: June 25, 2014
Copyright: © 2014 Xu et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This research was supported by a National Natural Science Foundation Grant in China (No. 71073176) awarded to H.B.L. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Chronic infection with hepatitis B virus (HBV) is an important global health problem. Approximately 350 million people are chronically infected with hepatitis B virus worldwide, especially in developing countries, 25% of whom will die from long term sequelae, such as cirrhosis, liver failure and hepatocellular carcinoma, resulting in 600,000 to one million deaths annually . Patients who are suffering from significant hepatic inflammation and fibrosis are at high risk of those complications . Assessment of liver significant fibrosis is critical to establishing effective clinical practice. It could be of great help for a doctor to determine patients' suitability and the optimal time for antiviral therapy to achieve the best curative effects as well as to prevent excessive medication . In addition, early prediction of cirrhosis is beneficial to reducing complications in patients with chronic viral hepatitis .
Liver biopsy, an invasive technique, is the gold standard for the assessment of fibrosis. It has several disadvantages, such as patients' reluctance, pain, hemoperitoneum, and pneumothorax, etc. . In addition, its accuracy in assessing fibrosis is questionable because of sampling errors and intra- and inter-observer variations . Therefore, many people are beginning to realize the importance of prediction of liver fibrosis by noninvasive biomarkers.
Aspartate aminotransferase-to-platelet ratio index (APRI), the fibrosis index based on the 4 factors (FIB-4) and FibroTest are examples of noninvise biomarkers predicting liver fibrosis based on routinely available clinical parameters . They were initially used in Western populations with hepatitis C virus (HCV) or HCV/ human immunodeficiency virus (HIV) co-infection  and had good performance. The area under the receiver operating characteristic (AUROC) curve of FibroTest for detecting significant fibrosis peaked out at 0.85 , and the AUROC curve of APRI and FIB-4 reached 0.80  and 0.81  respectively. For detecting cirrhosis, FibroTest also has the best result, and its AUROC curve topped out at 0.90 . The AUROC curve of APRI and FIB-4 are 0.83  and 0.89 , respectively. These three markers can be considered as “good”, even “better” markers, according to the criteria of Deeks JJ . Consequently, the researchers were regularly conducting those markers to predict significant fibrosis and cirrhosis among HBV-infected patients. APRI was first used to predict significant fibrosis or cirrhosis in patients with HBeAg-negative chronic hepatitis B by Chrysanthos et al. . They found APRI was strongly correlated to the fibrosis. Later FIB-4 and FibroTest were successively used to predict HBV-related fibrosis.
However, due to the fact that those markers were initially derived from evaluation of HCV-related fibrosis, their accuracy for HBV patients was under constant debate among the researchers. Some scholars indicated that all of those noninvasive markers were able to predict significant fibrosis or cirrhosis among HBV patients, and could potentially be used to decrease the number of liver biopsies . Others maintained that those markers were not directly applicable to evaluation of HBV-related fibrosis because of the small AUROC curve . Therefore, we decided to conduct this meta-analysis to assess the pooled performance of these biomarkers for prediction of significant fibrosis and cirrhosis among HBV-infected patients. It could provide the basis for future research and clinical application.
The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines  (see Checklist S1 for PRISMA checklist). A protocol (see Text S1) was developed and systematic methods were used to identify relevant studies, assess study eligibility for inclusion, and evaluate study quality. Online database search was completed on PubMed, EMBASE and the Cochrane Library (01/2003-04/2013) for terms including the following: aspartate aminotransferase-to-platelet ratio index, APRI, fibrosis index based on the 4 factors, FIB-4, FibroTest, hepatitis B virus, HBV, Chronic hepatitis B, CHB, fibrosis and cirrhosis (see Text S2 for full search strategies). Additional studies were identified via a manual search for the referenced studies and review articles. EndNote X5 software was used to manage the references.
Studies were included if they met the following inclusion criteria: (a) The study evaluated the performance of the APRI and/or FIB-4 and/or FibroTest for the prediction of fibrosis and/or cirrhosis in HBV infected patients. Studies on patients with other etiologies of liver disease were also included if data for HBV-infected patients could be independently extracted. In addition, special populations of HBV patients (e.g., HBV/HIV coinfection, HBV/HCV, and HBV/ hepatitis D virus [HDV]) were also included. (b) Liver biopsy was used to diagnose liver fibrosis as a golden standard. (c) Data could be extracted to construct at least one 2×2 table of test performance, based on some cutoff points of the APRI, FIB-4, and FibroTest for a fibrosis stage. (d) They assessed the diagnostic accuracy for fibrosis stage F≥2 or F≥4 according to METAVIR or a comparable staging system. (e) The study included at least 40 patients. Studies of smaller sample sizes were excluded due to concerns on their applicability.
Data Extraction and Quality Assessment
Two reviewers (XYX and RXS) screened the downloaded titles and abstracts against the inclusion criteria. Two reviewers (XYX and HK) independently evaluated study eligibility, graded the study quality, and extracted data from the study. Any disagreements between the reviewers were resolved with detailed discussions between them together with a third reviewer (HBL). The parameters in our literature search included author, year of publication, region, method, patient gender, age, number of patients, underlying chronic liver disease etiology, histological scoring system, average length of liver specimen, time interval between biopsy and laboratory tests, prevalence of the fibrosis stage, as well as cutoff values to identify the fibrosis stage .
The quality of included studies was independently appraised by two reviewers (XYX and YHZ) using the quality assessment of diagnostic accuracy studies (QUADAS) questionnaire  (see Text S3). It could estimate the internal and external validity of diagnostic accuracy studies used in systematic reviews.
Statistical Analysis and Data Synthesis
We extracted and tabulated the data in a series of 2×2 tables, which included sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) at each threshold value. The primary outcome was the identification of significant fibrosis, defined by METAVIR , Batts and Ludwig , and Scheuer  for stages F2 through F4, and Ishak  for stages F3 through F6. This gauge was chosen because significant fibrosis is often considered a threshold for the initiation of antiviral therapy . We also assessed cirrhosis (METAVIR, Batts and Ludwig, and Scheuer F4, and Ishak F5-6). In order to provide clinically meaningful results, the metrics of diagnostic test accuracy were examined.
The SROC curve, generated using linear regression, represents the relationship between the true positive rate and false positive rate across these studies, albeit they may have used different test thresholds . In this analysis, the area under SROC curve was examined according to Moses et al. , and each study was weighted with its sample size and with adjustment for the number of thresholds within each study .
The diagnostic odds ratio (DOR) describes the odds of a positive test in true disease cases compared with cases of no disease . The summary DOR was calculated using a DerSimonian and Laird random-effects model on a logarithmic scale with a corresponding test of heterogeneity . Because such analyses require a single measure of accuracy for each study and many studies reported multiple test thresholds, we calculate the average DOR among all thresholds for a given study . We also calculated summary sensitivities and specificities using the bivariate meta-analytic approach . Pairs of sensitivity and specificity for diagnostic thresholds are jointly analyzed, with any correlation that might exist between those two measures taken into account using a random-effects approach.
The heterogeneity (or the lack of homogeneity) of the results between studies was assessed statistically using the Cochran-Q and the quantity I2. I2 value describes the percentage of total variation across studies that is attributable to heterogeneity rather than chance . A meta-regression was conducted to further explore the covariates that may induce heterogeneity, according to the following predefined characteristics: (a) study design (retrospective or prospective); (b) etiology (HBV, HBV[HBeAg negative], or co-infection with other virus); (c) length of liver specimen (≥10 mm, ≥15 mm, ≥20 mm, or not); (d) liver biopsy scoring system (METAVIR, Ishak, Scheuer, Batts and Ludwig, and the Chinese Hospital System); (e) QUADAS score; (f) sample size; (g) median age (≤30, 31–40,41–50, or >50); (h) percentage of males; (i) location of study (Europe or Asia); (j) prevalence of significant fibrosis/cirrhosis.
The potential publication bias was assessed using the Deeks funnel plots (the logarithm of the DOR plotted against ) . is proportional to the square root of (1/n1+1/n2), where n1 is the number diseased and n2 not diseased. Data analyses were performed using the Meta-Disc software (v. 1.4).
The study selection process is presented with a flow chart in Figure 1. 306 studies were retrieved with the described search strategies, of which 196 were excluded following title and abstract screening. The full texts of 110 potentially eligible reports were obtained for further assessment. Of those, 30 papers were included in the review following full-text screening (Table 1); 20 studies were related to the APRI , , , -, 13 studies related to the FIB-4 , , , –, , , and 11 studies related to the FibroTest –, –.
Characteristics of the Included Studies
In the twenty APRI studies, a total of 4,208 patients (median age 36 yr, 72% male) were included. The overall prevalence of significant fibrosis and cirrhosis were 47% (ranged 17%–70%) and 11% (7%–27%), respectively. The liver biopsy scoring system used to classify the histology varied. 10 studies used a METAVIR score, 4 studies used an Ishak score, 4 studies used a Scheuer score, 1 study used a Batts and Ludwig score, and 1 study used the Chinese Hospital System. Nineteen of these studies (N = 3,955) included HBV-infected patients without comorbid conditions , , , –. The one remaining study included special populations of patients such as HBV/HDV-coinfected patients (N = 253) . According to the QUADAS scale, eight studies met all 14 requirements of this scale, nine studies met 13, two studies met 12, and one study met 11.
A total of 2,953 patients (median age 36 yr, 70% male) were included in the thirteen studies on FIB-4. The overall prevalence of significant fibrosis and cirrhosis were 53% (ranged 17%–76%) and 15% (11%–34%), respectively. All those studies (N = 2,953) included HBV-infected patients without comorbid conditions. The liver biopsy scoring system used to classify the histology varied. Six studies used a METAVIR score, three studies used a Scheuer score, two studies used an Ishak score, one study used a Batts and Ludwig score, and one study used the Chinese Hospital System. Seven studies met all 14 requirements of the QUADAS scale, 4 studies met 13, 1 study met 12, and one study met 11.
There were 1,640 patients (median age 42 yr, 69% male) used to assess the performance of FibroTest in eleven studies. The overall prevalence of significant fibrosis and cirrhosis were 63% (ranged 39%–85%) and 20% (8%–39%), respectively. Seven of these studies (N = 1,011) included HBV-infected patients without comorbid conditions , , –. The four remaining studies included special populations with HBV/HDV-coinfected patients (N = 462) , , HBV/HIV-coinfected patients (N = 59) , and HBV/HDV/HIV-coinfected patients (N = 108) . According to the Quality Assessment of Diagnostic Accuracy Studies scale, we can see that 5 studies met all 14 requirements of this scale, 2 study met 13, 3 studies met 12, and 1 study met 10.
Diagnostic Accuracy for the Prediction of Significant Fibrosis
In the seventeen studies assessing the APRI (N = 3,573), the AUROC curve ranged from 0.61 to 0.86. When combined, the area under the SROC curve was 0.77 08 (SE = 0.0172) (Figure 2A). The Pooled DOR was 5.41 (95% confidence interval [CI] 3.98–7.35) (Figure 2B). The Cochran-Q and I2 value of all measures were 38.32 and 58.2%, indicating significant heterogeneity across the included studies (P = 0.001) (Figure 2B). The pooled sensitivities and specificities could not be assessed. Instead, the sensitivities and specificities of the APRI at various diagnostic thresholds in the seventeen studies are listed in Table 2. We used the meta-regression analysis to explore the heterogeneity of the APRI accuracy for detecting significant fibrosis, which was mainly affected by median age (P = 0.0211, see Text S4 for meta-regression). There was no significant correlation between other covariates and the DOR.
(A) SROC curve of the APRI; (B) Diagnostic odds ratio of the APRI.
In the ten studies assessing the FIB-4 for the prediction of significant Fibrosis (N = 1,996), the AUROC curve ranged from 0.69 to 0.77. When combined, the area under the SROC curve was 0.75 (SE = 0.0168) (Figure 3A). The summary DOR was 5.3 (95% CI 4.3–6.6), and the score of Cochran-Q is 7.54 (P = 0.581) (Figure 3B). The result from the analysis of the heterogeneity was statistically insignificant. The summary sensitivities and specificities of the FIB-4 were 65.8% (95% CI 62.4%–69.1%) and 73.6% (95% CI 70.8%–76.3%), respectively (Figure S1–S2).
(A) SROC curve of the FIB-4; (B) Diagnostic odds ratio of the FIB-4.
The AUROC curve ranged from 0.69 to 0.90 in the 11 studies assessing the FibroTest (N = 1.640). When combined, the area under the SROC curve was 0.84 (SE = 0.0227) (Figure 4A). The summary DOR was 13.73 (95% CI 8.61–21.90), and the score of Cochran-Q is 22.52, indicating significant heterogeneity across the included studies (P = 0.0127) (Figure 4B). We didn't find the cause of the heterogeneity of FibroTest accuracy according to the predefined characteristics. But center description might affect heterogeneity beyond the predefined design (See Text S5).
(A) SROC curve of the FibroTest; (B) Diagnostic odds ratio of the FibroTest.
Diagnostic Accuracy for the Prediction of Cirrhosis
There were 11 studies on assessing the APRI for the predication of cirrhosis (N = 2,083). The AUROC curve of these studies ranged from 0.50 to 0.83. When combined, the area under the SROC curve was 0.75 (SE = 0.0174) (Figure 5A). The summary DOR was 4.4 (95% CI 2.9–6.8). The heterogeneity occurred in the meta-analysis for the twelve studies assessing the APRI for the predication of cirrhosis, which was statistically significant (Q = 23.10, P = 0.01; I2 = 56.7%, Figure 5B). However, when we further conducted the meta-analysis at the different thresholds of <1.0, 1.0, and 2.0, we found that the heterogeneity wasn't statistically significant (Figure S3). The summary sensitivity and specificity of the APRI at different diagnostic thresholds are listed in Table 3.
(A) SROC curve of the APRI; (B) Diagnostic odds ratio of the APRI.
According to the meta-regression analysis, the heterogeneity of APRI accuracy for detecting cirrhosis was mainly affected by etiology (P = 0.0159) (See Text S6), whereas the other covariates were not significant. After excluding the only one study which included HBV/HDV-coinfected patients, the pooled DOR was 5.03 (95% CI 3.45–7.35) and heterogeneity was no longer significant (Q = 14.05, P = 0.1204; I2 = 36.0%).(Figure S4) According to the meta-analysis, the pooled sensitivity and specificity were 60.9% (95% CI 55.0–66.6%) and 74.8% (72.4–77.1%), respectively (Figures S5–S6).
The AUROC curve in the six studies assessing the FIB-4 (N = 1,304) ranged from 0.74 to 0.93. When combined, the area under the SROC curve was 0.87 (SE = 0.0307) (Figure 6A). The summary DOR was 12.97 (95% CI 6.91–24.35) and the score of Cochran-Q is 10.01 (P = 0.07) (Figure 6B). The analysis showed that the heterogeneity was statistically insignificant. The summary sensitivities and specificities of the FIB-4 were 44.7% (95% CI 39.4%–50.2%) and 86.6% (95% CI 84.3%–88.7%), respectively (Figures S7–S8).
(A) SROC curve of the FIB-4; (B) Diagnostic odds ratio of the FIB-4.
In the nine studies assessing the FibroTest (N = 1101), the AUROC curve ranged from 0.68 to 0.92. When combined, the area under the SROC curve was 0.90 (SE = 0.0250) (Figure 7A). The summary DOR was 23.75 (95% CI 11.88–47.48) and the score of Cochran-Q is 20.25 (P = 0.0094) (Figure 7B). The heterogeneity was statistically significant. The pooled sensitivities and specificities could not be assessed. Instead, the sensitivities and specificities of the FibroTest at various diagnostic thresholds in the nine studies are listed in Table 4.
(A) SROC curve of the FibroTest; (B) Diagnostic odds ratio of the FibroTest.
According to the meta-regression analysis, the heterogeneity of FibroTest accuracy for detecting cirrhosis was mainly affected by sample size (P = 0.0385) and median age (P = 0.0436) (Text S7), whereas the other covariates were not significant.
Funnel plots of these three markers for assessing possible publication bias are illustrated in Figure 8. Mild asymmetry was noted in the funnel plots of the FIB-4 and FibroTest.
(A) APRI to predict significant fibrosis; (B) FIB-4 to predict significant fibrosis; (C) FibroTest to predict significant fibrosis; (D) APRI to predict cirrhosis; (E)FIB-4 to predict cirrhosis; (F) FibroTest to predict cirrhosis.
Liver fibrosis progression is commonly found in HBV-infected patients. Cirrhosis develops in approximately one third of those cases, usually after an extensive period of time during which liver biochemical indices are found to be predominantly or even persistently abnormal . Patients with significant fibrosis or cirrhosis should be considered for antiviral therapy, which can potentially reverse cirrhosis and reduce complications . Considering the limitations and risks of biopsy, the researchers make persistent efforts in exploring some noninvasive markers in order to more accurately identify patients with significant fibrosis or cirrhosis. APRI, FIB-4 and FibroTest are such noninvasive markers gaining increasing acceptance in clinical practice. Those markers may reduce the need for liver biopsy and may help to monitor the efficacy of treatment .
In our systematic review, the diagnostic accuracy of the APRI, FIB-4 and FibroTest for HBV-related significant fibrosis and cirrhosis has been comprehensively evaluated and summarized on a large scale, and we confirmed the results of many individual studies. Our meta-analysis also included the description of multiple measures of test performance using confirmed meta-analytic techniques and formal assessment for publication bias and heterogeneity, as well as exploratory analysis. All results should be valid and reasonably reliable.
FibroTest had the best result in not only significant fibrosis but also cirrhosis. The area under the SROC curve of FibroTest is bigger and even reaches the standard of “better” on cirrhosis , and the summary sensitivity and specificity have reached 84% and 82%, respectively. A meta-analysis about HCV-infected patients showed that the area under the SROC curve of significant fibrosis and cirrhosis are 0.81 and 0.90 . Evidently, the performance of FibroTest in evaluating HBV-related fibrosis is no worse than HCV-related. Therefore, FibroTest could be considered as a better marker in assessing fibrosis and cirrhosis of HBV-infected patients. The FibroTest, however, is calculated with alpha2 macroglobulin, alpha2 globulin (or haptoglobin), gamma globulin, apolipoprotein A1, GGT and total bilirubin . Alpha2 macroglobulin and alpha2 globulin (or haptoglobin) are not routine clinical measurements, and those two indicators are not tested for patients in most hospitals. Furthermore they cost more than conventional indicators. Those factors may bring restrictions to the wider application of the FibroTest in clinical practice.
The calculation method of FIB-4 is simpler than that of FibroTest. The area under the SROC curve of FIB-4 predicting HBV-related significant fibrosis and cirrhosis are 0.75 and 0.87, respectively. FIB-4 also has a better performance of predicting fibrosis . Its test items are easy to obtain in clinical practice, although its predictive results are not as good as FibroTest , . APRI shows lower diagnostic accuracy than FibroTest and Fib-4 to identify HBV-related significant fibrosis and cirrhosis. It has been introduced to assess HBV-related fibrosis the earliest because of its simple and easy practice. Presently, APRI is widely utilized in identifying the degree of fibrosis and cirrhosis of patients with hepatitis C and hepatitis B, particularly in regions with limited healthcare resources. Some scholars argue that the calculation method of APRI did not consider the factor of spleen size . If patients were grouped by spleen size, the performance of APRI in predicting HBV-related fibrosis would be improved. Our meta-analysis revealed that the area under the SROC curve of APRI was small and the accuracy of the evaluation of HBV-related fibrosis was poor. Our results showed similar performance of APRI for staging of significant fibrosis and cirrhosis .
Meta-regression method was convenient and reliable to screen the factors of heterogeneity. The strength of our study is that meta-regression analysis has been used to explore several factors that may be responsible for heterogeneity. Liver biopsy scoring systems and percentage of males emerged from many relevant factors to provide heterogeneity to summary test result on APRI to predict significant fibrosis . On the other hand, etiology of cirrhosis was found to be significantly associated with the heterogeneity on APRI to predict cirrhosis. But the heterogeneity of the meta-analysis of the FIB-4 and FibroTest to predict significant fibrosis and cirrhosis was not statistically significant. FIB-4 and FibroTest to predict fibrosis had better consistency, and summary test results were reasonably reliable.
However, there are several limitations in our systematic review. Firstly, we only focused our analysis on those patients with HBV-related fibrosis, without distinguishing between HBeAg negative and positive cases, or considering the virus replication rate due to the limited number of publications. Secondly, we included studies published in English and Chinese languages only, so the language bias may influence the results to some extent. Lastly, Fibroscan, a widely noninvasive tool, was not considered in this meta-analysis, because our focus was to compare the serum markers calculated by biochemical examination.
In summary, the FibroTest has excellent diagnostic accuracy for the identification of HBV-related significant fibrosis and cirrhosis. But FibroTest is seldom applied in clinical practice as a result of expensive cost. FIB-4, a relatively moderate marker, has better summary diagnostic accuracy and could be measured and calculated relatively easily. Furthermore, APRI shows some limited value in identifying hepatitis B-related significant fibrosis and cirrhosis. All of them have their own advantages and disadvantages. Future studies of novel fibrosis markers are needed to demonstrate improved accuracy and cost-effectiveness compared with those simple, economical, and widely available indeces.
Sensitivity of FIB-4 detecting significant fibrosis.
Specificity of FIB-4 detecting significant fibrosis.
DOR of APRI cirrhosis (subgroup).
DOR of APRI cirrhosis excluded patients with HBV and HDV coinfected.
Sensitivity of APRI cirrhosis excluded patients with HBV and HDV coinfected.
Specificity of APRI cirrhosis excluded patients with HBV and HDV coinfected.
Sensitivity of Fib-4 detecting cirrhosis.
Specificity of Fib-4 detecting cirrhosis.
PRISMA checklist of items.
Systematic review protocol.
Meta-regression of APRI detecting significant fibrosis.
Meta-regression of FibroTest detecting significant fibrosis.
Meta-regression of APRI detecting cirrhosis.
Meta-regression of FibroTest detecting cirrhosis.
Conceived and designed the experiments: HBL XYX. Analyzed the data: XYX WSA XFW HBL. Wrote the paper: HBL XYX HK RXS YHZ XFW WSA. Data collection: XYX HK RXS YHZ. First draft of the manuscript: XYX HBL.
- 1. Custer B, Sullivan SD, Hazlet TK, Iloeje U, Veenstra DL, et al. (2004) Global epidemiology of hepatitis B virus. J Clin Gastroenterol 38: S158–168.
- 2. Yu MW, Hsu FC, Sheen IS, Chu CM, Lin DY, et al. (1997) Prospective study of hepatocellular carcinoma and liver cirrhosis in asymptomatic chronic hepatitis B virus carriers. Am J Epidemiol 145: 1039–1047.
- 3. Gumusay O, Ozenirler S, Atak A, Sonmez C, Ozkan S, et al. (2013) Diagnostic potential of serum direct markers and non-invasive fibrosis models in patients with chronic hepatitis B. Hepatol Res. 43: 228–237.
- 4. Liaw YF, Sung JJ, Chow WC, Farrell G, Lee CZ, et al. (2004) Lamivudine for patients with chronic hepatitis B and advanced liver disease. N Engl J Med 351: 1521–1531.
- 5. Bravo AA, Sheth SG, Chopra S (2001) Liver biopsy. N Engl J Med 344: 495–500.
- 6. Colloredo G, Guido M, Sonzogni A, Leandro G (2003) Impact of liver biopsy size on histological evaluation of chronic viral hepatitis: the smaller the sample, the milder the disease. J Hepatol 39: 239–244.
- 7. Kim BK, Kim do Y, Park JY, Ahn SH, Chon CY, et al. (2010) Validation of FIB-4 and comparison with other simple noninvasive indices for predicting liver fibrosis and cirrhosis in hepatitis B virus-infected patients. Liver Int 30: 546–553.
- 8. Sterling RK, Wegelin JA, Smith PG, Stravitz RT, Luketic VA, et al. (2010) Similar progression of fibrosis between HIV/HCV-infected and HCV-infected patients: Analysis of paired liver biopsy samples. Clin Gastroenterol Hepatol 8: 1070–1076.
- 9. Poynard T, Morra R, Halfon P, Castera L, Ratziu V, et al. (2007) Meta-analyses of FibroTest diagnostic value in chronic liver disease. BMC Gastroenterol 7: 40.
- 10. Corradi F, Piscaglia F, Flori S, D'Errico-Grigioni A, Vasuri F, et al. (2009) Assessment of liver fibrosis in transplant recipients with recurrent HCV infection: usefulness of transient elastography. Dig Liver Dis 41: 217–225.
- 11. Amorim TG, Staub GJ, Lazzarotto C, Silva AP, Manes J, et al. (2012) Validation and comparison of simple noninvasive models for the prediction of liver fibrosis in chronic hepatitis C. Ann Hepatol. 11: 855–861.
- 12. Shaheen AA, Wan AF, Myers RP (2007) FibroTest and FibroScan for the prediction of hepatitis C-related fibrosis: a systematic review of diagnostic test accuracy. Am J Gastroenterol 102: 2589–2600.
- 13. Lin ZH, Xin YN, Dong QJ, Wang Q, Jiang XJ, et al. (2011) Performance of the aspartate aminotransferase-to-platelet ratio index for the staging of hepatitis C-related fibrosis: an updated meta-analysis. Hepatology 53: 726–736.
- 14. Martinez SM, Fernandez-Varo G, Gonzalez P, Sampson E, Bruguera M, et al. (2011) Assessment of liver fibrosis before and after antiviral therapy by different serum marker panels in patients with chronic hepatitis C. Aliment Pharmacol Ther. 33: 138–148.
- 15. Deeks JJ (2001) Systematic reviews in health care: Systematic reviews of evaluations of diagnostic and screening tests. BMJ 323: 157–162.
- 16. Chrysanthos NV, Papatheodoridis GV, Savvas S, Kafiri G, Petraki K, et al. (2006) Aspartate aminotransferase to platelet ratio index for fibrosis evaluation in chronic viral hepatitis. Eur J Gastroenterol Hepatol 18: 389–396.
- 17. Wang H, Xue L, Yan R, Zhou Y, Wang MS, et al. (2013) Comparison of FIB-4 and APRI in Chinese HBV-infected patients with persistently normal ALT and mildly elevated ALT. J Viral Hepat 20: e3–10.
- 18. Moher D, Liberati A, Tetzlaff J, Altman DG (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med 6: e1000097.
- 19. Whiting P, Rutjes AW, Reitsma JB, Bossuyt PM, Kleijnen J (2003) The development of QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Med Res Methodol 3: 25.
- 20. Group TFMCS (1994) Intraobserver and interobserver variations in liver biopsy interpretation in patients with chronic hepatitis C. The French METAVIR Cooperative Study Group. Hepatology 20: 15–20.
- 21. Batts KP, Ludwig J (1995) Chronic hepatitis. An update on terminology and reporting. Am J Surg Pathol 19: 1409–1417.
- 22. Scheuer PJ (1991) Classification of chronic viral hepatitis: a need for reassessment. J Hepatol 13: 372–374.
- 23. Ishak K, Baptista A, Bianchi L, Callea F, De Groote J, et al. (1995) Histological grading and staging of chronic hepatitis. J Hepatol 22: 696–699.
- 24. Strader DB, Wright T, Thomas DL, Seeff LB (2004) Diagnosis, management, and treatment of hepatitis C. Hepatology. 39: 1147–1171.
- 25. Walter SD (2002) Properties of the summary receiver operating characteristic (SROC) curve for diagnostic test data. Stat Med 21: 1237–1256.
- 26. Moses LE, Shapiro D, Littenberg B (1993) Combining independent studies of a diagnostic test into a summary ROC curve: data-analytic approaches and some additional considerations. Stat Med 12: 1293–1316.
- 27. Dukic V, Gatsonis C (2003) Meta-analysis of diagnostic test accuracy assessment studies with varying number of thresholds. Biometrics 59: 936–946.
- 28. DerSimonian R, Laird N (1986) Meta-analysis in clinical trials. Control Clin Trials 7: 177–188.
- 29. Doust JA, Glasziou PP, Pietrzak E, Dobson AJ (2004) A systematic review of the diagnostic accuracy of natriuretic peptides for heart failure. Arch Intern Med 164: 1978–1984.
- 30. Reitsma JB, Glas AS, Rutjes AW, Scholten RJ, Bossuyt PM, et al. (2005) Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. J Clin Epidemiol 58: 982–990.
- 31. Higgins JP, Thompson SG, Deeks JJ, Altman DG (2003) Measuring inconsistency in meta-analyses. BMJ 327: 557–560.
- 32. Deeks JJ, Macaskill P, Irwig L (2005) The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed. J Clin Epidemiol 58: 882–893.
- 33. Zhou K, Gao CF, Zhao YP, Liu HL, Zheng RD, et al. (2010) Simpler score of routine laboratory tests predicts liver fibrosis in patients with chronic hepatitis B. J Gastroenterol Hepatol. 25: 1569–1577.
- 34. Shin WG, Park SH, Jang MK, Hahn TH, Kim JB, et al. (2008) Aspartate aminotransferase to platelet ratio index (APRI) can predict liver fibrosis in chronic hepatitis B. Dig Liver Dis. 40: 267–274.
- 35. Kim BK, Kim SA, Park YN, Cheong JY, Kim HS, et al. (2007) Noninvasive models to predict liver cirrhosis in patients with chronic hepatitis B. Liver Int. 27: 969–976.
- 36. Hongbo L, Xiaohui L, Hong K, Wei W, Yong Z (2007) Assessing routine and serum markers of liver fibrosis in CHB patients using parallel and serial interpretation. Clin Biochem 40: 562–566.
- 37. Guzelbulut F, Sezikli M, Akkan-Cetinkaya Z, Yasar B, Ozkara S, et al. (2012) AST-platelet ratio index in the prediction of significant fibrosis and cirrhosis in patients with chronic hepatitis B. Turk J Gastroenterol. 23: 353–358.
- 38. Lesmana CR, Salim S, Hasan I, Sulaiman AS, Gani RA, et al. (2011) Diagnostic accuracy of transient elastography (FibroScan) versus the aspartate transaminase to platelet ratio index in assessing liver fibrosis in chronic hepatitis B: the role in primary care setting. J Clin Pathol 64: 916–920.
- 39. Seto WK, Lee CF, Lai CL, Ip PP, Fong DY, et al. (2011) A new model using routinely available clinical parameters to predict significant liver fibrosis in chronic hepatitis B. PLoS One. 6: e23077.
- 40. Liu XD, Wu JL, Liang J, Zhang T, Sheng QS (2012) Globulin-platelet model predicts minimal fibrosis and cirrhosis in chronic hepatitis B virus infected patients. World J Gastroenterol 18: 2784–2792.
- 41. Zhu X, Wang LC, Chen EQ, Chen XB, Chen LY, et al. (2011) Prospective evaluation of FibroScan for the diagnosis of hepatic fibrosis compared with liver biopsy/AST platelet ratio index and FIB-4 in patients with chronic HBV infection. Dig Dis Sci 56: 2742–2749.
- 42. Wu SD, Wang JY, Li L (2010) Staging of liver fibrosis in chronic hepatitis B patients with a composite predictive model: a comparative study. World J Gastroenterol 16: 501–507.
- 43. Wang Y, Xu MY, Zheng RD, Xian JC, Xu HT, et al. (2013) Prediction of significant fibrosis and cirrhosis in hepatitis B e-antigen negative patients with chronic hepatitis B using routine parameters. Hepatol Res 43: 441–451.
Ucar F, Sezer S, Ginis Z, Ozturk G, Albayrak A, et al.. (2013) APRI, the FIB-4 score, and Forn's index have noninvasive diagnostic value for liver fibrosis in patients with chronic hepatitis B. Eur J Gastroenterol Hepatol.
- 45. Basar O, Yimaz B, Ekiz F, Ginis Z, Altinbas A, et al. (2013) Non-invasive tests in prediction of liver fibrosis in chronic hepatitis B and comparison with post-antiviral treatment results. Clin Res Hepatol Gastroenterol 37: 152–158.
- 46. Liu HB, Zhou JP, Zhang Y, Lv XH, Wang W (2011) Prediction on liver fibrosis using different APRI thresholds when patient age is a categorical marker in patients with chronic hepatitis B. Clin Chim Acta. 412: 33–37.
- 47. Sebastiani G, Vario A, Guido M, Alberti A (2007) Sequential algorithms combining non-invasive markers and biopsy for the assessment of liver fibrosis in chronic hepatitis B. World J Gastroenterol. 13: 525–531.
- 48. Bonnard P, Sombie R, Lescure FX, Bougouma A, Guiard-Schmid JB, et al. (2010) Comparison of elastography, serum marker scores, and histology for the assessment of liver fibrosis in hepatitis B virus (HBV)-infected patients in Burkina Faso. Am J Trop Med Hyg 82: 454–458.
- 49. Sebastiani G, Castera L, Halfon P, Pol S, Mangia A, et al. (2011) The impact of liver disease aetiology and the stages of hepatic fibrosis on the performance of non-invasive fibrosis biomarkers: an international study of 2411 cases. Alimentary Pharmacology & Therapeutics 34: 1202–1216.
- 50. Zhang YF, Shi H, Chen LB, Xu QH (2010) [Value of FIB-4 for the diagnosis of liver fibrosis in chronic hepatitis B]. Zhonghua Shi Yan He Lin Chuang Bing Du Xue Za Zhi 24: 215–217.
- 51. Myers RP, Tainturier MH, Ratziu V, Piton A, Thibault V, et al. (2003) Prediction of liver histological lesions with biochemical markers in patients with chronic hepatitis B. J Hepatol. 39: 222–230.
- 52. Miailhes P, Pradat P, Chevallier M, Lacombe K, Bailly F, et al. (2011) Proficiency of transient elastography compared to liver biopsy for the assessment of fibrosis in HIV/HBV-coinfected patients. J Viral Hepat 18: 61–69.
- 53. Bottero J, Lacombe K, Guechot J, Serfaty L, Miailhes P, et al. (2009) Performance of 11 biomarkers for liver fibrosis assessment in HIV/HBV co-infected patients. J Hepatol 50: 1074–1083.
- 54. Kim BK, Kim SU, Kim HS, Park JY, Ahn SH, et al. (2012) Prospective validation of FibroTest in comparison with liver stiffness for predicting liver fibrosis in Asian subjects with chronic hepatitis B. PLoS One. 7: e35825.
- 55. Stibbe KJ, Verveer C, Francke J, Hansen BE, Zondervan PE, et al. (2011) Comparison of non-invasive assessment to diagnose liver fibrosis in chronic hepatitis B and C patients. Scand J Gastroenterol 46: 962–972.
- 56. Park MS, Kim BK, Cheong JY, Kim DJ, Park JY, et al. (2013) Discordance between liver biopsy and FibroTest in assessing liver fibrosis in chronic hepatitis B. PLoS One. 8: e55759.
- 57. Gui HL, Xie Q, Wang H (2008) [FibroTest-ActiTest for predicting liver fibrosis and inflammatory activity in Chinese patients with chronic hepatitis B]. Zhonghua Gan Zang Bing Za Zhi 16: 897–901.
- 58. Kim BK, Kim HS, Park JY, Kim do Y, Ahn SH, et al. (2012) Prospective validation of ELF test in comparison with Fibroscan and FibroTest to predict liver fibrosis in Asian subjects with chronic hepatitis B. PLoS One. 7: e41964.
- 59. Sebastiani G, Castera L, Halfon P, Pol S, Mangia A, et al. (2011) The impact of liver disease aetiology and the stages of hepatic fibrosis on the performance of non-invasive fibrosis biomarkers: an international study of 2411 cases. Aliment Pharmacol Ther 34: 1202–1216.
- 60. Lavanchy D (2004) Hepatitis B virus epidemiology, disease burden, treatment, and current and emerging prevention and control measures. J Viral Hepat 11: 97–107.
- 61. Imbert-Bismut F, Ratziu V, Pieroni L, Charlotte F, Benhamou Y, et al. (2001) Biochemical markers of liver fibrosis in patients with hepatitis C virus infection: a prospective study. Lancet 357: 1069–1075.
- 62. Jin W, Lin Z, Xin Y, Jiang X, Dong Q, et al. (2012) Diagnostic accuracy of the aspartate aminotransferase-to-platelet ratio index for the prediction of hepatitis B-related fibrosis: a leading meta-analysis. BMC Gastroenterol 12: 14.