Transient Elastography for Significant Liver Fibrosis and Cirrhosis in Chronic Hepatitis B: A Meta-Analysis.
Chronic hepatitis B virus infection continues to be a major public health issue worldwide with the prevalence of 3.61% . As well known, liver fibrosis, one of the main prognostic factors in chronic hepatitis B (CHB), was associated with the risk of developing cirrhosis and cirrhosis-related complications [2,3]. Therefore, liver fibrosis stage plays one of the most important roles in diagnostic and prognostic assessments in patients with CHB.
Liver biopsy (LB), as invasive in nature with related risks, is the gold standard for fibrosis assessment. However, LB is associated with obvious patient discomfort and risk of complications ranging from pain to more serious events with hospitalization rate of 1.4-3.2%  and mortality varying from 0.0088 to 0.3% . Besides, LB provides only a quite small part of the organ, and thus there is a risk that the small part might not be representative for the live fibrosis in the whole liver .
Noninvasive methods of assessing fibrosis and cirrhosis were urgently needed, and serologic tests and novel imaging techniques were recently developed [7, 8]. Most of these studied focused on whether noninvasive methods can accurately detect minimal (F0-1), significant ([greater than or equal to]F2), or advanced ([greater than or equal to]F3-4) fibrosis based on the METAVIR score . Transient elastography (TE), also known as FibroScan, was a device and a well-validated method with advantages of a short procedure time (<5min), immediate results, and the ability to perform the test at the bedside or in an outpatient clinic . Compared with blood tests, TE has a similar performance to predict significant fibrosis (SF) and higher accuracy to identify cirrhosis . Measurement of liver fibrosis without biopsy is very tempting. In spite of the fact that recommendations suggested that noninvasive tests were still not ready to replace LB [12, 13], TE has become widely present in clinical practice. The accuracy of TE for detection of fibrosis has been assessed extensively in a variety of liver diseases [14-17]. However, it was reported that the presence of an IQR/M > 30% and liver stiffness median [greater than or equal to]7.1 kPa lead to a lower accuracy determined by the area under receiver-operating curve (AUROC) and these cases were considered "poorly reliable" . Another study also indicated that there was a significant discrepancy in up to 20% of cases cirrhosis between different TE devices .
In the study, we performed an independent meta-analysis of the diagnostic accuracy of TE for predicting significant liver fibrosis (F2-4 versus F0-1) and cirrhosis (F4 versus F0-3) in CHB patients.
2.1. Literature Search Strategy. PubMed, Web of Science, and EMBASE database were searched to October 10, 2016, as well as Wanfang database and China National Knowledge Infrastructure. The search strategy was "FibroScan or transient elastography" in combination with "liver fibrosis assessment," "significant fibrosis or cirrhosis or advanced liver fibrosis," and "liver stiffness measurement." All eligible studies were retrieved and their reference lists were checked for additional relevant publications.
2.2. Inclusion Criteria. All diagnostic cross-sectional studies, cohort studies, and randomized studies that compared TE accuracy with biopsy in diagnosis fibrosis grade were eligible for inclusion. Studies that met all the following criteria were included: (i) studies which reported that all patients had undergone biopsy and TE; (ii) having enough data to create 2 x 2 table of test performance (with numbers of true and false positives and negatives); and (iii) studies which reported the method of definition of the fibrosis grade.
2.3. Exclusion Criteria. The exclusion criteria were as follows: (i) the patients belonging to the pediatric population, hepatitis C/hepatitis B virus coinfected patients, mixed chronic liver disease patients (but not CHB and nonalcoholic fatty liver disease), and liver/kidney transplant patients; (ii) studies that were clearly extensions of previously published cohorts; and (iii) studies unable to obtain sufficient data for statistical analysis.
2.4. Methodological Assessment. Methodological quality was assessed by the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. QUADAS-2 was designed to assess the internal and external validity. Any differences between two authors were resolved with discussion between the two review authors and the third author was final arbiter.
2.5. Data Extraction and Management. As for each study, the following information was extracted: year of publication, study design, sample size, presence of HIV coinfection, the QUADAS-2 methodological items, prevalence of each fibrosis stage on biopsy, along with total prevalence of SF and cirrhosis, interval between biopsy and TE, size of biopsy sample, type of scoring system used for histology (METAVIR versus other), and AUROC. Two authors performed the data extraction independently. Disagreement was resolved with discussion between the two review authors, with a third author as final arbiter.
2.6. Statistical Analysis and Data Synthesis. Initial analysis was performed with the Review Manager (RevMan) 5.0. Stata 12.0 was used for meta-analysis of diagnostic accuracy studies, to compute the pooled sensitivity and specificity and to plot the summary receiver-operating characteristics curve (SROC) with summary point and corresponding 95% confidence interval (CI). Regression analysis was performed by Stata 12.0, with each time point providing another covariate to verify the influence of the chosen covariate on the accuracy estimates. We used hierarchical SROC model and the bivariate random efforts model to produce SROC and pooled estimates of sensitivity and specificity. We performed Fagan test to detect clinical significant by Stata 12.0. Heterogeneity was assessed with the inconsistency index ([I.sup.2]) and [I.sup.2] values over 50% indicated substantial heterogeneity. Heterogeneity from threshold effect was explored by meta-disc 1.4.
3.1. Search Results. 1238 articles were obtained and 188 were excluded for duplicates. 882 were excluded based on title and abstracts, and full-text copies of 106 studies were obtained and assessed for eligibility. Furthermore, 62 were excluded for inappropriate methodology, duplicate sample, pediatric population, or inability to obtain data for at least 2 x 2 table. Finally, a total of 44 articles comprising 45 studies were enrolled in the meta-analysis (Figure 1).
3.2. Characteristics of Included Studies. The overall prevalence of SF (F2-4) and cirrhosis (F4) ranged from 14.8% to 92.3% and from 1.1% to 69.2%, respectively. Reported AUROCs for SF diagnosis ranged from 0.614 to 0.98 (Table 1).
As shown in Table 1, only Miailhes et al. (N = 59) reported HIV coinfected patients . In sixteen studies (N = 2664), LB was assessed with a histological score other than METAVIR [21-36]. In eight studies (N = 1109), mean length of biopsy sample was [greater than or equal to]20 mm [22,34,37-42]. Besides, in nineteen studies (N = 1358), data on time interval between biopsy and TE were not obtained [11, 21, 23, 25, 27, 28, 3234, 39,40,42-47]. Three studies did not report cirrhosis (F4) [24, 35,48]. Only four studies were retrospective [31,48-50].
As presented in Figure 2, the results of methodological quality assessment based on the QUADAS-2 scale were depicted for all of the 44 eligible studies. The majority of the methodological concern lies within the index test, because TE in ten studies interpreted with knowledge of the results of the biopsy [24, 29, 33, 39, 46, 48, 51-54] and TE in one study was conducted with assistance by a time-motion ultrasound image . Another possible issue was addressed in patient selection that participants might be enrolled consecutively with confirmed diagnosis in three studies [31, 50, 55]. Both of these concerns might be located in heterogeneity and sensitivity analyses.
3.3. Diagnosis of SF. We included 35 studies (N = 6,202) in the analysis for SF (F2-F4) [15-23, 25-27, 29-35, 37-40, 43, 56-59]. Summary representation of the overall analysis was presented in Figure 3(a) and Supplementary Figure 1. Sensitivity and specificity ranged from 51 to 97% and 38 to 100%, respectively (Supplementary Figure 1).
The area under SROC for SF was 0.86 (95% CI: 0.83-0.89) (Figure 3(a)). The meta-analysis summary estimate indicated pooled sensitivity of 0.78 (95% CI: 0.73-0.81, p < 0.01; [I.sup.2] = 85.59%), specificity of 0.81 (95% CI: 0.77-0.84, p < 0.01; [I.sup.2] = 88.20%) (Supplementary Figure 1(A)), positive likelihood ratio (LR+) of 4.01 (95% CI: 3.31-4.84, p < 0.01; [I.sup.2] = 86.27%), negative likelihood ratio (LR-) of 0.28 (95% CI: 0.23-0.33, p < 0.01; [I.sup.2] = 81.95%) (Supplementary Figure 1(B)), diagnostic score (DS) of 2.67 (95% CI: 2.38-2.96, p < 0.01; [I.sup.2] = 71.57%), and diagnostic odds ratio (DOR) of 14.44 (95% CI: 10.80-19.30, p < 0.01; [I.sup.2] = 100%) (Supplementary Figure 1(C)). However, it must be carefully considered as they were not pooled from studies with identical TE threshold. Overall, there was heterogeneity as graphically illustrated on the forest plot in Supplementary Figure 1. The cut-off value for SF (F2-4) ranged from 5.2 to 10.3 kPa with a mean value of 8.6 kPa and a median of 7.25 kPa.
As shown in Figure 3(b) and Table 2, in the analysis of LB-related factors with an impact on accuracy, there was no significant difference (joint p = 0.47 for classification criteria; joint p = 0.29 for interval time; joint p = 0.77 for average sample size). 26 studies conducted in Asian presented a better both pooled sensitivity (0.78, 95% CI: 0.73-0.82) and specificity (0.83, 95% CI: 0.79-0.87) than in Caucasian (joint p = 0.03).
As presented in Figure 3(c), it was indicated that posttest probability of LR+ increased to 86% and LR- decreased to 29% after TE was performed based on Fagan test.
3.4. Diagnosis of Cirrhosis. 41 studies were included in the cirrhotic analysis with a total of 7,205 patients, as four studies did not have any cases of liver cirrhosis (METAVIR F4) [21, 24, 35, 48]. The overall prevalence of METAVIR F4 and the AUROCs in the included studies ranged from 5% to 69.2% and from 0.80 to 0.98 (Table 1), respectively.
Summary representation of the overall analysis was shown in Figure 4(a). The area under the SROC for liver cirrhosis was 0.92 (95% CI: 0.90-0.94). Sensitivity ranged from 49% to 100%, much more widely than specificity which ranged from 62% to 99% (Supplementary Figure 2). The meta-analysis summary estimate covered the pooled sensitivity of 0.84 (95% CI: 0.80-0.88, p < 0.01; [I.sup.2] = 76.67%), specificity of 0.87 (95% CI: 0.84-0.90, p < 0.01; [I.sup.2] = 90.89%) (Supplementary Figure 2(A)), LR+ of 6.66 (95% CI: 5.34-8.31, p < 0.01; [I.sup.2] = 84.77%), LR- of 0.18 (95% CI: 0.14-0.23, p < 0.01; [I.sup.2] = 80.80%) (Supplementary Figure 2(B)), DS of 3.60 (95% CI: 3.23-3.97, p < 0.01; [I.sup.2] = 66.54%), and DOR of 36.63 (95% CI: 25.38-52.87, p < 0.01; [I.sup.2] = 100%), respectively (Supplementary Figure 2(C)). Again, these measures must be carefully considered without identical TE thresholds. The cut-off value for cirrhosis ranged from 9 kPa to 18.2 kPa with both a mean value and a median of 12.4 kPa.
As shown in Figure 4(b) and Table 3, although summary sensitivity was lower and summary specificity was higher in studies with METAVIR score (sensitivity: 0.82, 95% CI: 0.77-0.87; specificity: 0.88,95% CI: 0.85-0.91), TE performed on the next day of LB (sensitivity: 0.79, 95% CI: 0.71-0.86; specificity: 0.88, 95% CI: 0.84-0.93), and average sample length [much greater than] 20 mm (sensitivity: 0.79, 95% CI: 0.69-0.89; specificity: 0.88, 95% CI: 0.83-0.94), respectively, no statistical significance was detected (joint p = 0.17 for classification criteria; joint p = 0.21 for interval time; joint p = 0.47 for average sample size). Besides, pooled sensitivity and specificity were without significant difference (joint p = 0.12) between Caucasian (sensitivity: 0.78,95% CI: 0.67-0.88; specificity: 0.91, 95% CI: 0.86-0.95) and Asian (sensitivity: 0.86, 95% CI: 0.81-0.90; specificity: 0.86, 95% CI: 0.83-0.89).
In addition, based on Fagan test, it was illustrated that posttest probability of LR+ and LR- rose and declined to 59% and 4%, respectively (Figure 4(c)).
3.5. Publication Bias. The results of publication bias analysis were performed with Stata in Supplementary Figure 3. No significant publication bias was detected according to Deeks figures for SF (p = 0.26). However, there was bias among 41 studies enrolled in analysis of TE for cirrhosis (p = 0.02), which might result from the positive results of all 41 studies.
TE can provide a reliable detection of liver fibrosis in patients with CHB and thus has been recommended by the American Association for the Study of Liver Diseases (AASLD) and European Association for the Study of the Liver (EASL) [60, 61]. This meta-analysis was conducted in a total of 7,808 CHB patients to summarize the diagnostic accuracy of TE for CHB-related SF, with optimal statistical method SROC. In addition, regression analysis was carried out to further explore sources of heterogeneity.
In our study, TE performed well in both SF (F2-4) and cirrhosis (F4) with pooled sensitivity of 78% and 84%, summary specificity of 81% and 87%, DOR of 14.44 and 36.63, LR+ of 4.01 and 6.66, LR- of 0.28 and 0.18, respectively. Study by Li et al.  with hierarchical SROC model was also performed in CHB patients, with summary sensitivity and specificity for SF (F2-4) and cirrhosis (F4) of 80% and 86%, 82%, and 88%, however, without DOR, LR+ and LR-. Interestingly, the pooled specificity for diagnosis SF (F2-4) and cirrhosis (F4) in both studies were higher than summary sensitivity, which suggested that the currently cutoff values of TE performed better in excluding diseases rather than confirming diseases. Furthermore, the areas under the SROC were 0.86 for SF (F2-4) and 0.92 for cirrhosis (F4), respectively, which indicated that TE was performed well in staging fibrosis in CHB patients. In addition, TE performed better for cirrhosis than SF with a higher value of AUC, sensitivity, specificity, DOR, LR+, and a lower value of LR-. Although the diagnostic accuracy was higher for cirrhosis, TE could also increase the diagnostic accuracy for SF based on Fagan test with increased LR+ and decreased LR-.
The higher TE values were used to confirm diagnosis, while the lower one was used to exclude the false positive diagnosis. However, if the TE value located between the values for rule in and rule out, biopsy was then recommended. Based on the descriptive statistics of enrolled studies, the cut-off values for diagnosing SF (F2-4) and cirrhosis (F4) ranged from 5.2 to 10.3 kPa and 9 to 18.2 kPa, respectively. The optimal cut-off values of TE in CHB patients in our study were 7.25 kPa for SF (F2-4) and 12.4 kPa for cirrhosis (F4). In the previous meta-analysis by Li et al., the weighted mean cut-off values of TE were comparable with 7.2 kPa for SF (F2-4) and 12.2 kPa for cirrhosis (F4) . However, since there was no optimal statistical method to pool different cutoff values in individual studies, the optimal cut-off values in our meta-analysis were simply summarized as median, which could eliminate the impact resulting from the maximum and minimum values that was better than the mean value in previous study .
Elevated ALT levels might affect the predictive accuracy of TE [16, 24, 45, 50, 55, 56]; however, the study by Cardoso et al. reported that the use of TE cut-off values adjusted to ALT level did not improve the performance of liver stiffness in CHB patients . Although elevated ALT might be the most important confounder on liver stiffness measurement, the synthesis analysis of ALT elevation could not be conducted due to insufficient data. Therefore, it would be beneficial if more clinical studies focused on the correlation between ALT elevation and TE in CHB patients.
One of the main limitations in this meta-analysis was the significant heterogeneity of the included studies. Spearman correlation coefficient for SF and cirrhosis were 0.055 (p = 0.755) and 0.057 (p = 0.723), and no threshold effect was presented. Therefore, regression analysis was carried out. Besides, TE value could be applied as diagnosis criteria for both SF and cirrhosis in Asian. However, for Caucasian, it was noted that TE was valid to diagnosis of cirrhosis, while it was less precise for SF. Unfortunately, the regression analysis was not conducted owing to the small size of HIV- and non-HIV-coinfected patients. It should be noted that the overlapped cut-off values from included studies might also result in the heterogeneity.
In conclusion, TE is of great value for detection CHB-related cirrhosis, however, with a suboptimal performance in detection of SF. Further studies should focus on the TE cut-off value and the effect of ALT elevation in patients with CHB.
Abbreviations CHB: Chronic hepatitis B CI: Confidence interval DOR: Diagnostic odds ratio LB: Liver biopsy LR: Likelihood ratio QUADAS-2: Quality Assessment of Diagnostic Accuracy Studies-2 SF: Significant fibrosis SROC: Summary receiver-operating curves TE: Transient elastography AUROC: Area under receiver-operating curve.
Conflicts of Interest
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patients received or pending, or royalties.
Xiaolong Qi, Weidong Wang, Jing Wang, and CHESS Study Group contributed to study concepts and design; Min An and Tongwei Wu performed literature search; Min An and Jing Wang conducted data extraction; Min An, Tongwei Wu, Deke Jiang, Mengyun Peng, and Chunqing Zhang performed data analysis: Tongwei Wu, Weidong Wang, Chunqing Zhang, and CHESS Study Group were responsible for manuscript preparation and revision. All authors and CHESS Study Group have participated sufficiently in the study and approved the final version. Xiaolong Qi, Min An, and Tongwei Wu contributed equally to this work.
Collaborators of CHESS Study Group are as follows: Zhiwei Li, Department of General Surgery, 302 Hospital of PLA, Beijing, China; Fuquan Liu, Department of Interventional Therapy, Beijing Shijitan Hospital, Capital Medical University, Beijing, China; Guofeng Chen, Liver Cirrhosis Diagnosis and Treatment Center, 302 Hospital of PLA, Beijing, China; and Qingge Zhang, Department of Hepatology, Xingtai People's Hospital, Xingtai, China. This work was supported by the grants from the National Natural Science Foundation of China (81600510), Guangzhou Industry-Academia-Research Collaborative Innovation Major Project (201704020015), and President Foundation of Nanfang Hospital, Southern Medical University (2017Z012).
Supplementary Figure 1: meta-analysis of 32 studies that assessed the diagnosis accuracy of significant fibrosis (METAVIR F2-F4) based on transient elastography. A Forest plot of (A) sensitivity and specificity, (B) positive and negative likelihood ratio, and (C) diagnostic score (DS) and diagnostic odds ratio (DOR) for significant liver fibrosis (METAVIR F2-F4). Supplementary Figure 2: meta-analysis of 37 studies that assessed the diagnosis accuracy of cirrhosis (METAVIR F4) based on transient elastography. A Forest plot of (A) sensitivity and specificity, (B) positive and negative likelihood ratio, and (C) DS and DOR for cirrhosis (METAVIR F4). Supplementary Figure 3: Deeks' Funnel Plot Asymmetry Test for (A) significant fibrosis (METAVIR F2-F4) and (B) cirrhosis (METAVIR F4). (Supplementary Materials)
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Xiaolong Qife (iD), (1,2) Min An, (3) Tongwei Wu, (2) Deke Jiang, (2) Mengyun Peng, (4) Weidong Wang (iD), (5) Jing Wang (iD), (4) Chunqing Zhang, (1) and on behalf of the CHESS Study Group (2)
(1) Department of Gastroenterology, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China
(2) CHESS, Hepatic Hemodynamic Lab, Institute of Hepatology, Nanfang Hospital, Southern Medical University, Guangdong Provincial Research Center for Liver Fibrosis, Guangzhou, China
(3) The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
(4) Department of Hepatobiliary Disease, The Affiliated (T.C.M) Hospital of Southwest Medical University, Luzhou, China
(5) Department of Hepatobiliary Surgery, Shunde Hospital, Southern Medical University, Foshan, China
Correspondence should be addressed to Weidong Wang; firstname.lastname@example.org and Jing Wang; email@example.com
Received 9 December 2017; Accepted 25 February 2018; Published 24 May 2018
Academic Editor: Mingyu Sun
Caption: FIGURE 1: Flow diagram of study selection process.
Caption: FIGURE 2: Summary of methodological quality of 44 studies according to Quality Assessment of Diagnostic Studies-2 (QUDAS-2) tool. (a) Overall and (b) study-level of bias.
Caption: FIGURE 3: Meta-analysis of 32 studies that assessed the diagnosis accuracy of significant fibrosis based on transient elastography. (a) A summary receiver-operating characteristic (SROC) plot of transient elastography for detection of significant liver fibrosis (METAVIR F2-F4). (b) Regression analysis of studies whether reported with METAVIR score on the next day of biopsy or with sample size [greater than or equal to] 20 cm for significant liver fibrosis. (c) Detection of clinical significance for significant liver fibrosis (METAVIR F2-F4) based on Fagan test. Heterogeneity was generated if p < 0.01 in sensitivity or specificity separately. However, joint p value was generated synthesisly for analysis of both sensitivity and specificity.
Caption: FIGURE 4: Meta-analysis of 37 studies that assessed the diagnosis accuracy of cirrhosis based on transient elastography. (a) A summary receiver-operating characteristic (SROC) plot of transient elastography for detection of cirrhosis (METAVIR F4). (b) Regression analysis of studies whether reported with METAVIR score on the next day of biopsy or with sample size [greater than or equal to] 20 cm for cirrhosis. (c) Detection of clinical significance for cirrhosis (METAVIR F4) based on Fagan test.
TABLE 1: Characteristics of the included studies. Author Study type Year HIV/HBV METAVIR Cao et al. Prospective 2014 NO YES Cardoso et al. Retrospective 2011 NO YES Castera et al. Prospective 2010 NO YES Chan et al. Prospective 2009 NO YES Chen et al. Retrospective 2011 NO YES Chen et al. Prospective 2012 NO YES Cheng et al. Prospective 2015 NO YES Cheng et al. Prospective 2014 NO NO Cho et al. Prospective 2011 NO YES Degos et al. Prospective 2010 NO YES Dong et al. Prospective 2015 NO NO Gaia et al. Prospective 2011 NO YES Goyal et al. Prospective 2013 NO YES Huang et al. Prospective 2016 NO NO Jia et al. Prospective 2015 NO YES Kim et al. 1 Prospective 2012 NO NO Kim et al. 2 Prospective 2012 NO YES Kim et al. Prospective 2009 NO YES Kim et al. 1 Prospective 2009 NO YES Kim et al. 2 Prospective 2009 NO YES Kim et al. 3 Prospective 2012 NO NO Lesmana et al. Retrospective 2011 NO YES Liu et al. Prospective 2015 NO NO Liu et al. Prospective 2012 NO NO Marcellin et al. Prospective 2009 NO YES Meng et al. Prospective 2015 NO YES Meng et al. Prospective 2016 NO NO Miailhes et al. Prospective 2011 YES YES Osakabe et al. Prospective 2011 NO YES Qin et al. Prospective 2015 NO NO Seo et al. Retrospective 2015 NO NO Sporea et al. Prospective 2010 NO YES Stibbe et al. Prospective 2011 NO YES Trembling et al. Prospective 2013 NO YES Vigano et al. Prospective 2011 NO YES Wang et al. Prospective 2015 NO NO Wang et al. Prospective 2014 NO NO Wang et al. Prospective 2016 NO NO Wong et al. Prospective 2009 NO YES Wong et al. Tr-c Prospective 2014 NO YES Wong et al. Va-c Prospective 2014 NO YES Zhang et al. Prospective 2016 NO NO Zhang et al. Prospective 2016 NO NO Zhang et al. Prospective 2011 NO NO Zhu et al. Prospective 2011 NO YES Author Biopsy size Biopsy to TE time (days) Cao et al. >=15 mm and >=6 portal tracts NA Cardoso et al. >=15 mm and/or >=6 portal tracts 1 Castera et al. >=16 mm NA Chan et al. >=15 mm and >=6 portal tracts 28 Chen et al. >=15 mm 7 Chen et al. >=15 mm and >=10 portal tracts 7 Cheng et al. >=10 mm and >=8 portal tracts 1 Cheng et al. >=15 mm and >=6 portal tracts 1 Cho et al. >=15 mm 1 Degos et al. >=18 mm 1 Dong et al. >=15 mm and >=6 portal tracts NA Gaia et al. >=20 mm 120 Goyal et al. >=15 mm and >=6 portal tracts 38 Huang et al. >=15 mm NA Jia et al. >=10 mm and >=8 portal tracts NA Kim et al. 1 >=20 mm 1 Kim et al. 2 >=20 mm 1 Kim et al. >=10 mm and >=10 portal tracts 1 Kim et al. 1 >=6 portal tracts 1 Kim et al. 2 >=15 mm NA Kim et al. 3 >=15 mm 1 Lesmana et al. >=15 mm and >=5 portal tracts 1 Liu et al. >=8 portal tracts NA Liu et al. >=10 mm NA Marcellin et al. >=6 portal tracts 1 Meng et al. >=12 mm and >=6 portal tracts 2 Meng et al. >=15 mm 7 Miailhes et al. >=10 mm 3 Osakabe et al. >=15 mm and >=8 portal tracts 30 Qin et al. NA 1 Seo et al. >=15 mm 90 Sporea et al. >=20 mm and >=8 portal tracts NA Stibbe et al. >=20 mm NA Trembling et al. >=20 mm 1 Vigano et al. >=20 mm NA Wang et al. >=15 mm and >=6 portal tracts NA Wang et al. >=15 mm NA Wang et al. NA NA Wong et al. >=15 mm and >=6 portal tracts NA Wong et al. Tr-c >=15 mm and >=6 portal tracts NA Wong et al. Va-c >=15 mm and >=6 portal tracts NA Zhang et al. >=22 mm 7 Zhang et al. >=15 mm NA Zhang et al. >=15 mm and >=6 portal tracts NA Zhu et al. >=15 mm and >=6 portal tracts 1 Author Sample Prevalence Prevalence F2-F4 F4 Cao et al. 162 0.61 0.12 Cardoso et al. 202 0.421 0.079 Castera et al. 60 0.73 0.25 Chan et al. 136 NA 0.25 Chen et al. 213 0.479 0.15 Chen et al. 315 0.771 0.235 Cheng et al. 459 0.61 0.152 Cheng et al. 99 0.54 NA Cho et al. 121 0.727 0.074 Degos et al. 284 0.415 0.102 Dong et al. 81 0.604 0.098 Gaia et al. 70 0.53 0.31 Goyal et al. 357 0.792 0.059 Huang et al. 263 0.148 0.011 Jia et al. 469 0.612 0.122 Kim et al. 1 194 0.845 0.387 Kim et al. 2 170 0.712 0.276 Kim et al. 91 NA 0.692 Kim et al. 1 130 0.923 0.515 Kim et al. 2 91 0.868 0.396 Kim et al. 3 150 0.847 0.453 Lesmana et al. 117 0.624 NA Liu et al. 115 0.53 0.15 Liu et al. 134 0.43 0.11 Marcellin et al. 173 0.503 0.081 Meng et al. 287 0.488 0.157 Meng et al. 168 NA 0.15 Miailhes et al. 59 0.61 0.203 Osakabe et al. 51 0.882 0.275 Qin et al. 152 0.68 0.07 Seo et al. 567 0.72 0.2 Sporea et al. 140 0.764 0.05 Stibbe et al. 48 0.458 0.104 Trembling et al. 182 0.626 0.198 Vigano et al. 125 0.53 0.16 Wang et al. 142 0.585 0.092 Wang et al. 80 0.7 0.1125 Wang et al. 127 0.76 0.24 Wong et al. 134 0.78 0.24 Wong et al. Tr-c 238 0.693 0.235 Wong et al. Va-c 85 0.565 0.259 Zhang et al. 180 0.72 0.18 Zhang et al. 124 0.54 NA Zhang et al. 88 0.671 0.159 Zhu et al. 175 NA 0.166 Author TE cut-off AUROC Cao et al. 7.3/17.5 NA/NA Cardoso et al. 7.2/11 0.867/0.935 Castera et al. 7.1/9.6 0.76/0.89 Chan et al. NA/9 NA/0.93 Chen et al. 7.0/13.0 0.916/0.971 Chen et al. NA/10.4 NA/0.88 Cheng et al. 7.2/18.2 0.82/0.87 Cheng et al. 8.15/NA 0.896/NA Cho et al. 7.8/14.0 0.849/0.867 Degos et al. 5.2/12.9 0.78/0.90 Dong et al. 10.3/9.4 0.753/0.873 Gaia et al. 7.2/10.6 0.674/0.763 Goyal et al. 6.0/11.0 0.84/0.93 Huang et al. 8/NA 0.911/NA Jia et al. 7.3/10.7 0.82/0.90 Kim et al. 1 8.8/14.1 0.873/0.910 Kim et al. 2 8.0/14.0 0.937/0.963 Kim et al. NA/10.3 NA/0.803 Kim et al. 1 NA/10.1 NA/0.840 Kim et al. 2 NA/NA 0.837/0.913 Kim et al. 3 6.0/9.4 NA/NA Lesmana et al. 5.85/NA 0.614/NA Liu et al. 8.50/11.75 0.838/0.914 Liu et al. 7.60/13.20 0.93/0.96 Marcellin et al. 7.2/11.0 0.81/0.93 Meng et al. 8.85/17.05 0.909/0.815 Meng et al. 15.1 0.927 Miailhes et al. 5.9/9.4 0.85/0.96 Osakabe et al. 7.1/16.0 0.844/0.93 Qin et al. 8.2/13.1 0.752/0.973 Seo et al. 7.8/11.6 0.774/0.902 Sporea et al. 7/13.6 0.658/0.974 Stibbe et al. 7.0/14.0 NA/0.89 Trembling et al. NA/11.85 NA/O.95 Vigano et al. 6.2/13.1 NA/NA Wang et al. 8.15/13.95 0.897/0.968 Wang et al. 7.3/12.4 0.865/0.944 Wang et al. NA/15.2 NA/0.805 Wong et al. NA/13.4 NA/0.89 Wong et al. Tr-c NA/10 NA/0.9 Wong et al. Va-c NA/10 NA/0.87 Zhang et al. 7.5/10.6 0.813/0.799 Zhang et al. 6.95 0.732 Zhang et al. 7.25/12.40 0.857/0/948 Zhu et al. 7.9/13.8 NA/0.98 AUROC, area under the receiver-operating curve; TE, transient elastography; HIV/HBV, hepatitis B and HIV-coinfected patients; METAVIR, liver biopsy assessed according to METAVIR or not; TE cut-off, TE cut-off used to predict; NA, data not available. TABLE 2: Results of meta-regression for significant fibrosis. Covariate Number Pooled sensitivity Classification criteria METAVIR score 21 0.78 (0.75-0.83) Non-METAVIR score 14 0.77 (0.70-0.83) Interval time On the next day of liver biopsy 11 0.76 (0.69-0.84) More than one day after liver biopsy 24 0.78 (0.73-0.83) Average sample size [greater than or equal to]20 mm 7 0.76 (0.66-0.86) Not [greater than or equal to] 20 mm 28 0.78 (0.74-0.82) Region Asian 26 0.78 (0.73-0.82) Caucasian 9 0.77 (0.68-0.85) Covariate p value Pooled specificity Classification criteria METAVIR score <0.01 0.79 (0.73-0.84) Non-METAVIR score 0.83 (0.78-0.89) Interval time On the next day of liver biopsy <0.01 0.85 (0.79-0.90) More than one day after liver biopsy 0.78 (0.74-0.83) Average sample size [greater than or equal to]20 mm <0.01 0.79 (0.69-0.88) Not [greater than or equal to] 20 mm 0.81 (0.77-0.85) Region Asian <0.01 0.83 (0.79-0.87) Caucasian 0.72 (0.63-0.80) Covariate p value Joint p value Classification criteria METAVIR score <0.01 0.47 Non-METAVIR score Interval time On the next day of liver biopsy <0.01 0.29 More than one day after liver biopsy Average sample size [greater than or equal to]20 mm <0.01 0.77 Not [greater than or equal to] 20 mm Region Asian 0.04 0.03 Caucasian TABLE 3: Results of meta-regression for cirrhosis. Covariate Number Pooled sensitivity Classification criteria METAVIR score 28 0.82 (0.77-0.87) Non-METAVIR score 13 0.89 (0.83-0.94) Interval time On the next day of liver biopsy 13 0.79 (0.71-0.86) More than one day after liver biopsy 28 0.86 (0.82-0.90) Average sample size [greater than or equal to]20 mm 8 0.79 (0.69-0.89) Not [greater than or equal to] 20 mm 33 0.85 (0.81-0.89) Region Asian 31 0.86 (0.81-0.90) Caucasian 10 0.78 (0.67-0.88) Covariate p value Pooled specificity Classification criteria METAVIR score <0.01 0.88 (0.85-0.91) Non-METAVIR score 0.86 (0.80-0.91) Interval time On the next day of liver biopsy <0.01 0.88 (0.84-0.93) More than one day after liver biopsy 0.87(0.83-0.90) Average sample size [greater than or equal to]20 mm <0.01 0.88 (0.83-0.94) Not [greater than or equal to] 20 mm 0.87 (0.84-0.90) Region Asian <0.01 0.86 (0.83-0.89) Caucasian 0.91 (0.86-0.95) Covariate p value Joint p value Classification criteria METAVIR score <0.01 0.17 Non-METAVIR score Interval time On the next day of liver biopsy <0.01 0.21 More than one day after liver biopsy Average sample size [greater than or equal to]20 mm <0.01 0.47 Not [greater than or equal to] 20 mm Region Asian <0.01 0.12 Caucasian
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|Title Annotation:||Review Article|
|Author:||Qi, Xiaolong; An, Min; Wu, Tongwei; Jiang, Deke; Peng, Mengyun; Wang, Weidong; Wang, Jing; Zhang, Ch|
|Publication:||Canadian Journal of Gastroenterology and Hepatology|
|Date:||Jan 1, 2018|
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