ABSTRACT
-
Background/Aims
Opinions differ regarding vibration-controlled transient elastography and magnetic resonance elastography (VCTE/MRE) cut-offs for diagnosing advanced fibrosis (AF) in patients with non-alcoholic fatty liver disease (NAFLD). We investigated the diagnostic performance and optimal cut-off values of VCTE and MRE for diagnosing AF.
-
Methods
Literature databases, including Medline, EMBASE, Cochrane Library, and KoreaMed, were used to identify relevant studies published up to June 13, 2023. We selected studies evaluating VCTE and MRE regarding the degree of liver fibrosis using liver biopsy as the reference. The sensitivity, specificity, and area under receiver operating characteristics curves (AUCs) of the pooled data for VCTE and MRE for each fibrosis stage and optimal cut-offs for AF were investigated.
-
Results
A total of 19,199 patients from 63 studies using VCTE showed diagnostic AUC of 0.83 (95% confidence interval: 0.80–0.86), 0.83 (0.80–0.86), 0.87 (0.84–0.90), and 0.94 (0.91–0.96) for ≥F1, ≥F2, ≥F3, and F4 stages, respectively. Similarly, 1,484 patients from 14 studies using MRE showed diagnostic AUC of 0.89 (0.86–0.92), 0.92 (0.89–0.94), 0.89 (0.86–0.92), and 0.94 (0.91–0.96) for ≥F1, ≥F2, ≥F3, and F4 stages, respectively. The diagnostic AUC for AF using VCTE was highest at 0.90 with a cut-off of 7.1–7.9 kPa, and that of MRE was highest at 0.94 with a cut-off of 3.62–3.8 kPa.
-
Conclusions
VCTE (7.1–7.9 kPa) and MRE (3.62–3.8 kPa) with the suggested cut-offs showed favorable accuracy for diagnosing AF in patients with NAFLD. This result will serve as a basis for clinical guidelines for non-invasive tests and differential diagnosis of AF.
-
Keywords: Non-alcoholic fatty liver disease; Meta-analysis; Advanced fibrosis; Vibration-controlled transient elastography; Magnetic resonance elastography
Study Highlights
• The vibration-controlled transient elastography and magnetic resonance elastography with the suggested cut-offs (7.1–7.9 kPa and 3.62–3.8 kPa, respectively) showed favorable accuracy for diagnosing advanced fibrosis in patients with nonalcoholic fatty liver disease. This result will serve as a basis for clinical guidelines for non-invasive tests and differential diagnosis of advanced fibrosis.
Graphical Abstract
INTRODUCTION
Nonalcoholic fatty liver disease (NAFLD) is the hepatic manifestation of metabolic syndrome and the most common chronic liver disease affecting 25–40% of the worldwide population [
1,
2]. Most patients remain asymptomatic for long periods; however, some patients slowly progress to cirrhosis, end-stage liver disease, and hepatocellular carcinoma (HCC) [
3].
The degree of liver fibrosis is the critical determinant of the long-term prognosis of patients with NAFLD, such as the development of liver-related events, death, and HCC [
4,
5]. Liver biopsy (LB) is the gold standard for identifying and staging liver fibrosis in patients with NAFLD [
5,
6]. However, LB is invasive and carries infrequent but fatal risk of complications such as bleeding or pneumothorax, and has sampling and intra- and inter-observer variability in pathological reporting [
7,
8]. Therefore, in the clinical setting, clinicians should essentially have alternative tests for LB that can estimate the long-term prognosis of patients with NAFLD. In particular, clinicians are interested in the critical point at which patients begin to deteriorate and should be referred to a liver specialist. Growing evidence shows advanced fibrosis (AF) is a turning gate for increased risk of liver-related events [
9-
11].
Various non-invasive tests (NITs) have been developed to stratify the risk of individual patients according to the presence of AF [
6,
11,
12]. Serum markers are generally simple and inexpensive and can be easily used in the clinical setting; however, caution is required in interpretation as they can be affected by patient’s systemic condition. In contrast, the diagnostic accuracy of liver stiffness (LS) measurement using vibration-controlled transient elastography (VCTE) and magnetic resonance elastography (MRE) for liver fibrosis in patients with NAFLD is higher than that of other serum markers; based on research published so far, diagnostic area under receiver operating characteristics (ROC) curves (AUCs) for AF is 0.65–0.98 for VCTE [
13-
30], and 0.83–0.93 for MRE [
31-
34]. Several meta-analyses have analyzed the cut-off ranges for AF using VCTE, yielding a range of 6.8–13.6 kPa [
32,
35-
38]. However, some of the studies are outdated, with only a small number of papers included [
35,
36], and recent papers published after 2023 have not been included in any meta-analysis [
32,
35-
38]. Moreover, all these papers showed wide cut-off ranges for AF to demonstrate optimal cut-off. In meta-studies that investigated the cut-off of AF using MRE in NAFLD, the value ranged widely from 2.43 to 5.97 kPa [
32,
39-
41].
Therefore, this study, including the most recent studies, comprehensively analyzed the diagnostic performance of VCTE and MRE in patients with NAFLD and investigated the optimal cut-off values of VCTE and MRE for diagnosing AF.
MATERIALS AND METHODS
This meta-analysis was conducted in accordance with the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy Studies: The PRISMA-DTA Statement [
42]. The study protocol for this systematic review was registered in the International Prospective Register of Systematic Reviews with registration number CRD42024539470.
We searched Medline, EMBASE, Cochrane Library, and KoreaMed for relevant articles published up to June 13, 2023. The Patient/Intervention/Comparison/Outcomes used for this study were as follows: P, NAFLD; I, VCTE or MRE; C, LB; and O, AF. We used Medical Subject Heading terms and combined them with free-text words where applicable, according to the databases. The search words (NAFLD, VCTE, MRE, LB, and liver fibrosis-related index words), search strategy, and subsequent results are listed in
Supplementary Table 1. Inclusion criteria were as follows: (1) adult patients with NAFLD (≥18 years), (2) adequate description of VCTE or MRE procedures, (3) reliable diagnostic AUC and available cut-off values of VCTE or MRE at least one fibrosis stage, (4) LB as the reference standard for liver fibrosis assessment, (5) interval less than 6 months between LB and VCTE/MRE, and (6) availability of all parameters including true positive, false positive, true negative, and false negative rates. Exclusion criteria were as follows: (1) duplications, (2) articles with only conference abstracts or articles for which the full text was not available, (3) no human subjects, and (4) language not written in English or Korean. The search process was conducted by a professional statistician (M.C.).
Two independent experts in the field of NAFLD (Y.E.C. and H.Y.K.) reviewed relevant titles and abstracts. In cases where it was difficult to decide on inclusion or exclusion, or any discrepancy between the two reviewers was resolved by further discussion with third reviewers (D.W.J. or S.U.K.). Variables collected for meta-analysis included methods of NIT (VCTE or MRE), authors, publication year, study region, study design, number of patients, mean age, sex, mean body mass index (BMI), presence of diabetes mellitus, and fibrosis stages. The data of AUC, test performance parameters, and cut-off values for each liver fibrosis stage using VCTE and MRE were recorded. The quality of studies was assessed independently using the Quality Assessment of Diagnostic Accuracy Studies tool-2 in pairs, and disagreements were resolved by consensus with the third review author. Publication bias was assessed using a funnel plot.
Statistical analysis
We calculated the pooled diagnostic accuracy (sensitivity, specificity, and AUC) using the weighted mean of the transformed diagnostic accuracy using a bivariate random-effect model [
43]. A two-tailed
P<0.05 was defined as significant. Statistical heterogeneity was evaluated using I
2 values, and I
2 values of 50% and 75% indicated moderate and high degrees of heterogeneity, respectively. Review Manager software version 5.4 (The Cochrane Collaboration, Copenhagen, Denmark) and STATA statistical package (release 15.1; Stata, College Station, TX, USA) were used for statistical analyses.
RESULTS
Characteristics of included studies
A total of 2,815 records were initially retrieved through database research (Medline: 1,103; EMBASE: 1,577; Cochrane Library: 111; and KoreaMed: 24). After removing duplicates, 2,171 records remained. We obtained 217 eligible records from the first article selection process after excluding 1,947 records by abstract and title screening. After excluding more articles during the second article selection process, 72 articles were included for the final analysis.
Figure 1 depicts the study selection flow chart.
Table 1 shows the characteristics of the 72 included articles. Studies were conducted in various countries across the world (at least from 19 countries worldwide). Thirty-eight studies were from Western countries, 29 were from Eastern countries, and five were global studies. Among the 72 studies, 63 and 14 articles dealt with diagnostic accuracy of liver fibrosis using VCTE [
13,
15-
21,
23-
28,
30,
44-
90] and MRE [
16,
26,
48,
75,
87,
91-
99], respectively. Five articles measured both VCTE and MRE [
16,
26,
48,
74,
87]. Of the 63 VCTE-related studies, the mean age of the participants was 50.8 years, 49.3% were male, their mean BMI was 31.5 kg/m
2, and diabetes mellitus was present in 43.0%. Of the 14 VCTE-related studies, the mean age of the participants was 53.3 years, 45.5% were male, mean BMI was 30.6 kg/m
2, and diabetes mellitus was present in 40.8%. Since cut-offs for single to all fibrosis stages were presented in one paper, articles were used multiple times for analyses if they contained cut-offs for various liver fibrosis stages. Quality and bias risk assessment results are listed in
Supplementary Figure 1, and most included studies were of good quality.
In a meta-analysis of 19,199 patients from 63 studies using VCTE as an intervention, 20 studies were included for the diagnosis of F1 [
15,
17,
19,
21,
26,
44-
58], 48 for the diagnosis of ≥F2 (significant fibrosis) [
15-
21,
23-
27,
30,
44-
54,
56-
79], 53 for the diagnosis of ≥F3 (AF) [
13-
15,
17-
21,
23-
28,
30,
44-
46,
48-
58,
61,
62,
64-
68,
70-
72,
74,
76,
78-
89], and 34 for the diagnosis of F4 (cirrhosis) [
15,
17,
19,
20,
23,
25,
26,
30,
44,
46,
48-
51,
53,
54,
56-
59,
61-
64,
70-
74,
78,
79,
82,
84,
90]. The diagnostic AUC for ≥F1, ≥F2, ≥F3, and F4 fibrosis stages was 0.83 (95% confidence interval [CI]: 0.80–0.86), 0.83 (95% CI: 080–0.86), 0.87 (95% CI: 0.84–0.90), and 0.94 (95% CI: 0.91–0.96), respectively (
Table 2). The summary ROC curves (sROC) of VCTE to assess each fibrosis stage is depicted in
Figure 2. The sensitivity and specificity for each fibrosis stage according to sROC were F1 (0.78 and 0.75), F2 (0.79 and 0.74), F3 (0.81 and 0.79), and F4 (0.88 and 0.89), respectively. Forest plots of sensitivity and specificity estimates from VCTE studies for assessing each fibrosis stage are shown in
Supplementary Figure 2. The cut-off ranges for each fibrosis stage ≥F1, ≥F2, ≥F3, and F4 were 5.0–9.6 kPa, 4.8– 16.4 kPa, 7.1–14.1 kPa, and 6.9–20.1 kPa, respectively (
Table 2).
Supplementary Figure 3 shows funnel plots of VCTE-related studies for each stage, and publication bias was documented regarding results for the F2 and F3 stages.
In a meta-analysis of 1,484 patients from 14 studies using MRE as an intervention, eight studies were included for the diagnosis of F1 [
26,
48,
91-
96], 11 for the diagnosis of ≥F2 [
16,
26,
48,
74,
91-
97], 12 for the diagnosis of ≥F3 [
26,
48,
74,
87,
91-
96,
98,
99], and eight for the diagnosis of F4 [
26,
48,
74,
91-
93,
95,
96]. The diagnostic AUC for ≥F1, ≥F2, ≥F3, and F4 fibrosis stages was 0.89 (95% CI: 0.86–0.92), 0.92 (95% CI: 0.89–0.94), 0.89 (95% CI: 0.86–0.92), and 0.94 (95% CI: 0.91–0.96), respectively (
Table 2).
Figure 3 shows the sROC with the corresponding sensitivity and specificity (F1 [0.78 and 0.87], F2 [0.85 and 0.86], F3 [0.85 and 0.89], and F4 [0.88 and 0.89]), respectively, of MRE to assess each fibrosis stage. Forest plots of sensitivity and specificity estimates from studies of MRE for assessing each fibrosis stage are depicted in
Supplementary Figure 4. The cut-off ranges for each fibrosis stage F≥1, F≥2, F≥3, and F4 were 2.5–3.14 kPa, 2.77– 4.14 kPa, 2.3–4.8 kPa, and 3.35–6.7 kPa, respectively.
Supplementary Figure 5 shows funnel plots of MRE-related studies for each stage, and publication bias was documented in the F1 and F3 stages.
Considering the significant clinical importance of diagnosing AF accurately, we further analyzed the diagnostic performances of VCTE and MRE according to the subgroups of cut-off ranges. Among 53 VCTE-related studies analyzed for determining cut-offs for AF, five cut-offs from four studies were used in duplicate; thus, 58 VCTE-related studies (including duplicates) presented the cut-off values for AF. Characteristics of the studies used for determining AF cut-offs are depicted in
Supplementary Table 2. Twenty-seven (26.6%) of the studies were Western studies, including 50.4% male participants, with 51.3 years mean age, 31.1 kg/m
2 mean BMI, and diabetes mellitus was present in 44.6%. The cut-off values for six, 33, 13, and six studies were 7.1–7.9 kPa, 8.0–9.9 kPa, 10.0–11.9 kPa, and 12.0–14.1 kPa, respectively, demonstrating pooled diagnostic AUCs of 0.90 (95% CI: 0.87–0.92; sensitivity: 0.89; specificity: 0.67), 0.87 (95% CI: 0.00–1.00; sensitivity: 0.83; specificity: 0.77), 0.87 (95% CI: 0.84–0.90; sensitivity: 0.80; specificity: 0.84), and 0.79 (95% CI: 0.75–0.82; sensitivity: 0.55; specificity: 0.88), respectively (
Table 3).
Among 12 MRE-related studies that presented the cut-off values for AF, eight (66.7%) were Western studies, including 45.8% male participants, with 52.6 years mean age, 30.5 kg/m
2 mean BMI, and diabetes mellitus was present in 40.3% (
Supplementary Table 2). Three, five, and four studies had cut-off values of 2.3–2.99 kPa, 3.62–3.8 kPa, and 3.9–4.8 kPa, respectively. Due to the insufficient number of studies, pooled AUC calculation was not possible for the group with cut-offs of 2.3–2.99 kPa. The pooled diagnostic AUC for five studies with cut-off values of 3.62–3.8 kPa and four studies with cut-off values of 3.9–4.8 kPa were 0.94 (95% CI: 0.91–0.96; sensitivity: 0.88; specificity: 0.91) and 0.93 (95% CI: 0.91–0.95; sensitivity: 0.83; specificity: 0.91), respectively (
Table 3).
DISCUSSION
This comprehensive systematic review and meta-analysis of 72 pertinent studies demonstrated that VCTE and MRE are reliable tools for assessing the degree of liver fibrosis in patients with NAFLD. In addition, VCTE (7.1–7.9 kPa) and MRE (3.62–3.8 kPa) with the suggested cut-offs showed favorable performance for diagnosing AF in patients with NAFLD. The outcomes of our study carry important clinical significance as they can aid clinicians in deciding on the management of patients with NAFLD by providing an accurate prediction of AF.
Our study has some important implications. First, to the best of our knowledge, this systematic review and meta-analysis is the most comprehensive, large-scale, and accurate study for assessing liver fibrosis using VCTE and MRE in patients with NAFLD. Compared to LB, the pooled AUC of VCTE and MRE for assessing each liver fibrosis stage was 0.83–0.94 and 0.89–0.94, respectively. The diagnostic performance for VCTE was comparable to the results of previous meta-analyses, showing similar pooled AUC of 0.76–0.99 and a trend toward higher AUC values with the F3 and F4 stages than with the F1 and F2 stages [
32,
35-
38]. Similarly, the diagnostic performance for MRE was comparable to that of previous studies at 0.87–0.95 [
32,
39-
41]. In contrast, this study dealt with the most recently updated papers published until mid-2023. We attempted to reduce heterogeneity by excluding studies including patients with alcoholic fatty liver disease or other chronic viral hepatitis, those on pediatric patients, and those without LB results as a reference standard. Although NAFLD can co-exist with increased alcohol intake, we wanted to clarify that the main driver of the disease is a metabolic factor. Besides, as children and adults NAFLD have different histopathological features, studies for children should be conducted separately.
Second, this study can serve as the basis for clinical guidelines for diagnosing and managing AF in patients with NAFLD through VCTE. According to the 2023 American Association for the Study of the Liver Disease practical guidance on the clinical assessment and management of NAFLD, if AF is suspected, improvement of patient prognosis by referring the patients to a high-grade institution capable of specialized treatment given by a gastroenterologist or hepatologist is recommended [
6]. According to the algorithm for assessing the risk of patients with NAFLD in this guidance, LS measured by VCTE 8 kPa at a primary medical institution is recommended as a cut-off to rule out AF. The suggested cut-offs to diagnose AF in previous meta-analyses were 8.0–10.4 kPa in the study by Kwok et al. [
35], 6.95–12.85 kPa in the study by Hashemi et al. [
36], 6.8–12.9 kPa in the study by Selvaraj et al. [
32], 9.75 kPa in the study by Cao et al. [
37], and 9.68 kPa in the study by Mózes et al. [
38]. Similarly, the suggestion of LS 8 kPa to rule out AF is documented in the European Association for the Study of the Liver Clinical Practice Guidelines on NITs 2021 updates [
12]. In our study, diagnostic performance was highest when the cut-off for AF was set at 7.1–7.9 kPa, slightly lower value than 8 kPa. This study confirms the accuracy of VCTE for assessing each fibrosis stage in patients with NAFLD and suggests that the cut-off value of 7.1–7.9 kPa is the optimal benchmark to rule out AF. These findings are expected to serve as the basis for newly established Korean NIT guidelines 2024.
Third, our result suggested a useful cut-off for diagnosing AF using MRE in patients with NAFLD. MRE is recommended as the most accurate imaging test to diagnose liver fibrosis at higher-level institutions when patients are referred due to suspicion of AF. The pooled AUC of MRE for diagnosing AF in our study was high at 0.89 but slightly lower than those from other meta-analyses. Selvaraj et al. [
32], Xiao et al. [
40], Liang et al. [
41], and Liang et al. [
39] reported the AUC of MRE for diagnosing AF to be 0.92, 0.96, 0.92, and 0.94, respectively. The cut-off values of MRE for AF show a wide range at 2.99–4.80 kPa, 3.62–4.8 kPa, 3.53 (3.40–3.66) kPa, and 2.43–5.97 kPa in the study by Selvarai et al. [
32], Xiao et al. [
40], Liang et al. [
41], and Liang et al. [
39], respectively. Although the cut-off range of our study was also wide (2.3–4.80 kPa), we further sub-grouped the studies according to the cut-off levels and calculated the pooled AUCs for each group. Compared with studies with an AF cut-off set at 3.9–4.8 kPa, studies with an AF cut-off value of 3.62–3.8 kPa showed higher AUC at 0.94. This narrowing the AF cut-off range of MRE may be clinically helpful for clinicians to put more effort into preventing complications of cirrhosis and to perform regular HCC surveillance for patients whose cut-offs were beyond that specific point.
Lastly, detecting AF through NIT according to the suggested F3 cut-offs from this meta-analysis may provide a practical guide for primary care and tertiary hospital physicians in clinical settings. AF in patients with NAFLD is known to be an important surrogate for liver-related complications, liver-related mortality, and overall mortality [
9-
11]. Since NAFLD is a disease with high prevalence, primary care physicians often encounter many patients with NAFLD and consider performing liver blood tests, patients’ metabolic and environmental risk factors evaluation, and history of liver disease assessments collectively. As the negative predictive value of LS assessed with VCTE is known to be high in patients with NAFLD [
12,
30], patients with LS <7.1–7.9 kPa with none to minimal risk factors or history of liver disease may have a very low risk of cirrhotic complications and HCC and can be safely managed by primary physicians. At the tertiary center, hepatologists use NITs to monitor disease progression, predict future liver-related complications, and make treatment decisions. According to our results, if LS is assessed with VCTE >7.1–7.9 kPa or MRE with >3.62–3.8 kPa, there is a high probability of F3 disease being present. However, as the positive predictive value of VCTE for diagnosing AF in NAFLD is known to be higher than that in viral chronic hepatitis [
12], and the positive predictive value in this meta-analysis varied from 0.39 to 0.84, there is a chance of overestimation of the degree of liver fibrosis in patients who have been referred to tertiary hospitals with suspicion of AF. Therefore, to predict liver-related complications more accurately and perform proper treatment interventions in these patients, combinations of NITs are often considered and are under active investigation. The FibroScan-aspartate aminotransferase (AST) score combining VCTE and AST levels [
100], and the magnetic resonance imaging-AST score combining MRE and AST levels to detect AF showed AUC of 0.8 and 0.9, respectively [
101]. The MRE combined with fibrosis-4 index showed an AUC of 0.90 for detecting significant fibrosis in patients with NAFLD [
102]. As a lot of research is being conducted on TE-or MRE-based combination NITs, meta-analysis should be considered in the future.
There are some limitations to our study. First, the application of the diagnostic performance obtained from the LBbased patient cohort to the NAFLD population with a low prevalence of AF or cirrhosis portends generalization error. Second, as the number of enrolled studies is small for the currently proposed cut-off for MRE, further validation of the appropriate cut-off value for AF appears to be necessary. Third, we could not consider confounding factors such as sex, BMI, presence of diabetes mellitus, or probe types, which may affect diagnostic accuracy. Fourth, we did not simultaneously measure or adjust steatosis to diagnose fibrosis. Lastly, publication bias was present in assessing some liver fibrosis stages.
In summary, VCTE (7.1–7.9 kPa) and MRE (3.62–3.8 kPa) with the suggested cut-offs showed favorable accuracy for diagnosing AF in patients with NAFLD. This result will serve as a basis for clinical guidelines for NITs and will be clinically useful to rule out AF. Future studies with a combination of NITs or the addition of genetic biomarkers in NAFLD may provide more accurate data on disease progression and treatment decisions.
ACKNOWLEDGMENTS
The authors thank the Clinical Practice Guideline Committee for Noninvasive Tests (NIT) to Assess Liver Fibrosis in Chronic Liver Disease of the Korean Association for the Study of the Liver (KASL) for providing the opportunity to conduct this research.
FOOTNOTES
-
Authors’ contribution
All authors take responsibility for the data integrity and the accuracy of the data analyses. YE Chon, Y-J Jin, HY Kim, JH Yu, and SU Kim were responsible for the conception and design of the study; YE Chon, Y-J Jin, HY Kim, M Choi, DW Jun, MN Kim, JW Han, HA Lee, JH Yu, J An, and SU Kim were responsible for the acquisition, analysis, and interpretation of data, and drafting the manuscript. M Choi performed the statistical analyses. All authors approved the final version of the manuscript.
-
Conflicts of Interest
The authors have no conflicts to disclose.
SUPPLEMENTAL MATERIAL
Supplementary material is available at Clinical and Molecular Hepatology website (
http://www.e-cmh.org).
Supplementary Figure 2.
Forrest plots of VCTE for assessing fibrosis stages (A) ≥F1, (B) ≥F2, (C) ≥F3, and (D) F4. VCTE, vibration-controlled transient elastography.
Supplementary Figure 3.
Funnel plots of VCTE for assessing fibrosis stages (A) ≥F1, (B) ≥F2, (C) ≥F3, and (D) F4. VCTE, vibration-controlled transient elastography.
Supplementary Figure 4.
Forrest plots of MRE for assessing fibrosis stages (A) ≥F1, (B) ≥F2, (C) ≥F3, and (D) F4. MRE, magnetic resonance elastography.
Supplementary Figure 5.
Funnel plots of MRE for assessing fibrosis stages (A) ≥F1, (B) ≥F2, (C) ≥F3, and (D) F4. MRE, magnetic resonance elastography.
Figure 1.Flow chart of study selection.
Figure 2.Summary of receiver operating characteristics curves of vibration-controlled transient elastography for assessing fibrosis stages (A) ≥F1, (B) ≥F2, (C) ≥F3, and (D) F4. ROC, receiver operating characteristics; sROC, summary ROC curves; AUC, area under the receiver operating characteristics curve.
Figure 3.Summary of receiver operating characteristics curves of magnetic resonance elastography for assessing fibrosis stages (A) ≥F1, (B) ≥F2, (C) ≥F3, and (D) F4. ROC, receiver operating characteristics; sROC, summary ROC curves; AUC, area under the receiver operating characteristics curve.
Table 1.Characteristics of the included studies
Table 1.
|
Author |
Year |
Region |
Study design |
Patients, n |
Age, years |
Male, % |
BMI, kg/m2
|
Diabetes mellitus, % |
Fibrosis stag for analyses |
|
VCTE |
|
|
|
|
|
|
|
|
|
|
Argalia et al. [44] |
2022 |
Italy |
CS, SS |
50 |
52.2 |
64 |
29.4 |
NR |
≥F1, ≥F2, ≥F3, F4 |
|
Barsamian et al. [45] |
2020 |
France |
CS, SS |
108 |
41 |
21 |
43 |
24 |
≥F1, ≥F2, ≥F3 |
|
Chan et al. [15] |
2015 |
Malaysia |
CS, SS |
101 |
50.5 |
54.4 |
29.3 |
52.4 |
≥F1, ≥F2, ≥F3, F4 |
|
Chan et al. [46] |
2017 |
Malaysia, Hongkong |
CS, SS |
57 |
50.1 |
49 |
39.2 |
NR |
≥F1, ≥F2, ≥F3, F4 |
|
Gaia et al. [17] |
2011 |
Italy |
CS, SS |
72 |
48 |
72.2 |
27.5 |
NR |
≥F1, ≥F2, ≥F3, F4 |
|
Garteiser et al. [47] |
2021 |
France |
CS, SS |
152 |
42 |
16 |
44.1 |
21 |
≥F1, ≥F2 |
|
Imajo et al. [48] |
2022 |
Japan |
CS, SS |
231 |
61 |
52.7 |
27.1 |
61.7 |
≥F1, ≥F2, ≥F3, F4 |
|
Kim et al. [49] |
2022 |
Korea |
CS, SS |
60 |
50.9 |
45.9 |
29.9 |
61.7 |
≥F1, ≥F2, ≥F3, F4 |
|
Kumar et al. [19] |
2013 |
India |
CS, SS |
120 |
39.1 |
75 |
26.1 |
16.6 |
≥F1, ≥F2, ≥F3, F4 |
|
Lee et al. [50] |
2016 |
Korea |
CS, SS |
183 |
40.6 |
60.7 |
27.9 |
14.2 |
≥F1, ≥F2, ≥F3, F4 |
|
Leong et al. [51] |
2020 |
Malaysia |
CS, SS |
100 |
57.1 |
46 |
30.8 |
NR |
≥F1, ≥F2, ≥F3, F4 |
|
Lupsor et al. [21] |
2010 |
Netherlands |
CS, SS |
72 |
42 |
70.8 |
28.7 |
NR |
≥F1, ≥F2, ≥F3 |
|
Okajima et al. [52] |
2017 |
Japan |
CS, SS |
163 |
55.8 |
48.5 |
27.2 |
NR |
≥F1, ≥F2, ≥F3 |
|
Park et al. [26] |
2017 |
US |
CS, SS |
104 |
50.8 |
43.3 |
30.4 |
27.9 |
≥F1, ≥F2, ≥F3, F4 |
|
Sharpton et al. [53] |
2021 |
US |
CS, SS |
114 |
55 |
45.6 |
31.2 |
NR |
≥F1, ≥F2, ≥F3, F4 |
|
Shi et al. [54] |
2020 |
China |
CS, SS |
158 |
48.9 |
30.4 |
25.9 |
26.6 |
≥F1, ≥F2, ≥F3, F4 |
|
Shima et al. [55] |
2020 |
Japan |
CS, SS |
278 |
57.8 |
48.2 |
27.5 |
58.6 |
≥F1, ≥F3 |
|
Siddiqui et al. [56] |
2019 |
US |
CS, SS |
393 |
51 |
32 |
34.4 |
44 |
≥F1, ≥F2, ≥F3, F4 |
|
Yang et al. [57] |
2021 |
China |
CS, SS |
91 |
40 |
50.5 |
29.1 |
71.4 |
≥F1, ≥F2, ≥F3, F4 |
|
Yoneda et al. [58] |
2008 |
Japan |
CS, SS |
97 |
51.8 |
41.2 |
26.6 |
NR |
≥F1, ≥F2, ≥F3, F4 |
|
Boursier et al. [59] |
2023 |
France |
CS, MS |
1,051 |
58 |
60 |
31 |
49.8 |
≥F2, F4 |
|
Cardoso et al. [60] |
2020 |
Brazil |
CS, SS |
81 |
54.2 |
26 |
32.8 |
60 |
≥F2 |
|
Cassinotto et al. [61] |
2016 |
France |
CS, MS |
291 |
56.7 |
59.1 |
32.1 |
52.6 |
≥F2, ≥F3, F4 |
|
Chang et al. [62] |
2023 |
US |
CS, MS |
1,370 |
56.6 |
44.5 |
34.2 |
38.0 |
≥F2, ≥F3, F4 |
|
Chang et al. [63] |
2019 |
Singapore |
CS, MS |
51 |
49.4 |
55.6 |
23.9 |
NR |
≥F2, F4 |
|
Eddowes et al. [64] |
2019 |
UK |
CS, MS |
373 |
54 |
55 |
33.8 |
50 |
≥F2, ≥F3, F4 |
|
Eilenberg et al. [65] |
2021 |
Austria |
CS, SS |
170 |
42 |
35.4 |
44.4 |
28.2 |
≥F2, ≥F3 |
|
Ergelen et al. [66] |
2015 |
Turkey |
CS, SS |
87 |
45.8 |
49.4 |
30.6 |
NR |
≥F2, ≥F3 |
|
Furlan et al. [16] |
2020 |
US |
CS, SS |
62 |
50 |
42 |
34.8 |
35 |
≥F2 |
|
Garg et al. [18] |
2018 |
India |
CS, SS |
76 |
39.3 |
23.3 |
46.2 |
NR |
≥F2, ≥F3 |
|
Inadomi et al. [67] |
2020 |
Japan |
CS, SS |
200 |
59.5 |
48 |
28.1 |
50.3 |
≥F2, ≥F3 |
|
Jafarov et al. [68] |
2020 |
Turkey |
CS, SS |
139 |
49 |
59 |
32.9 |
64 |
≥F2, ≥F3 |
|
Lee et al. [23] |
2022 |
Korea |
CS, SS |
539 |
56 |
47.5 |
26.9 |
36.2 |
≥F2, ≥F3, F4 |
|
Lee et al. [69] |
2019 |
Korea |
CS, SS |
184 |
44.6 |
69 |
29.3 |
37.5 |
≥F2 |
|
Lee et al. [70] |
2022 |
Korea |
CS, SS |
251 |
44 |
52.6 |
28.6 |
46.6 |
≥F2, ≥F3, F4 |
|
Lee et al. [20] |
2017 |
Korea |
CS, SS |
94 |
55.5 |
43.6 |
27.1 |
39.4 |
≥F2, ≥F3, F4 |
|
Mendoza et al. [71] |
2022 |
Switzerland |
CS, SS |
104 |
53.4 |
58.7 |
30.9 |
47.1 |
≥F2, ≥F3, F4 |
|
Myers et al. [72] |
2010 |
Canada |
CS, MS |
20 |
NR |
NR |
NR |
NR |
≥F2, ≥F3, F4 |
|
Myers et al. [73] |
2012 |
Canada |
CS, MS |
276 |
50 |
63 |
30 |
NR |
≥F2, F4 |
|
Naveau et al. [24] |
2014 |
France |
CS, SS |
100 |
42.5 |
19 |
41.3 |
15 |
≥F2, ≥F3 |
|
Nogami et al. [74] |
2022 |
Japan |
CS, SS |
163 |
59.7 |
52.8 |
28.5 |
61.3 |
≥F2, ≥F3, F4 |
|
Oeda et al. [25] |
2020 |
Japan |
CS, MS |
137 |
NR |
NR |
NR |
NR |
≥F2, ≥F3, F4 |
|
Ooi et al. [75] |
2018 |
Australia |
CS, SS |
182 |
44 |
24.7 |
45.1 |
27.1 |
≥F2 |
|
Petta et al. [27] |
2011 |
Italy |
CS, SS |
146 |
44.1 |
71 |
29.1 |
14 |
≥F2, ≥F3 |
|
Taibbi et al. [76] |
2021 |
Italy |
CS, SS |
56 |
54.7 |
58.7 |
29.4 |
39.1 |
≥F2, ≥F3 |
|
Vali et al. [77] |
2023 |
Europe |
CS, MS |
632 |
51.2 |
58 |
34.1 |
42 |
≥F2 |
|
Wong et al. [78] |
2019 |
France, Hongkong |
CS, MS |
496 |
54 |
42.7 |
30.4 |
60.5 |
≥F2, ≥F3, F4 |
|
Wong et al. [30] |
2010 |
France, Hongkong |
CS, MS |
246 |
51 |
54.9 |
28 |
36.2 |
≥F2, ≥F3, F4 |
|
Yu et al. [79] |
2021 |
China |
CS, SS |
85 |
58 |
40 |
29.7 |
100 |
≥F2, ≥F3, F4 |
|
Petta et al. [28] |
2019 |
Global |
CS, MS |
968 |
50.1 |
62.9 |
29.3 |
37 |
≥F3 |
|
Tovo et al. [80] |
2019 |
Brazil |
CS, MS |
104 |
55.3 |
26 |
33 |
64.4 |
≥F3 |
|
Kosick et al. [81] |
2021 |
Canada |
CS, MS |
407 |
48.5 |
54 |
32.3 |
30 |
≥F3 |
|
Boursier et al. [14] |
2016 |
France |
CS, MS |
452 |
55.9 |
60 |
31.1 |
46.7 |
≥F3 |
|
Sanyal et al. [82] |
2023 |
Global |
CS, MS |
1,434 |
55 |
50.8 |
31.7 |
50.4 |
≥F3, F4 |
|
Armandi et al. [83] |
2023 |
Turkey |
LS, SS |
96 |
49.5 |
62.2 |
28.4 |
30.6 |
≥F3 |
|
Noureddin et al. [84] |
2023 |
US |
CS, MS |
548 |
58 |
35 |
33.3 |
53 |
≥F3, F4 |
|
Petta et al. [85] |
2017 |
Global |
CS, MS |
761 |
50.9 |
60.2 |
29.6 |
54.7 |
≥F3 |
|
Petta et al. [86] |
2015 |
Italy |
CS, MS |
321 |
44.7 |
69.5 |
28.5 |
17.8 |
≥F3 |
|
Anstee et al. [13] |
2019 |
US |
CS, MS |
3,202 |
58 |
38 |
NR |
60 |
≥F3 |
|
Troelstra et al. [87] |
2021 |
Netherlands |
CS, SS |
37 |
49 |
62 |
33.2 |
43 |
≥F3 |
|
Seki et al. [88] |
2017 |
Japan |
CS, SS |
171 |
57.1 |
50.3 |
27.7 |
NR |
≥F3 |
|
Labenz et al. [89] |
2018 |
Germany |
CS, MS |
261 |
51 |
52.5 |
30.9 |
29.9 |
≥F3 |
|
Pavlides et al. [90] |
2017 |
UK |
CS, SS |
71 |
53.4 |
43 |
32.7 |
35 |
F4 |
|
MRE |
|
|
|
|
|
|
|
|
|
|
Costa-Silva et al. [91] |
2018 |
Brazil |
CS, SS |
49 |
53.8 |
14.3 |
32.2 |
NR |
≥F1, ≥F2, ≥F3, F4 |
|
Cui et al. [92] |
2016 |
US |
CS, SS |
125 |
48.9 |
45.6 |
31.8 |
26 |
≥F1, ≥F2, ≥F3, F4 |
|
Imajo et al. [93] |
2016 |
Japan |
CS, SS |
142 |
57.5 |
57 |
28.1 |
71 |
≥F1, ≥F2, ≥F3, F4 |
|
Imajo et al. [48] |
2022 |
Japan |
CS, SS |
231 |
61 |
52.7 |
27.1 |
61.7 |
≥F1, ≥F2, ≥F3, F4 |
|
Kim et al. [94] |
2020 |
Korea |
CS, SS |
47 |
51 |
34 |
28.3 |
NR |
≥F1, ≥F2, ≥F3 |
|
Loomba et al. [95] |
2014 |
US |
CS, SS |
117 |
50.1 |
43.6 |
32.4 |
34.2 |
≥F1, ≥F2, ≥F3, F4 |
|
Park et al. [26] |
2017 |
US |
CS, SS |
104 |
50.8 |
43.3 |
30.4 |
27.9 |
≥F1, ≥F2, ≥F3, F4 |
|
Zhang et al. [96] |
2022 |
US |
CS, SS |
100 |
51.8 |
46 |
31.6 |
NR |
≥F1, ≥F2, ≥F3, F4 |
|
Furlan et al. [16] |
2020 |
US |
CS, SS |
62 |
50 |
42 |
34.8 |
35 |
≥F2 |
|
Inada et al. [97] |
2022 |
Japan |
CS, SS |
105 |
65 |
44.8 |
27.5 |
50.5 |
≥F2 |
|
Nogami et al. [74] |
2022 |
Japan |
CS, SS |
163 |
55.8 |
48.5 |
27.2 |
NR |
≥F2, ≥F3, F4 |
|
Troelstra et al. [87] |
2021 |
Netherlands |
CS, SS |
37 |
49 |
62 |
33.2 |
43 |
≥F3 |
|
Cui et al. [98] |
2015 |
US |
CS, SS |
102 |
51.3 |
58.8 |
31.7 |
25.5 |
≥F3 |
|
Loomba et al. [99] |
2016 |
US |
CS, SS |
100 |
50.2 |
44 |
32.1 |
33 |
≥F3 |
Table 2.Pooled diagnostic performance of VCTE and MRE for assessing fibrosis stages in patients with NAFLD
Table 2.
|
Cut-off range, kPa |
Studies, n |
AUC (95% CI) |
Sensitivity (95% CI) |
I2, % (95% CI) |
Specificity (95% CI) |
I2, % (95% CI) |
|
VCTE |
|
|
|
|
|
|
|
|
≥F1 |
5.0–9.6 |
20 |
0.83 (0.80–0.86) |
0.78 (0.72–0.82) |
88.1 (83.9–92.3) |
0.75 (0.68–0.81) |
83.5 (77.1–89.9) |
|
≥F2 |
4.8–16.4 |
48 |
0.83 (0.80–0.86) |
0.79 (0.74–0.82) |
95.2 (94.5–96.0) |
0.74 (0.70–0.78) |
92.3 (90.9–93.7) |
|
≥F3 |
7.1–14.1 |
53 |
0.87 (0.84–0.90) |
0.81 (0.78–0.84) |
87.2 (84.6–89.9) |
0.79 (0.76–0.82) |
90.0 (88.0–91.9) |
|
F4 |
6.9–20.1 |
34 |
0.94 (0.91–0.96) |
0.91 (0.85–0.94) |
89.6 (86.8–92.3) |
0.87 (0.84–0.89) |
92.8 (91.1–94.4) |
|
MRE |
|
|
|
|
|
|
|
|
≥F1 |
2.5–3.14 |
8 |
0.89 (0.86–0.92) |
0.78 (0.67–0.86) |
84.5 (74.9–94.1) |
0.87 (0.74–0.94) |
88.1 (81.3–95.0) |
|
≥F2 |
2.77–4.14 |
11 |
0.92 (0.89–0.94) |
0.85 (0.78–0.90) |
79.5 (68.0–91.0) |
0.86 (0.78–0.92) |
83.3 (74.4-92.2) |
|
≥F3 |
2.3–4.8 |
12 |
0.89 (0.86–0.92) |
0.85 (0.80–0.88) |
0.0 (0.0–87.5) |
0.89 (0.85–0.92) |
61.8 (37.9-85.8) |
|
F4 |
3.35–6.7 |
8 |
0.94 (0.91–0.96) |
0.88 (0.79–0.93) |
0.0 (0.0–96.1) |
0.89 (0.83–0.92) |
84.1 (74.2-94.0) |
Table 3.Summary diagnostic performance of VCTE and MRE for detecting advanced fibrosis in patients with NAFLD according to cutoff ranges
Table 3.
|
Cut-off range, kPa |
Studies, n |
Patients, n |
AUC (95% CI) |
Sensitivity (95% CI) |
I2, % (95% CI) |
Specificity (95% CI) |
I2, % (95% CI) |
|
VCTE |
|
|
|
|
|
|
|
|
7.1–7.9 |
6 |
1,895 |
0.90 (0.87–0.92) |
0.89 (0.85–0.91) |
35.9 (0.0–94.7) |
0.67 (0.59–0.74) |
88.8 (81.4–96.3) |
|
8.0–9.9 |
33 |
11,862 |
0.87 (0.00–1.00) |
0.83 (0.80–0.86) |
75.0 (66.6–83.4) |
0.77 (0.74–0.80) |
88.9 (86.0–91.9) |
|
10.0–11.9 |
13 |
2,195 |
0.87 (0.84–0.90) |
0.80 (0.76–0.84) |
40.1 (0.9–79.3) |
0.84 (0.79–0.88) |
77.1 (65.0–89.3) |
|
12.0–14.1 |
6 |
1,256 |
0.79 (0.75–0.82) |
0.55 (0.49–0.61) |
25.7 (0.0–90.4) |
0.88 (0.84–0.90) |
32.5 (0.0–93.7) |
|
MRE |
|
|
|
|
|
|
|
|
2.3–2.99 |
3 |
241 |
Cannot be synthesized |
|
3.62–3.8 |
5 |
607 |
0.94 (0.91–0.96) |
0.88 (0.81–0.93) |
0.0 (0.0–100.0) |
0.91 (0.86–0.94) |
64.1 (29.3–98.8) |
|
3.9–4.8 |
4 |
439 |
0.93 (0.91–0.95) |
0.83 (0.73–0.89) |
22.2 (0.0–100.0) |
0.91 (0.85–0.95) |
34.3 (0.0–100.0) |
Abbreviations
aspartate aminotransferase
area under the receiver operating characteristics curve
magnetic resonance elastography
nonalcoholic fatty liver disease
receiver operating characteristics
vibration-controlled transient elastography
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, Seung Up Kim7,8
