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United European Gastroenterology Journal logoLink to United European Gastroenterology Journal
. 2019 Jul 12;7(8):1113–1123. doi: 10.1177/2050640619865133

Evaluation and comparison of six noninvasive tests for prediction of significant or advanced fibrosis in nonalcoholic fatty liver disease

Katharina Staufer 1,2, Emina Halilbasic 1, Walter Spindelboeck 3, Magdalena Eilenberg 4, Gerhard Prager 4, Vanessa Stadlbauer 3, Andreas Posch 3, Petra Munda 1, Rodrig Marculescu 5, Barbara Obermayer-Pietsch 3, Judith Stift 6, Carolin Lackner 7, Michael Trauner 1, Rudolf E Stauber 3,
PMCID: PMC6794685  PMID: 31662868

Abstract

Background

In nonalcoholic fatty liver disease (NAFLD), advanced fibrosis has been identified as an important prognostic factor with increased liver-related mortality and treatment need. Due to the high prevalence of NAFLD, noninvasive risk stratification is needed to select patients for liver biopsy and treatment.

Objective

To compare the diagnostic accuracy of several widely available noninvasive tests for assessment of fibrosis among patients with NAFLD with or without nonalcoholic steatohepatitis (NASH).

Methods

We enrolled consecutive patients with NAFLD admitted to two Austrian referral centers who underwent liver biopsy. Liver stiffness measurement (LSM) was obtained by vibration-controlled transient elastography (VCTE, FibroScan) and blood samples were collected for determination of enhanced liver fibrosis (ELF) test, FibroMeterV2G, FibroMeterV3G, NAFLD fibrosis score (NFS), and fibrosis-4 index (FIB-4).

Results

Our study cohort contained 186 patients with histologically confirmed NAFLD. On liver histology, NASH was present in 92 patients (50%), significant fibrosis (F ≥ 2) in 71 patients (38%), advanced fibrosis (F ≥ 3) in 49 patients (26%), and F ≥ 3 plus NASH in 35 patients (19%). For diagnosis of F ≥ 2, F ≥ 3, and F ≥ 3 plus NASH, respectively, receiver operating characteristic (ROC) analysis revealed superior diagnostic accuracy of ELF score (area under ROC curve (AUROC) 0.85, 0.90, 0.90), FibroMeterV2G (AUROC 0.86, 0.88, 0.89), FibroMeterV3G (AUROC 0.84, 0.88, 0.88), and LSM per protocol (AUROC 0.87, 0.95, 0.91) versus FIB-4 (AUROC 0.80, 0.82, 0.81) or NFS (AUROC 0.78, 0.80, 0.79).

Conclusion

Proprietary fibrosis panels and VCTE show superior diagnostic accuracy for noninvasive diagnosis of fibrosis stage in NAFLD as compared to FIB-4 and NFS.

Keywords: Enhanced liver fibrosis score, FibroMeter, vibration-controlled transient elastography, liver stiffness measurement, fibrosis-4 index, NAFLD fibrosis score

Introduction

Nonalcoholic fatty liver disease (NAFLD) is highly prevalent in Western countries, closely linked to obesity and the metabolic syndrome, and represents an increasing cause for chronic liver failure, hepatocellular carcinoma, and need for liver transplantation. Within NAFLD, two stages are discerned: (a) nonalcoholic fatty liver (NAFL), which shows low liver-related morbidity, and (b) nonalcoholic steatohepatitis (NASH), which has a higher risk for progressive hepatic fibrosis and shows substantial liver-related mortality.1

Previous studies have identified advanced fibrosis (F ≥ 3) as the major prognostic factor in NAFLD.24 Besides lifestyle modification, there is currently no accepted treatment for NAFLD, but clinical trials of novel pharmacologic agents are focusing on patients with NASH and advanced fibrosis. Presence of NASH and advanced fibrosis is currently best determined by liver biopsy. However, due to the high prevalence of NAFLD, universal liver biopsy is not feasible and noninvasive triage tests are needed either as an alternative or to select patients for liver biopsy.57

Enhanced liver fibrosis (ELF™) test, a proprietary fibrosis panel based on extracellular matrix proteins containing hyaluronic acid (HA), procollagen-3 N-terminal peptide (P3NP), and tissue inhibitor of metalloproteinase-1 (TIMP-1), has been found useful for staging of NAFLD in adult as well as pediatric populations,811 with cut-offs varying between 9.8 and 10.5 for the diagnosis of advanced fibrosis.1214 Additional proprietary fibrosis panels that have been validated in various chronic liver diseases include FibroMeterV2G (based on platelet count, prothrombin index, aspartate transaminase (AST), alpha-2-macroglobulin, HA, urea, age, and sex),15,16 FibroMeterV3G (using gamma-glutamyl transferase (GGT) instead of HA),17 and FibroTest (based on alpha-2-macroglobulin, haptoglobin, GGT, age, bilirubin, apolipoprotein A1, and sex).18 On the other hand, simple fibrosis tests based on routine clinical and laboratory parameters might provide similar diagnostic information at much lower cost. Among these, NAFLD fibrosis score (NFS) has been developed specifically for NAFLD considering the parameters age, hyperglycemia, body mass index (BMI), platelet count, albumin, and AST/alanine transaminase (ALT) ratio,19 while FIB-4 has been derived from a HCV-HIV co-infected cohort and includes age, AST, ALT, and platelet count.20

Vibration-controlled transient elastography (VCTE) now enables accurate staging in a variety of liver diseases, including NAFLD.2124 However, this method is limited to referral centers due to high equipment cost and has a substantial failure rate, especially in obese patients. Besides, VCTE results may be influenced by the type of probe used, by BMI, and by hepatic fat content.2527

The aim of the present study was to prospectively evaluate and compare the diagnostic accuracy of several blood fibrosis tests including ELF test and the simple tests, NFS and FIB-4, as well as VCTE for detection of fibrosis stage among patients with NAFLD with or without NASH. In addition, we performed a post-hoc comparison with FibroMeterV2G and FibroMeterV3G.

Patients, materials, and methods

We conducted a prospective, biopsy-controlled, two-center study to compare the diagnostic accuracy of available noninvasive tools for the detection of F ≥ 2, F ≥ 3, and the combined endpoint of F ≥ 3 plus the presence of NASH. The cohort was part of a larger Austrian study aiming at biomarker development in metabolic syndrome, BioPersMed (Biomarkers for Personalized Medicine), approved by the Ethics Committee of the Medical University of Graz (EC 24-224 ex 11/12) and the Medical University of Vienna (EC #747/2011). The study was performed in accordance with the Declaration of Helsinki including current revisions after written informed consent was obtained. This report follows the Liver-FibroSTARD checklist.28

Patients

Between 2011 and 2016, we enrolled consecutive patients with NAFLD at two Austrian tertiary referral centers (Medical University of Graz and Medical University of Vienna) who had been referred for evaluation of suspected NAFLD based on elevated liver function tests, fatty liver on ultrasound, and/or presence of metabolic risk factors with or without diabetes. Selection criteria were presence of steatosis >5% on liver histology, history of alcohol consumption <30 g/day for men and <20 g/day for women, absence of concomitant viral hepatitis, and absence of other liver disease on histology. All patients underwent liver biopsy, mainly for staging purposes and less often for differential diagnosis (see flowchart in Figure 1). Blood fibrosis tests were obtained on the same day prior to liver biopsy while VCTE was performed with a median interval of two months prior to liver biopsy.

Figure 1.

Figure 1.

Study flowchart.

Histology

Histological NASH was defined by the minimal criteria for steatohepatitis in adults, i.e. presence of >5% macrovesicular steatosis, lobular inflammation, and hepatocellular ballooning, typically with a predominantly centrilobular distribution.29 Fibrosis was staged according to the Clinical Research Network (CRN) score.30 All liver biopsies were assessed by either of two experienced specialized hepatopathologists (CL, JS) who were unaware of the results of noninvasive fibrosis tests. Only biopsies with ≥15 mm length were entered into the database.

Noninvasive fibrosis tests

VCTE was performed in patients fasted for at least two hours using a FibroScan® 502 Touch (Echosens, Paris, France) at both centers. Initially all patients were examined using the M-probe; the XL-probe was additionally available at Graz from 2012 and at Vienna from 2014 onwards and was used if probe-to-capsule distance was >25 mm as recommended by the manufacturer. Liver stiffness measurement (LSM) values were considered unreliable if IQR/med was >30% for values above 7.0 kPa.28 For diagnosis of significant or advanced fibrosis, we applied the recently published cut-off values of 8.2 and 9.7 kPa, respectively, based on a large UK study in 383 NAFLD patients.24

Serum samples obtained at the time of liver biopsy were used to perform ELF™ test on an Advia Centaur XP (Siemens Healthcare Diagnostics, Vienna, Austria). According to the manufacturer, coefficient of variation ranges from 5.5% to 7.7% for HA, from 2.8% to 6.6% for P3NP, and from 3.1% to 6.0% for TIMP-1. For diagnosis of significant or advanced fibrosis, the published ELF score cut-offs of 7.7 and 9.8, respectively, were applied.12

NFS and FIB-4 were calculated from routine clinical and laboratory parameters obtained at the time of liver biopsy and published cut-offs were used for diagnosis of advanced fibrosis.19,20,31,32 In addition, following previous reports on the influence of age on FIB-4 and of BMI on LSM, we analyzed the effect of age, BMI, and presence of diabetes/IFG on the results of the noninvasive fibrosis tests evaluated in our study.3335

Post-hoc, we obtained the parameters necessary for calculation of FibroMeterV2G and FibroMeterV3G (Echosens, Paris, France). Calculation of the fibrometers was kindly provided by Prof. Paul Cales, Angers, France. For FibroMeterV2G/V3G, cut-offs were derived by Youden index within our cohort, i.e. 0.309/0.378 for F ≥ 2 and 0.385/0.461 for F ≥ 3.

All persons who performed noninvasive fibrosis tests were unaware of the results of liver biopsy.

Statistical analysis

Summary data are reported as median (Q1, Q3) or frequencies. Chi-square test or Mann–Whitney U test was performed for group comparisons. The diagnostic accuracy of noninvasive fibrosis tests for significant or advanced fibrosis was assessed by receiver operating characteristic (ROC) analysis. Areas under the ROC curves (AUROCs) were compared by the method of DeLong et al.36 For assessing the diagnostic accuracy of VCTE, we performed a per protocol (PP) analysis excluding unreliable results as well as an intention-to-diagnose (ITD) analysis based on all VCTE examinations including unreliable and failed measurements. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated using cut-offs previously published or calculated by Youden index in the present study. We used MedCalc Statistical Software 18.11.3 (MedCalc Software, Ostend, Belgium) for AUROC comparisons and SPSS 25 (IBM Statistics, New York, United States) for all other calculations.

Results

Patients

Between 2011 and 2016 we included 192 patients at both centers, 73 from Graz, and 119 from Vienna. Liver biopsy was performed for staging purposes (presence/absence of NASH, determination of fibrosis stage) in 169 patients and (primarily) for differential diagnosis in 23 patients (Figure 1). Liver biopsy was obtained percutaneously in 142 patients and intraoperatively during bariatric surgery in 50 patients. Histology did not confirm NAFLD in four patients and a representative liver biopsy specimen was lacking in two patients, leaving 186 for analysis. Patient characteristics for the whole NAFLD cohort and for subgroups according to fibrosis stage are given in Table 1.

Table 1.

Patient characteristics.

All NAFLD
F < 2
F ≥ 2
p-value
F < 3
F ≥ 3
p-value
N = 186 N = 115 N = 71 F ≥ 2 vs. F < 2 N = 137 N = 49 F ≥ 3 vs. F < 3
Age (years) 52 (39, 60) 46 (35, 55) 57 (52, 64) <0.001 47 (35, 56) 58 (52, 67) <0.001
Male sex (%) 57 62 49 0.096 60 49 0.187
BMI 30.5 (27.0, 37.8) 30.4 (27.0, 38.4) 30.7 (27.0, 34.1) 0.355 30.4 (27.0, 38.5) 30.9 (27.0, 33.9) 0.226
AST (U/L) 41 (30, 59) 35 (27, 51) 51 (34, 77) <0.001 37 (29, 54) 53 (36, 97) <0.001
ALT (U/L) 55 (36, 84) 51 (36, 80) 60 (37, 87) 0.320 52 (36, 87) 57 (37, 83) 0.742
Albumin (g/dL) 4.5 (4.2, 4.7) 4.5 (4.3, 4.8) 4.3 (4.0, 4.6) <0.001 4.5 (4.2, 4.8) 4.2 (3.9, 4.5) <0.001
PLT (109/L) 223 (182, 271) 239 (202, 280) 206 (154, 251) <0.001 233 (203, 275) 180 (136, 253) <0.001
Diabetes/IFG (%) 30 17 52 <0.001 21 55 <0.001
HOMA-IR 3.65 (1.91, 6.53) 3.34 (1.55, 5.89) 4.43 (2.64, 8.12) 0.016 3.55 (1.59, 5.98) 4.17 (2.62, 8.39) 0.031
NAS 0–2 / 3–4/5–8 (%) 31/41/28 40/37/23 17/46/37 0.003 36.5/36.5/27 16/53/31 0.026

Data are shown as median (Q1, Q3). BMI, body mass index; AST, aspartate aminotransferase; ALT, alanine aminotransferase; PLT, platelet count; IFG; impaired fasting glucose; HOMA-IR, homeostatic model assessment – insulin resistance; NAS, NAFLD activity score.

Liver histology

On liver histology, CRN fibrosis stage was distributed as follows: F0, 64 patients (34%); F1, 51 patients (27%); F2, 22 patients (12%); F3, 29 patients (16%); F4, 20 patients (11%). NASH was present in 92 patients (50%), significant fibrosis (F ≥ 2) in 71 patients (38%), advanced fibrosis (F ≥ 3) in 49 patients (26%), and F ≥ 3 plus NASH in 38 patients (20%). Median length of biopsy cylinders was 22 mm.

Blood fibrosis tests

ELF score, FibroMeterV2G, FibroMeterV3G, FIB-4, and NFS increased stepwise with fibrosis stage (Figure 2, Table 2).

Figure 2.

Figure 2.

Boxplots of noninvasive fibrosis tests by histological fibrosis stage.

LSM, liver stiffness measurement; ELF score, enhanced liver fibrosis score; FIB-4, fibrosis-4 index; NFS, NAFLD fibrosis score.

Table 2.

Noninvasive fibrosis tests in NAFLD.

N All NAFLD
F < 2
F ≥ 2
p-value
F < 3
F ≥ 3
p-value
N = 186 N = 115 N = 71 F ≥ 2 vs. F < 2 N = 137 N = 49 F ≥ 3 vs. F < 3
ELF score 181 8.9 (8.2, 9.9) 8.4 (8.0, 9.0) 10.0 (9.2, 11.4) <0.001 8.5 (8.1, 9.2) 10.5 (9.6, 11.7) <0.001
FMV2G 131 0.226 (0.109, 0.562) 0.144 (0.077, 0.274) 0.595 (0.322, 0.935) <0.001 0.167 (0.093, 0.325) 0.798 (0.464, 0.976) <0.001
FMV3G 132 0.267 (0.133, 0.638) 0.178 (0.097, 0.347) 0.661 (0.392, 0.903) <0.001 0.207 (0.109, 0.421) 0.796 (0.530, 0.956) <0.001
FIB-4 186 1.17 (0.78, 2.11) 0.92 (0.61, 1.39) 1.74 (1.18, 4.15) <0.001 1.00 (0.67, 1.45) 2.54 (1.33, 4.66) <0.001
NFS 167 −1.49 (−2.76, −0.26) −2.13 (−3.26, −1.17) −0.31 (−1.58, 0.94) <0.001 −1.95 (−3.01, −0.93) −0.22 (−1.20, 1.54) <0.001
LSM (kPa) 140 8.9 (6.1, 14.8) 6.8 (5.5, 9.2) 16.6 (10.0, 25.9) <0.001 7.3 (5.8, 10.3) 21.3 (14.8, 33.3) <0.001

Data are shown as median (Q1, Q3). ELF score, enhanced liver fibrosis score; FM, FibroMeter™; FIB-4, fibrosis-4 index; NFS, NAFLD fibrosis score; LSM, liver stiffness measurement (FibroScan®).

ELF score and FibroMeterV2G/V3G had the highest accuracies for the diagnosis of fibrosis stage and of the combined diagnostic endpoint of advanced fibrosis plus NASH (Tables 37).

Table 3.

AUROCs of noninvasive fibrosis tests for diagnosis of fibrosis stage in NAFLD.

N AUROC F ≥ 2
AUROC F ≥ 3
AUROC F ≥ 4
AUROC NASH & F ≥ 3
n = 71 n = 49 n = 20 n = 35
ELF 181 0.85 (0.80–0.91) 0.90 (0.85–0.95) 0.92 (0.88–0.97) 0.90 (0.85–0.95)
FMV2G 131 0.86 (0.79–0.93) 0.88 (0.80–0.96) 0.95 (0.90–0.99) 0.89 (0.81–0.96)
FMV3G 132 0.84 (0.77–0.92) 0.88 (0.80–0.95) 0.94 (0.89–0.99) 0.88 (0.81–0.95)
FIB-4 186 0.80 (0.74–0.87) 0.82 (0.75–0.90) 0.86 (0.78–0.95) 0.81 (0.73–0.90)
NFS 167 0.78 (0.71–0.85) 0.80 (0.72–0.88) 0.79 (0.67–0.92) 0.79 (0.70–0.89)
LSM 140a 0.85 (0.78–0.91) 0.91 (0.86–0.97) 0.95 (0.91–0.99) 0.87 (0.80–0.94)
LSMPP 122b 0.87 (0.80–0.94) 0.95 (0.90–0.99) 0.98 (0.95–1.00) 0.91 (0.85–0.98)

ELF, enhanced liver fibrosis score; FM, FibroMeter™; FIB-4, fibrosis-4 index; NFS, NAFLD fibrosis score; LSM, liver stiffness measurement.

a

All cases with LSM results (including 18 cases with unreliable results, excluding 10 cases with failed measurements). bLSM per protocol (reliable results only)

b

LSM per protocol (reliable results only).

Table 7.

Accuracy of noninvasive fibrosis tests for diagnosis of F ≥ 3 and NASH. Calculations were based on published cut-offs for ELF, FIB-4, and LSM as well as optimized cut-offs determined in our patient cohort.

Cut-off Sensitivity Specificity PPV NPV DA
ELF score 9.8 78% 85% 53% 95% 84%
FMV2G 0.385a 88% 78% 49% 97% 80%
FMV3G 0.461a 88% 75% 45% 96% 77%
FIB-4 1.30 74% 64% 32% 91% 66%
2.67 54% 93% 63% 90% 85%
LSMPP (kPa) 9.7 90% 73% 39% 97% 75%
11.0a 90% 80% 47% 98% 82%
LSMITD (kPa) 9.7 87% 61% 29% 96% 65%
11.0a 87% 68% 33% 97% 71%
a

Cut-off for F ≥ 3 calculated by Youden index in the present study.

DA, diagnostic accuracy; LSMPP, per protocol (reliable results only); LSMITD, intention-to-diagnose (based on 122 reliable results, 18 unreliable results, and 10 failed measurements coded as false-negative or false-positive).

For diagnosis of significant fibrosis, the published ELF score cut-off of 7.7 was not found useful. Instead an optimized cut-off of 9.1 derived by Youden index within our cohort was calculated (Table 5).37

Table 5.

Accuracy of noninvasive fibrosis tests for diagnosis of F ≥ 2 in NAFLD. Calculations were based on published cut-offs for ELF, FIB-4, and LSM as well as optimized cut-offs determined in our patient cohort.

Cut-off Sensitivity Specificity PPV NPV DA
ELF score 7.7 100% 11% 40% 100% 44%
9.1a 82% 76% 67% 88% 78%
FMV2G 0.309a 80% 80% 72% 86% 80%
FMV3G 0.378a 78% 80% 71% 86% 80%
FIB-4 1.30 69% 72% 60% 79% 71%
2.67 38% 97% 90% 72% 75%
LSMPP (kPa) 8.2 83% 68% 56% 89% 73%
LSMITD (kPa) 8.2 84% 58% 51% 88% 67%
a

Cut-off for F ≥ 2 calculated by Youden index in the present study.

DA, diagnostic accuracy; LSMPP, per protocol (reliable results only); LSMITD, intention-to-diagnose (based on 122 reliable results, 18 unreliable results, and 10 failed measurements coded as false-negative or false-positive).

Vibration-controlled transient elastography

VCTE was attempted in 150 patients and successfully performed in 140 patients (M probe, 88; XL probe, 52). The XL probe was available in 97 of the 150 VCTE examinations (65%). VCTE failed due to technical reasons in 10 patients (7%) and produced unreliable values in 18 patients (12%). Interestingly, the proportion of unreliable/failed VCTE measurements was similar independently of whether the XL probe was available (20%) or not (17%).

In parallel to blood fibrosis tests, LSM increased stepwise with fibrosis stage (Figure 2, Table 2). As expected, diagnostic accuracy for F ≥ 3 was higher in LSM PP (n = 122, AUROC 0.95 (0.90–0.99)) than in unreliable LSM (n = 18, AUROC 0.64 (0.37–0.91)) (p = 0.030 by DeLong test).

For diagnosis of advanced fibrosis, the recently published LSM cut-off of 9.7 kPa was found less useful than an optimized cut-off of 11.0 kPa derived by Youden index within our cohort (Tables 6 and 7).37

Table 6.

Accuracy of noninvasive fibrosis tests for diagnosis of F ≥ 3 in NAFLD. Calculations were based on published cut-offs for ELF, FIB-4, and LSM as well as optimized cut-offs determined in our patient cohort.

Cut-off Sensitivity Specificity PPV NPV DA
ELF score 9.8 72% 90% 70% 90% 85%
FMV2G 0.385a 81% 81% 58% 93% 81%
FMV3G 0.461a 84% 78% 55% 94% 80%
FIB-4 1.30 76% 68% 46% 89% 70%
2.67 49% 96% 80% 84% 83%
LSMPP (kPa) 9.7 92% 77% 52% 97% 80%
11.0a 92% 85% 63% 98% 87%
LSMITD (kPa) 9.7 91% 65% 41% 96% 71%
11.0a 91% 73% 48% 97% 77%
a

Cut-off for F ≥ 3 calculated by Youden index in the present study.

DA, diagnostic accuracy; LSMPP, per protocol (reliable results only); LSMITD, intention-to-diagnose (based on 122 reliable results, 18 unreliable results, and 10 failed measurements coded as false-negative or false-positive).

Comparison of noninvasive fibrosis tests

On ROC analysis, ELF score, FibroMeterV2G/V3G, and LSM showed superior diagnostic accuracy than FIB-4 and NFS for diagnosis of F ≥ 2, F ≥ 3, and the combined endpoint F ≥ 3 plus NASH (Table 3, Figure 3(a) to (c)). On DeLong test, ELF score, FibrometerV2G/V3G, and LSM (PP) outperformed NFS for diagnosis of both F ≥ 3 and F ≥ 3 & NASH (Table 4). Likewise, ELF score, FibrometerV2G, and LSM (PP) outperformed NFS for diagnosis of F ≥ 2 (Table 4).

Figure 3.

Figure 3.

Receiver operating characteristic (ROC) curves of six noninvasive tests for diagnosis of CRN fibrosis stage: (a) significant fibrosis (F ≥ 2); (b) advanced fibrosis (F ≥ 3); (c) combined endpoint F ≥ 3 plus NASH. Areas under the ROC curves (AUROCs) are shown in Table 3.

ELF score, enhanced liver fibrosis score; FIB-4, fibrosis-4 index; NFS, NAFLD fibrosis score; LSM, liver stiffness measurement.

Table 4.

AUROC comparisons of noninvasive fibrosis tests in NAFLD.

N AUROC
p-valuea
AUROC
p-valuea
AUROC
p-valuea
F ≥ 2 vs. NFS F ≥ 3 vs. NFS F ≥ 3 & NASH vs. NFS
ELF 181 0.85 0.036 0.90 0.003 0.90 0.010
FMV2G 131 0.86 0.025 0.88 0.004 0.89 0.020
FMV3G 132 0.84 0.058 0.88 0.004 0.88 0.031
FIB-4 186 0.80 0.308 0.82 0.179 0.82 0.360
NFS 167 0.78 0.79 0.79
LSM 140 0.85 0.051 0.91 0.017 0.87 0.142
LSMPP 122 0.87 0.008 0.95 0.008 0.91 0.027
a

AUROCs of ELF, FMV2G, FMV3G, LSM, and LSMPP were compared with that of NFS according to DeLong et al.36

ELF, enhanced liver fibrosis score; FM, FibroMeter™; FIB-4, fibrosis-4 index; NFS, NAFLD fibrosis score; LSM, liver stiffness measurement (all cases with LSM results); LSMPP, LSM per protocol (reliable results only).

For diagnosis of significant fibrosis, best results with ELF score were obtained at an optimized cut-off of 9.1 whereas the cut-off of 7.7 recommended by the manufacturer was not found useful (Table 5). Similar diagnostic accuracies could be demonstrated for the published LSM cut-off of 8.2 kPa and the calculated cut-offs for FibroMeterV2G/V3G of 0.309/0.378 (Table 5). For diagnosis of advanced fibrosis, using the published cut-offs of 9.8 for ELF score and of 9.7 kPa for LSM,12,24 and the calculated cut-offs for FibroMeterV2G/V3G of 0.385/0.461, all showed moderate to good PPV and excellent NPV (≥90%) (Table 6). For LSM, diagnosis of advanced fibrosis was slightly improved using an optimized cut-off of 11.0 kPa obtained by Youden index (Table 6). When the combined endpoint F ≥ 3 plus NASH was analyzed using the same cut-offs as for F ≥ 3, PPVs were somewhat lower while NPVs remained excellent (Table 7).

Sequential analysis of noninvasive fibrosis tests

Aiming to optimize cost-effectiveness of noninvasive fibrosis testing in NAFLD, we designed a post hoc sequential strategy, first testing the inexpensive (non-commercial) FIB-4 index followed by the costlier (proprietary) ELF test in cases with FIB-4 values ≥1.30 only. However, diagnostic accuracy of this sequential approach for F ≥ 3 (sensitivity 57%, specificity 94%, PPV 77%, NPV 86%, DA 84%) was not better than that of FIB-4 alone at the ≥2.67 cut-off value (Table 6).

Effect of age, BMI, and diabetes/IFG on diagnostic accuracy of noninvasive fibrosis tests

As expected, age per se was associated with advanced fibrosis (AUROC 0.77 (0.69–0.84)). However, when our cohort was split at an age of <60 years (n = 143) vs. ≥60 years (n = 43), no major differences were evident for AUROCs of noninvasive fibrosis tests for F ≥ 3: ELF, 0.87 (0.79–0.95) vs. 0.92 (0.81–1.00), p = 0.517; FIB-4, 0.76 (0.65–0.87) vs. 0.85 (0.73–0.97), p = 0.315; LSM, 0.88 (0.80–0.96) vs. 0.96 (0.89–1.00), p = 0.151.

When the cohort was split by BMI < 30 (n = 86) vs. ≥30 (n = 100), blood fibrosis tests showed similar AUROCs for diagnosis of F ≥ 3: ELF, 0.92 (0.87–0.98) vs. 0.89 (0.81–0.97), p = 0.469; FIB-4, 0.82 (0.73–0.92) vs. 0.82 (0.72–0.92), p = 0.959. In contrast, accuracy of LSM for F ≥ 3 decreased with increasing body mass: BMI < 30, AUROC 0.98 (0.96–1.00) vs. BMI ≥ 30, AUROC 0.84 (0.74–0.94), p = 0.005.

Similar performance of all noninvasive fibrosis tests was observed when the cohort was split by absence vs. presence of diabetes/IFG, respectively (data not shown).

Discussion

In this study we demonstrate superior diagnostic accuracy of ELF score, FibrometerV2G/V3G, and LSM (using PP analysis) compared to the simple fibrosis tests, FIB-4 and NFS, in a large cohort of adult NAFLD patients. As expected, LSM analyzed PP showed higher diagnostic accuracies than on ITD analysis. Of note, accuracy of FIB-4 was numerically higher than that of NFS in all analyses and thus proved very useful given its simple calculation.

Comparisons of noninvasive fibrosis tests in NAFLD patients have shown variable results. Guha et al. reported only marginally superior accuracy of ELF score compared to NFS for the diagnosis of F ≥ 3 (AUROC 0.93 vs. 0.89).8 On the other hand, consistent with the results of our study, diagnostic accuracy of VCTE was found clearly superior to NFS 22 or to FIB-4.16 We recently reported an AUROC of 0.876 by ELF test (n = 162) and of 0.935 by VCTE (n = 75) for the diagnosis of F ≥ 3 in various cohorts of NAFLD patients.38 However, this study did not provide direct comparison of ELF and VCTE in the same patients, did not consider intent-to-diagnose analysis for VCTE and did not account for the presence or absence of NASH. Karlas et al. compared VCTE and ELF test in a small cohort of morbidly obese patients (n = 41, median BMI 47) prior to bariatric surgery with intraoperative liver biopsy and obtained valid LSM data in only 50% of the patients while ELF test was feasible in all patients.35

Determination of advanced fibrosis in NAFLD is crucial for prognosis estimation and treatment need in general, and is now especially useful to determine eligibility of patients for clinical trials with novel anti-inflammatory/antifibrotic drugs focusing on patients with fibrosis stage F ≥ 3 and NASH. Furthermore, a diagnosis of advanced fibrosis/cirrhosis establishes the need for HCC surveillance. Our patient cohort represents the spectrum of NAFLD typically admitted to referral centers, with a relatively low prevalence of advanced fibrosis (F ≥ 3) (26%). Hence any of the fibrosis tests studied show good NPV at the selected cut-offs, allowing to safely spare liver biopsy, whereas patients with test results above the respective cut-off should undergo liver biopsy to determine whether NASH with advanced fibrosis is truly present.

Among the tests investigated in the present study, FIB-4 tended to show higher diagnostic accuracy than NFS and seems therefore preferable, given its simple calculation which may be easily implemented into automated lab reports. We confirmed the previously published low cut-off of 1.30 for ruling out advanced fibrosis, while the published high cut-off for NAFLD of 2.67 proved good accuracy to rule in advanced fibrosis (PPV 80%).31 However, the diagnostic utility of FIB-4 is limited considering the proportion of patients who lie within the “grey zone” of 1.30–2.67 (27% of the patients in the present study). Likewise, the chosen single cut-offs for ELF score (9.8), FibroMeterV2G/V3G (0.385/0.461), and LSM (9.7 or 11.0 kPa) allow for safe exclusion of advanced fibrosis while they provide moderate to good PPVs. Of note, the published LSM cut-offs for F ≥ 3 in NAFLD are lower than the 15.0 kPa cut-off recently reported for diagnosis of advanced fibrosis in alcoholic liver disease,39 which may be explained by different fibrosis patterns and/or spectrum bias.40

Considering VCTE, it should be kept in mind that this method is not always feasible, with unreliable LSM values or failed measurements in approximately 20% of our study patients, irrespective of the availability of the XL probe. Other studies investigating VCTE in NAFLD using the M probe have reported similar failure rates of VCTE.41,42 Studies comparing values obtained by both probes demonstrate lower LSM values and suggest lower cut-offs for the XL probe.41 In addition, recent data indicate that LSM values should be corrected for simultaneously measured controlled attenuation parameter (CAP).26 Of note, published LSM cut-off values for F ≥ 3 in NAFLD vary between 7.9 and 12.5 kPa for the M probe and between 5.7 and 9.3 kPa for the XL probe.21,22,41,42

For FIB-4, significant effects of age on its diagnostic accuracy have been reported. Boursier et al. noted a loss of specificity for FIB-4 in patients above age 60,33 while McPherson et al. proposed a different FIB-4 cut-off of 2.00 for patients aged >65 years.34 We could not clearly reproduce these observations in our cohort probably due to the limited number of patients in the respective subgroups defined by age and fibrosis stage.

Strengths of our study include (a) evaluation of several commonly used noninvasive fibrosis tests in a large cohort of unselected NAFLD patients in a clinical real life setting; (b) direct comparison of ELF score, FibroMeterV2G/V3G, FIB-4, and LSM in the same patients; (c) definition of liver histology by two experienced specialized hepatopathologists; (d) evaluation of various endpoints of high clinical relevance (F ≥ 2, F ≥ 3, F ≥ 3 and NASH); (e) providing optimized cut-offs for ELF, FibroMeterV2G/V3G, and LSM. Limitations of our study include the lack of an internal validation of our findings, the shortage of data on some fibrosis tests evaluated (VCTE, FibroMeterV2G/V3G), the time interval between VCTE and liver biopsy, and the lack of availability of XL probes in the early phase of the study. Nevertheless, diagnostic accuracy of LSM was excellent and superior to that of the simple fibrosis tests on per-protocol analysis.

In conclusion, fibrosis stage in NAFLD is best assessed by ELF test, FibroMeterV2G/V3G, and/or VCTE. When VCTE produces reliable results (as in 81% in the present study), it shows superior diagnostic accuracy. Accuracy of VCTE decreases with increasing BMI while blood fibrosis tests are not affected by BMI. Among the blood fibrosis tests studied, ELF test and FibroMeterV2G show the best performance. In settings where neither VCTE nor proprietary blood fibrosis tests are available, FIB-4 is a reasonably accurate and cost-effective alternative to assess advanced fibrosis in NAFLD. Further research is needed (a) to noninvasively delineate presence of NASH from fibrosis stage and (b) to evaluate noninvasive markers as treatment endpoints in NAFLD.

Acknowledgments

The authors wish to thank Prof. Paul Calès for calculation of FibroMeterV2G/V3G, Ms. Andrea Streit for excellent technical assistance, and Dr. Tatjana Stojakovic and the team of the Endo-Lab-Platform for analytical assistance.

Declaration of conflicting interests

R.M. received speaker honoraria from Siemens.

Funding

This work was in part supported by BioPersMed (COMET K-project 825329) funded by the Austrian Research Promotion Agency (FFG).

Ethics approval

This study was approved by the Ethics Committee of the Medical University of Graz (EC 24-224 ex 11/12) and the Medical University of Vienna (EC #747/2011) and was performed in accordance with the 1975 Declaration of Helsinki.

Informed consent

Written informed consent was obtained from all study participants.

References

  • 1.Singh S, Allen AM, Wang Z, et al. Fibrosis progression in nonalcoholic fatty liver vs nonalcoholic steatohepatitis: a systematic review and meta-analysis of paired-biopsy studies. Clin Gastroenterol Hepatol 2015; 13: 643–654. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Angulo P, Kleiner DE, Dam-Larsen S, et al. Liver fibrosis, but no other histologic features, is associated with long-term outcomes of patients with nonalcoholic fatty liver disease. Gastroenterology 2015; 149: 389–397. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Ekstedt M, Hagstrom H, Nasr P, et al. Fibrosis stage is the strongest predictor for disease-specific mortality in NAFLD after up to 33 years of follow-up. Hepatology 2015; 61: 1547–1554. [DOI] [PubMed] [Google Scholar]
  • 4.Hagstrom H, Nasr P, Ekstedt M, et al. SAF score and mortality in NAFLD after up to 41 years of follow-up. Scand J Gastroenterol 2017; 52: 87–91. [DOI] [PubMed] [Google Scholar]
  • 5.Kwok R, Tse YK, Wong GL, et al. Systematic review with meta-analysis: non-invasive assessment of non-alcoholic fatty liver disease–the role of transient elastography and plasma cytokeratin-18 fragments. Aliment Pharmacol Ther 2014; 39: 254–269. [DOI] [PubMed] [Google Scholar]
  • 6.Younossi ZM, Loomba R, Anstee QM, et al. Diagnostic modalities for nonalcoholic fatty liver disease, nonalcoholic steatohepatitis, and associated fibrosis. Hepatology 2018; 68: 349–360. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Vilar-Gomez E, Chalasani N. Non-invasive assessment of non-alcoholic fatty liver disease: clinical prediction rules and blood-based biomarkers. J Hepatol 2018; 68: 305–315. [DOI] [PubMed] [Google Scholar]
  • 8.Guha IN, Parkes J, Roderick P, et al. Noninvasive markers of fibrosis in nonalcoholic fatty liver disease: validating the European Liver Fibrosis Panel and exploring simple markers. Hepatology 2008; 47: 455–460. [DOI] [PubMed] [Google Scholar]
  • 9.Miele L, De Michele T, Marrone G, et al. Enhanced liver fibrosis test as a reliable tool for assessing fibrosis in nonalcoholic fatty liver disease in a clinical setting. Int J Biol Markers 2017; 32: e397–e402. [DOI] [PubMed] [Google Scholar]
  • 10.Lopez IC, Aroca FG, Bernal MDF, et al. Utility of the ELF test for detecting steatohepatitis in morbid obese patients with suspicion of nonalcoholic fatty liver disease. Obes Surg 2017; 27: 2347–2353. [DOI] [PubMed] [Google Scholar]
  • 11.Nobili V, Parkes J, Bottazzo G, et al. Performance of ELF serum markers in predicting fibrosis stage in pediatric non-alcoholic fatty liver disease. Gastroenterology 2009; 136: 160–167. [DOI] [PubMed] [Google Scholar]
  • 12.Lichtinghagen R, Pietsch D, Bantel H, et al. The Enhanced Liver Fibrosis (ELF) score: normal values, influence factors and proposed cut-off values. J Hepatol 2013; 59: 236–242. [DOI] [PubMed] [Google Scholar]
  • 13.Fagan KJ, Pretorius CJ, Horsfall LU, et al. ELF score >/=9.8 indicates advanced hepatic fibrosis and is influenced by age, steatosis and histological activity. Liver Int 2015; 35: 1673–1681. [DOI] [PubMed] [Google Scholar]
  • 14.Glen J, Floros L, Day C, et al. Non-alcoholic fatty liver disease (NAFLD): summary of NICE guidance. BMJ 2016; 354: i4428–i4428. [DOI] [PubMed] [Google Scholar]
  • 15.Leroy V, Halfon P, Bacq Y, et al. Diagnostic accuracy, reproducibility and robustness of fibrosis blood tests in chronic hepatitis C: a meta-analysis with individual data. Clin Biochem 2008; 41: 1368–1376. [DOI] [PubMed] [Google Scholar]
  • 16.Boursier J, Vergniol J, Guillet A, et al. Diagnostic accuracy and prognostic significance of blood fibrosis tests and liver stiffness measurement by FibroScan in non-alcoholic fatty liver disease. J Hepatol 2016; 65: 570–578. [DOI] [PubMed] [Google Scholar]
  • 17.Cales P, Boursier J, Bertrais S, et al. Optimization and robustness of blood tests for liver fibrosis and cirrhosis. Clin Biochem 2010; 43: 1315–1322. [DOI] [PubMed] [Google Scholar]
  • 18.Imbert-Bismut F, Ratziu V, Pieroni L, et al. Biochemical markers of liver fibrosis in patients with hepatitis C virus infection: a prospective study. Lancet 2001; 357: 1069–1075. [DOI] [PubMed] [Google Scholar]
  • 19.Angulo P, Hui JM, Marchesini G, et al. The NAFLD fibrosis score: a noninvasive system that identifies liver fibrosis in patients with NAFLD. Hepatology 2007; 45: 846–854. [DOI] [PubMed] [Google Scholar]
  • 20.Sterling RK, Lissen E, Clumeck N, et al. Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV coinfection. Hepatology 2006; 43: 1317–1325. [DOI] [PubMed] [Google Scholar]
  • 21.Wong VW, Vergniol J, Wong GL, et al. Diagnosis of fibrosis and cirrhosis using liver stiffness measurement in nonalcoholic fatty liver disease. Hepatology 2010; 51: 454–462. [DOI] [PubMed] [Google Scholar]
  • 22.Tapper EB, Challies T, Nasser I, et al. The performance of vibration controlled transient elastography in a US cohort of patients with nonalcoholic fatty liver disease. Am J Gastroenterol 2016; 111: 677–684. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Siddiqui MS, Vuppalanchi R, Van Natta ML, et al. Vibration-controlled transient elastography to assess fibrosis and steatosis in patients with nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol 2019; 17: 156–163. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Eddowes PJ, Sasso M, Allison M, et al. Accuracy of FibroScan controlled attenuation parameter and liver stiffness measurement in assessing steatosis and fibrosis in patients with nonalcoholic fatty liver disease. Gastroenterology 2019; 156: 1717–1730. [DOI] [PubMed] [Google Scholar]
  • 25.Petta S, Maida M, Macaluso FS, et al. The severity of steatosis influences liver stiffness measurement in patients with nonalcoholic fatty liver disease. Hepatology 2015; 62: 1101–1110. [DOI] [PubMed] [Google Scholar]
  • 26.Petta S, Wong VW, Camma C, et al. Improved noninvasive prediction of liver fibrosis by liver stiffness measurement in patients with nonalcoholic fatty liver disease accounting for controlled attenuation parameter values. Hepatology 2017; 65: 1145–1155. [DOI] [PubMed] [Google Scholar]
  • 27.Petta S, Di Marco V, Camma C, et al. Reliability of liver stiffness measurement in non-alcoholic fatty liver disease: the effects of body mass index. Aliment Pharmacol Ther 2011; 33: 1350–1360. [DOI] [PubMed] [Google Scholar]
  • 28.Boursier J, de Ledinghen V, Poynard T, et al. An extension of STARD statements for reporting diagnostic accuracy studies on liver fibrosis tests: the Liver-FibroSTARD standards. J Hepatol 2015; 62: 807–815. [DOI] [PubMed] [Google Scholar]
  • 29.Sanyal AJ, Brunt EM, Kleiner DE, et al. Endpoints and clinical trial design for nonalcoholic steatohepatitis. Hepatology 2011; 54: 344–353. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Kleiner DE, Brunt EM, Van Natta M, et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology 2005; 41: 1313–1321. [DOI] [PubMed] [Google Scholar]
  • 31.Shah AG, Lydecker A, Murray K, et al. Comparison of noninvasive markers of fibrosis in patients with nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol 2009; 7: 1104–1112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.McPherson S, Stewart SF, Henderson E, et al. Simple non-invasive fibrosis scoring systems can reliably exclude advanced fibrosis in patients with non-alcoholic fatty liver disease. Gut 2010; 59: 1265–1269. [DOI] [PubMed] [Google Scholar]
  • 33.Boursier J, de Ledinghen V, Leroy V, et al. A stepwise algorithm using an at-a-glance first-line test for the non-invasive diagnosis of advanced liver fibrosis and cirrhosis. J Hepatol 2017; 66: 1158–1165. [DOI] [PubMed] [Google Scholar]
  • 34.McPherson S, Hardy T, Dufour JF, et al. Age as a Confounding Factor for the Accurate Non-Invasive Diagnosis of Advanced NAFLD Fibrosis. Am J Gastroenterol 2017; 112: 740–751. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Karlas T, Dietrich A, Peter V, et al. Evaluation of transient elastography, acoustic radiation force impulse imaging (ARFI), and Enhanced Liver Function (ELF) score for detection of fibrosis in morbidly obese patients. PLoS One 2015; 10: e0141649–e0141649. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 1988; 44: 837–845. [PubMed] [Google Scholar]
  • 37.Youden WJ. Index for rating diagnostic tests. Cancer 1950; 3: 32–35. [DOI] [PubMed] [Google Scholar]
  • 38.Staufer K, Dengler M, Huber H, et al. The non-invasive serum biomarker soluble Axl accurately detects advanced liver fibrosis and cirrhosis. Cell Death Dis 2017; 8: e3135–e3135. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Thiele M, Madsen BS, Hansen JF, et al. Accuracy of the enhanced liver fibrosis test vs FibroTest, elastography, and indirect markers in detection of advanced fibrosis in patients with alcoholic liver disease. Gastroenterology 2018; 154: 1369–1379. [DOI] [PubMed] [Google Scholar]
  • 40.European Association for Study of the Liver. EASL-ALEH clinical practice guidelines: non-invasive tests for evaluation of liver disease severity and prognosis. J Hepatol 2015; 63: 237–264. [DOI] [PubMed] [Google Scholar]
  • 41.De Ledinghen V, Wong VW, Vergniol J, et al. Diagnosis of liver fibrosis and cirrhosis using liver stiffness measurement: comparison between M and XL probe of FibroScan(R). J Hepatol 2012; 56: 833–839. [DOI] [PubMed] [Google Scholar]
  • 42.Cassinotto C, Boursier J, de Ledinghen V, et al. Liver stiffness in nonalcoholic fatty liver disease: A comparison of supersonic shear imaging, FibroScan, and ARFI with liver biopsy. Hepatology 2016; 63: 1817–1827. [DOI] [PubMed] [Google Scholar]

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