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Research Article

JHEPAT 3490 No. of Pages 11

29 November 2010

Elastography for the diagnosis of severity of fibrosis in chronicliver disease: A meta-analysis of diagnostic accuracy

E.A. Tsochatzis1, K.S. Gurusamy2, S. Ntaoula1, E. Cholongitas1, B.R. Davidson2, A.K. Burroughs1,⇑

1The Royal Free S heila Sherlock Liver Centre and Division of Surgery, Royal Free Hospital, London NW3 2QG, UK; 2University Department ofSurgery, Royal Free Hospital, London NW3 2QG, UK

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Background & Aims: Transient elastography is a non-invasive ing of liver fibrosis [2]. However, it is invasive and can lead to 48

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method of assessing hepatic fibrosis developed as an alternativeto liver biopsy. We assessed the performance of elastographyfor diagnosis of fibrosis using meta-analysis.Methods: MEDLINE, EMBASE, SCI, Cochrane Library, conferenceabstracts books, and article references were searched. Weincluded studies using biopsy as a reference standard, with thedata necessary to calculate the true and false positive, true andfalse negative diagnostic results of elastography for a fibrosisstage, and with a 3-month maximum interval between tests.Quality of studies was rated with the QUADAS tool.Results: We identified 40 eligible studies. Summary sensitivityand specificity was 0.79 (95% CI 0.74–0.82) and 0.78 (95% CI0.72–0.83) for F2 stage and 0.83 (95% CI 0.79–0.86) and 0.89(95% CI 0.87–0.91) for cirrhosis. After an elastography result at/over the threshold value for F2 or cirrhosis (‘‘positive’’ result),the corresponding post-test probability for their presence (ifpre-test probability was 50%) was 78%, and 88% respectively,while if values were below these thresholds (‘‘negative’’ result)the post-test probability was 21% and 16%, respectively. No opti-mal stiffness cut-offs for individual fibrosis stages were validatedin independent cohorts and cut-offs had a wide range and overlapwithin and between stages.Conclusion: Elastography theoretically has good sensitivity andspecificity for cirrhosis (and less for lesser degrees of fibrosis);however, it should be cautiously applied to everyday clinicalpractice because there is no validation of the stiffness cut-offsfor the various stages. Such validation is required before elastog-raphy is considered sufficiently accurate for non-invasive stagingof fibrosis.� 2010 European Association for the Study of the Liver. Publishedby Elsevier B.V. All rights reserved.

Liver fibrosis represents the final common outcome of chronicliver injury and is often progressive, eventually evolving into cir-rhosis [1]. Cirrhosis is the severest form of fibrosis with the worstclinical outcomes.

Currently, histological examination of a liver biopsy specimenis the reference standard for the diagnosis, staging, and monitor-

Journal of Hepatology 20

Received 11 March 2010; received in revised form 16 July 2010; accepted 20 July 2010⇑ Corresponding author. Address: The Royal Free Sheila Sherlock Liver Centre andDivision of Surgery, Royal Free Hospital, Pond Street, Hampstead, London NW32QG, UK. Tel.: +44 2074726229; fax: +44 2074726226.E-mail address: Andrew.Burroughs@royalfree.nhs.uk (A.K. Burroughs).

Please cite this article in press as: Tsochatzis EA et al. Elastography for the diadiagnostic accuracy. J Hepatol (2010), doi:10.1016/j.jhep.2010.07.033

fatal bleeding [2].Transient elastography is a non-invasive method of quantify-

ing fibrosis developed as an alternative to liver biopsy. Ultra-sound elastography analyses ultrasound frequency waves whichare related to the elasticity (deforming capacity) of the liver. Itis simple, highly reproducible and can be completed in 10 minin an outpatient setting with no significant expertise [3]. Mag-netic resonance elastography involves measuring the elasticityof the liver tissues using complex algorithms [4]. An increasingnumber of studies have evaluated the accuracy of elastographyin the staging of fibrosis and compared it to liver biopsy.

In the present study, we used meta-analysis to assess the per-formance of elastography in the diagnosis of severity of liverfibrosis using liver biopsy as the reference standard.

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Methods

Criteria for the selection of studies

We included full papers and abstracts, without language restrictions that (1) eval-uated elastography in the diagnosis of severity of liver fibrosis or monitoringthereof, using liver biopsy as the reference standard, and (2) reported on datanecessary to calculate the true positive, false positive, true negative and false neg-ative diagnostic results of elastography for the diagnosis of a fibrosis stage basedon a defined cut-off point for liver stiffness. If such data were unavailable, the cor-responding author was contacted via e-mail to provide them; if he/she failed toreply, the study was excluded. We also excluded studies reporting on <10patients, or in which the maximum time interval between performing elastogra-phy and liver biopsy was >3 months.

Literature search

MEDLINE (Pubmed), Embase, Science Citation Index expanded and The CochraneHepato-Biliary Group Controlled Trials Register, the Cochrane Central Register ofControlled Trials in The Cochrane Library were searched until May 2009. Confer-ence abstracts from the American Association for the Study of Liver Diseases(AASLD) and the European Association for the Study of the Liver (EASL) weremanually searched from 2007 to 2009. Reference lists of identified studies andreviews were also hand-searched. Search terms for each database are shown inthe Appendix.

Study selection and data extraction

The identified studies were screened independently by E.T. and S.N., and thenverified reciprocally. The data were extracted independently by E.T. and S.N. usinga predefined form. Any differences in study selection or data extraction were

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gnosis of severity of fibrosis in chronic liver disease: A meta-analysis of

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1289 studies identified

398 duplicates618 excluded by title and/or abstract

306 references retrieved formore detailed evaluation

94 no comparison with liver biopsy41 published in full paper42 long interval between tests80 not enough data on sensitivity-specificity5 no original data2 less than 10 patients2 no elastography performed3 did not use untrasound elastography

40 studies for analysis

Fig. 1. Flow diagram of search results and study selection.

Research Article

JHEPAT 3490 No. of Pages 11

29 November 2010

resolved by K.S.G. and A.K.B. The following data were extracted: country ofstudy’s origin, year of publication, patient number, patients’ epidemiologicaland laboratory characteristics, aetiology of liver disease, technical failures inundertaking liver biopsy or elastography, liver stiffness cut-offs for stages offibrosis, histological score used, true positive, false positive, true negative, andfalse negative elastography results and methodological quality.

Methodological quality

The quality of the studies was assessed independently by E.T. and S.N. using theQuality Assessment of Studies of Diagnostic Accuracy included in SystematicReview (QUADAS) assessment tool which contains 14 questions [5]. We alsoassessed if the index test (elastography) was performed according to the manu-facturer’s instructions i.e. at least ten successful measurements with a successrate of at least 60% and was thus likely to correctly classify the target condition.Liver biopsy was rated as an acceptable reference standard if the specimen wasP15 mm long and included P6 portal tracts [2].

Statistical analysis and data synthesis

Data were combined using the hierarchical summary receiver operator character-istics (HSROC) method and the bivariate normal random-effects analysis of sen-sitivity and specificity within the METANDI module [6,7] in the STATA 10statistical software (Statacorp LP, Texas, USA). METANDI performs meta-analysisof diagnostic test accuracy studies in which both the index test under study andthe reference test (gold standard) are dichotomous. It fits a two-level mixed logis-tic regression model, with independent binomial distributions for the true posi-tives and true negatives within each study, and a bivariate normal model forthe logit transforms of sensitivity and specificity between studies [6]. Currentlythese methods are considered more reliable than the Littenberg and Mosesmeta-analytical method of diagnostic accuracies [8]. The Metandiplot, which usesa HSROC plot, was used for graphical representation.

We evaluated pre-test probabilities of 25%, 50%, and 75% versus correspond-ing post-test probabilities following a ‘‘positive’’ or ‘‘negative’’ elastography resultbased on the summary sensitivity and specificity. ‘‘Positive’’ elastography resultswere defined as all results above the optimal liver stiffness threshold for a givenfibrosis stage, given in each individual study, while ‘‘negative’’ test results wereall results below the same threshold.

Exploration of heterogeneity, subgroup and sensitivity analysis

We planned to perform the following subgroup analyses: high versus low meth-odological quality, different stages of fibrosis (scoring systems were converted tocomparable stages in METAVIR [9]), aetiological diagnoses, different stiffness cut-offs for a specific stage of fibrosis, initial diagnosis versus monitoring of fibrosis,different specific treatments such as interferon therapy which may alter the scor-ing of liver biopsy, different ranges of body mass index (BMI) (<18.5, 18.5–24.9,25–29.9, and P30), different ranges of transaminases (normal range, betweennormal, and P3 or >3 times the upper limit of normal) and country of the study’sorigin.

We computed the diagnostic odds ratio (DOR) as a single indicator of elastog-raphy performance in each study and disease stage [10]. We used the test ofinteraction to assess if the diagnostic odds ratio (DOR) was statistically differentbetween subgroups by computing the DOR ratio and the 95% confidence intervalsof the DOR ratio between the subgroups [11].

We explored heterogeneity in each fibrosis stage by computing Higgin’s I2

and v2 tests for heterogeneity using the generic inverse variance method ofmeta-analysis of DOR [12]. We considered an I2 value of more than 30% and av2 p value of 0.10 to indicate statistically significant heterogeneity. We furtherexplored heterogeneity by using meta-regression of logarithmically transformedDOR (ln DOR) for continuous variables that could potentially cause heterogeneityand used test of interaction for binary variables in each fibrosis stage. The numberof studies in each fibrosis stage was not sufficient to perform a multiple meta-regression analysis.

We performed sensitivity analyses by excluding studies of low methodolog-ical quality and studies solely published as abstracts from the main analysis.

Publication bias

We performed a funnel plot; visual assessment was used to assess the bias, aswell as the methods by Deeks et al. [13].

Please cite this article in press as: Tsochatzis EA et al. Elastography for the diadiagnostic accuracy. J Hepatol (2010), doi:10.1016/j.jhep.2010.07.033

2 Journal of Hepatology 201

Results

Description of studies

We identified 1289 references. The reference flow is shown inFig. 1. The inclusion criteria were fulfilled in 43 studies (35 fullpapers, eight abstracts) [3,4,14–54]. From these, three studieswere excluded, as they evaluated magnetic resonance elastogra-phy [4], real time elastography [27] or used a probe especiallybuilt for children [23]. Important characteristics of the includedstudies are shown in Table 1. The risk of bias of these studies isdetailed in Appendix Figure 1.

Transient elastography for the detection of fibrosis METAVIR stages1–4

The diagnostic accuracy of transient elastography for cirrhosis(METAVIR F = 4) was evaluated in 30 studies: the summary sen-sitivity was 0.83 (95% CI 0.79–0.86) and specificity was 0.89(95% CI 0.87–0.91). The mean optimal cut-off point of liver stiff-ness was 15 ± 4.1 kPa (median 14.5), however, values rangedfrom 9.0–26.5 kPa.

The diagnostic accuracy for F = 3 was evaluated in 24 studies,with summary sensitivity 0.82 (95% CI 0.78–0.86) and summarysensitivity 0.86 (0.82–0.89). The mean optimal cut-off was10.2 ± 1.9 kPa (median 9.6), with a range of 7.3–15.4 kPa.

The detection of F = 2 was evaluated in 31 studies, with sum-mary sensitivity 0.79 (95% CI 0.74–0.82) and specificity 0.78 (95%CI 0.72–0.83). The mean optimal cut-off was 7.3 ± 1.4 kPa (med-ian 7.2) with a range of 4.0–10.1.

Finally, the detection of F = 1 was evaluated in 10 studies withsummary sensitivity 0.78 (95% CI 0.731–0.830) and summaryspecificity 0.83 (95% CI 0.72–0.0.90). The mean optimal cut-offwas 6.5 ± 1.1 kPa (median 6.0), with a range of 4.9–8.8 kPa.

The above is summarised in Table 2, while the correspondingHSROC plots are shown in Fig. 2.

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Table 1. Main characteristics of the studies included in the meta-analysis.

Alric [14]Arena [15]Carrion [16]Castera [17], 2005Castera [18], 2009Chan [19]Chang [20]Corradi [21]de Lendighen [22]Degos [24]Foucher [25]Fraquelli [3]Harada [26]Kettaneh [28]Kim 2007 [30]Kim 2007 [30]Kim 2009 [29]Kim 2009a [31]Lewin [32]Lupsor [33]Marcellin [34]Masuzaki [35]Mueller [36]Nahon [37]Nguyen-Khac [38]Nitta [39]Nudo [40]Ogawa [41]Petta [42]Reiberger [43]Rigamonti [44]Schlosser [45]Sporea 2008 [47]Sporea 2008a [46]Tanwandee [48]Tatsumi [54]Verveer [49]Verveer [49]Wang [50]Wong 2008 [52]Wong 2009 [51]Yoneda [53]

CHC:26 CHB:12CHCPost-transplant CHCCHCCHCCHBVariousPost-transplant CHCHCV-HIV coinfectionCHCVariousVariousCHCCHCVariousPotential living donorsCHBCHBCHCCHCCHBCHCALDALDALDCHCVariousCHC: 83CHB: 20CHCVariousPost-transplant CHCVariousCHCCHCCHBVariousCHBCHCCHC: 214CHB:88NAFLD

381611691933101861205677913354200609354771130112543242023941031741051651021031561519410319993104125687336466167102

50.0250.6605151.74549.55842.4-50-63.148.445.529.142.545.456.448.440.168.2-54.452.65750.5-52.54658-49.847.74457--50.84943.751.8

24.723.5252525.1242424.922.4-24.524.823.924.523.722.525.323.524.726.524.522.9-25.627.7-

---24.8--25.823.6---24.426.62426.6

METAVIRMETAVIRScheuerMETAVIRMETAVIRMETAVIRMETAVIRMETAVIRMETAVIR

METAVIRMETAVIRMETAVIRMETAVIRMETAVIRMETAVIRMETAVIRMETAVIRMETAVIRMETAVIRMETAVIRMETAVIRKleinerBruntMETAVIRMETAVIRScheuerMETAVIRScheuerMETAVIRIshakMETAVIRMETAVIRMETAVIRMETAVIRDesmetMETAVIRMETAVIRMETAVIRKleinerMETAVIRBrunt

0.700.830.900.67--0.83-0.930.900.640.720.900.630.790.87-0.960.870.760.70---0.810.810.710.810.610.710.830.750.60-0.7-0.860.590.70--0.88

0.750.820.810.89--0.85-0.180.310.850.840.910.830.870.52-0.750.740.830.82---0.920.800.790.770.6410.700.670.93-0.79-0.720.760.83--0.74

7.110.88.57.1--9.0-4.55.17.27.99.9-7.354.0--8.77.47.2---7.87.17.0-6.57.26.37.256.8-6.9-7.07.09.5--6.7

Study Patients, N

Liver disease Age BMI

Sensitivity Specificity

F>2 F = 4HistologicalSystem

Stiffness cut-off

-0.910.95-0.830.970.920.940.880.710.77-10.840.75-0.760.83-0.870.930.790.960.830.850.620.500.780.830.900.93----0.880.33-0.79-0.691

-0.940.91-0.950.750.820.890.960.900.97-0.980.850.79-0.810.93-0.900.870.810.800.820.840.910.960.820.850.790.93----0.830.97-0.85-0.940.97

-14.814.5-12.59.016.010.114.513.417.6-26.5-15.1-10.1--11.811.015.912.522.719.516.920.9-14.512.112.0----18.813.0-12.0-13.417.5

Sensitivity Specificity Stiffness cut-off

Abbreviations: BMI: body mass index, CHC: chronic hepatitis C, CHB: chronic hepatitis B, ALD: alcoholic liver disease, NAFLD: non-alcoholic fatty liver disease.

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JHEPAT 3490 No. of Pages 11

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Transient elastography and aetiology of liver disease

The aetiology of liver disease was documented in 17 studies eval-uating patients with chronic hepatitis C (CHC), 10 studies withchronic hepatitis B (CHB), 3 studies with alcoholic liver disease,two studies with non-alcoholic fatty liver disease and one studywith CHC/HIV co-infection. Further analysis was possible forCHC and CHB, as P4 studies are needed for a metanalysis usingMetandi.

Please cite this article in press as: Tsochatzis EA et al. Elastography for the diadiagnostic accuracy. J Hepatol (2010), doi:10.1016/j.jhep.2010.07.033

Journal of Hepatology 201

The diagnostic accuracy of elastography did not significantlydiffer between CHC and CHB in any METAVIR stage. The liverstiffness cut-offs had wider ranges and were higher for a givenfibrosis stage in CHC: they were 7.6 (range 5.1–10.1), 10.9 (8.0–15.4), and 15.3 (11.9–26.5) kPa for F = 2, 3, and 4, respectively,in CHC, and 7.0 (range 6.9–7.2), 8.2 (7.3–9.0), and 11.3 (9.0–13.4) kPa for F = 2, 3, and 4 respectively, in CHB. All the aboveinformation is summarised in Tables 3 and 4.

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Table 2. Summary sensitivity and specificity of: (A) all studies evaluating the diagnostic accuracy of elastography and (B) those studies with optimal biopsy qualityand elastography measurements. ‘‘Positive’’ elastography results were considered all results over the optimal liver stiffness threshold for a given fibrosis stage ineach individual study, while ‘‘negative’’ test results all results below that threshold. Post-test (+) denotes the probability following a positive test, while post-test (-)denotes the probability following a negative test.

≥1

≥2

≥3

4

10

31

24

30

0.78 (0.73-0.83)

0.79 (0.74-0.82)

0.82 (0.78-0.86)

0.83 (0.79-0.86)

0.83 (0.72-0.90)

0.78 (0.72-0.83)

0.86 (0.82-0.89)

0.89 (0.87-0.91)

0.250.50.750.250.50.750.250.50.750.250.50.75

0.600.820.930.550.780.920.660.850.950.720.880.96

0.080.210.440.080.210.450.070.170.390.060.160.36

Fibrosisstage

Studies,N

Sensitivity(95%CI)

Specificity(95%CI)

All studies Studies with optimal biopsy and elastographyPre-test

probabilityPost-test

(+)Post-test

(-)<4

6

7

6

-

0.75(0.65-0.83)

0.82(0.77-0.87)

0.90(0.78-0.96)

-

0.79(0.71-0.85)

0.86(0.80-0.91)

0.91(0.84-0.95)

0.250.50.750.250.50.750.250.50.750.250.50.75

0.550.780.920.670.860.950.760.910.97

0.090.240.480.060.170.380.030.100.24

Studies,N

Sensitivity(95%CI)

Specificity(95%CI)

Pre-testprobability

Post-test(+)

Post-test(-)

Abbreviations: CI: confidence interval.

Research Article

JHEPAT 3490 No. of Pages 11

29 November 2010

Transient elastography and stiffness cut-offs

All but three studies reported on optimal stiffness cut-offs for thediagnosis of specific fibrosis stages [28,29,41]. However, thesestudies derived these cut-offs for each stage statistically, onlyafter data collection, and no study prospectively validated themin an independent cohort. There was a wide range and overlapof cut-offs within and between different fibrosis stages. Roundingup the cut-offs to the nearest 0.5, a metanalysis was only possiblefor cut-offs P7, P9.5, and P12 Kpa in stages 2, 3, and 4, respec-tively, due to a wide distribution that resulted in small studynumbers for other cut-offs. The corresponding summary sensitiv-ity and specificity were: for F = 2, 0.70 (95% CI 0.66–0.75) and0.81 (95% CI 0.77–0.85), for F = 3 0.80 (95% CI 0.72–0.85) and0.85 (95% CI 0.79–0.90), and for F = 4, 0.86 (95% CI 0.80–0.91)and 0.88 (95% CI 0.82–0.91), respectively. No direct comparisonsof different cut-offs within the same fibrosis stage were possible.

We performed a meta-regression analysis of ln DOR andstiffness cut-offs in fibrosis stages 1–4. There was a statisticallysignificant negative correlation (P <0.05) for F1, positive correla-tions for F2 and 3, and non-significance for cirrhosis. The scatterplot is shown in Appendix Fig. 2.

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Methodological bias risk

No study was identified as being free of any bias risk. Therefore,all our estimates may be biased.

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Transient elastography in studies with acceptable reference (liverbiopsy) and index (elastography) test quality

There were 12 studies with biopsies P15 mm long and containingP6 portal tracts and 21 studies where elastography measure-ments were made according to the manufacturer’s recommenda-tion. In the diagnosis of F4, there was a significant difference inDOR between studies with acceptable and unreported elastogra-phy measurements (DOR ratio 2.69, 95% CI 1.24–5.84). The

Please cite this article in press as: Tsochatzis EA et al. Elastography for the diadiagnostic accuracy. J Hepatol (2010), doi:10.1016/j.jhep.2010.07.033

4 Journal of Hepatology 201

summary sensitivity and specificity according to reference andindex test quality are summarised in Tables 3 and 4.

Nine studies had both acceptable reference and index testquality. The summary sensitivity and specificity are summarisedin Table 2.

Transient elastography and type of publication

There was a statistical difference in the diagnostic accuracy ofF = 2 among studies published in full-paper and abstract forms(DOR ratio 2.57, 95% CI 1.44–4.58), but not in the rest of the fibro-sis stages. These results are summarised in Tables 3 and 4.

Transient elastography and ALT levels

There were no studies with a mean ALT level within normal lim-its. Data were available for comparisons only within fibrosis F2and F4 (Tables 3 and 4), for which DOR was statistically and sig-nificantly different for F = 2 (DOR ratio 1.87, 95% CI 1.01–3.55).Linear regression between logarithm of the diagnostic accuracyand ALT values did not demonstrate significant relation withinany fibrosis stage.

Further subgroup analyses

Only one study involved monitoring of fibrosis [44], and anotherscreening for fibrosis in apparently healthy individuals [55]. Nostudies evaluated the effect of treatment. There were no signifi-cant differences in summary sensitivity and specificity whenevaluating different histological scoring systems, country of ori-gin or different ranges of BMI. However, high BMI was the mostcommon cause of unsuccessful elastography measurements(Data not shown).

Exploration of heterogeneity

There was statistically significant heterogeneity in DOR in fibro-sis stages 2 (v2 p <0.001, I2 = 67%) and 4 (v2 p = 0.002, I2 = 49) but

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Fig. 2. The hierarchical summary receiver operating characteristic (HSROC) plot for the sensitivity and specificity in METAVIR stages 1, 2, 3, and 4. The summarypoint represents the summary sensitivity and specificity, the 95% confidence region represents the 95% confidence intervals of the summary sensitivity and specificity andthe 95% prediction region represents the 95% confidence interval of sensitivity and specificity of each individual study included in the analysis. The plot also includes studyestimates indicating the sensitivity and specificity estimated using the data from each study separately. The size of the marker is scaled according to the total number ineach study. (A) HSROC plot for METAVIR F1, (B) HSROC plot for METAVIR F2, (C) HSROC plot for METAVIR F3 (D) HSROC plot for METAVIR F4.

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not in stages 1 (v2 p = 0.32, I2 = 13) and 3 (v2 p = 0.27, I2 = 13). Asalready mentioned, potential sources of heterogeneity includeliver stiffness cut-offs in fibrosis stages 1–3, ALT levels and typeof publication in F = 2 and index test quality in F = 4. Finally, therewas no significant correlation of ln DOR with cohort size in anyfibrosis stage.

Publication bias

The funnel plots for METAVIR 1–4 are shown in Appendix Fig. 3.Asymmetry was visually present for MEATVIR 2 and 4. However,the studies causing the asymmetry were of high bias risk, as 3

Please cite this article in press as: Tsochatzis EA et al. Elastography for the diadiagnostic accuracy. J Hepatol (2010), doi:10.1016/j.jhep.2010.07.033

Journal of Hepatology 201

outlier studies overestimated the diagnostic odds ratio in F = 2,and 2 outlier studies underestimated it in F = 4. By using the lin-ear regression approach [56], a possible publication bias waspresent in F = 2 (p = 0.077), but not in F = 4. However, when weexcluded the F2 and F4 outlier studies, the summary sensitivityand specificity did not significantly change.

Discussion

In our meta-analysis, we evaluated the diagnostic accuracy oftransient elastography in the staging of liver fibrosis, as reported

gnosis of severity of fibrosis in chronic liver disease: A meta-analysis of

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Table 3. Subgroup analysis in METAVIR stage 2. ‘‘Positive’’ elastography results were considered all results over the optimal liver stiffness threshold for a givenfibrosis stage in each individual study, while ‘‘negative’’ test results all results below that threshold. Post-test (+) denotes the probability following a positive test,while post-test (-) denotes the probability following a negative test.

CHC

CHB

Acceptable biopsy quality

Unreported biopsy quality

Low biopsy quality

Acceptable elastography quality

Unreported elastography quality

Low elastography quality

Full-paper publication

Abstract publication

ULN<ALT < 3 ULN

ALT>3ULN

14

4

11

8

11

15

7

9

32

8

13

4

0.78 (0.71-0.84)

0.84 (0.67-0.93)

0.76 (0.68-0.82)

0.81 (0.75-0.86)

0.79 (0.71-0.86)

0.79 (0.73-0.84)

0.76 (0.68-0.83)

0.81 (0.70-0.88)

0.80 (0.75-0.85)

0.74 (0.64-0.82)

0.80 (0.74-0.85)

0.65 (0.60-0.70)

0.80 (0.71-0.86)

0.78 (0.68-0.85)

0.76 (0.69-0.82)

0.78 (0.63-0.88)

0.80 (0.70-0.87)

0.82 (0.79-0.84)

0.71 (0.56-0.83)

0.75 (0.60-0.86)

0.80 (0.75-0.84)

0.69 (0.54-0.80)

0.80 (0.71-0.87)

0.82 (0.76-0.87)

13.9 (8.5-22.8)

17.9 (7.7-41.7)

10.1 (6.4-16.0)

15.4 (8.4-28.3)

15.5 (10.0-24.0)

15.0 (7.6-29.5)

8.0 (5.0-12.6)

12.7 (7.0-23.2)

16.2 (12.3-21.2)

6.3 (3.8-10.5)

16.1 (10.8-24.7)

8.6 (5.3-14.1)

0.250.50.750.250.50.750.250.50.750.250.50.750.250.50.750.250.50.750.250.50.750.250.50.750.250.50.750.250.50.750.250.50.750.250.50.75

0.560.790.920.550.790.920.520.760.910.550.790.920.570.800.920.590.810.930.470.730.890.520.770.910.520.760.910.440.700.880.570.800.920.550.780.92

0.080.220.450.070.170.390.100.240.490.070.190.420.080.200.440.080.200.430.100.250.500.080.200.440.080.210.440.110.270.530.080.200.430.120.300.56

Subgroup Studies,N

Sensitivity(95%CI)

Specificity(95%CI)

DOR (95%CI)

Pre-testprobability

Post-test(+)

Post-test(-)

Abbreviations: DOR: diagnostic odds ratio, CI: confidence intervals, CHC: chronic hepatitis C, CHB: chronic hepatitis B, ULN: upper limits of normal.

Research Article

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in 40 studies. Although three meta-analyses have already beenpublished on this subject [57–59], our meta-analysis evaluates29 different studies compared to these, with an overlap of 25%or less. Moreover, none of these meta-analyses has used the opti-mal statistical methods of combining the studies, i.e. HSROC orbivariate model [8]. Furthermore, none has incorporated in theinclusion criteria a maximum interval between performing liverbiopsy and transient elastography. This is important, as compar-ing the two techniques at a similar point minimises differencesdue to progression of fibrosis, which may not be constant overtime [1]. Efficacy of drug therapies in major trials is assessed aschanges in 6-month or 1-year biopsies [60], whereas elastogra-phy studies have included patients with as long as a 3-year inter-val between tests, making comparisons meaningless [61]. Most

Please cite this article in press as: Tsochatzis EA et al. Elastography for the diadiagnostic accuracy. J Hepatol (2010), doi:10.1016/j.jhep.2010.07.033

6 Journal of Hepatology 201

importantly, our conclusions are different and have a potentialimpact on everyday clinical practice, as we will furtherdiscuss.

Our results show that elastography could be used to diagnosecirrhosis (when pre-test probability = 50%), with 90% probabilityof correctly diagnosing cirrhosis following a ‘‘positive’’ measure-ment. However, results are less promising for lesser fibrosisstages, as the probability of correctly diagnosing stages 1–3ranges from 78% to 85% following a ‘‘positive’’ measurement. A‘‘negative’’ measurement is less informative, as cirrhosis mightstill be present in 16%, or F2 in 20%, of patients (Table 2). Whenthere is a high pre-test index of suspicion (pre-test probabil-ity = 75%), then the probability of a correct diagnosis followinga ‘‘positive’’ measurement exceeded 90% for all fibrosis stages,

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309

310

311

312

313

314

315

316

317

318

319

320

321

322

323

324

325

326

327

328

329

330

331

332

Table 4. Subgroup analysis in cirrhosis (METAVIR stage 4). ‘‘Positive’’ elastography results were considered all results over the optimal liver stiffness threshold for agiven fibrosis stage in each individual study, while ‘‘negative’’ test results all results below that threshold. Post-test (+) denotes the probability following a positivetest, while post-test (-) denotes the probability following a negative test.

CHC

CHB

Acceptable biopsy quality

Unreported biopsy quality

Low biopsy quality

Acceptable elastography quality

Unreported elastography quality

Low elastography quality

Full-paper publication

Abstract publication

ULN<ALT < 3 ULN

ALT>3ULN

11

6

9

8

13

14

5

11

32

8

12

6

0.83 (0.77-0.88)

0.80 (0.61-0.91)

0.84 (0.67-0.93)

0.83 (0.74-0.89)

0.82 (0.79-0.84)

0.84 (0.78-0.89)

0.73 (0.47-0.89)

0.82 (0.78-0.85)

0.83 (0.79-0.87)

0.80 (0.59-0.92)

0.80 (0.76-0.83)

0.84 (0.77-0.90)

0.90 (0.87-0.93)

0.89 (0.82-0.94)

0.92 (0.86-0.95)

0.86 (0.82-0.89)

0.90 (0.86-0.93)

0.89 (0.86-0.92)

0.90 (0.81-0.95)

0.89 (0.84-0.92)

0.90 (0.87-0.92)

0.87 (0.90-0.92)

0.89 (0.85-0.93)

0.89 (0.82-0.93)

46.5 (26.7-91.0)

34.3 (17.0-69.2)

58.4 (27.7-122.7)

29.6 (19.4-45.0)

40.8 (26.6-62.7)

65.7 (38.0-113.)

24.4 (14.1-42.4)

35.5 (24.2-51.9)

43.1 (30.5-61.1)

28.2 (15.2-52.1)

33.5 (21.3-52.8)

43.0 (27.1-68.2)

0.250.50.750.250.50.750.250.50.750.250.50.750.250.50.750.250.50.750.250.50.750.250.50.750.250.50.750.250.50.750.250.50.750.250.50.75

0.740.900.960.710.880.960.770.910.970.660.860.950.730.890.960.730.890.960.710.880.960.710.880.960.730.890.960.680.860.950.710.880.960.700.870.95

0.060.160.360.070.180.400.050.150.340.060.170.380.060.170.380.060.150.350.090.230.470.060.170.380.060.160.360.070.180.400.0070.180.400.060.150.35

Subgroup Studies,N

Sensitivity(95%CI)

Specificity(95%CI)

DOR (95%CI)

Pre-testprobability

Post-test(+)

Post-test(-)

Abbreviations: DOR: diagnostic odds ratio, CI: confidence intervals, CHC: chronic hepatitis C, CHB: chronic hepatitis B, ULN: upper limits of normal.

JOURNAL OF HEPATOLOGY

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but with a ‘‘negative’’ measurement, the diagnosis would still bewrong in 24–44% of patients.

The above results, especially those following a ‘‘positive’’ mea-surement, have been considered encouraging in individual stud-ies and in some reviews. However, the major drawback is that thestiffness cut-off value, for which a particular measurement islabelled as ‘‘positive’’ for a particular stage, is different acrossstudies and has not been validated. Studies have derived thesedifferent liver stiffness cut-offs for each stage statistically onlyafter data collection, and none has been prospectively validatedin an independent cohort. These cut-offs not only have wideranges (in cirrhosis the range is from 9.0 to 26.5 Kpa) but alsooverlap between different fibrosis stages in different studies.

Journal of Hepatology 201

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Pooling such ‘‘optimal’’ results from these studies may artificiallyincrease the summary sensitivity and specificity. In our meta-analysis, we showed that the DOR was better in higher stiffnesscut-offs in F2 and F3, and in lower cut-offs in F1, but no optimalcut-off could be computed. Moreover, the fact that different aeti-ologies of liver disease might have different stiffness cut-offs for agiven fibrosis stage is likely, but has not been tested. Further-more, our meta-analysis confirms that higher transaminase levelsinfluence the accuracy of elastography measurements [57] andalso exposes a possible publication bias. Therefore, the sensitivityand specificity values obtained from the meta-analysis might notbe easily applicable in everyday clinical practice. In clinical prac-tice, in patients with an established cause of chronic liver disease,

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‘‘positive’’ elastography results for the diagnosis of F4 and espe-cially those above 15.4 kPa, which is the highest published opti-mal stiffness cut-off for the diagnosis of a lesser stage, wouldmean a probability for cirrhosis of 90% and would warrant furthertesting and screening for varices and HCC. ‘‘Negative’’ results donot sufficiently exclude cirrhosis and this is an equally importantmessage.

Although liver biopsy is currently the best-accepted standardagainst which the performance of any non-invasive marker ismade, it is not a gold standard. Apart from sample size, bothintra- and inter-observer variability influence fibrosis staging byhistological assessment [62,63]. The potential error in the histo-logical staging makes it difficult to correctly evaluate a non-inva-sive marker: even with a ‘‘high’’ liver biopsy sensitivity andspecificity of 90%, the calculated AUROC for a perfect markerwould be 0.90 (versus 0.99 actual accuracy) [64]. Therefore, a dif-ferent gold standard or surrogate marker is urgently neededagainst which non-invasive markers of fibrosis can be evaluated.

Another issue is that the elastographic measurements, whichare quantitative and continuous, are compared to liver biopsystaging scores, which are categorical and descriptive and whichdo not have a quantitative relationship between them [62]. How-ever, histology could still represent a gold standard. The collagenproportionate area [65] quantifies liver collagen and could be abetter candidate for comparison with transient elastography.Hepatic venous pressure gradient, another continuous measure-ment, has been used to further characterise patients with cirrho-sis in relation to their stiffness measurement [16]. The diagnosticaccuracy of elastography in various disease stages should be eval-uated with respect to continuous measurements of fibrosis andprospectively in terms of clinical outcomes.

A potential limitation of our metanalysis is that results werepooled for all aetiologies of liver disease. We chose to do so asno validated data are available on whether aetiology impactson elastography measurements. However, to address this issue,we performed subgroup analyses in which no significant differ-ences were noted, at least for CHB and CHC, as there were insuf-ficient data for other aetiologies. Moreover, most publishedstudies had a high bias risk and therefore all the estimates wederived may also have significant bias. Overall, only nine studies,comprising 1364 patients, had acceptable standards for both liverbiopsy and elastography, limiting the robustness of the conclu-sions that can be reached. Finally, significant heterogeneity waspresent in the evaluation of F2 and F4 stages, and therefore inter-pretation should be cautious.

In conclusion, our meta-analysis shows that elastographycould be used as a good screening test for cirrhosis, with a 90%disease probability following a ‘‘positive’’ measurement, but notfor lesser fibrosis degrees. A ‘‘negative’’ measurement is less accu-rate and informative, with disease being present in 15% ofpatients. Our meta-analysis exposes the problem of the absenceof validated cut-off values for the various fibrosis stages and fordifferent aetiologies of liver disease. These are a prerequisitebefore elastography results can be generally applicable in every-day clinical practice. This is a very important message to be con-veyed, particularly as the use of transient elastography isexpanding and decisions on patients’ management are madebased on unverified and potentially inaccurate fibrosis classifica-tions. Based on existing evidence, we would not recommenddiagnosing stages other than cirrhosis with the use of elastogra-phy. Better quality studies are needed as current studies have a

8 Journal of Hepatology 201

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high bias risk. Future studies should compare elastography mea-surements with quantitative histological assessments of fibrosis,such as collagen proportionate area or evaluate these withrespect to clinical outcomes.

Conflict of interest

The authors who have taken part in this study declare that theydo not have anything to disclose regarding funding or conflictof interest with respect to this manuscript.

Acknowledgements

E.A. Tsochatzis has received an educational grant from the Hel-lenic Association for the Study of the Liver.

Appendix A. Supplementary data

Supplementary data associated with this article can be found, inthe online version, at doi:10.1016/j.jhep.2010.07.033.

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