Open Access

A brief review on molecular, genetic and imaging techniques for HCV fibrosis evaluation

  • Waqar Ahmad1,
  • Bushra Ijaz1,
  • Sana Gull1,
  • Sultan Asad1,
  • Saba Khaliq1,
  • Shah Jahan1,
  • Muhammad T Sarwar1,
  • Humera Kausar1,
  • Aleena Sumrin1,
  • Imran Shahid1 and
  • Sajida Hassan1Email author
Virology Journal20118:53

https://doi.org/10.1186/1743-422X-8-53

Received: 18 January 2011

Accepted: 8 February 2011

Published: 8 February 2011

Abstract

Background

Chronic HCV is one of the major causes of morbidity and mortality in the present day world. The assessment of disease progression not only provides useful information for diagnosis and therapeutic supervision judgment but also for monitoring disease. Different invasive and non invasive methods are applied to diagnose the disease from initial to end stage (mild fibrosis to cirrhosis). Although, liver biopsy is still considered as gold standard to identify liver histological stages, an assessment of the disease development based on non-invasive clinical findings is also emerging and this may replace the need of biopsy in near future. This review gives brief insight on non-invasive methods currently available for predicting liver fibrosis in HCV with their current pros and cons to make easier for a clinician to choose better marker to assess liver fibrosis in HCV infected patients.

Methods

More than 200 studies regarding invasive and noninvasive markers available for HCV liver disease diagnosis were thoroughly reviewed. We examined year wise results of these markers based on their sensitivity, specificity, PPV, NPV and AUROCs.

Results

We found that in all non-invasive serum markers for HCV, FibroTest, Forn's Index, Fibrometer and HepaScore have high five-year predictive value but with low AUROCs (0.60~0.85) and are not comparable to liver biopsy (AUROC = 0.97). Even though from its beginning, Fibroscan is proved to be best with high AUROCs (> 0.90) in all studies, no single noninvasive marker is able to differentiate all fibrosis stages from end stage cirrhosis. Meanwhile, specific genetic markers may not only discriminate fibrotic and cirrhotic liver but also differentiate individual fibrosis stages.

Conclusions

There is a need of marker which accurately determines the stage based on simplest routine laboratory test. Genetic marker in combination of imaging technique may be the better non invasive diagnostic method in future.

1. Introduction

Chronic Hepatitis C (HCV) is one of the major causes of liver fibrosis, with distortion of the hepatic architecture, and ultimate progression to cirrhosis. Approximately more than 3% of the total world population is chronically infected with HCV and due to gradual increase in the prevalence of HCV; future burden of chronic HCV is predicted to raise at least 3 fold by the year 2020. Common causes of liver fibrosis are viral hepatitis and steato hepatitis with alcohol or obesity. Fibrosis caused by excessive deposition of extracellular matrix (ECM) by histological and molecular reshuffling of various components like collagens, glycoproteins, proteoglycans, matrix proteins and matrix bound growth factors. These changes can lead to metabolic and synthesis impairment to hepatocytes, epithelial cells and hepatic stellate cells (HSC). HSC activation the main step leading to fibrosis, involves several changes in liver like fibrogenesis, proliferation, contractility, chemotaxis, matrix degradation and cytokine release. Fibrosis can be defined as net result of the balance between ECM production and degradation. As ECM tissues not only involve matrix production but also matrix degradation leading to ECM remodeling, fibrosis is potentially a reversible process in early stages (advance stages in some cases) [16].

Fibrosis stages information not only indicate treatment response but also reflect/indicate cirrhosis development disaster. We can evaluate fibrosis in HCV infected patients invasively or non-invasively. Liver biopsy an invasive method is used for histological scoring and still used as reference test for fibrosis staging. With the increasing knowledge of molecular biology, genetics and availability of modern imaging techniques, many clinicians and related scientists developed several non-invasive methods to assess liver fibrosis and cirrhosis. These markers need to be more precise, reproducible and non-invasive to evaluate liver fibrosis in HCV infected patients. Therefore, an assessment of the disease development based on clinical findings is still critical for patients infected with HCV. The accuracy of a serological test either individually or in combination is given as the area under the curve (AUC) of the receiver operator characteristic (ROC) of specific serum diagnosis test. In the meantime, genetic marker should reflect differential expression in different fibrosis stages [4, 713]. This article will focus on the technologies that can be used to assess hepatic fibrosis in HCV infected patients with unequal values. Figure 1 shows an outline of possible methods used for fibrosis evaluation in HCV infected patients.
Figure 1

Schematic diagram of noninvasive methods used to assess liver fibrosis and cirrhosis in HCV or co-infected patients.

2. Invasive Method

In clinical practice, grading and staging involve semi-quantitative scoring systems, and elementary lesion expressed as a numerical value [14, 15]. Three scoring systems, Knodell, Ishak and Metavir are extensively used to assess fibrosis [1618]. In Metavir system, one of the most clinically validated systems; F0-F1 is considered none to mild, F2-F3 moderate to advance fibrosis and F4 as cirrhosis. Liver biopsy, an invasive method is considered the gold standard to identify liver fibrosis. Unfortunately, procedure of liver biopsy is invasive, expensive with severe side effects leading to death and not suitable for all patients. Other limitations of liver biopsy comprises sampling error, intra and inter observer variation and somehow static, not accurately predict disease progression [19, 20].

3. Non-invasive Methods

Non-invasive methods can be classified as serum, genetic and imaging techniques. These markers are addressed below in detail.

4. Serum markers

Serological markers refer to the measurement of one or more molecules within blood or serum correlating to hepatic fibrosis [2123]. There are several proposed serological markers or combinations of serum markers for hepatic fibrosis measurement. Their levels vary by changes in their clearance, metabolism, and excretion, and their significant contribution from non-hepatic sources, such as, bones, joints, lungs, kidneys and skin [24, 25]. Proposed hepatic fibrosis serological markers can be divided in three categories as direct, indirect or composite. Combinations of both direct and indirect, markers are taking place as an emerging and promising alternative to liver biopsy [2629]. Figure 1 gives a brief idea about the non-invasive methods used for fibrosis and cirrhosis prediction in HCV infected patients.

4.1. Direct serum markers

Direct serum markers reflect ECM turnover, balance between hepatic fibrogenesis and fibrolysis, and in the deposition and removal of ECM. Levels of direct serum markers are elevated during disease progression and an independent association between stage of fibrosis and direct markers was observed [3032]. Some of the markers reported are discussed below.

4.1.1. Matrix deposition and removal markers

These may be classified into following

Procollagen I carboxy terminal peptide (PICP), Procollagen III amino-terminal peptide (PIIINP) and Type IV collagen

PICP and PIIINP released into the serum during matrix removal and deposition. PIIINP reflects the stage of fibrosis and known to be elevated in chronic liver disease. PIIINP is a good inflammatory score predictor as compared to fibrosis. PICP usually indicates cirrhosis and used for quantifying disease severity. However, it reflects alcohol etiology better than diagnosis of chronic liver disease. Type IV serum collagen reflects matrix degradation and increased in chronic liver disease. Murawaki et al (1996) established the cutoff value of 110 ng/mL for stages greater than F2 and 130 ng/mL for F3 fibrosis stage [3337].

Matrix metalloproteinase (MMP's) and tissue inhibitor of metalloproteinases (TIMPs)

MMP's enzymes produced intracellularly and secreted in a pro-enzyme form that requires cleavage by cell surface mechanisms control matrix degradation. Although these proteins act both to degrade and deposition of ECM, also involve in activation of growth factor, effect on cell proliferation and inhibition of apoptosis; their association with liver fibrosis is not clear [4, 23]. TIMPs also increased during HCV infection, while a decrease is reported after interferon therapy. These have high diagnostic ability to detect cirrhosis [38].

Cytokines

Two types of cytokines TGF-β 1 (transforming growth factors β 1) and PDGF (platelet derived growth factor) are mainly used to assess the fibrosis progression. TGF-β 1 is the dominant stimulus for producing extracellular matrix and it showed a significant correlation with degree of hepatic fibrosis. A significant association was found between TGF-β 1 serum levels and fibrosis progression. Serum level of PDGF has also showed high ability as serum marker for fibrosis progression [3941].

4.1.2.Combined direct markers

FibroSpect

FibroSpect assay is a combination of three parameters: HA, TIMP-1 and alpha-2-macroglobulin and can differentiate between no/mild and moderate/severe fibrosis [42, 43]. Maximum sensitivity and specificity of this assay was observed at two extreme stages (F0 and F4). This assay was further developed by adding YKL-40 serum marker for assessing Ishak stages and digital quantification of fibrosis [23].

ELF

European liver fibrosis group (ELF) developed an algorithm consisted of HA, PIIINP, TIMP-1 and age. However this assay showed low performance while predicting fibrosis in chronic HCV patients [44].Leroy Score

This score was developed by Leroy et al and contains PIIINP and MMP-1 as basic components. It can differentiate between mild and significant fibrosis [45].

4.1.3.Others

Hyaluronic acid (HA)

HA is best validated, an essential component of extracellular matrix of body tissues. HA levels increases with the fibrosis progression and correlate with the degree of fibrosis and inflammation in chronic HCV patients. The diagnostic accuracy of HA is better than that of PIIINP [32, 35, 4649].

Chondrex, human cartilage glycoprotein (YKL-40)

In liver fibrosis, YKL-40 plays role in tissue degradation and extracellular matrix remodeling. YKL-40 level is observed to decrease after interferon therapy. In a combination of different direct serum markers, HA and YKL-40 were more useful for monitoring fibrosis progression with 80% PPV of predicting stage specific fibrosis. A significant association of HA with liver fibrosis was observed when compared with TGF-β1 [5053].

Table 1 briefly describes a year wise overview of the AUROCs, PPV, NPV, sensitivity and specificity of direct serum markers used in various studies to predict fibrosis and cirrhosis in HCV infected patients. Direct serum markers; HA, YKL-40 and ELF were able to predict significant fibrosis as well as cirrhosis with AUROC 0.70-0.85. However, these markers showed low sensitivity and NPV for predicting fibrosis and high efficiency to detect cirrhosis.
Table 1

Diagnostic accuracies of direct serum markers

Markers

Study

Year

Prognosis

Sen

Spe

PPV

NVP

AUC

ELF Score

Rosenberg [44]

2004

Fibrosis

90

41

99

92

0.80

   

Cirrhosis

-

-

-

-

0.89

 

Cales [79]

2005

Fibrosis

-

-

-

-

0.88

 

Parkes [12]

2006

Fibrosis

-

-

-

-

0.78

 

Lee [107]

2010

Cirrhosis

    

0.70

FibroSpect

Patel [42]

2004

Fibrosis

77

73

74

75

0.83

 

Cales [79]

2005

Fibrosis

-

-

-

-

0.87

 

Zaman [43]

2007

Fibrosis

72

74

61

82

0.82

HA

Guechot [34]

1996

Fibrosis

64

91

-

-

0.86

   

Cirrhosis

79

89

-

-

0.92

 

Murawaki [47]

2001

Fibrosis

75

80

77

78

0.86

   

Cirrhosis

50

79

42

84

0.92

 

Halfon [49]

2005

Fibrosis

14

99

94

57

0.75

   

Cirrhosis

31

99

57

96

0.89

 

Suzuki [48]

2005

Fibrosis

85

80

51

96

0.89

   

Cirrhosis

-

-

-

-

0.92

 

Saitou [51]

2005

Fibrosis

80

80

80

80

0.92

 

Parise [81]

2006

Fibrosis

85

71

-

-

0.88

   

Cirrhosis

91

82

-

-

0.91

Leroy Score

Leroy [45]

2004

Fibrosis

43

64

45

40

-

PIIINP

Guechot [34]

1996

Fibrosis

70

63

-

-

0.69

   

Cirrhosis

60

74

-

-

0.73

 

Murawaki [47]

2001

Fibrosis

74

75

75

92

-

   

Cirrhosis

64

59

33

84

-

 

Saitou [51]

2005

Fibrosis

78

75

76

77

0.75

   

Cirrhosis

77

66

69

67

0.79

PIVNP

Murawaki [47]

2001

Fibrosis

70

73

71

72

-

   

Cirrhosis

63

73

41

87

-

TIMP

Murawaki [47]

2001

Fibrosis

79

56

63

73

-

   

Cirrhosis

82

54

34

94

-

 

Boeker [38]

2002

Fibrosis

52

88

-

-

0.71

   

Cirrhosis

100

75

-

-

0.90

YKL-40

Saitou [51]

2005

Fibrosis

78

81

80

79

0.81

   

Cirrhosis

80

71

73

78

0.80

5. Indirect serum fibrosis markers

The other category of serum marker is indirect markers that are based on the disturbance of hepatic function or structure.

5.1. Serum ALT, AST and AFP levels

Serum ALT released from liver tissue into the circulation in proportion to the degree of hepatocellular damage due to viral infections and toxic substances [54, 55]. ALT is thought as one of the more sensitive marker of liver injury and disease progression [5658]. However, ALT enzymatic activity may not always reflect the degree of hepatic damage as about 26% patients have persistently normal ALT levels but have a histological score greater than A1F1 [59]. Serum AST levels are most important predictor of histological activity than ALT [6062]. Serum AFP is alpha-1-globulin secreted by fetal hepatocytes and fetal gastrointestinal tract. Elevated serum AFP levels are associated with acute and chronic HCV, toxic liver injury concentrations and correlate with tumor size and decrease or normalize after tumor removal. Elevated AFP levels are observed in cirrhotic patients [6366].

5.2. Platelet count (PLT)

Decreased production of thrombopoietin by hepatocytes and reduced platelet production is associated with fibrosis progression. Platelet count (< 150 × 109/L < 100) can differentiate cirrhotic (F4) from fibrosis (F1-F3) in 75-80% chronic HCV patients [6770].

5.3. Prothrombin time (PT)

PT reflects the synthesis capacity of the liver and essential mechanism of blood coagulation. Its clinical reference range is usually around 12-15 seconds. Prolonged PT is associated with esophageal varices and is one of the earliest indicators of liver cirrhosis [7173].

5.4. AST/ALT ratio (AAR)

Sheth et al. reported an AST/ALT ratio ≥ 1 having 100% PPV for the presence of cirrhosis in chronic HCV patients [74]. Reedy et al. observed that AAR failed to predict cirrhosis accurately in HCV patients [75], while Giannini et al. reported high diagnostic accuracy of the AAR for prediction of cirrhosis in HCV infected patients [76]. However, many authors could not able to find high accuracy of this marker [4, 70, 77].

5.5. AST to platelet ratio Index (APRI)

APRI was the simplest and accurate test for significant liver fibrosis and cirrhosis [28]. Several authors verified this marker for fibrosis and cirrhosis and found it better than AAR. However, APRI was unable to identify individual stages of fibrosis [7786].

5.6. PGA and PGAA Index

PGA was known to be the original index of hepatic fibrosis in 1990 s and combines gamma glutamyl transferase (γGT), apolipoprotein A1 (PGA) and prothrombin index. PGAA index is modified form of PGA index by the addition of alpha-2-macroglobulin, resulted in its improved version. The diagnostic accuracy of the PGA and PGAA for detecting cirrhosis reported between 66-72% and 80%, respectively [8792].

5.7. FibroTest/FibroSure

FibroTest is the combination of five markers: alpha-2-macroglobulin, haptoglobin, apolipoprotein A1, GGT and total bilirubin [26, 80]. This marker has 75% sensitivity and 85% specificity with reproducibility for fibrosis diagnosis [8385]. However, Rossi et al. reported low AUROC (0.739) for significant fibrosis with NPV and PPV 85% and 78%, respectively. Meanwhile, FibroTest is validated and suggested as an alternative to liver biopsy in chronic HCV patients [93105].

5.8. Fibro Index

It combines three markers; AST, platelet count and gamma globulin. AUROC for prediction of significant fibrosis was 0.83 [106].

5.9. Forns Index

This index is based on four available variables; age, GGT, platelet count and cholesterol levels in a study on HCV patients, included both test and validation cohorts [27]. The limitation of this index was the identification of advance liver disease with minimal fibrosis [79, 80, 106, 107].

5.10. ActiTest

ActiTest reflects both necroinflamatory activity and liver cirrhosis. It is modified form of Fibrotest with addition of ALT level (26). Fibrotest and ActiTest were found to be potential non-invasive assays for the assessment of hepatic fibrosis and necro-inflammatory activity in pediatric patients with chronic HCV in comparison with liver biopsy [90, 91, 108].

5.11. SteatoTest

It incorporates the FibroTest, ALT, body mass index, serum cholesterol, triglycerides and glucose adjusted for age and gender. It has 63% PPV for steatosis prevalence with 93% NPV [109].

5.12. Model 3

This model is based on AST, platelet count and prothrombin time expressed as international normalized ration (INR). Patients with liver cirrhosis can be excluded at cutoff value of < 0.20 with 99% NPV [110, 111].

5.13. Goteborg University Cirrhosis Index (GUCI)

Islam et al. found strong association between AST, prothrombin-INR and platelet count. By using a cutoff value 1.0, the sensitivity and specificity for the diagnosis of cirrhosis was 80% and 78% respectively, while the NPV and PPV were 97% and 31%, respectively [112].

5.14. Fibrosis Index

This index comprises of platelet count and albumin contents. It can differentiate significant fibrosis and cirrhosis from mild fibrosis [113].

5.15. Phol Score

This index comprises of AST, ALT and platelet count. It showed great accuracy for discriminating significant fibrosis and cirrhosis with high PPV and NPV. However, it showed limited ability to predict fibrosis in later study [114, 115].

5.16. Bonacini Index

This index incorporates ALT/AST ratio, INR and platelet count. It showed 94% specificity for predicting significant fibrosis in initial cohort [116].

Table 2 represents the diagnostic accuracies of indirect serum markers. Indirect serum markers are easily available and routinely used. These markers have the ability to differentiate fibrosis and cirrhosis but lesser extent to direct serum markers. APRI and FibroTest are most validated serum markers with AUROC range between 0.60-0.85 for predicting fibrosis and cirrhosis.
Table 2

Diagnostic accuracies of indirect serum markers

Markers

Study

Year

Prognosis

Sen

Spe

PPV

NVP

AUC

AAR

Sheth [74]

1998

Cirrhosis

53

100

100

81

0.85

 

Afdhal [4]

2004

Fibrosis

47

-

-

88

-

   

Cirrhosis

-

96

74

-

-

 

Lackner [70]

2005

Fibrosis

53

100

-

-

0.57

   

Cirrhosis

36

90

41

87

0.73

 

Fuji [77]

2009

Fibrosis

-

-

-

-

0.56

ActiTest

Imbert-Bismut [26]

2001

Fibrosis

91

42

-

-

0.79

 

Halfon [100]

2008

Fibrosis

90

38

-

-

0.75

APRI

Wai [28]

2003

Fibrosis

41

95

64

90

0.88

   

Cirrhosis

-

-

57

-

0.94

 

Cales [79]

2005

Fibrosis

-

-

-

-

0.79

 

Bourliere [80]

2006

Fibrosis

22

95

63

76

0.71

   

Cirrhosis

38

96

96

40

0.81

 

Parise [81]

2006

Fibrosis

85

66

-

-

0.82

   

Cirrhosis

73

81

-

-

0.84

 

De Ledinghen [82]

2006

Cirrhosis

-

-

-

-

0.73

 

Halfon [83]

2007

Fibrosis

77

66

61

80

0.76

   

Cirrhosis

100

83

18

100

0.92

 

Leroy [84]

2008

Fibrosis

39

95

88

62

0.79

 

Cales [85]

2008

Fibrosis

62

83

80

67

0.78

   

Cirrhosis

-

-

-

-

0.84

 

Kamphues [86]

2010

Fibrosis

70

63

80

80

0.68

   

Cirrhosis

89

44

14

97

0.63

 

Fuji [77]

2009

Cirrhosis

-

-

-

-

0.76

Fibro Index

Koda [106]

2007

Fibrosis

36

97

94

59

0.83

Fibrosis Index

Ohta [113]

2006

Fibrosis

68

71

75

81

0.85

FibroTest

Imbert-Bismut [26]

2001

Fibrosis

87

59

63

85

0.87

   

Cirrhosis

     
 

Bedosa [102]

2003

Fibrosis

27

97

90

55

-

 

Myers [101]

2003

Fibrosis

-

95

88

-

0.83

 

Poynard [90]

2003

Fibrosis

-

-

-

-

0.73

 

Rossi [97]

2003

Fibrosis

83

52

52

83

0.74

 

Colletta [103]

2005

Fibrosis

64

31

33

62

-

 

Bourliere [80]

2006

Fibrosis

55

90

73

79

0.82

 

De Ledinghen [82]

2006

Cirrhosis

-

-

-

-

0.73

 

Halfon [83]

2007

Fibrosis

67

80

70

78

0.79

   

Cirrhosis

85

74

11

99

0.86

 

Leroy [84]

2008

Fibrosis

57

85

78

68

0.80

 

Cales [85]

2008

Fibrosis

67

82

80

70

0.81

 

Shaheen [104]

2008

Fibrosis

47

90

-

-

0.81

   

Cirrhosis

-

-

-

-

0.90

 

Cales [105]

2010

Fibrosis

-

-

-

-

0.81

   

Cirrhosis

-

-

-

-

0.88

Forn's Index

Forn [27]

2002

Fibrosis

94

51

40

96

0.78

 

Cales [79]

2005

Fibrosis

-

-

-

-

0.82

 

Bourliere [80]

2006

Fibrosis

30

96

65

83

0.76

 

Koda [106]

2007

Fibrosis

-

-

-

-

0.79

Model 3

Lok [110]

2005

Cirrhosis

10

100

100

86

0.78

PGA

Teare [87]

1993

Fibrosis

94

81

-

-

-

   

Cirrhosis

-

-

86

-

-

 

Poynard [90]

2003

Fibrosis

91

81

-

-

-

 

Poynard [91]

2004

Fibrosis

79

89

-

-

-

PGAA

Naveau [92]

2005

Cirrhosis

89

79

-

-

0.93

Phol Score

Pohl [114]

2001

Fibrosis

41

99

93

85

-

 

Cheung [115]

2008

Fibrosis

-

-

-

-

0.53

6. Composite fibrosis markers

6.1. FibroMeter

FibroMeter can differentiate fibrosis progression in viral disease consist of combination of HA, AST, platelet count, prothrombin index, alpha-2-macroglobulin, urea and age of the patients [105].

6.2. Hepascore

Hepascore is a model consisting of bilirubin, GGT, HA, alpha-2-macroglobulin, gender and age. AUROC of this test is 0.85, 0.96 and 0.94 for significant fibrosis, advanced fibrosis and cirrhosis, respectively [117120].

6.3. Shasta Index

It combines HA, AST and albumin. Optimal results of this assay are observed in extreme conditions. This assay showed similar accuracy with FibroTest [121].

6.4. Apricot (FIB-4)

This assay combines four markers: AST, ALT, platelet count and age. This index can predict significant fibrosis in patients infected with HIV/HCV [122]. Later studies validated this index not only in co-infected patients but also in HCV infected patients [85, 123, 124].

6.5. Sud Index

This assay is also known as FPI comprises of age, AST, cholesterol, insulin resistance and alcohol intake. This index showed high specificity and PPV for detecting advance fibrosis [125].

6.6. Testa Index

This index relate platelet count and spleen diameter. This ratio showed 78% concordance with the histological score [126].

6.7. Fortunato score

This model contains fibronectin, prothrombin time, PCHE, ALT, Mn-SOD and β-NAG as essential components. It has ability to classify cirrhotic from chronic patients with high accuracy in initial and validation cohort [127].

Table 3 gives an idea about the prediction levels of combined serum markers. These markers showed high AUROCs (0.80-0.90) for predicting fibrosis and cirrhosis in HCV infected patients. FIB-4, Fibrometer and Hepascore are most precise and validated serum markers. Combined serum markers are easily available and most preferable non invasive serum markers now a day.
Table 3

Prognosis accuracies of combined serum markers

Markers

Study

Year

Prognosis

Sen

Spe

PPV

NVP

AUC

FIB-4

Sterling [122]

2006

Fibrosis

70

74

42

71

0.80

   

Cirrhosis

     
 

De Ledingh [82]

2006

Cirrhosis

-

-

-

-

0.73

 

Vallet-Pichard [123]

2007

Fibrosis

74

80

82

95

0.85

 

Cales [85]

2008

Fibrosis

74

72

74

71

0.80

   

Cirrhosis

-

-

-

-

0.87

 

Mallet [124]

2009

Fibrosis

71

73

52

86

0.81

   

Cirrhosis

-

-

-

-

0.87

 

Lee [107]

2010

Cirrhosis

-

-

-

-

0.71

Fibrometer

Halfon [83]

2007

Fibrosis

92

87

21

100

0.94

   

Cirrhosis

62

87

21

100

0.94

 

Cales [85]

2008

Fibrosis

-

-

-

-

0.90

   

Cirrhosis

-

-

-

-

0.90

 

Cales [105]

2010

Fibrosis

-

-

-

-

0.88

   

Cirrhosis

-

-

-

-

0.88

Fortunato Score

Fortunato [127]

2001

Fibrosis

-

94

-

-

-

HepaScore

Adams [117]

2005

Fibrosis

63

89

88

90

0.82

   

Cirrhosis

71

89

-

-

0.90

 

Bourliere [80]

2006

Fibrosis

-

-

-

-

0.82

   

Cirrhosis

-

-

-

-

0.90

 

Halfon [83]

2007

Fibrosis

77

63

59

80

0.76

   

Cirrhosis

92

72

11

100

0.89

 

Leroy [118]

2007

Fibrosis

54

84

78

64

0.79

 

Leroy [84]

2008

Fibrosis

63

80

75

70

0.78

 

Cales [85]

2008

Fibrosis

66

79

77

68

0.78

   

Cirrhosis

-

-

-

-

0.90

 

Becker [119]

2009

Fibrosis

82

65

70

78

0.81

   

Cirrhosis

-

-

-

-

0.88

 

Cales [105]

2010

Fibrosis

-

-

-

-

0.78

   

Cirrhosis

-

-

-

-

0.89

 

Guechot [120]

2010

Fibrosis

77

70

71

77

0.81

   

Cirrhosis

86

74

37

97

0.88

Shasta Index

Kelleher [121]

2005

Fibrosis

88

72

55

94

0.87

Sud Index

Sud [125]

2004

Fibrosis

42

98

97

54

0.84

Testa Index

Testa [126]

2006

Fibrosis

78

79

-

-

0.80

7. Imaging/scanning techniques

Imaging techniques are rational noninvasive approach to assess liver fibrosis. Imaging techniques are not only capable to detect changes in the hepatic parenchyma, these can differentiate between moderate and severe fibrosis. However, high cost and lack of validation of concerning studies remains controversial. Brief detail of these techniques is given under, while there limitations are addressed in Table 4.
Table 4

Summarized imaging techniques with their limitations

Method

Technique

Limitations

Ultrasonography

Identification of portal hypertension

Limited capability to measure mild or moderate fibrosis and cirrhosis, contradictory results

Elastography

Liver stiffness

Vulnerable measurements due to narrow intercostals spaces, ascites or obesity

Doppler Analysis

Measures velocity of blood flow, hemodynamic variations

Limited data, lack of reproducibility, contradictory results

Magnetic Resonance Imaging

Observe changes in hepatic parenchyma

High cost, lack of research support

Computed Tomography

Identifies micro vascular permeability changes

Recent technique, not much literature is available, can not performed in renal failure and contrast agent allergic patients

7.1. Ultrasonography (US)

Ultrasonography detects changes appear in liver echogenicity, nodularity and signs of portal hypertension. A number of studies proposed the role of ultrasonography as a non-invasive diagnostic marker of liver fibrosis and revealed a great sensitivity of ultrasonography to detect late stages of progressive hepatic fibrosis, but a limited capability to measure mild or moderate fibrosis. Ultrasound can identify cirrhosis in patients with sensitivity of 84% and specificity of 100% and diagnose accurately 94%. Shen et al. observed that the echo pattern of the hepatic surface contributed to diagnostic accuracy, which was also confirmed in a separate study. However, Oberti found ultrasonography as weak diagnostic marker when compared it with other clinical and biochemical examinations [128133].

7.2. Transient Elastography (FibroScan): an applicable alternative to liver biopsy

Transient elastography measures tissue stiffness. It can measure liver sample size 100 times greater than a standard biopsy sample size, as liver biopsy size strongly effects the grading of chronic viral hepatitis [134137]. FibroScan results reported 100% sensitivity and specificity for PPV & NPV respectively (103). In a study of 935 patients Fibroscan was found to be 97% successful in grading chronic HCV infection [138]. In another study on 711 patients, liver stiffness measurements (LSM) were also found closely related to fibrosis stage [139]. Vizzutti et al. has also reported a good correlation between liver stiffness measurement and HVPG (hepatic venous pressure gradient) in cirrhotic patients. Success rate depends on patient body mass index, observer expertise and inter-coastal spaces with 5% failure chances. Several authors assess the performance of elastography and configure it best for the diagnosis of fibrosis [13, 86, 103, 140149]. A combination of FibroScan with FibroTest also gives a better understanding to detect fibrosis and cirrhosis with high AUC [104]. Table 5 briefly describes the diagnostic accuracy of FibroScan with or without combination with FibroTest. In all studies, FibroScan showed highest AUROC (> 0.90) but not more than liver biopsy (AUROC > 0.970).
Table 5

Diagnostic accuracy of Fibroscan with and without FibroTest

Markers

Study

Year

Prognosis

Sen

Spe

PPV

NVP

AUC

Fibro Scan

Ziol [13]

2005

Fibrosis

56

91

88

56

0.79

   

Cirrhosis

86

96

78

97

0.97

 

Colletta [103]

2005

Fibrosis

100

100

100

100

1.00

 

Foucher [139]

2006

Fibrosis

64

85

90

52

0.80

   

Cirrhosis

77

97

91

92

0.96

 

Corpechot [145]

2006

Fibrosis

-

-

-

-

0.95

 

Ganne-Carrie [146]

2006

Cirrhosis

79

95

74

96

0.95

 

Kettaneh [138]

2007

Fibrosis

-

-

-

-

0.79

   

Cirrhosis

-

-

-

-

0.91

 

Shaheen [147]

2007

Fibrosis

64

87

-

-

0.83

   

Cirrhosis

-

-

-

-

0.95

 

Friedrich-Rust [148]

2009

Fibrosis

-

-

-

-

0.84

   

Cirrhosis

-

-

-

-

0.94

 

Kamphues [86]

2010

Fibrosis

72

83

96

58

0.81

   

Cirrhosis

100

65

23

100

0.87

 

Sanchez-Conde [149]

2010

Fibrosis

76

75

70

81

0.93

   

Cirrhosis

100

94

57

100

0.99

Fibro Scan + FibroTest

Castera [160]

2005

Fibrosis

-

-

-

-

0.88

   

Cirrhosis

-

-

-

-

0.95

 

Shaheen [104]

2008

Fibrosis

47

90

-

-

-

7.3. Doppler analysis

Doppler measures the velocity of blood flow hemodynamic variations in hepatic vasculature, as sever fibrosis causes irregularities and abnormalities in hepatic blood vessels. Recent data indicate a close correlation between arterioportal ratio and degree of fibrosis, higher ratio indicates severe fibrosis (F3-F4) and low ratio shows moderate fibrosis (F1-F2) [150153].

7.4. Magnetic resonance imaging (MRI)

MRI observes changes in hepatic parenchyma. Non-invasive prognosis of liver cirrhosis is proposed by using double contrast material-enhanced MR imaging. This can detect cirrhosis with great sensitivity and specificity of 90%. Combining Doppler ultrasonography with MRI can give a good picture of liver fibrosis in patients suffering with chronic HCV [154156].

7.5. Computed tomography (CT)

CT identifies microvascular permeability changes in a model of liver fibrosis. In a latest study, the severity of liver fibrosis was predicted by heterogeneous enhancement of the liver; hepatic parameters. Perfusion calculated with a dynamic contrast-enhanced single-section CT, linked with the severity of chronic liver disease. However, no well characterized study has specifically evaluated the worth of CT in diagnosing degree of fibrosis. Therefore, currently its role in diagnosis of liver fibrosis is still lacking [157159].

7.6. Fibroscan + Fibrotest

The combination of two useful noninvasive methods, fibroscan and fibrotest showed high AUROC for predicting cirrhosis [104, 160].

7.7. Modified imaging techniques

Imaging techniques with modification like Real-time elastography, Tissue strain imaging, Supersonic shear imaging, Contrast enhanced MRI, Diffusion-weighted MRI, Magnetic resonance spectroscopy, Positron emission tomography (PET), Single photon emission computed tomography (SPECT) are also in use to evaluate liver fibrosis and cirrhosis with considerable limitations like, lack of data and expertise, high cost, radiation exposure and short half-life of the tracer in PET and SPECT.

8. Genetic markers for liver fibrosis evaluation

ECM metabolism is very dynamic process and required an intricate balance between ECM deposition and removal. Several genetic polymorphisms influenced by factors/cytokines and affect fibrosis progression [98]. Genome-wide analysis of abnormal gene expression showed transcript deregulations during HCC development with identification of novel serum markers differentiating between normal, mild and severe fibrosis. Advantage of genetic markers over liver biopsy is intrinsic and long life while liver biopsy represents only one time point [161163].

Huang and colleagues developed an assay known as cirrhosis risk score (CRS), a set of seven marker genes to predict cirrhosis risk in HCV infected patients. Of the seven genes, AZIN1 and TLR4 have an identified role in hepatic fibrosis, while the identification of functional mechanism of the other 5 genes is under process. The authors suggested that fibrosis risk can be identified by host genetic factors like single nucleotide polymorphism (SNP's) [164, 165].

A strong association between CXCR3-associated chemokines CXCL9 and CXCL10 with liver fibrosis suggested that they may have promise as new non-invasive markers of liver fibrosis in HCV infected patients [166, 167].

CTGF expression is significantly correlated with fibrosis stages and remarkably increased in advanced stages in HCV patients. The AUROC of CTGF to discriminate between mild and advanced fibrosis is 0.842 for HCV infected patients [168].

Sharma et al. reported the significant association and elevated interleukin-18 (IL-18) levels in fibrotic and cirrhotic liver stages, severity of disease and necrosis in HCV patients [169].

A recent study by Caillot et al. used microarray technique and found a significant association of ITIH1, SERPINF2 and TTR genes expression and their related proteins with all fibrosis stages. Expression of these genes and related proteins gradually decreased during the fibrosis development to its end stage cirrhosis [170].

A review by Gutierrez-Reyes et al. briefly described role and selection of appropriate genes for fibrosis indication. They briefly explain the role of various genes like PDGF, TGF-β1, collagens COL1-A1, TNFα, interlukin, ADAMTS, MMPs, TIMPs, LAMB1, LAMC1, Cadherin, CD44, ICAM1, ITGA, APO and CYP2C8 [171]. Figure 2 represents gene clustering according to fibrosis progression on available data.
Figure 2

Genes expressed differentially between different fibrosis stages (F0-F3) including cirrhosis (F4).

9. Others markers for liver fibrosis evaluation

9.1. C-Caffeine Breath Test (CBT)

Caffeine has high oral bioavailability and undergoes hepatic metabolism and can be use as quantitative test for liver function [172]. Park et al. performed caffeine breath test (CBT) and observed the correlation of orally administrated caffeine with plasma caffeine clearance and degree of liver dysfunction. Chronic patients showed significantly reduced CBT values when compared with controls [173].

9.2.Differentially expressed proteins

Differentially expressed proteins were identified by mass spectroscopy among different degrees of fibrosis (F0-F4) and between early (F0-F1) and late (F2-F4) fibrosis. Mac-2-binding protein, alpha-2-macroglobulin and hemopexin levels were found increased while A-1-antitrypsin, leucine-rich alpha-2-glycoprotein and fetuin-A were decreased in advanced fibrosis F4 as compared to early fibrosis F0/F1 [115].

10. Clinical utilization and future of non-invasive markers

Non-invasive markers should be able to differentiate between different fibrosis stages but also reflect the treatment outcome. Even though the invasive liver biopsies considered as gold standard for final assessment of liver fibrosis, non-invasive markers are risk free, reflect the liver status and may offer an attractive alternative to liver biopsy in future. However, none of currently available serum markers completely fulfill these criteria. The outcome of non-invasive markers in several studies is not same. Due to this, non-invasive markers are used in parallel to liver biopsy and not in position to completely replace liver biopsy till date.

Poynard et al. reported the effect of interferon plus ribavirin before and after therapy with respect to FibroTest and Actitest scores. A substantial reduction in FibroTest and Actitest was observed in patients who had showed a sustained virological response [81, 90, 115]. Several other studies reported the down level of serum markers like HA, YKL-40, TIMP-1 and PIIINP after interferon therapy. In these studies, level of serum markers continue to fall following treatment but most often return to permanent levels with biochemical and virological relapse. These findings suggest that these assays may be useful for initial staging of disease progression as well as histological response to therapy [174177]. Fibroscan showed positive correlation with fibrosis stages. However, it is reported that AUROC value of Fibroscan and FibroTest must be improved as their values fall in treated patients irrespective of their virological response [178, 179]. Furthermore, HCV clearance is associated with a significant reduction in non-invasive fibrosis serological markers like FibroTest, Forns Index, age-platelet ratio index, Shasta, FIB-4, Hepascore and FibroMeter [180]. Patel et al. compared two commercially available serum marker panels Fibrosure and Fibrospect-II in HCV patients during interferon-based therapy. Both assays showed comparable performance for differentiating mild fibrosis from moderate-severe stage [181]. Imaging techniques also have some technical limitations. These are very expensive and are not easy to handle. Their presence in each hospital or laboratory is not possible especially in poor countries. On the other hand genetic markers showed a great variability for detecting cirrhosis and fibrosis. They are also able to differentiate among fibrosis stages. But a lot of work is needed for them to become an integral part of hepatic analysis.

11. Conclusions

Our study showed that there are only three to four markers or set of marker that are used continuously based on their precision and accuracy in various studies for fibrosis and cirrhosis prediction. In serum non-invasive markers, FibroTest, Forn's Index, Fibrometer and HeapaScore have a high five-year prognostic value but not compared to liver biopsy (AUROC = 0.97), while Fibroscan showed maximum accuracy nearer to liver biopsy (AUROC > 0.90). Recently, genetic markers showed differential gene expression in different fibrosis stages, but these are not frequently available in all labs. Imaging techniques like ultrasound and elastography not only used to diagnose liver fibrosis but also monitor disease progression. However, genetic markers showed high ability to distinguish not only mild and advance stages of liver fibrosis but also differentiate between intermediate fibrosis stages. Although present published literature do not provide any evidence for non-invasive markers to become an integrated part of the complete assessment of liver fibrosis in HCV patients, a combination of two or more serum markers with imaging techniques may improve the accuracy of diagnosis.

Authors' information

Shah Jahan, Saba Khaliq and Samrin A (PhD in Molecular biology), Bushra Ijaz (M Phil Molecular Biology), Waqar Ahmad (M Phil Chemistry) and Gull S (MSc Biochemistry) are Research Officer; Sawar MT and Shahid I are Phd scholars, Asad S is MPhil scholars, while Sajida Hassan (PhD Molecular Biology) is Principal Investigator at CEMB, University of the Punjab, Lahore

Declarations

Acknowledgements

Financial support by Higher Education Commission (Grant # 863) is highly acknowledged.

Authors’ Affiliations

(1)
Applied and Functional Genomics Laboratory, Centre of Excellence in Molecular Biology University of the Punjab

References

  1. Memon MI, Memon MA: Hepatitis C: an epidemiological review. J Viral Hepat 2002, 9: 84-100. 10.1046/j.1365-2893.2002.00329.xPubMedGoogle Scholar
  2. WHO: Global distribution of hepatitis A, B and C, 2001. Weakly Epidimiological Records 2002., 77: 41,48Google Scholar
  3. Marcellin P, Asselah T, Boyer N: Fibrosis and disease progression in hepatitis C. Hepatology 2002, 36: S47-56. 10.1002/hep.1840360707PubMedGoogle Scholar
  4. Afdhal NH, Nunes D: Evaluation of liver fibrosis: a concise review. Am J Gastroenterol 2004, 99: 1160-1174. 10.1111/j.1572-0241.2004.30110.xPubMedGoogle Scholar
  5. Dienstag JL, McHutchison JG: American Gastroenterological Association technical review on the management of hepatitis C. Gastroenterology 2006, 130: 231-264. quiz 214-237 10.1053/j.gastro.2005.11.010PubMedGoogle Scholar
  6. Clark JM: The epidemiology of nonalcoholic fatty liver disease in adults. J Clin Gastroenterol 2006,40(Suppl 1):S5-10.PubMedGoogle Scholar
  7. Harbin WP, Robert NJ, Ferrucci JT Jr: Diagnosis of cirrhosis based on regional changes in hepatic morphology: a radiological and pathological analysis. Radiology 1980, 135: 273-283.PubMedGoogle Scholar
  8. Gressner AM: The cell biology of liver fibrogenesis - an imbalance of proliferation, growth arrest and apoptosis of myofibroblasts. Cell Tissue Res 1998, 292: 447-452. 10.1007/s004410051073PubMedGoogle Scholar
  9. Arthur MJ: Reversibility of liver fibrosis and cirrhosis following treatment for hepatitis C. Gastroenterology 2002, 122: 1525-1528. 10.1053/gast.2002.33367PubMedGoogle Scholar
  10. Adinolfi LE, Gambardella M, Andreana A, Tripodi MF, Utili R, Ruggiero G: Steatosis accelerates the progression of liver damage of chronic hepatitis C patients and correlates with specific HCV genotype and visceral obesity. Hepatology 2001, 33: 1358-1364. 10.1053/jhep.2001.24432PubMedGoogle Scholar
  11. El-Serag HB: Hepatocellular carcinoma and hepatitis C in the United States. Hepatology 2002, 36: S74-83. 10.1002/hep.1840360710PubMedGoogle Scholar
  12. Parkes J, Guha IN, Roderick P, Rosenberg W: Performance of serum marker panels for liver fibrosis in chronic hepatitis C. J Hepatol 2006, 44: 462-474. 10.1016/j.jhep.2005.10.019PubMedGoogle Scholar
  13. Ziol M, Handra-Luca A, Kettaneh A, Christidis C, Mal F, Kazemi F, de Ledinghen V, Marcellin P, Dhumeaux D, Trinchet JC, Beaugrand M: Noninvasive assessment of liver fibrosis by measurement of stiffness in patients with chronic hepatitis C. Hepatology 2005, 41: 48-54. 10.1002/hep.20506PubMedGoogle Scholar
  14. Saadeh S, Cammell G, Carey WD, Younossi Z, Barnes D, Easley K: The role of liver biopsy in chronic hepatitis C. Hepatology 2001, 33: 196-200. 10.1053/jhep.2001.20534PubMedGoogle Scholar
  15. Booth JC, O'Grady J, Neuberger J: Clinical guidelines on the management of hepatitis C. Gut 2001,49(Suppl 1):I1-21. 10.1136/gut.49.suppl_1.I1PubMed CentralPubMedGoogle Scholar
  16. Knodell RG, Ishak KG, Black WC, Chen TS, Craig R, Kaplowitz N, Kiernan TW, Wollman J: Formulation and application of a numerical scoring system for assessing histological activity in asymptomatic chronic active hepatitis. Hepatology 1981, 1: 431-435. 10.1002/hep.1840010511PubMedGoogle Scholar
  17. group TFMcs: Intraobserver and interobserver variations in liver biopsy interpretation in patients with chronic hepatitis C. The French METAVIR Cooperative Study Group. Hepatology 1994, 20: 15-20.Google Scholar
  18. Ishak K, Baptista A, Bianchi L, Callea F, De Groote J, Gudat F, Denk H, Desmet V, Korb G, MacSween RN, et al.: Histological grading and staging of chronic hepatitis. J Hepatol 1995, 22: 696-699. 10.1016/0168-8278(95)80226-6PubMedGoogle Scholar
  19. Goldin RD, Goldin JG, Burt AD, Dhillon PA, Hubscher S, Wyatt J, Patel N: Intra-observer and inter-observer variation in the histopathological assessment of chronic viral hepatitis. J Hepatol 1996, 25: 649-654. 10.1016/S0168-8278(96)80234-0PubMedGoogle Scholar
  20. Westin J, Lagging LM, Wejstal R, Norkrans G, Dhillon AP: Interobserver study of liver histopathology using the Ishak score in patients with chronic hepatitis C virus infection. Liver 1999, 19: 183-187. 10.1111/j.1478-3231.1999.tb00033.xPubMedGoogle Scholar
  21. Friedman SL: Molecular regulation of hepatic fibrosis, an integrated cellular response to tissue injury. J Biol Chem 2000, 275: 2247-2250. 10.1074/jbc.275.4.2247PubMedGoogle Scholar
  22. Friedman SL: Liver fibrosis -- from bench to bedside. J Hepatol 2003,38(Suppl 1):S38-53. 10.1016/S0168-8278(02)00429-4PubMedGoogle Scholar
  23. Kelleher TB, Afdhal N: Noninvasive assessment of liver fibrosis. Clin Liver Dis 2005, 9: 667-683. vii 10.1016/j.cld.2005.08.002PubMedGoogle Scholar
  24. Idobe Y, Murawaki Y, Ikuta Y, Koda M, Kawasaki H: Post-prandial serum hyaluronan concentration in patients with chronic liver disease. Intern Med 1998, 37: 568-575. 10.2169/internalmedicine.37.568PubMedGoogle Scholar
  25. Saif MW, Alexander D, Wicox CM: Serum Alkaline Phosphatase Level as a Prognostic Tool in Colorectal Cancer: A Study of 105 patients. J Appl Res 2005, 5: 88-95.PubMed CentralPubMedGoogle Scholar
  26. Imbert-Bismut F, Ratziu V, Pieroni L, Charlotte F, Benhamou Y, Poynard T: Biochemical markers of liver fibrosis in patients with hepatitis C virus infection: a prospective study. Lancet 2001, 357: 1069-1075. 10.1016/S0140-6736(00)04258-6PubMedGoogle Scholar
  27. Forns X, Ampurdanes S, Llovet JM, Aponte J, Quinto L, Martinez-Bauer E, Bruguera M, Sanchez-Tapias JM, Rodes J: Identification of chronic hepatitis C patients without hepatic fibrosis by a simple predictive model. Hepatology 2002, 36: 986-992.PubMedGoogle Scholar
  28. Wai CT, Greenson JK, Fontana RJ, Kalbfleisch JD, Marrero JA, Conjeevaram HS, Lok AS: A simple noninvasive index can predict both significant fibrosis and cirrhosis in patients with chronic hepatitis C. Hepatology 2003, 38: 518-526. 10.1053/jhep.2003.50346PubMedGoogle Scholar
  29. Thabut D, Simon M, Myers RP, Messous D, Thibault V, Imbert-Bismut F, Poynard T: Noninvasive prediction of fibrosis in patients with chronic hepatitis C. Hepatology 2003, 37: 1220-1221. author reply 1221 10.1053/jhep.2003.50109PubMedGoogle Scholar
  30. Guechot J, Loria A, Serfaty L, Giral P, Giboudeau J, Poupon R: Serum hyaluronan as a marker of liver fibrosis in chronic viral hepatitis C: effect of alpha-interferon therapy. J Hepatol 1995, 22: 22-26. 10.1016/0168-8278(95)80255-XPubMedGoogle Scholar
  31. Pares A, Deulofeu R, Gimenez A, Caballeria L, Bruguera M, Caballeria J, Ballesta AM, Rodes J: Serum hyaluronate reflects hepatic fibrogenesis in alcoholic liver disease and is useful as a marker of fibrosis. Hepatology 1996, 24: 1399-1403. 10.1002/hep.510240615PubMedGoogle Scholar
  32. McHutchison JG, Blatt LM, de Medina M, Craig JR, Conrad A, Schiff ER, Tong MJ: Measurement of serum hyaluronic acid in patients with chronic hepatitis C and its relationship to liver histology. Consensus Interferon Study Group. J Gastroenterol Hepatol 2000, 15: 945-951. 10.1046/j.1440-1746.2000.02233.xPubMedGoogle Scholar
  33. Hayasaka A, Saisho H: Serum markers as tools to monitor liver fibrosis. Digestion 1998, 59: 381-384. 10.1159/000007493PubMedGoogle Scholar
  34. Guechot J, Laudat A, Loria A, Serfaty L, Poupon R, Giboudeau J: Diagnostic accuracy of hyaluronan and type III procollagen amino-terminal peptide serum assays as markers of liver fibrosis in chronic viral hepatitis C evaluated by ROC curve analysis. Clin Chem 1996, 42: 558-563.PubMedGoogle Scholar
  35. Fabris C, Falleti E, Federico E, Toniutto P, Pirisi M: A comparison of four serum markers of fibrosis in the diagnosis of cirrhosis. Ann Clin Biochem 1997,34(Pt 2):151-155.PubMedGoogle Scholar
  36. George DK, Ramm GA, Walker NI, Powell LW, Crawford DH: Elevated serum type IV collagen: a sensitive indicator of the presence of cirrhosis in haemochromatosis. J Hepatol 1999, 31: 47-52. 10.1016/S0168-8278(99)80162-7PubMedGoogle Scholar
  37. Murawaki Y, Ikuta Y, Koda M, Yamada S, Kawasaki H: Comparison of serum 7 S fragment of type IV collagen and serum central triple-helix of type IV collagen for assessment of liver fibrosis in patients with chronic viral liver disease. J Hepatol 1996, 24: 148-154. 10.1016/S0168-8278(96)80023-7PubMedGoogle Scholar
  38. Boeker KH, Haberkorn CI, Michels D, Flemming P, Manns MP, Lichtinghagen R: Diagnostic potential of circulating TIMP-1 and MMP-2 as markers of liver fibrosis in patients with chronic hepatitis C. Clin Chim Acta 2002, 316: 71-81. 10.1016/S0009-8981(01)00730-6PubMedGoogle Scholar
  39. Zhang BB, Cai WM, Weng HL, Hu ZR, Lu J, Zheng M, Liu RH: Diagnostic value of platelet derived growth factor-BB, transforming growth factor-beta1, matrix metalloproteinase-1, and tissue inhibitor of matrix metalloproteinase-1 in serum and peripheral blood mononuclear cells for hepatic fibrosis. World J Gastroenterol 2003, 9: 2490-2496.PubMed CentralPubMedGoogle Scholar
  40. Johansen JS, Christoffersen P, Moller S, Price PA, Henriksen JH, Garbarsch C, Bendtsen F: Serum YKL-40 is increased in patients with hepatic fibrosis. J Hepatol 2000, 32: 911-920. 10.1016/S0168-8278(00)80095-1PubMedGoogle Scholar
  41. Kanzler S, Baumann M, Schirmacher P, Dries V, Bayer E, Gerken G, Dienes HP, Lohse AW: Prediction of progressive liver fibrosis in hepatitis C infection by serum and tissue levels of transforming growth factor-beta. J Viral Hepat 2001, 8: 430-437. 10.1046/j.1365-2893.2001.00314.xPubMedGoogle Scholar
  42. Patel K, Gordon SC, Jacobson I, Hezode C, Oh E, Smith KM, Pawlotsky JM, McHutchison JG: Evaluation of a panel of non-invasive serum markers to differentiate mild from moderate-to-advanced liver fibrosis in chronic hepatitis C patients. J Hepatol 2004, 41: 935-942. 10.1016/j.jhep.2004.08.008PubMedGoogle Scholar
  43. Zaman A, Rosen HR, Ingram K, Corless CL, Oh E, Smith K: Assessment of FIBROSpect II to detect hepatic fibrosis in chronic hepatitis C patients. Am J Med 2007, 120: 280. e289-214 10.1016/j.amjmed.2006.06.044PubMedGoogle Scholar
  44. Rosenberg WM, Voelker M, Thiel R, Becka M, Burt A, Schuppan D, Hubscher S, Roskams T, Pinzani M, Arthur MJ: Serum markers detect the presence of liver fibrosis: a cohort study. Gastroenterology 2004, 127: 1704-1713. 10.1053/j.gastro.2004.08.052PubMedGoogle Scholar
  45. Leroy V, Monier F, Bottari S, Trocme C, Sturm N, Hilleret MN, Morel F, Zarski JP: Circulating matrix metalloproteinases 1, 2, 9 and their inhibitors TIMP-1 and TIMP-2 as serum markers of liver fibrosis in patients with chronic hepatitis C: comparison with PIIINP and hyaluronic acid. Am J Gastroenterol 2004, 99: 271-279. 10.1111/j.1572-0241.2004.04055.xPubMedGoogle Scholar
  46. Murawaki Y, Ikuta Y, Nishimura Y, Koda M, Kawasaki H: Serum markers for connective tissue turnover in patients with chronic hepatitis B and chronic hepatitis C: a comparative analysis. J Hepatol 1995, 23: 145-152. 10.1016/0168-8278(95)80328-9PubMedGoogle Scholar
  47. Murawaki Y, Ikuta Y, Okamoto K, Koda M, Kawasaki H: Diagnostic value of serum markers of connective tissue turnover for predicting histological staging and grading in patients with chronic hepatitis C. J Gastroenterol 2001, 36: 399-406. 10.1007/s005350170084PubMedGoogle Scholar
  48. Suzuki A, Angulo P, Lymp J, Li D, Satomura S, Lindor K: Hyaluronic acid, an accurate serum marker for severe hepatic fibrosis in patients with non-alcoholic fatty liver disease. Liver Int 2005, 25: 779-786. 10.1111/j.1478-3231.2005.01064.xPubMedGoogle Scholar
  49. Halfon P, Bourliere M, Penaranda G, Deydier R, Renou C, Botta-Fridlund D, Tran A, Portal I, Allemand I, Rosenthal-Allieri A, Ouzan D: Accuracy of hyaluronic acid level for predicting liver fibrosis stages in patients with hepatitis C virus. Comp Hepatol 2005, 4: 6. 10.1186/1476-5926-4-6PubMed CentralPubMedGoogle Scholar
  50. Hakala BE, White C, Recklies AD: Human cartilage gp-39, a major secretory product of articular chondrocytes and synovial cells, is a mammalian member of a chitinase protein family. J Biol Chem 1993, 268: 25803-25810.PubMedGoogle Scholar
  51. Saitou Y, Shiraki K, Yamanaka Y, Yamaguchi Y, Kawakita T, Yamamoto N, Sugimoto K, Murata K, Nakano T: Noninvasive estimation of liver fibrosis and response to interferon therapy by a serum fibrogenesis marker, YKL-40, in patients with HCV-associated liver disease. World J Gastroenterol 2005, 11: 476-481.PubMed CentralPubMedGoogle Scholar
  52. Sanvisens A, Serra I, Tural C, Tor J, Ojanguren I, Barluenga E, Rey-Joly C, Clotet B, Muga R: Hyaluronic acid, transforming growth factor-beta1 and hepatic fibrosis in patients with chronic hepatitis C virus and human immunodeficiency virus co-infection. J Viral Hepat 2009, 16: 513-518. 10.1111/j.1365-2893.2009.01103.xPubMedGoogle Scholar
  53. Schiavon LL, Carvalho-Filho RJ, Narciso-Schiavon JL, Medina-Pestana JO, Lanzoni VP, Ferraz ML, Silva AE: YKL-40 and hyaluronic acid (HA) as noninvasive markers of liver fibrosis in kidney transplant patients with HCV chronic infection. Scand J Gastroenterol 2010, 45: 615-622. 10.3109/00365521003637203PubMedGoogle Scholar
  54. Felig P: The glucose-alanine cycle. Metabolism 1973, 22: 179-207. 10.1016/0026-0495(73)90269-2PubMedGoogle Scholar
  55. Daxboeck F, Gattringer R, Mustafa S, Bauer C, Assadian O: Elevated serum alanine aminotransferase (ALT) levels in patients with serologically verified Mycoplasma pneumoniae pneumonia. Clin Microbiol Infect 2005, 11: 507-510. 10.1111/j.1469-0691.2005.01154.xPubMedGoogle Scholar
  56. Sherman KE: Alanine aminotransferase in clinical practice. A review. Arch Intern Med 1991, 151: 260-265. 10.1001/archinte.151.2.260PubMedGoogle Scholar
  57. Dufour DR, Lott JA, Nolte FS, Gretch DR, Koff RS, Seeff LB: Diagnosis and monitoring of hepatic injury. I. Performance characteristics of laboratory tests. Clin Chem 2000, 46: 2027-2049.PubMedGoogle Scholar
  58. Akkaya O, Kiyici M, Yilmaz Y, Ulukaya E, Yerci O: Clinical significance of activity of ALT enzyme in patients with hepatitis C virus. World J Gastroenterol 2007, 13: 5481-5485.PubMed CentralPubMedGoogle Scholar
  59. Kim HJ, Oh SW, Kim DJ, Choi EY: Abundance of immunologically active alanine aminotransferase in sera of liver cirrhosis and hepatocellular carcinoma patients. Clin Chem 2009, 55: 1022-1025. 10.1373/clinchem.2008.102996PubMedGoogle Scholar
  60. Shiffman ML, Diago M, Tran A, Pockros P, Reindollar R, Prati D, Rodriguez-Torres M, Lardelli P, Blotner S, Zeuzem S: Chronic hepatitis C in patients with persistently normal alanine transaminase levels. Clin Gastroenterol Hepatol 2006, 4: 645-652. 10.1016/j.cgh.2006.02.002PubMedGoogle Scholar
  61. Okuda M, Li K, Beard MR, Showalter LA, Scholle F, Lemon SM, Weinman SA: Mitochondrial injury, oxidative stress, and antioxidant gene expression are induced by hepatitis C virus core protein. Gastroenterology 2002, 122: 366-375. 10.1053/gast.2002.30983PubMedGoogle Scholar
  62. Zechini B, Pasquazzi C, Aceti A: Correlation of serum aminotransferases with HCV RNA levels and histological findings in patients with chronic hepatitis C: the role of serum aspartate transaminase in the evaluation of disease progression. Eur J Gastroenterol Hepatol 2004, 16: 891-896. 10.1097/00042737-200409000-00013PubMedGoogle Scholar
  63. Cedrone A, Covino M, Caturelli E, Pompili M, Lorenzelli G, Villani MR, Valle D, Sperandeo M, Rapaccini GL, Gasbarrini G: Utility of alpha-fetoprotein (AFP) in the screening of patients with virus-related chronic liver disease: does different viral etiology influence AFP levels in HCC? A study in 350 western patients. Hepatogastroenterology 2000, 47: 1654-1658.PubMedGoogle Scholar
  64. Chu CW, Hwang SJ, Luo JC, Lai CR, Tsay SH, Li CP, Wu JC, Chang FY, Lee SD: Clinical, virologic, and pathologic significance of elevated serum alpha-fetoprotein levels in patients with chronic hepatitis C. J Clin Gastroenterol 2001, 32: 240-244. 10.1097/00004836-200103000-00014PubMedGoogle Scholar
  65. Chen TM, Huang PT, Tsai MH, Lin LF, Liu CC, Ho KS, Siauw CP, Chao PL, Tung JN: Predictors of alpha-fetoprotein elevation in patients with chronic hepatitis C, but not hepatocellular carcinoma, and its normalization after pegylated interferon alfa 2a-ribavirin combination therapy. J Gastroenterol Hepatol 2007, 22: 669-675. 10.1111/j.1440-1746.2007.04898.xPubMedGoogle Scholar
  66. Tamura Y, Yamagiwa S, Aoki Y, Kurita S, Suda T, Ohkoshi S, Nomoto M, Aoyagi Y: Serum alpha-fetoprotein levels during and after interferon therapy and the development of hepatocellular carcinoma in patients with chronic hepatitis C. Dig Dis Sci 2009, 54: 2530-2537. 10.1007/s10620-008-0642-yPubMedGoogle Scholar
  67. Aster RH: Pooling of platelets in the spleen: role in the pathogenesis of "hypersplenic" thrombocytopenia. J Clin Invest 1966, 45: 645-657. 10.1172/JCI105380PubMed CentralPubMedGoogle Scholar
  68. Kawasaki T, Takeshita A, Souda K, Kobayashi Y, Kikuyama M, Suzuki F, Kageyama F, Sasada Y, Shimizu E, Murohisa G, et al.: Serum thrombopoietin levels in patients with chronic hepatitis and liver cirrhosis. Am J Gastroenterol 1999, 94: 1918-1922. 10.1111/j.1572-0241.1999.01231.xPubMedGoogle Scholar
  69. Adinolfi LE, Giordano MG, Andreana A, Tripodi MF, Utili R, Cesaro G, Ragone E, Durante Mangoni E, Ruggiero G: Hepatic fibrosis plays a central role in the pathogenesis of thrombocytopenia in patients with chronic viral hepatitis. Br J Haematol 2001, 113: 590-595. 10.1046/j.1365-2141.2001.02824.xPubMedGoogle Scholar
  70. Lackner C, Struber G, Liegl B, Leibl S, Ofner P, Bankuti C, Bauer B, Stauber RE: Comparison and validation of simple noninvasive tests for prediction of fibrosis in chronic hepatitis C. Hepatology 2005, 41: 1376-1382. 10.1002/hep.20717PubMedGoogle Scholar
  71. Croquet V, Vuillemin E, Ternisien C, Pilette C, Oberti F, Gallois Y, Trossaert M, Rousselet MC, Chappard D, Cales P: Prothrombin index is an indirect marker of severe liver fibrosis. Eur J Gastroenterol Hepatol 2002, 14: 1133-1141. 10.1097/00042737-200210000-00015PubMedGoogle Scholar
  72. Pilette C, Oberti F, Aube C, Rousselet MC, Bedossa P, Gallois Y, Rifflet H, Cales P: Non-invasive diagnosis of esophageal varices in chronic liver diseases. J Hepatol 1999, 31: 867-873. 10.1016/S0168-8278(99)80288-8PubMedGoogle Scholar
  73. Craxi A, Camma C, Giunta M: Clinical aspects of bleeding complications in cirrhotic patients. Blood Coagul Fibrinolysis 2000,11(Suppl 1):S75-79.PubMedGoogle Scholar
  74. Sheth SG, Flamm SL, Gordon FD, Chopra S: AST/ALT ratio predicts cirrhosis in patients with chronic hepatitis C virus infection. Am J Gastroenterol 1998, 93: 44-48. 10.1111/j.1572-0241.1998.044_c.xPubMedGoogle Scholar
  75. Reedy DW, Loo AT, Levine RA: AST/ALT ratio > or = 1 is not diagnostic of cirrhosis in patients with chronic hepatitis C. Dig Dis Sci 1998, 43: 2156-2159. 10.1023/A:1018888021118PubMedGoogle Scholar
  76. Giannini E, Risso D, Botta F, Chiarbonello B, Fasoli A, Malfatti F, Romagnoli P, Testa E, Ceppa P, Testa R: Validity and clinical utility of the aspartate aminotransferase-alanine aminotransferase ratio in assessing disease severity and prognosis in patients with hepatitis C virus-related chronic liver disease. Arch Intern Med 2003, 163: 218-224. 10.1001/archinte.163.2.218PubMedGoogle Scholar
  77. Fujii H, Enomoto M, Fukushima W, Ohfuji S, Mori M, Kobayashi S, Iwai S, Morikawa H, Tamori A, Sakaguchi H, et al.: Noninvasive laboratory tests proposed for predicting cirrhosis in patients with chronic hepatitis C are also useful in patients with non-alcoholic steatohepatitis. J Gastroenterol 2009, 44: 608-614. 10.1007/s00535-009-0046-6PubMedGoogle Scholar
  78. Poynard T, Morra R, Halfon P, Castera L, Ratziu V, Imbert-Bismut F, Naveau S, Thabut D, Lebrec D, Zoulim F, et al.: Meta-analyses of FibroTest diagnostic value in chronic liver disease. BMC Gastroenterol 2007, 7: 40. 10.1186/1471-230X-7-40PubMed CentralPubMedGoogle Scholar
  79. Cales P, Oberti F, Michalak S, Hubert-Fouchard I, Rousselet MC, Konate A, Gallois Y, Ternisien C, Chevailler A, Lunel F: A novel panel of blood markers to assess the degree of liver fibrosis. Hepatology 2005, 42: 1373-1381. 10.1002/hep.20935PubMedGoogle Scholar
  80. Bourliere M, Penaranda G, Renou C, Botta-Fridlund D, Tran A, Portal I, Lecomte L, Castellani P, Rosenthal-Allieri MA, Gerolami R, et al.: Validation and comparison of indexes for fibrosis and cirrhosis prediction in chronic hepatitis C patients: proposal for a pragmatic approach classification without liver biopsies. J Viral Hepat 2006, 13: 659-670. 10.1111/j.1365-2893.2006.00736.xPubMedGoogle Scholar
  81. Parise ER, Oliveira AC, Figueiredo-Mendes C, Lanzoni V, Martins J, Nader H, Ferraz ML: Noninvasive serum markers in the diagnosis of structural liver damage in chronic hepatitis C virus infection. Liver Int 2006, 26: 1095-1099. 10.1111/j.1478-3231.2006.01356.xPubMedGoogle Scholar
  82. de Ledinghen V, Douvin C, Kettaneh A, Ziol M, Roulot D, Marcellin P, Dhumeaux D, Beaugrand M: Diagnosis of hepatic fibrosis and cirrhosis by transient elastography in HIV/hepatitis C virus-coinfected patients. J Acquir Immune Defic Syndr 2006, 41: 175-179. 10.1097/01.qai.0000194238.15831.c7PubMedGoogle Scholar
  83. Halfon P, Bacq Y, De Muret A, Penaranda G, Bourliere M, Ouzan D, Tran A, Botta D, Renou C, Brechot MC, et al.: Comparison of test performance profile for blood tests of liver fibrosis in chronic hepatitis C. J Hepatol 2007, 46: 395-402. 10.1016/j.jhep.2006.09.020PubMedGoogle Scholar
  84. Leroy V, Halfon P, Bacq Y, Boursier J, Rousselet MC, Bourliere M, de Muret A, Sturm N, Hunault G, Penaranda G, 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. 10.1016/j.clinbiochem.2008.06.020PubMedGoogle Scholar
  85. Cales P, de Ledinghen V, Halfon P, Bacq Y, Leroy V, Boursier J, Foucher J, Bourliere M, de Muret A, Sturm N, et al.: Evaluating the accuracy and increasing the reliable diagnosis rate of blood tests for liver fibrosis in chronic hepatitis C. Liver Int 2008, 28: 1352-1362. 10.1111/j.1478-3231.2008.01789.xPubMed CentralPubMedGoogle Scholar
  86. Kamphues C, Lotz K, Rocken C, Berg T, Eurich D, Pratschke J, Neuhaus P, Neumann UP: Chances and limitations of non-invasive tests in the assessment of liver fibrosis in liver transplant patients. Clin Transplant 2010, 24: 652-659. 10.1111/j.1399-0012.2009.01152.xPubMedGoogle Scholar
  87. Teare JP, Sherman D, Greenfield SM, Simpson J, Bray G, Catterall AP, Murray-Lyon IM, Peters TJ, Williams R, Thompson RP: Comparison of serum procollagen III peptide concentrations and PGA index for assessment of hepatic fibrosis. Lancet 1993, 342: 895-898. 10.1016/0140-6736(93)91946-JPubMedGoogle Scholar
  88. Naveau S, Poynard T, Benattar C, Bedossa P, Chaput JC: Alpha-2-macroglobulin and hepatic fibrosis. Diagnostic interest. Dig Dis Sci 1994, 39: 2426-2432. 10.1007/BF02087661PubMedGoogle Scholar
  89. Oberti F, Valsesia E, Pilette C, Rousselet MC, Bedossa P, Aube C, Gallois Y, Rifflet H, Maiga MY, Penneau-Fontbonne D, Cales P: Noninvasive diagnosis of hepatic fibrosis or cirrhosis. Gastroenterology 1997, 113: 1609-1616. 10.1053/gast.1997.v113.pm9352863PubMedGoogle Scholar
  90. Poynard T, McHutchison J, Manns M, Myers RP, Albrecht J: Biochemical surrogate markers of liver fibrosis and activity in a randomized trial of peginterferon alfa-2b and ribavirin. Hepatology 2003, 38: 481-492. 10.1053/jhep.2003.50319PubMedGoogle Scholar
  91. Poynard T, Munteanu M, Imbert-Bismut F, Charlotte F, Thabut D, Le Calvez S, Messous D, Thibault V, Benhamou Y, Moussalli J, Ratziu V: Prospective analysis of discordant results between biochemical markers and biopsy in patients with chronic hepatitis C. Clin Chem 2004, 50: 1344-1355. 10.1373/clinchem.2004.032227PubMedGoogle Scholar
  92. Naveau S, Raynard B, Ratziu V, Abella A, Imbert-Bismut F, Messous D, Beuzen F, Capron F, Thabut D, Munteanu M, et al.: Biomarkers for the prediction of liver fibrosis in patients with chronic alcoholic liver disease. Clin Gastroenterol Hepatol 2005, 3: 167-174. 10.1016/S1542-3565(04)00625-1PubMedGoogle Scholar
  93. Sebastiani G, Alberti A: Non invasive fibrosis biomarkers reduce but not substitute the need for liver biopsy. World J Gastroenterol 2006, 12: 3682-3694.PubMed CentralPubMedGoogle Scholar
  94. Friedrich-Rust M, Rosenberg W, Parkes J, Herrmann E, Zeuzem S, Sarrazin C: Comparison of ELF, FibroTest and FibroScan for the non-invasive assessment of liver fibrosis. BMC Gastroenterol 2010, 10: 103. 10.1186/1471-230X-10-103PubMed CentralPubMedGoogle Scholar
  95. Halfon P, Imbert-Bismut F, Messous D, Antoniotti G, Benchetrit D, Cart-Lamy P, Delaporte G, Doutheau D, Klump T, Sala M, et al.: A prospective assessment of the inter-laboratory variability of biochemical markers of fibrosis (FibroTest) and activity (ActiTest) in patients with chronic liver disease. Comp Hepatol 2002, 1: 3. 10.1186/1476-5926-1-3PubMed CentralPubMedGoogle Scholar
  96. Poynard T, Imbert-Bismut F, Ratziu V, Chevret S, Jardel C, Moussalli J, Messous D, Degos F: Biochemical markers of liver fibrosis in patients infected by hepatitis C virus: longitudinal validation in a randomized trial. J Viral Hepat 2002, 9: 128-133. 10.1046/j.1365-2893.2002.00341.xPubMedGoogle Scholar
  97. Rossi E, Adams L, Prins A, Bulsara M, de Boer B, Garas G, MacQuillan G, Speers D, Jeffrey G: Validation of the FibroTest biochemical markers score in assessing liver fibrosis in hepatitis C patients. Clin Chem 2003, 49: 450-454. 10.1373/49.3.450PubMedGoogle Scholar
  98. Ngo Y, Munteanu M, Messous D, Charlotte F, Imbert-Bismut F, Thabut D, Lebray P, Thibault V, Benhamou Y, Moussalli J, et al.: A prospective analysis of the prognostic value of biomarkers (FibroTest) in patients with chronic hepatitis C. Clin Chem 2006, 52: 1887-1896. 10.1373/clinchem.2006.070961PubMedGoogle Scholar
  99. Halfon P, Bourliere M, Deydier R, Botta-Fridlund D, Renou C, Tran A, Portal I, Allemand I, Bertrand JJ, Rosenthal-Allieri A, et al.: Independent prospective multicenter validation of biochemical markers (fibrotest-actitest) for the prediction of liver fibrosis and activity in patients with chronic hepatitis C: the fibropaca study. Am J Gastroenterol 2006, 101: 547-555. 10.1111/j.1572-0241.2006.00411.xPubMedGoogle Scholar
  100. Halfon P, Munteanu M, Poynard T: FibroTest-ActiTest as a non-invasive marker of liver fibrosis. Gastroenterol Clin Biol 2008, 32: 22-39. 10.1016/S0399-8320(08)73991-5PubMedGoogle Scholar
  101. Myers RP, De Torres M, Imbert-Bismut F, Ratziu V, Charlotte F, Poynard T: Biochemical markers of fibrosis in patients with chronic hepatitis C: a comparison with prothrombin time, platelet count, and age-platelet index. Dig Dis Sci 2003, 48: 146-153. 10.1023/A:1021702902681PubMedGoogle Scholar
  102. Bedossa P, Dargere D, Paradis V: Sampling variability of liver fibrosis in chronic hepatitis C. Hepatology 2003, 38: 1449-1457.PubMedGoogle Scholar
  103. Colletta C, Smirne C, Fabris C, Toniutto P, Rapetti R, Minisini R, Pirisi M: Value of two noninvasive methods to detect progression of fibrosis among HCV carriers with normal aminotransferases. Hepatology 2005, 42: 838-845. 10.1002/hep.20814PubMedGoogle Scholar
  104. Shaheen AA, Myers RP: Systematic review and meta-analysis of the diagnostic accuracy of fibrosis marker panels in patients with HIV/hepatitis C coinfection. HIV Clin Trials 2008, 9: 43-51. 10.1310/hct0901-43PubMedGoogle Scholar
  105. Cales P, Boursier J, Bertrais S, Oberti F, Gallois Y, Fouchard-Hubert I, Dib N, Zarski JP, Rousselet MC: Optimization and robustness of blood tests for liver fibrosis and cirrhosis. Clin Biochem 2010, 43: 1315-1322. 10.1016/j.clinbiochem.2010.08.010PubMedGoogle Scholar
  106. Koda M, Matunaga Y, Kawakami M, Kishimoto Y, Suou T, Murawaki Y: FibroIndex, a practical index for predicting significant fibrosis in patients with chronic hepatitis C. Hepatology 2007, 45: 297-306. 10.1002/hep.21520PubMedGoogle Scholar
  107. Lee MH, Cheong JY, Um SH, Seo YS, Kim DJ, Hwang SG, Yang JM, Han KH, Cho SW: Comparison of surrogate serum markers and transient elastography (Fibroscan) for assessing cirrhosis in patients with chronic viral hepatitis. Dig Dis Sci 2010, 55: 3552-3560. 10.1007/s10620-010-1219-0PubMedGoogle Scholar
  108. El-Shabrawi MH, Mohsen NA, Sherif MM, El-Karaksy HM, Abou-Yosef H, El-Sayed HM, Riad H, Bahaa N, Isa M, El-Hennawy A: Noninvasive assessment of hepatic fibrosis and necroinflammatory activity in Egyptian children with chronic hepatitis C virus infection using FibroTest and ActiTest. Eur J Gastroenterol Hepatol 2010, 22: 946-951. 10.1097/MEG.0b013e328336ec84PubMedGoogle Scholar
  109. Poynard T, Ratziu V, Naveau S, Thabut D, Charlotte F, Messous D, Capron D, Abella A, Massard J, Ngo Y, et al.: The diagnostic value of biomarkers (SteatoTest) for the prediction of liver steatosis. Comp Hepatol 2005, 4: 10. 10.1186/1476-5926-4-10PubMed CentralPubMedGoogle Scholar
  110. Lok AS, Ghany MG, Goodman ZD, Wright EC, Everson GT, Sterling RK, Everhart JE, Lindsay KL, Bonkovsky HL, Di Bisceglie AM, et al.: Predicting cirrhosis in patients with hepatitis C based on standard laboratory tests: results of the HALT-C cohort. Hepatology 2005, 42: 282-292. 10.1002/hep.20772PubMedGoogle Scholar
  111. Cheong JY, Um SH, Seo YS, Kim DJ, Hwang SG, Lee YJ, Cho M, Yang JM, Kim YB, Park YN, Cho SW: Non-Invasive Index for Predicting Significant Liver Fibrosis: Comparison of Diagnostic Performances in Patients with Chronic Hepatitis B and C. Dig Dis Sci 2010, 56: 555-563. 10.1007/s10620-010-1305-3PubMedGoogle Scholar
  112. Islam S, Antonsson L, Westin J, Lagging M: Cirrhosis in hepatitis C virus-infected patients can be excluded using an index of standard biochemical serum markers. Scand J Gastroenterol 2005, 40: 867-872. 10.1080/00365520510015674PubMedGoogle Scholar
  113. Ohta T, Sakaguchi K, Fujiwara A, Fujioka S, Iwasaki Y, Makino Y, Araki Y, Shiratori Y: Simple surrogate index of the fibrosis stage in chronic hepatitis C patients using platelet count and serum albumin level. Acta Med Okayama 2006, 60: 77-84.PubMedGoogle Scholar
  114. Pohl A, Behling C, Oliver D, Kilani M, Monson P, Hassanein T: Serum aminotransferase levels and platelet counts as predictors of degree of fibrosis in chronic hepatitis C virus infection. Am J Gastroenterol 2001, 96: 3142-3146. 10.1111/j.1572-0241.2001.05268.xPubMedGoogle Scholar
  115. Cheung RC, Currie S, Shen H, Bini EJ, Ho SB, Anand BS, Hu KQ, Wright TL, Morgan TR: Can we predict the degree of fibrosis in chronic hepatitis C patients using routine blood tests in our daily practice? J Clin Gastroenterol 2008, 42: 827-834. 10.1097/MCG.0b013e318046ea9aPubMedGoogle Scholar
  116. Bonacini M, Hadi G, Govindarajan S, Lindsay KL: Utility of a discriminant score for diagnosing advanced fibrosis or cirrhosis in patients with chronic hepatitis C virus infection. Am J Gastroenterol 1997, 92: 1302-1304.PubMedGoogle Scholar
  117. Adams LA, Bulsara M, Rossi E, DeBoer B, Speers D, George J, Kench J, Farrell G, McCaughan GW, Jeffrey GP: Hepascore: an accurate validated predictor of liver fibrosis in chronic hepatitis C infection. Clin Chem 2005, 51: 1867-1873. 10.1373/clinchem.2005.048389PubMedGoogle Scholar
  118. Leroy V, Hilleret MN, Sturm N, Trocme C, Renversez JC, Faure P, Morel F, Zarski JP: Prospective comparison of six non-invasive scores for the diagnosis of liver fibrosis in chronic hepatitis C. J Hepatol 2007, 46: 775-782. 10.1016/j.jhep.2006.12.013PubMedGoogle Scholar
  119. Becker L, Salameh W, Sferruzza A, Zhang K, ng Chen R, Malik R, Reitz R, Nasser I, Afdhal NH: Validation of hepascore, compared with simple indices of fibrosis, in patients with chronic hepatitis C virus infection in United States. Clin Gastroenterol Hepatol 2009, 7: 696-701. 10.1016/j.cgh.2009.01.010PubMedGoogle Scholar
  120. Guechot J, Lasnier E, Sturm N, Paris A, Zarski JP: Automation of the Hepascore and validation as a biochemical index of liver fibrosis in patients with chronic hepatitis C from the ANRS HC EP 23 Fibrostar cohort. Clin Chim Acta 2010, 411: 86-91. 10.1016/j.cca.2009.10.011PubMedGoogle Scholar
  121. Kelleher TB, Mehta SH, Bhaskar R, Sulkowski M, Astemborski J, Thomas DL, Moore RE, Afdhal NH: Prediction of hepatic fibrosis in HIV/HCV co-infected patients using serum fibrosis markers: the SHASTA index. J Hepatol 2005, 43: 78-84. 10.1016/j.jhep.2005.02.025PubMedGoogle Scholar
  122. Sterling RK, Lissen E, Clumeck N, Sola R, Correa MC, Montaner J, M SS, Torriani FJ, Dieterich DT, Thomas DL, et al.: Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV coinfection. Hepatology 2006, 43: 1317-1325. 10.1002/hep.21178PubMedGoogle Scholar
  123. Vallet-Pichard A, Mallet V, Nalpas B, Verkarre V, Nalpas A, Dhalluin-Venier V, Fontaine H, Pol S: FIB-4: an inexpensive and accurate marker of fibrosis in HCV infection. comparison with liver biopsy and fibrotest. Hepatology 2007, 46: 32-36. 10.1002/hep.21669PubMedGoogle Scholar
  124. Mallet V, Dhalluin-Venier V, Roussin C, Bourliere M, Pettinelli ME, Giry C, Vallet-Pichard A, Fontaine H, Pol S: The accuracy of the FIB-4 index for the diagnosis of mild fibrosis in chronic hepatitis B. Aliment Pharmacol Ther 2009, 29: 409-415. 10.1111/j.1365-2036.2008.03895.xPubMedGoogle Scholar
  125. Sud A, Hui JM, Farrell GC, Bandara P, Kench JG, Fung C, Lin R, Samarasinghe D, Liddle C, McCaughan GW, George J: Improved prediction of fibrosis in chronic hepatitis C using measures of insulin resistance in a probability index. Hepatology 2004, 39: 1239-1247. 10.1002/hep.20207PubMedGoogle Scholar
  126. Testa R, Testa E, Giannini E, Borro P, Milazzo S, Isola L, Ceppa P, Lantieri PB, Risso D: Noninvasive ratio indexes to evaluate fibrosis staging in chronic hepatitis C: role of platelet count/spleen diameter ratio index. J Intern Med 2006, 260: 142-150. 10.1111/j.1365-2796.2006.01673.xPubMedGoogle Scholar
  127. Fortunato G, Castaldo G, Oriani G, Cerini R, Intrieri M, Molinaro E, Gentile I, Borgia G, Piazza M, Salvatore F, Sacchetti L: Multivariate discriminant function based on six biochemical markers in blood can predict the cirrhotic evolution of chronic hepatitis. Clin Chem 2001, 47: 1696-1700.PubMedGoogle Scholar
  128. Aube C, Oberti F, Korali N, Namour MA, Loisel D, Tanguy JY, Valsesia E, Pilette C, Rousselet MC, Bedossa P, et al.: Ultrasonographic diagnosis of hepatic fibrosis or cirrhosis. J Hepatol 1999, 30: 472-478. 10.1016/S0168-8278(99)80107-XPubMedGoogle Scholar
  129. Mathiesen UL, Franzen LE, Aselius H, Resjo M, Jacobsson L, Foberg U, Fryden A, Bodemar G: Increased liver echogenicity at ultrasound examination reflects degree of steatosis but not of fibrosis in asymptomatic patients with mild/moderate abnormalities of liver transaminases. Dig Liver Dis 2002, 34: 516-522. 10.1016/S1590-8658(02)80111-6PubMedGoogle Scholar
  130. Colli A, Fraquelli M, Andreoletti M, Marino B, Zuccoli E, Conte D: Severe liver fibrosis or cirrhosis: accuracy of US for detection--analysis of 300 cases. Radiology 2003, 227: 89-94. 10.1148/radiol.2272020193PubMedGoogle Scholar
  131. Zheng RQ, Wang QH, Lu MD, Xie SB, Ren J, Su ZZ, Cai YK, Yao JL: Liver fibrosis in chronic viral hepatitis: an ultrasonographic study. World J Gastroenterol 2003, 9: 2484-2489.PubMed CentralPubMedGoogle Scholar
  132. Colli A, Colucci A, Paggi S, Fraquelli M, Massironi S, Andreoletti M, Michela V, Conte D: Accuracy of a predictive model for severe hepatic fibrosis or cirrhosis in chronic hepatitis C. World J Gastroenterol 2005, 11: 7318-7322.PubMed CentralPubMedGoogle Scholar
  133. Shen L, Li JQ, Zeng MD, Lu LG, Fan ST, Bao H: Correlation between ultrasonographic and pathologic diagnosis of liver fibrosis due to chronic virus hepatitis. World J Gastroenterol 2006, 12: 1292-1295.PubMed CentralPubMedGoogle Scholar
  134. Sandrin L, Tanter M, Gennisson JL, Catheline S, Fink M: Shear elasticity probe for soft tissues with 1-D transient elastography. IEEE Trans Ultrason Ferroelectr Freq Control 2002, 49: 436-446. 10.1109/58.996561PubMedGoogle Scholar
  135. Sandrin L, Fourquet B, Hasquenoph JM, Yon S, Fournier C, Mal F, Christidis C, Ziol M, Poulet B, Kazemi F, et al.: Transient elastography: a new noninvasive method for assessment of hepatic fibrosis. Ultrasound Med Biol 2003, 29: 1705-1713. 10.1016/j.ultrasmedbio.2003.07.001PubMedGoogle Scholar
  136. Colloredo G, Guido M, Sonzogni A, Leandro G: Impact of liver biopsy size on histological evaluation of chronic viral hepatitis: the smaller the sample, the milder the disease. J Hepatol 2003, 39: 239-244. 10.1016/S0168-8278(03)00191-0PubMedGoogle Scholar
  137. Cobbold JF, Morin S, Taylor-Robinson SD: Transient elastography for the assessment of chronic liver disease: ready for the clinic? World J Gastroenterol 2007, 13: 4791-4797.PubMed CentralPubMedGoogle Scholar
  138. Kettaneh A, Marcellin P, Douvin C, Poupon R, Ziol M, Beaugrand M, de Ledinghen V: Features associated with success rate and performance of FibroScan measurements for the diagnosis of cirrhosis in HCV patients: a prospective study of 935 patients. J Hepatol 2007, 46: 628-634. 10.1016/j.jhep.2006.11.010PubMedGoogle Scholar
  139. Foucher J, Chanteloup E, Vergniol J, Castera L, Le Bail B, Adhoute X, Bertet J, Couzigou P, de Ledinghen V: Diagnosis of cirrhosis by transient elastography (FibroScan): a prospective study. Gut 2006, 55: 403-408. 10.1136/gut.2005.069153PubMed CentralPubMedGoogle Scholar
  140. Maor Y, Halfon P, Bashari D, Penaranda G, Morali G, Klar R, Bar-Meir S, Martinowitz U, Oren R: Fibrotest or Fibroscan for evaluation of liver fibrosis in haemophilia patients infected with hepatitis C. Haemophilia 2010, 16: 148-154. 10.1111/j.1365-2516.2009.02092.xPubMedGoogle Scholar
  141. Friedrich-Rust M, Ong MF, Herrmann E, Dries V, Samaras P, Zeuzem S, Sarrazin C: Real-time elastography for noninvasive assessment of liver fibrosis in chronic viral hepatitis. AJR Am J Roentgenol 2007, 188: 758-764. 10.2214/AJR.06.0322PubMedGoogle Scholar
  142. Fraquelli M, Rigamonti C, Casazza G, Conte D, Donato MF, Ronchi G, Colombo M: Reproducibility of transient elastography in the evaluation of liver fibrosis in patients with chronic liver disease. Gut 2007, 56: 968-973. 10.1136/gut.2006.111302PubMed CentralPubMedGoogle Scholar
  143. Vizzutti F, Arena U, Romanelli RG, Rega L, Foschi M, Colagrande S, Petrarca A, Moscarella S, Belli G, Zignego AL, et al.: Liver stiffness measurement predicts severe portal hypertension in patients with HCV-related cirrhosis. Hepatology 2007, 45: 1290-1297. 10.1002/hep.21665PubMedGoogle Scholar
  144. de Ledinghen V, Vergniol J: Transient elastography for the diagnosis of liver fibrosis. Expert Rev Med Devices 2010, 7: 811-823. 10.1586/erd.10.46PubMedGoogle Scholar
  145. Corpechot C, El Naggar A, Poujol-Robert A, Ziol M, Wendum D, Chazouilleres O, de Ledinghen V, Dhumeaux D, Marcellin P, Beaugrand M, Poupon R: Assessment of biliary fibrosis by transient elastography in patients with PBC and PSC. Hepatology 2006, 43: 1118-1124. 10.1002/hep.21151PubMedGoogle Scholar
  146. Ganne-Carrie N, Ziol M, de Ledinghen V, Douvin C, Marcellin P, Castera L, Dhumeaux D, Trinchet JC, Beaugrand M: Accuracy of liver stiffness measurement for the diagnosis of cirrhosis in patients with chronic liver diseases. Hepatology 2006, 44: 1511-1517. 10.1002/hep.21420PubMedGoogle Scholar
  147. Shaheen AA, Wan AF, Myers RP: FibroTest and FibroScan for the prediction of hepatitis C-related fibrosis: a systematic review of diagnostic test accuracy. Am J Gastroenterol 2007, 102: 2589-2600. 10.1111/j.1572-0241.2007.01466.xPubMedGoogle Scholar
  148. Friedrich-Rust M, Wunder K, Kriener S, Sotoudeh F, Richter S, Bojunga J, Herrmann E, Poynard T, Dietrich CF, Vermehren J, et al.: Liver fibrosis in viral hepatitis: noninvasive assessment with acoustic radiation force impulse imaging versus transient elastography. Radiology 2009, 252: 595-604. 10.1148/radiol.2523081928PubMedGoogle Scholar
  149. Sanchez-Conde M, Montes-Ramirez ML, Miralles P, Alvarez JM, Bellon JM, Ramirez M, Arribas JR, Gutierrez I, Lopez JC, Cosin J, et al.: Comparison of transient elastography and liver biopsy for the assessment of liver fibrosis in HIV/hepatitis C virus-coinfected patients and correlation with noninvasive serum markers. J Viral Hepat 2010, 17: 280-286. 10.1111/j.1365-2893.2009.01180.xPubMedGoogle Scholar
  150. Abu-Yousef MM: Duplex Doppler sonography of the hepatic vein in tricuspid regurgitation. AJR Am J Roentgenol 1991, 156: 79-83.PubMedGoogle Scholar
  151. Albrecht T, Blomley MJ, Cosgrove DO, Taylor-Robinson SD, Jayaram V, Eckersley R, Urbank A, Butler-Barnes J, Patel N: Non-invasive diagnosis of hepatic cirrhosis by transit-time analysis of an ultrasound contrast agent. Lancet 1999, 353: 1579-1583. 10.1016/S0140-6736(98)06373-9PubMedGoogle Scholar
  152. Hirata M, Akbar SM, Horiike N, Onji M: Noninvasive diagnosis of the degree of hepatic fibrosis using ultrasonography in patients with chronic liver disease due to hepatitis C virus. Eur J Clin Invest 2001, 31: 528-535. 10.1046/j.1365-2362.2001.00840.xPubMedGoogle Scholar
  153. Bonekamp S, Kamel I, Solga S, Clark J: Can imaging modalities diagnose and stage hepatic fibrosis and cirrhosis accurately? J Hepatol 2009, 50: 17-35. 10.1016/j.jhep.2008.10.016PubMedGoogle Scholar
  154. Lucidarme O, Baleston F, Cadi M, Bellin MF, Charlotte F, Ratziu V, Grenier PA: Non-invasive detection of liver fibrosis: Is superparamagnetic iron oxide particle-enhanced MR imaging a contributive technique? Eur Radiol 2003, 13: 467-474.PubMedGoogle Scholar
  155. Numminen K, Tervahartiala P, Halavaara J, Isoniemi H, Hockerstedt K: Non-invasive diagnosis of liver cirrhosis: magnetic resonance imaging presents special features. Scand J Gastroenterol 2005, 40: 76-82. 10.1080/00365520410009384PubMedGoogle Scholar
  156. Aguirre DA, Behling CA, Alpert E, Hassanein TI, Sirlin CB: Liver fibrosis: noninvasive diagnosis with double contrast material-enhanced MR imaging. Radiology 2006, 239: 425-437. 10.1148/radiol.2392050505PubMedGoogle Scholar
  157. Taura T, Nakamura K, Takashima S, Kaminou T, Yamada R, Shuto T, Wakasa K: Heterogeneity of hepatic parenchymal enhancement on computed tomography during arterial portography: quantitative analysis of correlation with severity of hepatic fibrosis. Hepatol Res 2001, 20: 182-192. 10.1016/S1386-6346(01)00074-2PubMedGoogle Scholar
  158. Materne R, Annet L, Dechambre S, Sempoux C, Smith AM, Corot C, Horsmans Y, Van Beers BE: Dynamic computed tomography with low- and high-molecular-mass contrast agents to assess microvascular permeability modifications in a model of liver fibrosis. Clin Sci (Lond) 2002, 103: 213-216. 10.1042/CS20020095Google Scholar
  159. Wang S, Fu D, Xu M, Hu D: Advanced fuzzy cellular neural network: application to CT liver images. Artif Intell Med 2007, 39: 65-77. 10.1016/j.artmed.2006.08.001PubMedGoogle Scholar
  160. Castera L, Vergniol J, Foucher J, Le Bail B, Chanteloup E, Haaser M, Darriet M, Couzigou P, De Ledinghen V: Prospective comparison of transient elastography, Fibrotest, APRI, and liver biopsy for the assessment of fibrosis in chronic hepatitis C. Gastroenterology 2005, 128: 343-350. 10.1053/j.gastro.2004.11.018PubMedGoogle Scholar
  161. Asselah T, Bieche I, Laurendeau I, Paradis V, Vidaud D, Degott C, Martinot M, Bedossa P, Valla D, Vidaud M, Marcellin P: Liver gene expression signature of mild fibrosis in patients with chronic hepatitis C. Gastroenterology 2005, 129: 2064-2075. 10.1053/j.gastro.2005.09.010PubMedGoogle Scholar
  162. Smith MW, Walters KA, Korth MJ, Fitzgibbon M, Proll S, Thompson JC, Yeh MM, Shuhart MC, Furlong JC, Cox PP, et al.: Gene expression patterns that correlate with hepatitis C and early progression to fibrosis in liver transplant recipients. Gastroenterology 2006, 130: 179-187. 10.1053/j.gastro.2005.08.015PubMedGoogle Scholar
  163. Huang H, Shiffman ML, Cheung RC, Layden TJ, Friedman S, Abar OT, Yee L, Chokkalingam AP, Schrodi SJ, Chan J, et al.: Identification of two gene variants associated with risk of advanced fibrosis in patients with chronic hepatitis C. Gastroenterology 2006, 130: 1679-1687. 10.1053/j.gastro.2006.02.032PubMedGoogle Scholar
  164. Machida K, Cheng KT, Sung VM, Levine AM, Foung S, Lai MM: Hepatitis C virus induces toll-like receptor 4 expression, leading to enhanced production of beta interferon and interleukin-6. J Virol 2006, 80: 866-874. 10.1128/JVI.80.2.866-874.2006PubMed CentralPubMedGoogle Scholar
  165. Huang H, Shiffman ML, Friedman S, Venkatesh R, Bzowej N, Abar OT, Rowland CM, Catanese JJ, Leong DU, Sninsky JJ, et al.: A 7 gene signature identifies the risk of developing cirrhosis in patients with chronic hepatitis C. Hepatology 2007, 46: 297-306. 10.1002/hep.21695PubMedGoogle Scholar
  166. Zeremski M, Petrovic LM, Chiriboga L, Brown QB, Yee HT, Kinkhabwala M, Jacobson IM, Dimova R, Markatou M, Talal AH: Intrahepatic levels of CXCR3-associated chemokines correlate with liver inflammation and fibrosis in chronic hepatitis C. Hepatology 2008, 48: 1440-1450. 10.1002/hep.22500PubMed CentralPubMedGoogle Scholar
  167. Zeremski M, Dimova R, Brown Q, Jacobson IM, Markatou M, Talal AH: Peripheral CXCR3-associated chemokines as biomarkers of fibrosis in chronic hepatitis C virus infection. J Infect Dis 2009, 200: 1774-1780. 10.1086/646614PubMedGoogle Scholar
  168. Kovalenko E, Tacke F, Gressner OA, Zimmermann HW, Lahme B, Janetzko A, Wiederholt T, Berg T, Muller T, Trautwein C, et al.: Validation of connective tissue growth factor (CTGF/CCN2) and its gene polymorphisms as noninvasive biomarkers for the assessment of liver fibrosis. J Viral Hepat 2009, 16: 612-620. 10.1111/j.1365-2893.2009.01110.xPubMedGoogle Scholar
  169. Sharma A, Chakraborti A, Das A, Dhiman RK, Chawla Y: Elevation of interleukin-18 in chronic hepatitis C: implications for hepatitis C virus pathogenesis. Immunology 2009, 128: e514-522. 10.1111/j.1365-2567.2008.03021.xPubMed CentralPubMedGoogle Scholar
  170. Caillot F, Hiron M, Goria O, Gueudin M, Francois A, Scotte M, Daveau M, Salier JP: Novel serum markers of fibrosis progression for the follow-up of hepatitis C virus-infected patients. Am J Pathol 2009, 175: 46-53. 10.2353/ajpath.2009.080850PubMed CentralPubMedGoogle Scholar
  171. Gutierrez-Reyes G, Gutierrez-Ruiz MC, Kershenobich D: Liver fibrosis and chronic viral hepatitis. Arch Med Res 2007, 38: 644-651. 10.1016/j.arcmed.2006.10.001PubMedGoogle Scholar
  172. Desmond PV, Patwardhan RV, Johnson RF, Schenker S: Impaired elimination of caffeine in cirrhosis. Dig Dis Sci 1980, 25: 193-197. 10.1007/BF01308138PubMedGoogle Scholar
  173. Park GJ, Katelaris PH, Jones DB, Seow F, Le Couteur DG, Ngu MC: Validity of the 13C-caffeine breath test as a noninvasive, quantitative test of liver function. Hepatology 2003, 38: 1227-1236. 10.1053/jhep.2003.50475PubMedGoogle Scholar
  174. Manns MP, McHutchison JG, Gordon SC, Rustgi VK, Shiffman M, Reindollar R, Goodman ZD, Koury K, Ling M, Albrecht JK: Peginterferon alfa-2b plus ribavirin compared with interferon alfa-2b plus ribavirin for initial treatment of chronic hepatitis C: a randomised trial. Lancet 2001, 358: 958-965. 10.1016/S0140-6736(01)06102-5PubMedGoogle Scholar
  175. Kumar D, Farrell GC, Fung C, George J: Hepatitis C virus genotype 3 is cytopathic to hepatocytes: Reversal of hepatic steatosis after sustained therapeutic response. Hepatology 2002, 36: 1266-1272. 10.1053/jhep.2002.36370PubMedGoogle Scholar
  176. Abe S, Tabaru A, Ono M, Tai M, Narita R, Moriyama A, Otsuki M: High-dose interferon-alpha therapy lowers the levels of serum fibrogenesis markers over 5 years in chronic hepatitis C. Hepatol Res 2003, 25: 22-31. 10.1016/S1386-6346(02)00203-6PubMedGoogle Scholar
  177. Derbala MF, Al Kaabi SR, El Dweik NZ, Pasic F, Butt MT, Yakoob R, Al-Marri A, Amer AM, Morad N, Bener A: Treatment of hepatitis C virus genotype 4 with peginterferon alfa-2a: impact of bilharziasis and fibrosis stage. World J Gastroenterol 2006, 12: 5692-5698.PubMed CentralPubMedGoogle Scholar
  178. Takemoto R, Nakamuta M, Aoyagi Y, Fujino T, Yasutake K, Koga K, Yoshimoto T, Miyahara T, Fukuizumi K, Wada Y, et al.: Validity of FibroScan values for predicting hepatic fibrosis stage in patients with chronic HCV infection. J Dig Dis 2009, 10: 145-148. 10.1111/j.1751-2980.2009.00377.xPubMedGoogle Scholar
  179. Vergniol J, Foucher J, Castera L, Bernard PH, Tournan R, Terrebonne E, Chanteloup E, Merrouche W, Couzigou P, de Ledinghen V: Changes of non-invasive markers and FibroScan values during HCV treatment. J Viral Hepat 2009, 16: 132-140. 10.1111/j.1365-2893.2008.01055.xPubMedGoogle Scholar
  180. Halfon P, Carrat F, Bedossa P, Lambert J, Penaranda G, Perronne C, Pol S, Cacoub P: Effect of antiviral treatment on serum markers of liver fibrosis in HIV-hepatitis C virus-coinfected patients: the Fibrovic 2 Study - ANRS HC02. Antivir Ther 2009, 14: 211-219.PubMedGoogle Scholar
  181. Patel K, Benhamou Y, Yoshida EM, Kaita KD, Zeuzem S, Torbenson M, Pulkstenis E, Subramanian GM, McHutchison JG: An independent and prospective comparison of two commercial fibrosis marker panels (HCV FibroSURE and FIBROSpect II) during albinterferon alfa-2b combination therapy for chronic hepatitis C. J Viral Hepat 2009, 16: 178-186. 10.1111/j.1365-2893.2008.01062.xPubMedGoogle Scholar

Copyright

© Ahmad et al; licensee BioMed Central Ltd. 2011

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.