Medical Policy


Subject: Serum Markers for Liver Fibrosis in the Evaluation and Monitoring of Chronic Liver Disease
Document #: LAB.00019 Publish Date:    12/27/2017
Status: Reviewed Last Review Date:    11/02/2017


This document addresses serum markers used in the evaluation and monitoring of chronic liver disease. These markers are indirect and direct measures of liver fibrosis. The stage of fibrosis is the most important single predictor of significant morbidity and mortality in individuals with hepatitis C and other chronic liver diseases.

Position Statement

Investigational and Not Medically Necessary:

Serum marker tests of hepatic fibrosis, used to produce a predictive score indicating the probability of liver fibrosis, are considered investigational and not medically necessary in the diagnosis and monitoring of individuals with hepatitis C or other chronic liver disease.


There has been increasing interest in analyzing multiple markers using proprietary algorithms to generate a liver fibrosis score that corresponds to the METAVIR score. METAVIR is a commonly used system that scores the presence and degree of liver fibrosis and inflammation. Liver biopsy is considered the current “gold standard” for assessing liver fibrosis. It is proposed that serum markers for liver fibrosis can be used as an alternative to liver biopsy in individuals with liver disease, particularly hepatitis C. Proprietary algorithm-based serum markers for liver fibrosis currently available in the United States include, but may not be limited to the following:

Initial research into the FibroSure algorithm (known as Fibrotest in Europe) involved testing an initial panel of 11 serum markers in 339 individuals with liver fibrosis who had undergone liver biopsy (Imbert-Bismut, 2001). From the original group of 11 markers, 5 were selected as the most informative, based on logistic regression and receiver operating curves. Markers included alpha-2 macroglobulin, haptoglobin, gamma globulin, apolipoprotein A1, gamma glutamyl transpeptidase and total bilirubin. Using an algorithm-derived scoring system ranging from 0–1.0, the authors reported a score of less than 0.10 was associated with a negative predictive value of 100% (that is, absence of significant fibrosis, as judged by liver biopsy scores of METAVIR F0-F1). A score greater than 0.60 was associated with a 90% positive predictive value of fibrosis (that is, METAVIR F2-F4). The authors concluded liver biopsy might be deferred in those with a score less than 0.10.

Further evaluation of the FibroSure algorithm included a cross section of individuals, including those with hepatitis C participating in large clinical trials before and after the initiation of antiviral therapy. Poynard and colleagues (2003) evaluated individuals with hepatitis C participating in a randomized study of peginterferon and ribavirin. A total of 352 subjects from the 1530 participants with stored serum samples and liver biopsies at study entry and at 24-week follow-up were selected. The FibroSure score was calculated and then compared to the liver biopsy score. At a cutoff point of 0.30, the FibroSure score had 90% sensitivity and 88% positive predictive value for the diagnosis of F2-F4. The specificity was 36%, and the negative predictive value was 40%. There was a large overlap in scores for those in the F2-F4 categories, and thus the scoring system has been primarily used to subdivide individuals with and without fibrosis (that is, F0-F1 vs. F2-F4). When used as a monitoring test, individuals can serve as their own baseline. Those with a sustained virological response to interferon also experienced reductions in the FibroTest or ActiTest scores.

Additional studies were done to formally validate the parameters used to calculate the FibroSure scores. Acceptable levels of “intra-laboratory and intra-patient variability” were reported (Halfon, 2002; Imbert-Bismut, 2004). Poynard and colleagues (2004) also evaluated discordant results in 537 individuals who underwent liver biopsy and the FibroTest and ActiTest on the same day; with the discordance attributed to either the limitations in the biopsy or serum markers. In this study, cut-off values were used for the individual METAVIR scores (that is, F0-F4) and for combinations of METAVIR scores (that is, F0-F1, F1-F2, etc.). The definition of a significant discordance between FibroTest, ActiTest and biopsy scores was at least two stages or grades in the METAVIR system. Discordance was observed in 29% of these individuals. Risk factors for biopsy failure included the biopsy size, number of fragments, and the number of portal tracts represented in the biopsy sample. Risk factors for failure of the FibroSure scoring system were presence of hemolysis, inflammation, possible Gilbert syndrome, acute hepatitis, drugs inducing cholestasis, or an increase in transaminases. Discordance was attributable to markers in 2.4%, to the biopsy in 18%, and could not be attributed in 8.2% of these individuals. The authors suggest that biopsy failure, frequently due to the small size of the biopsy sample, is a common problem. As noted in two reviews, the bulk of the research regarding FibroSure was conducted by researchers with an interest in the commercialization of the algorithm (Afdhal, 2003; Lichtinghagen, 2004). Rossi (2003) attempted to independently duplicate the results of FibroSure in 125 individuals with hepatitis C. Using the cut-off point of less than 0.1 to identify lack of bridging fibrosis (stages F0-F1) and greater than 0.6 to identify fibrosis (stages F2-F4), the negative predictive value for a score < 0.1 was 89%, compared to the 100% originally reported by Imbert-Bismut, and the positive predictive value of a score greater than 0.6 was 78% compared to 90%. The reasons for the inferior results in this study are unclear, but the authors concluded the FibroSure score did not accurately predict the presence or absence of fibrosis and could not reliably be used to reduce the need for liver biopsy.

Ratzui and colleagues (2006) conducted a study to determine the diagnostic validity of the FibroTest in non-alcoholic liver disease. For advanced fibrosis, FibroTest had a sensitivity of 77% and a specificity of 98%. Halfon and colleagues (2006) compared liver biopsy results with the FibroTest in individuals with chronic hepatitis C. In 18% of those tested, there were at least 2 stages of discordance between the serum test and liver biopsy. Poynard and colleagues (2007) studied the diagnostic value of FibroTest in chronic liver disease by performing meta-analyses of both published studies and individual data. Based upon study results, the authors concluded the FibroTest could be used as an alternative to biopsy in those with chronic hepatitis C and B, alcoholic liver disease, and non-alcoholic fatty liver disease. Shaheen and colleagues (2007) compared FibroTest and another technique (FibroScan) to biopsy in individuals with hepatitis C related fibrosis. For significant fibrosis, FibroTest had a sensitivity of 47% and a specificity of 90%. There was lesser accuracy for earlier stages of fibrosis. The authors noted these tests are not ready to replace liver biopsy and additional studies should be conducted.

There are minimal published data regarding FIBROSpect II. Patel and colleagues (2004) investigated the use of these serum markers in an initial training set of 294 individuals with hepatitis C and further validated the resulting algorithm in a validated set of 402 individuals. The algorithm was designed to distinguish between no or mild fibrosis (F0-F1) and moderate to severe fibrosis (F2-F4). With the prevalence of F2-F4 disease of 52% and a cut-off value of 0.36; the positive and negative predictive values were 74.3% and 75.8%, respectively. No studies were identified in the published literature in which results of the FIBROSpect II test were actively used in the management of the individual’s medical care. Zaman and colleagues (2007) prospectively studied FIBROSpect II by obtaining serum from 108 consecutive individuals with hepatitis C seen at a single center hepatology clinic at the time of liver biopsy. The performance of FIBROSpect II was assessed by comparing the serum results with the liver biopsy. The sensitivity and specificity of FIBROSpect II were 71.8%, and 73.9%, respectively. In a more recent study, Patel and colleagues (2008) prospectively compared the FIBROSpect II against pathology assessments and a quantitative measure of fibrosis. Liver biopsy specimens and serum were obtained from 252 individuals with chronic hepatitis C from three centers. Biopsy specimens were scored at each center and quantification of fibrosis was performed by digitized morphometry. Serum tests were blinded to clinical or histologic evaluation. The sensitivity and specificity of FIBROSpect II were determined to be 83.5% and 66.7%, respectively, with an accuracy of 80.2%. The authors noted: “Assessing the diagnostic utility of biomarkers is limited by variability in methods to quantify fibrosis and poor inter-observer agreement for histologic staging.”

In a French study, Bourlier and colleagues (2008) attempted to validate the Hepascore in 472 participants with hepatitis C virus. Based on the results of their study, the authors concluded that before Hepascore can be used in routine practice it should be validated on blood donor populations and on a larger population.

Adams (2011) reported current limitations of serum markers for liver fibrosis to include “a significant indeterminate range and a predictive ability that is limited to only a few stages of fibrosis.” The author also noted “what remains to be demonstrated is whether the use of biomarker models can influence patient outcomes.” Serum markers included in this review were: Fibrotest, Hepascore, and Fibrospect II.

Sebastiani and colleagues (2011) reported on an international retrospective study investigating the effect of etiology and stages of hepatic fibrosis on the performance of liver fibrosis biomarkers. A total of 2411 individuals with compensated chronic liver disease were consecutively enrolled in 9 centers. APRI, Forns' index, Lok index, AST-to-ALT ratio, FIB-4, platelets and Fibrotest/Fibrosure were tested against liver biopsy. Results included:

The authors concluded that for the diagnosis of liver fibrosis, the performance of non-invasive biomarkers is not such to replace liver biopsy and recommended further prospective study. Study limitations include potential selection bias and suboptimal liver biopsy length.

In a 2013 systematic review, Chou and Wasson evaluated the accuracy of a wide variety of blood tests in determining fibrosis and/or cirrhosis. Both “simple” tests, such as platelet count, and more complex scoring systems, such as the FibroTest were included. A total of 172 studies were identified that compared the diagnostic accuracy of blood tests to liver biopsy. Blood tests associated with areas under the receiver-operating characteristic curve (AUROCs) of 0.70 or greater (range, 0.70 to 0.86) were considered fair to good for identifying fibrosis and AUROCs of 0.80 or greater (range, 0.80 to 0.91) were considered good to excellent for identifying cirrhosis. Tests for identifying clinically significant fibrosis with AUROCs of 0.70-0.86 included platelet count, age-platelet index, aspartate aminotransferase-platelet ratio index (APRI), FibroIndex, FibroTest, and Forns index with median positive likelihood ratios of 5 to 10 at commonly used cutoffs. Tests for identifying cirrhosis with AUROCs of 0.80 to 0.91 included platelet count, age-platelet index, APRI, and Hepascore also with median positive likelihood ratios of 5 to 10. Most tests did not have high negative predictive values for fibrosis, and negative likelihood ratios were found in the moderately useful range (0.10 to 0.20) at commonly used cutoffs, only with FibroIndex and FibroTest. This suboptimal negative predictive value suggests that these tests perform better in identifying fibrosis than in ruling it out. Additionally, differences were small between the FibroTest or APRI and other blood tests, suggesting routinely available blood tests and simple calculations are not outperformed by additional blood tests and more complex algorithms in identifying fibrosis.

Salkic and colleagues (2014) conducted a heterogeneous meta-analysis of studies on the diagnostic performance of FibroTest/Fibrosure (proprietary formula; Biopredictive, Paris, France) in chronic hepatitis B virus (HBV). The meta-analysis included 16 studies (n=2494) on liver fibrosis diagnosis and 13 studies (n=1754) on cirrhosis diagnosis. For significant liver fibrosis (F2-F4) diagnosis using all of the fibrosis studies, the area under the hierarchical summary receiver operating curve was 0.84 (95% confidence interval [CI], 0.78 to 0.88). At the recommended FibroTest/Fibrosure threshold of 0.48 for a significant liver fibrosis diagnosis, the sensitivity was 60.9%, specificity was 79.9%, and the diagnostic odds ratio was 6.2%. For liver cirrhosis (F4) diagnosis using all of the cirrhosis studies, the area under the hierarchical summary receiver operating curve was 0.87 (95% CI, 0.85 to 0.9). At the recommended FibroTest/Fibrosure threshold of 0.74 for cirrhosis diagnosis, the sensitivity was 61.5%, specificity was 90.8%, and the diagnostic odds ratio was 15.7. Although study results suggested that FibroTest/Fibrosure may be useful for excluding cirrhosis in individuals with chronic HBV, the authors concluded that the test had suboptimal performance in detection of significant fibrosis and cirrhosis and in exclusion of significant fibrosis.

In a 2014 study, Leroy and colleagues compared FibroTest, FibroMeter, and Hepascore for diagnosing fibrosis in individuals with HCV or HBV. For 510 subjects, blood samples were collected the day of liver biopsy. To avoid spectrum bias, HCV subjects (n=255) and HBV subjects (n=255) were matched to stages of liver fibrosis. The authors found a significant correlation between the blood test results and the liver biopsy fibrosis stages, and HCV and HBV groups were similar: (FibroMeter: r=0.67 vs. 0.64, FibroTest r=0.58 vs. 0.62, and Hepascore r=0.57 vs. 0.60, p <0.001 for all tests). For significant fibrosis (F ≥ 2), FibroMeter (AUROC 0.84) was superior to FibroTest (0.79; p<0.001) and Hepascore (0.77; p<0.001). In addition, for extensive fibrosis (F ≥ 3), FibroMeter was superior (AUROC 0.88) to FibroTest (0.83; p<0.02) and Hepascore (0.84; p<0.05). For cirrhosis, there were no significant differences between the tests. The Youden method was used to define cut-offs for the HCV and HBV groups. All of the blood tests underestimated extensive fibrosis (F ≥ 3) in HBV and HVC individuals: Fibrotest 47% vs. 26%, Fibrometer 24% vs. 6%, and Hepascore 41% vs. 24%, respectively (p<0.01). However, the blood tests were significantly lower for the CHB group, thus increasing the risk of underestimating severe fibrosis and cirrhosis in HBV individuals. The authors concluded:

The overall diagnostic performance of blood tests of fibrosis is similar in CHB [chronic hepatitis B] and CHC [chronic hepatitis C]. However, applying to CHB the cut offs validated in CHC is clearly associated with a low but significant increased risk of under-diagnosing extensive fibrosis and cirrhosis. Stringent cut-offs should be used along with a fine analyse of the clinical condition and patient characteristics to avoid misdiagnosis of cirrhosis.

Other Scoring Systems

Other serum marker scoring systems have been developed that use non-proprietary formulas. The APRI scoring system (aspartate aminotransferase [AST] to platelet ratio) requires only the serum level of AST and the number of platelets, and uses a simple formula that can be calculated at the bedside to produce a score for the prediction of fibrosis (Wai, 2003). Using an optimized cutoff value derived from a training set and validation set of subjects with hepatitis C, the negative predictive value for fibrosis was 86% and the positive predictive value was 88%. Rosenberg and colleagues (2004) developed a scoring system based on an algorithm combining hyaluronic acid, amino terminal propeptide of type III collagen, and TIMP-1. The algorithm was developed in a test set of 400 individuals with a wide variety of chronic liver diseases and then validated in another 521 subjects. The algorithm was designed to discriminate between no or mild fibrosis and moderate to severe fibrosis, and had a negative predictive value for fibrosis of 92%.

Another system reported to help identify fibrosis (advanced) is the nonalcoholic fatty liver disease (NAFLD) Fibrosis Score. The NAFLD Fibrosis Score is based on age, body mass index, platelet count, albumin, AST/ALT ratio and is calculated using a published formula.

The Fibrosis-4 (FIB-4) index is a liver fibrosis serum marker that combines common laboratory values (platelet count, ALT, and AST) and age. A simple published formula is used that can be calculated at the bedside. No randomized controlled trials directly evaluating the FIB-4 index were identified in the published literature. However, other publications including retrospective analyses and systematic reviews have evaluated the predictive accuracy of FIB-4 for liver fibrosis.

Sterling and colleagues (2006) performed a retrospective analysis of liver histology in 832 subjects co-infected with both HCV and HIV. Individuals were assigned to either a training set (n=555) or a validation set (n=277). Liver biopsy was performed at baseline and correlated to laboratory tests obtained prior to the start of study treatment. In both the training and validation sets an overall FIB-4 accuracy of 86% was reported, reducing need for biopsy in at least 70%. Study limitations include the retrospective nature and potential for selection bias. The authors indicated additional studies in individuals with chronic HCV are needed to support their findings.

Vallet-Pichard and colleagues (2007) evaluated the FIB-4 index in a series of 847 liver biopsies performed in HCV-mono-infected subjects. FIB-4 values ranged from 0.13 to 12.62 in the entire sample. A FIB-4 index below 1.45 had a negative predictive value of 94% to exclude extensive fibrosis with a sensitivity of 74.3% and a specificity of 80.1%. A FIB-4 index greater than 3.25 had a positive predictive value to confirm significant fibrosis of 82.1% with a specificity of 98.2% and a sensitivity of 37.6%. Of the 617 liver biopsies with FIB-4 values outside the range of 1.45-3.25, a total of 93.3% were correctly classified. In the second part of this study, results of 780 FIB-4 and Fibro tests performed in 592 HCV infected subjects were compared. Of 454 subjects with a FIB-4 score < 1.45, a total of 418 (92.1%) were consistent with the Fibro test results to exclude severe fibrosis. The authors concluded that other studies are required for validation of the FIB-4.

The FIB-4 index has also been evaluated for use in individuals with non-alcoholic fatty liver disease (NAFLD). In 2009, Shah and colleagues compared the FIB-4 index with other non-invasive markers for fibrosis using a nationwide database of 541 adults with NAFLD. The median FIB-4 score was 1.11. For a fixed specificity of 90% (FIB-4=1.93), the sensitivity for identifying advanced fibrosis was 50%. A FIB-4 index ≤ 1.30 had a 90% negative predictive value and a FIB-4 score of ≥ 2.67 had an 80% positive predictive value. In a retrospective, international, cohort series of 320 individuals with NAFLD (Angulo, 2013), the area under the ROC curve for predicting adverse liver-related outcomes was 0.81 and for predicting death or liver transplantation was 0.67. Study limitations include selection bias inherent to retrospective studies.

Xu and colleagues (2014) performed a systematic review and meta-analysis of 30 studies to evaluate the effectiveness and accuracy of APRI, FIB-4 and FibroTest to detect fibrosis in HBV. For significant fibrosis, the areas under the SROC curve for APRI, FIB-4, and FibroTest were 0.77, 0.75, and 0.84, respectively. For cirrhosis, the areas under the SROC curve for APRI, FIB-4 and FibroTest were 0.75, 0.87, and 0.90, respectively. The heterogeneity of FIB-4 and FibroTest were not statistically significant. The heterogeneity of APRI for detecting significant fibrosis was affected by median age, and for cirrhosis was affected by etiology. Limitations of the review reported by the authors included that “the analysis focused on only individuals with HBV related fibrosis, without distinguishing between HBeAg negative and positive cases, or considering the virus replication rate due to the limited number of publications.” The authors also reported that further studies are needed.

A multicenter, retrospective, U.S. cohort study consisting of 92 children with biopsy-proven NAFLD evaluated pediatric liver fibrosis scores (Mansoor, 2015). The fibrosis scores calculated for each child were: AST/ALT ratio, AST/platelet ratio index (APRI), NAFLD fibrosis score (NFS) and the FIB-4 index. Results indicated that APRI had a fair diagnostic accuracy for the presence of any fibrosis and poor diagnostic accuracy for significant or advanced fibrosis. The other tests (AST/ALT, NFS, and FIB-4) all had either poor diagnostic accuracy or failed to diagnose the presence of fibrosis. Study limitations included a small sample size. The authors concluded that for children “FIB-4 index, NFS, and AST/ALT ratio are poor predictors for fibrosis and cannot replace liver biopsy as diagnostic modality at this time.”

A systematic review and meta-analysis by Xiao (2015) assessed the performance of FIB-4 and APRI for evaluating liver fibrosis in adults with hepatitis B virus (HBV). A total of 39 studies, consisting of 9377 subjects from Asia and Europe, were selected for review. Included were two FIB-4 articles, 16 APRI only articles and 21 articles addressing both APRI and FIB-4. An APRI threshold of 0.5, 1.0, and 1.5, demonstrated sensitivity and specificity values of 70.0% and 60.0%, 50.0% and 83.0%, and 36.9% and 92.5% for significant fibrosis, advanced fibrosis, and cirrhosis, respectively. A FIB-4 threshold of 1.45 and 3.25, demonstrated sensitivity and specificity values of 65.4% and 73.6% and 16.2% and 95.2% for significant fibrosis. Limitations of the review and meta-analysis include the possibility of publication bias. The authors concluded that the diagnostic accuracy of FIB-4 and APRI was not high, but the tests still could be considered as a choice for the prediction of fibrosis caused by chronic HBV infection in regions with limited health care resources.

In a cross-sectional study, Boursier and colleagues (2016) compared 8 serum markers and elastography for the diagnosis of liver fibrosis against liver biopsy results in 452 individuals with non-alcoholic fatty liver disease (NAFLD). Within a week prior to liver biopsy, subjects gave fasting blood samples that were tested for NAFLD-specific markers (BARD, NFS, and FibroMeter NAFLD) and non-specific markers (APRI, FIB4, Fibrotest, Hepascore, and FibroMeter V2G). Within 3 months of the biopsy, elastography (Fibroscan) was performed to evaluate liver stiffness measurement (LSM). For advanced fibrosis, FibroMeter V2G had a significantly higher AUROC (0.817 ± 0.020) than the other blood tests (p≤0.041), and was similar to LSM (0.831 ± 0.019). For detecting fibrosis stages, LSM and Fibrometer V2G had the best scores (ordROC 0.834 ± 0.014, p≤0.001; 0.798 ± 0.016, p≤0.036, respectively). The authors note this is the first study that evaluates FibroMeter V2G, Hepascore and LSM for NAFLD. Limitations of the study included improvements in LSM technology since the study began. The authors state that the results “need validation in large cohorts of unselected NAFLD patients with long-term follow-up allowing for the study of a sufficient number of events.”

Houot and colleagues (2016) published an industry-supported systematic review and meta-analysis comparing the AUROCs between APRI, FIB4, FibroTest and transient elastography (TE). Using liver biopsy METAVIR scores as a reference, the authors compared the outcomes of HCV and HBV subjects in 71 studies between 2002 and 2014. The FibroTest scored better than TE or APRI for identifying advanced fibrosis (credibility interval 0.06 [0.02-0.09] and 0.05 [0.03-0.07], respectively). For identifying cirrhosis, TE and FIB4 scored better than APRI, (0.07 [0.02-0.13] and 0.04 [0.02-0.05], respectively). Other comparisons were not statistically significant. The authors noted several limitations including the first-time use of the Bayesian method, the inability to assess pooled sensitivity and specificity data, lack of fibrosis staging information in some studies, and a relatively small number of studies for comparisons.

Tanwar and colleagues (2017) compared the performance of 10 serum biomarkers of liver fibrosis in HCV subjects with previous treatment failure. Serum samples were collected and stored after 80 subjects underwent liver biopsy. Within 6 months of collection, the samples were analyzed for direct markers (Hepascore, Fibrometer V2G, HA, ELF and Fibrospect II) and indirect markers (AST:ALT ratio, APRI, Forns, FIB4 and Fibrometer 3G) and compared to METAVIR scores. Good performance was defined as an AUROC > 0.8. All direct markers and Fibrometer V3G were able to detect moderate fibrosis, and Fibrometer V2G had the highest AUROC of 0.88 (95% CI, [0.80-0.95]; p<0.001). For the detection of advanced fibrosis, Fibrometer V2G had the highest AUROC of 0.84 (95% CI, [0.75-0.93]; p<0.001), but it was only found to be significantly higher than AST:ALT and APRI. All markers were able to detect advanced fibrosis except Fibrospect II, AST:ALT and APRI. For the detection of cirrhosis, Forns had the highest AUROC of 0.92 (95% CI, [0.86-0.98]; p<0.001), and all markers had good performance except AST:ALT and APRI. For detecting fibrosis stages for HCV, the Fibrometer V2G (Obuchowski measure [ordROC] 0.94) and Fibrometer V3G (ordROC 0.94) were only significantly higher (p<0.05) than AST:ALT and APRI. ELF and Hepascore, both ordROC 0.93, were best for detecting fibrosis for all liver disease etiologies. Because results differed for some biomarkers depending on the assay used, the researchers noted the importance of using the individual component assays that have been validated for each test. Limitations noted by the authors included a small sample size (predominately male).

Other Considerations

In a 2017 clinical care pathway on the screening and evaluation of hepatitis C, the American Gastroenterological Association (AGA) states:

In the absence of clinically apparent cirrhosis, there is the need to assess degree of liver fibrosis. Such assessment can be done noninvasively via elastography (usually “vibration-controlled” or Fibroscan®), serum biomarkers (FIB4 or aspartate aminotransferase to platelet ratio index), or various proprietary markers. The routine use of the invasive gold standard liver biopsy has become less popular, recognizing that even liver biopsy may miss the presence of cirrhosis. The results of non-invasive studies provide helpful information to patient and clinician regarding fibrosis stage, though all may suffer from occasional false readings and must be tempered by clinical judgment.

The American College of Gastroenterology (ACG) recommendations on the diagnosis, management, and treatment of hepatitis C (2009) state:

Currently available noninvasive tests may be useful in defining the presence or absence of advanced fibrosis in persons with chronic hepatitis C infection, but should not replace the liver biopsy in routine clinical practice (Class IIb, Level C, usefulness/efficacy is less well established by evidence/opinion, evidence has only consensus opinion of experts, case studies, or standard-of-care).

The 2012 ACG recommendations for the diagnosis and management of NAFLD indicate that a major limitation of prediction models and biomarkers (including the NAFLD Fibrosis Score) is that they have largely been investigated in cross-sectional studies and their utility in monitoring disease natural history and predicting outcomes or response to therapeutic intervention is unknown.

The American Association for the Study of Liver Diseases (AASLD) guidelines for the treatment of chronic hepatitis B (2016) state:

Whereas liver biopsy is regarded as the best method to assess the severity of inflammatory activity and fibrosis, noninvasive methods to assess fibrosis severity are also useful. Acute-on-chronic exacerbations of hepatitis B may lead to overestimation of fibrosis stage by noninvasive tests, and different cutoffs for significant and advanced fibrosis depending on ALT levels have been proposed. Serum markers of fibrosis, such as aspartate aminotransferase (AST)-to-platelet ratio index (APRI), FIB-4, FibroTest, and vibration-controlled transient elastography, have only moderate accuracy in identifying persons with significant fibrosis (fibrosis stage 2 or greater on the Metavir scale), but good diagnostic accuracy in excluding advanced fibrosis, and may be useful aids in decision making.

The 2017 AASLD and Infectious Diseases Society of America (IDSA) recommendations for testing, managing, and treating hepatitis C include the following statements:

Evaluation for advanced fibrosis using liver biopsy, imaging, and/or noninvasive markers is recommended for all persons with HCV infection, to facilitate an appropriate decision regarding HCV treatment strategy and to determine the need for initiating additional measures for the management of cirrhosis (eg, hepatocellular carcinoma screening). (Rating: Class I, Level A-Evidence and/or general agreement; data derived from multiple randomized clinical trials, meta-analyses, or equivalent).

Noninvasive tests to stage the degree of fibrosis in patients with chronic HCV infection include models incorporating indirect serum biomarkers (routine tests), direct serum biomarkers (components of the extracellular matrix produced by activated hepatic stellate cells), and vibration-controlled transient liver elastography. No single method is recognized to have high accuracy alone and each test must be interpreted carefully. A recent publication of the Agency for Healthcare Research and Quality found evidence in support of a number of blood tests; however, at best, they are only moderately useful for identifying clinically significant fibrosis or cirrhosis… Biopsy should be considered in those in whom more accurate fibrosis staging would impact treatment decisions.


There is no compelling evidence indicating that changes in serum marker values over time correlates with changes in liver fibrosis. Published studies have emphasized ‘static’ time points rather than changes over time. Additionally, no studies were identified that used the results of any of the markers to reduce the number of biopsies, or to improve health outcomes. Current evidence does not support the use of serum markers for liver fibrosis in the evaluation and monitoring of chronic liver disease.


The hepatitis C virus (HCV) causes liver inflammation and can lead to severe liver damage, cirrhosis and hepatocellular carcinoma (HCC). It is estimated that 70% of all HCV-infected individuals will eventually develop chronic liver disease, and at least 20% will develop cirrhosis over 10 to 20 years. After 20 to 40 years, a smaller percentage of individuals with chronic liver disease develop HCC. The population identified as high-risk for developing HCC includes males, people with a history of substance abuse, those diagnosed with cirrhosis, individuals over age 40, and those infected for 20 to 40 years.

Antiviral therapy is the recommended treatment for individuals with a reactive enzyme immunoassay for antibody to HCV, the presence of HCV RNA, and compensated liver disease. Liver biopsy is typically recommended prior to the initiation of antiviral therapy, and repeat biopsies may be performed to monitor fibrosis progression. Liver biopsies are analyzed according to a histologic scoring system; the most commonly used is the METAVIR scoring system, which scores fibrosis from F0-F4. A METAVIR score of F2 to F4 indicates significant fibrosis, while a score of F3 and F4 signifies advanced fibrosis. Biopsies can also be evaluated according to the degree of inflammation present, referred to as the grade or activity level. For example, the METAVIR system includes scores for necroinflammatory activity ranging from A0 to A3 (A0 = no activity, A1 = minimal activity, A2 = moderate activity, A3 = severe activity). However, there are several limitations to liver biopsy, including its invasive nature and subjective grading system.

A noninvasive alternative to liver biopsy would be helpful, both as an initial assessment and as a monitoring tool to assess response to therapy. A variety of laboratory tests have been proposed as an alternative to liver biopsy. Laboratory tests can be broadly categorized into indirect and direct markers of liver fibrosis. Indirect markers include liver function tests such as ALT (alanine aminotransferase), AST (aspartate aminotransferase), the ALT/AST ratio (also referred to as the AAR), platelet count and prothrombin index. In recent years there has been growing understanding of the underlying pathophysiology of fibrosis leading to direct measurement of the factors involved. For example, the central event in the pathophysiology of fibrosis is activation of the hepatic stellate cell. Normally, the stellate cells are quiescent, but are activated in the setting of liver injury, producing a variety of extracellular matrix (ECM) proteins. In normal livers, the rate of ECM production equals its degradation, but in the setting of fibrosis, production exceeds degradation. Metalloproteinases are involved in intracellular degradation of ECM, and a profibrogenic state exists when there is either a down regulation of metalloproteinases or an increase in tissue inhibitors of metalloproteinases (TIMP). Both metalloproteinases and TIMP can be measured in the serum, which directly reflect fibrotic activity. Other direct measures of ECM deposition include hyaluronic acid or alpha-2 macroglobulin.

Proprietary, algorithm-based serum markers for liver fibrosis commercially available in the United States are described below.

ASH FibroSURE (ASH test) assesses the liver status of individuals with alcoholic liver disease (ALD). Quantitative results of 10 biochemicals, including alpha-2-macroglobulin, haptoglobin, apolipoprotein A1, bilirubin, GGT, ALT, AST, total cholesterol, triglycerides, and fasting glucose, in combination with age, gender, height, and weight, are analyzed, using a proprietary algorithm, to provide quantitative surrogate markers for liver fibrosis, hepatic steatosis, and ASH. ASH FibroSURE is offered by LabCorp.

FibroTest-ActiTest (HCV FibroSure) uses a combination of six serum indirect biochemical markers of liver function plus age and gender in a patented algorithm to generate a measure of fibrosis and necroinflammatory activity in the liver corresponding to the METAVIR scoring system for stage (fibrosis) and grade (necroinflammatory activity). The biochemical markers include measurements of alpha-2 macroglobulin, haptoglobin, total bilirubin, gamma glutamyltransferase (GGT), apolipoprotein A1 and alanine aminotransferase (ALT, SGPT). FibroTest-ActiTest is offered by Quest Diagnostics. The older version of the test, HCV FibroSure, is offered by LabCorp.

Nash FibroSURE (NASH Test) assesses the liver status of individuals with nonalcoholic fatty liver disease (NAFLD). Quantitative results of 10 biochemicals, including α2-macroglobulin, haptoglobin, apolipoprotein A1, bilirubin, γ-glutamyl transpeptidase (GGT), alanine aminotransferase (ALT), aspartate aminotransferase (AST), total cholesterol, triglycerides, and fasting glucose, in combination with age, gender, height, and weight, are analyzed, using a proprietary algorithm, to provide quantitative surrogate markers for liver fibrosis, hepatic steatosis, and NASH. Nash FibroSURE is offered by LabCorp.

FIBROSpect II uses a combination of three markers that directly measure fibrogenesis of the liver, analyzed with a patented algorithm. The markers include hyaluronic acid, TIMP-1 and alpha-2 macroglobulin. FibroSpect II is offered by Prometheus Laboratories.

FibroMeter is a panel of tests for evaluating liver fibrosis in individuals with viral hepatitis, NAFLD, and alcoholic liver disease (ALD). Fibrometer VIRUS, which assesses liver fibrosis in individuals with hepatitis C or B, is based on seven blood markers (platelets, alpha-2-macroglobulin, ALT, urea, prothrombin index, GGT, and AST). The results include a fibrosis score that signifies METAVIR stage F2 or higher, a cirrhosis score that signifies the probability of cirrhosis, and an activity grade that assesses necrotico-inflammatory activity. FibroMeter is offered by ARUP Laboratories.


Algorithm: A process or set of rules by which a calculation or process can be carried out usually referring to calculations that will be done by a computer.

Biopsy: A procedure that involves obtaining a tissue specimen for microscopic analysis to establish a precise diagnosis.

Fibrosis: The development of excess fibrous connective tissue in an organ.

Serum: The clear, straw-colored, liquid portion of blood plasma that does not contain fibrinogen or blood cells and remains fluid after clotting.


The following codes for treatments and procedures applicable to this document are included below for informational purposes. Inclusion or exclusion of a procedure, diagnosis or device code(s) does not constitute or imply member coverage or provider reimbursement policy. Please refer to the member's contract benefits in effect at the time of service to determine coverage or non-coverage of these services as it applies to an individual member.

When Services are Investigational and Not Medically Necessary:
When the code describes a procedure indicated in the Position Statement section as investigational and not medically necessary.




Unlisted multianalyte assay with algorithmic analysis [when specified as serum markers for liver fibrosis, including FIBROSpect II, FibroMeter]


Unlisted chemistry procedure [when specified as serum markers for liver fibrosis]



ICD-10 Diagnosis



All diagnoses, including but not limited to the following:


Acute hepatitis B


Acute hepatitis C


Chronic viral hepatitis B


Chronic viral hepatitis C


Unspecified viral hepatitis B


Unspecified viral hepatitis C


Diseases of liver

When Services are also Investigational and Not Medically Necessary:




Infectious disease, HCV, six biochemical assays (ALT, A2-macroglobulin, apolipoprotein A-1, total bilirubin, GGT, and haptoglobin) utilizing serum, prognostic algorithm reported as scores for fibrosis and necroinflammatory activity in liver [HCV FibroSURE™, LabCorp; FibroTest™, Quest Diagnostics/BioPredictive]


Liver disease, ten biochemical assays (ALT, A2-macroglobulin, apolipoprotein A-1, total bilirubin, GGT, haptoglobin, AST, glucose, total cholesterol and triglycerides) utilizing serum, prognostic algorithm reported as quantitative scores for fibrosis, steatosis and alcoholic steatohepatitis (ASH) [ASH FibroSURE™, LabCorp]


Liver disease, ten biochemical assays (ALT, A2-macroglobulin, apolipoprotein A-1, total bilirubin, GGT, haptoglobin, AST, glucose, total cholesterol and triglycerides) utilizing serum, prognostic algorithm reported as quantitative scores for fibrosis, steatosis and nonalcoholic steatohepatitis (NASH) [NASH FibroSURE™, LabCorp]



ICD-10 Diagnosis



All diagnoses


Peer Reviewed Publications:

  1. Adams LA. Biomarkers of liver fibrosis. J Gastroenterol Hepatol. 2011; 26(5):802-809.
  2. Afdhal NH, Nunes D. Evaluation of liver fibrosis: a concise review. Am J Gastroenterol. 2004; 99(6):1160-1174.
  3. Bourliere M, Penaranda G, Ouzan D, et al. Optimized stepwise combination algorithms of non-invasive liver fibrosis scores including Hepascore in hepatitis C virus patients. Aliment Pharmacol Ther. 2008; 28(4):458-467.
  4. Boursier J, Vergniol J, Guillet A, et al. Diagnostic accuracy and prognostic significance of blood fibrosis tests and liver stiffness measurement by FibroScan in non-alcoholic fatty liver disease. J Hepatol. 2016; 65(3):570-578.
  5. Callewaert N, Van Vleirberghe H, Van Heckle A, et al. Noninvasive diagnosis of liver cirrhosis using DNA sequence-based total serum protein glycomics. Nat Med. 2004; 10(4):429-434.
  6. Chou R, Wasson N. Blood tests to diagnose fibrosis or cirrhosis in patients with chronic hepatitis C virus infection: a systematic review. Ann Intern Med. 2013; 158(11):807-820.
  7. Colletta C, Smirne C, Fabris C, et al. Value of two noninvasive methods to detect progression of fibrosis among HCV carriers with normal aminotransferases. Hepatology. 2005; 42(4):838-845.
  8. Crockett SD, Kaltenbach T, Keeffe EB. Do we still need a liver biopsy? Are the serum fibrosis tests ready for prime time? Clin Liver Dis. 2006; 10(3):513-534.
  9. Halfon P, Bourliere M, Deydier R, 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(3):547-555.
  10. Halfon P, Imbert-Bismut F, Messous D, et al. A prospective assessment of the interlaboratory variability of biochemical markers of fibrosis (FibroTest) and activity test (ActiTest) in patients with chronic liver disease. Comp Hepatol. 2002; 1(1):3.
  11. Houot M, Ngo Y, Munteanu M, et al. Systematic review with meta-analysis: direct comparisons of biomarkers for the diagnosis of fibrosis in chronic hepatitis C and B. Aliment Pharmacol Ther. 2016; 43(1):16-29.
  12. Imbert-Bismut F, Messous D, Thibaut V, et al. Intra-laboratory analytical variability of biochemical markers of fibrosis (Fibrotest) and activity (Actitest) and reference ranges in healthy blood donors. Clin Chem Lab Med. 2004; 42(3):323-333.
  13. Imbert-Bismut F, Ratziu V, Pieroni L, et al. Biochemical markers of liver fibrosis in patients with hepatitis C virus infection: a prospective study. Lancet. 2001; 357(9262):1069-1075.
  14. Kelleher TB, Afdhal N. Noninvasive assessment of liver fibrosis. Clin Liver Dis. 2005; 9(4):667-683.
  15. Kelleher TB, Mehta SH, Bhaskar R, et al. Prediction of hepatic fibrosis in HIV/HCV co-infected patients using serum fibrosis markers: the SHASTA index. J Hepatol. 2005; 43(1):78-84.
  16. Lackner C, Struber G, Liegl B, et al. Comparison and validation of simple noninvasive tests for prediction of fibrosis in chronic hepatitis C. Hepatology. 2005; 41(6):1376-1382.
  17. Leroy, V, Sturm N, Faure P, et al. Prospective evaluation of FibroTest®, FibroMeter®, and HepaScore® for staging liver fibrosis in chronic hepatitis B: comparison with hepatitis C. 2014; 61(1):28-34.
  18. Lichtinghagen R, Bahr MJ. Noninvasive diagnosis of fibrosis in chronic liver disease. Expert Rev Mol Diagn. 2004; 4(5):715-726.
  19. Mansoor S, Yerian L, Kohli R, et al. The evaluation of hepatic fibrosis scores in children with nonalcoholic fatty liver disease. Dig Dis Sci. 2015; 60(5):1440-1447.
  20. Patel K, Gordon SC, Jacobson I, et al. 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(6):935-942.
  21. Patel K, Nelson DR, Rockey DC, et al. Correlation of FIBROSpect II with histologic and morphometric evaluation of liver fibrosis in chronic hepatitis C. Clin Gastroenterol Hepatol. 2008; 6(2):242-247.
  22. Poynard T, McHutchison J, Manns M, et al. Biochemical surrogate markers of liver fibrosis and activity in a randomized trial of peginterferon alfa-2b and ribavirin. Hepatology. 2003; 38(2):481-492.
  23. Poynard T, Morra R, Halfon P, et al. Meta-analyses of FibroTest diagnostic value in chronic liver disease. BMC Gastroenterol. 2007; 7:40.
  24. Poynard T, Munteanu M, Imbert-Bismut F, et al. Prospective analysis of discordant results between biochemical markers and biopsy in patients with chronic hepatitis C. Clin Chem. 2004; 50(8):1344-1355.
  25. Ratziu V, Massard J, Charlotte F, et al. Diagnostic value of biochemical markers (FibroTest-FibroSURE) for the prediction of liver fibrosis in patients with non-alcoholic fatty liver disease. BMC Gastroenterol. 2006; 14(6):6.
  26. Rockey DC, Bissell DM. Noninvasive measures of liver fibrosis. Hepatology. 2006; 43(2 Suppl 1):S113-120.
  27. Rosenberg WM, Voelker M, Thiel R, et al. Serum markers detect the presence of liver fibrosis: a cohort study. Gastroenterology. 2004; 127(6):1704-1713.
  28. Rossi E, Adams L, Prins A, et al. Validation of the FibroTest biochemical markers score in assessing liver fibrosis in hepatitis C patients. Clin Chem 2003; 49(3):450-454.
  29. Salkic NN, Jovanovic P, Hauser G, Brcic M. FibroTest/Fibrosure for significant liver fibrosis and cirrhosis in chronic hepatitis B: a meta-analysis. Am J Gastroenterol. 2014; 109(6):796-809.
  30. Sebastiani G, Castera L, Halfon P, et al. The impact of liver disease aetiology and the stages of hepatic fibrosis on the performance of non-invasive fibrosis biomarkers: an international study of 2411 cases. Aliment Pharmacol Ther. 2011; 34(10):1202-1216.
  31. Shah AG, Lydecker A, Murray K, et al; Nash Clinical Research Network. Comparison of noninvasive markers of fibrosis in patients with nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol. 2009; 7(10):1104-1112.
  32. 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(11):2589-2600.
  33. Sterling RK, Lissen E, Clumeck N, et al; APRICOT Clinical Investigators. Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV coinfection. Hepatology. 2006; 43(6):1317-1325.
  34. Tanwar S, Trembling PM, Hogan BJ, et al. Biomarkers of hepatic fibrosis in chronic hepatitis C: a comparison of 10 biomarkers using 2 different assays for hyaluronic acid. J Clin Gastroenterol. 2017; 51(3):268-277.
  35. Vallet-Pichard A, Mallet V, Nalpas B, et al. FIB-4: an inexpensive and accurate marker of fibrosis in HCV infection. Comparison with liver biopsy and fibrotest. Hepatology. 2007; 46(1):32-36.
  36. Wai CT, Greenson JK, Fontana RJ, et al. A simple noninvasive index can predict both significant fibrosis and cirrhosis in patients with chronic hepatitis C. Hepatology. 2003; 38(2):518-526.
  37. Xiao G, Yang J, Yan L. Comparison of diagnostic accuracy of aspartate aminotransferase to platelet ratio index and fibrosis-4 index for detecting liver fibrosis in adult patients with chronic hepatitis B virus infection: a systemic review and meta-analysis. Hepatology. 2015; 61(1):292-302.
  38. Xu XY, Kong H, Song RX, et al. The effectiveness of noninvasive biomarkers to predict hepatitis B-related significant fibrosis and cirrhosis: a systematic review and meta-analysis of diagnostic test accuracy. PLoS One. 2014; 9(6):e100182.
  39. Zaman A, Rosen HR, Ingram K, et al. Assessment of FIBROSpect II to detect hepatic fibrosis in chronic hepatitis C patients. Am J Med. 2007; 120(3):280.e9-14.

Government Agency, Medical Society, and Other Authoritative Publications:

  1. American Association for the Study of Liver Diseases and Infectious Diseases Society of America. Recommendations for testing, managing, and treating hepatitis C. July 6, 2016. Available at: Accessed on September 22, 2017.
  2. Chalasani N, Younossi Z, Lavine JE, et al; American Gastroenterological Association; American Association for the Study of Liver Diseases; American College of Gastroenterology. The diagnosis and management of non-alcoholic fatty liver disease: practice guideline by the American Gastroenterological Association, American Association for the Study of Liver Diseases, and American College of Gastroenterology. Gastroenterology. 2012; 142(7):1592-1609.
  3. Dienstag JL, McHutchison JG. American Gastroenterological Association medical position statement on the management of hepatitis C. Gastroenterology. 2006a; 130(1):225-230.
  4. Dienstag DL, McHutchison JG. American Gastroenterological Association technical review on the management of hepatitis C. Gastroenterology 2006b; 120(1):231-264.
  5. Ghany MG, Strader DB, Thomas DL, Seeff LB; American Association for the Study of Liver Diseases. Diagnosis, management, and treatment of hepatitis C: an update. Hepatology. 2009; 49(4):1335-1374.
  6. Kanwal, F, Bacon BR, Beste LA, et al. Hepatitis C virus infection care pathway—a report from the American Gastroenterological Association Institute HCV Care Pathway Work Group. Gastroenterology. 2017; 152(6):1588-1598.
  7. National Institute of Health (NIH). Management of hepatitis C. 2002. Rockville, MD NIH, August 26, 2002.
  8. Strader DB, Wright T, Thomas DL, Seeff LB; American Association for the Study of Liver Diseases.  Diagnosis, management, and treatment of hepatitis C. Hepatology. 2004; 39(4):1147-1171.
  9. Terrault NA, Bzowej NH, Chang K, et al. AASLD Guidelines for the treatment of chronic hepatitis B. Hepatology. 2016; 63(1):261-283.

FIB-4 Index

The use of specific product names is illustrative only.  It is not intended to be a recommendation of one product over another, and is not intended to represent a complete listing of all products available.

Document History






Medical Policy & Technology Assessment Committee (MPTAC) review. Rationale, Background, Index and References sections updated. The document header wording updated from “Current Effective Date” to “Publish Date.”



MPTAC review. Rationale, Background and Reference sections updated.



MPTAC review. Rationale, Background, Coding, Reference and Index sections updated. Removed ICD-9 codes from Coding section.



Updated Coding section with 07/01/2015 CPT change to descriptor for 0001M.



MPTAC review. Rationale, Background and Reference sections updated.



MPTAC review. Rationale, Background and Reference sections updated.



MPTAC review. Rationale, Background, Coding, Index, and Reference sections updated.



Updated Coding section with CPT changes effective 09/15/2012.



MPTAC review. Description, Rationale, Background, Reference and Index sections updated. Websites for additional information removed.



MPTAC review. Description, Rationale, Definitions, Reference link, and Index updated.



MPTAC review. Title of document, Description, Rationale, Background, and References updated.



MPTAC review. Description, Rationale, References and Index updated. Wording of position statement clarified, but no change to stance.



MPTAC review. Updated References. The phrase “investigational/not medically necessary” was clarified to read “investigational and not medically necessary” at the November 29, 2007 MPTAC meeting.



MPTAC review. Rationale and References updated.



MPTAC initial document development.