Coverage Policy Manual
Policy #: 2012025
Category: Laboratory
Initiated: June 2012
Last Review: April 2022
  Biomarkers for Liver Disease

Description:
Multianalyte serum assays with algorithmic analysis are being evaluated as a substitute for biopsy in the screening, evaluation, and monitoring of patients with chronic liver disease. Several commercially available tests are proposed to detect fibrosis, steatosis (fatty liver), or steatohepatitis (fatty liver with inflammation) in patients with hepatitis C, alcoholic liver disease, and non-alcoholic fatty liver disease.
 
Biopsy for Chronic Liver Disease. The diagnosis of non-neoplastic liver disease is often made from needle biopsy samples. In addition to establishing a disease etiology, liver biopsy can determine the degree of inflammation present and can stage the degree of fibrosis. The degree of inflammation and fibrosis may be assessed by different scoring schemes. Most of these scoring schemes grade inflammation from 0-4 (with 0 being no or minimal inflammation and 4 being severe) and fibrosis from 0-4 (with 0 being no fibrosis and 4 cirrhosis). There are several limitations to liver biopsy, including its invasive nature, small tissue sample size, and subjective grading system. Regarding small tissue sample size, liver fibrosis can be patchy and thus missed on a biopsy sample, which includes only 0.002% of the liver tissue. A noninvasive alternative to liver biopsy would be particularly helpful, both to initially assess patients and then as a monitoring tool to assess response to therapy.
 
Hepatitis C. Infection with the hepatitis C virus can lead to permanent liver damage. Liver biopsy is typically recommended prior to the initiation of antiviral therapy. Repeat biopsies may be performed to monitor fibrosis progression. Liver biopsies are analyzed according to a histologic scoring system; the most commonly used one for hepatitis C is the Metavir scoring system, which scores the presence and degree of inflammatory activity and fibrosis. The fibrosis is graded from F0-F4, with a Metavir score of F0 signifying no fibrosis and F4 signifying cirrhosis (which is defined as the presence throughout the liver of fibrous septa that subdivide the liver parenchyma into nodules and represents the final and irreversible form of disease). The stage of fibrosis is the most important single predictor of morbidity and mortality in patients with hepatitis C. Biopsies for hepatitis C are also 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.)
 
Alcoholic Liver Disease (ALD). ALD is the leading cause of liver disease in most Western countries. Histologic features of ALD usually include steatosis, alcoholic steatohepatitis (ASH), hepatocyte necrosis, Mallory bodies (tangled proteins seen in degenerating hepatocytes), a large polymorphonuclear inflammatory infiltrate, and, with continued alcohol abuse, fibrosis and possibly cirrhosis. The grading of fibrosis is similar to the scoring system used in hepatitis C. The commonly used Laënnec scoring system uses grades 0-4, with 4 being cirrhosis.
 
Non-alcoholic Fatty Liver Disease (NAFLD). NAFLD is defined as a condition that pathologically resembles ALD but occurs in patients who are not heavy users of alcohol. It may be associated with a variety of conditions, including obesity, diabetes, and dyslipidemia. The characteristic feature of NAFLD is steatosis. At the benign end of the spectrum of the disease, there is usually no appreciable inflammation, hepatocyte death, or fibrosis. In contrast, non-alcoholic steatohepatitis (NASH), which shows overlapping histologic features with ALD, is an intermediate form of liver damage, and liver biopsy may show steatosis, Mallory bodies, focal inflammation, and degenerating hepatocytes. NASH can progress to fibrosis and cirrhosis. A variety of histological scoring systems have been used to evaluate NAFLD. The NAS system for NASH includes scores for steatosis (0-3), lobular inflammation (0-3), and ballooning (0-2). Cases with scores of 5 or greater are considered NASH, while cases with scores of 3 and 4 are considered borderline (probable or possible) NASH. The grading of fibrosis is similar to the scoring system used in hepatitis C. The commonly used Laënnec scoring system uses grades 0-4, with 4 being cirrhosis.
 
Non-invasive Alternatives to Liver Biopsy. A variety of non-invasive laboratory tests are being evaluated as an alternative to liver biopsy. Biochemical 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 reflects fibrotic activity. Other direct measures of ECM deposition include hyaluronic acid or alpha-2 macroglobulin.
 
While many studies have been done on these individual markers, or on groups of markers in different populations of patients with liver disease, there has been interest in analyzing multiple markers using mathematical algorithms to generate a score that categorizes patients according to the biopsy score. It is proposed that these algorithms can be used as an alternative to liver biopsy in patients with liver disease. The following proprietary, algorithm-based tests are commercially available in the U.S.
 
HCV FibroSure™ (FibroTest™) uses a combination of 6 serum biochemical indirect markers of liver function plus age and gender in a patented algorithm to generate a measure of fibrosis and necroinflammatory activity in the liver that correspond to the Metavir scoring system for stage (i.e., fibrosis) and grade (i.e., necroinflammatory activity). The biochemical markers include the readily available measurements of alpha-2 macroglobulin, haptoglobin, bilirubin, gamma glutamyl transpeptidase (GGT), ALT, and apolipoprotein A1. Developed in France, the test has been clinically available in Europe under the name FibroTest™ since 2003 and is exclusively offered by LabCorp in the U.S. as HCV FibroSure™.
 
FibroSpect II uses a combination of 3 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 exclusively by Prometheus Laboratories.
 
ASH FibroSURE™ (ASH Test) uses a combination of 10 serum biochemical markers of liver function together with age, gender, height, and weight in a proprietary algorithm and is proposed to provide surrogate markers for liver fibrosis, hepatic steatosis, and alcoholic steatohepatitis (ASH). The biochemical markers include alpha-2 macroglobulin, haptoglobin, apolipoprotein A1, bilirubin, GGT, ALT, AST, total cholesterol, triglycerides, and fasting glucose. The test has been available in Europe under the name ASH Test™ and is exclusively offered by LabCorp in the U.S. as ASH FibroSure™.
 
NASH FibroSURE™ (NASH Test) uses a proprietary algorithm of the same 10 biochemical markers of liver function in combination with age, gender, height, and weight and is proposed to provide surrogate markers for liver fibrosis, hepatic steatosis, and NASH. The biochemical markers include alpha-2 macroglobulin, haptoglobin, apolipoprotein A1, bilirubin, GGT, ALT, AST, total cholesterol, triglycerides, and fasting glucose. The test has been available in Europe under the name NASH Test™ and is exclusively offered by LabCorp in this country as NASH FibroSure™.
 
HepaScore® Liver Fibrosis Panel is based on serum levels of alpha-2 macroglobulin, hyaluronic acid, GGT, and total bilirubin. HepaScore is a score from 0.00–1.00 calculated from the results of these four analyses and the age and sex of the patient. This test is meant as a screening tool to avoid unnecessary biopsies in patients with HCV. The lowest and highest scores may obviate the need for a biopsy, while intermediary scores should be interpreted in the overall clinical context of the individual patient (Rossi, et al., 2007; Quest Diagnostics, 2010).
 
Enhanced Liver Fibrosis (ELF™) Test measures three direct markers of fibrosis: hyaluronic acid (HA), procollagen III amino-terminal peptide (PIIINP), and tissue inhibitor of matrix metalloproteinase 1 (TIMP-1). The ELF Test, in conjunction with other laboratory and clinical findings, can be used to assess the risk of progression to cirrhosis and LREs in patients with chronic liver disease. The ELF Test is exclusively offered by Siemens.
 
LIVERFASt™ is a blood based diagnostic test that combines 10 biomarkers (Alpha-2-Macroglobulin, Haptoglobin, Apolipoprotein A1, Total Bilirubin, GGT, ALT [P5P], AST [P5P], Fasting Glucose, Triglyceride, and Total Cholesterol) and algorithm technology to determine the fibrosis, activity and steatosis stages of the liver. LIVERFASt™ is exclusively offered by Fibronostics.
 
Coding
Multianalyte assays with algorithmic analyses (MAAAs) use the results from multiple assays of various types in an algorithmic analysis to determine and report a numeric score(s) or probability. The results of individual component assays are not reported separately.
 
Effective in September 2012, there are specific CPT MAAA codes for the 3 FibroSURE™ tests performed by LabCorp –
 
HCV FibroSURE™, LabCorp
81596 - Infectious disease, HCV, 6 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 (Replaces 0001M as of 1/1/19.)
 
ASH FibroSURE™, LabCorp
0002M - Liver disease, 10 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)
 
NASH FibroSURE™, LabCorp
0003M - Liver disease, 10 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 non-alcoholic steatohepatitis (NASH)
 
There are no specific CPT codes that represent FibroSpect as a whole. At this time, it may be reported using the unlisted chemistry procedure code 84999 or with the codes for each component test. There is no specific CPT code for the use of the associated proprietary algorithm for FibroSpect.
 
FibroSpect
        • hyaluronic acid [CPT 83520 – Immunoassay, analyte, quantitative; not otherwise specified]
        • tissue inhibitor of metalloproteinase (TIMP-1) [CPT 83520 – Immunoassay, analyte, quantitative; not otherwise specified]  
        • alpha-2 macroglobulin [CPT 83883 – Nephelometry, each analyte not elsewhere specified]
 
Effective in April 2020, there are specific Proprietary Laboratory Analyses (PLA) codes for the ELF™ and LIVERFASt™ tests.
 
ELF™
0014M Liver disease, analysis of 3 biomarkers (hyaluronicacid [HA], procollagen III amino terminal peptide [PIIINP], tissue inhibitor of metalloproteinase 1[TIMP 1]), using immunoassays, utilizing serum, prognostic algorithm reported as a risk score and risk of liver fibrosis and liver related clinical events within 5 years
 
LIVERFASt™
0166U Liver disease, 10 biochemical assays (a2 macroglobulin, haptoglobin, apolipoprotein A1, bilirubin, GGT, ALT, AST, triglycerides, cholesterol, fasting glucose) and biometric and demographic data, utilizing serum, algorithm reported as scores for fibrosis, necroinflammatory activity, and steatosis with a summary interpretation

Policy/
Coverage:
Effective January 2022
 
Does Not Meet Primary Coverage Criteria Or Is Investigational For Contracts Without Primary Coverage Criteria
 
The use of FibroSURE, FibroTest, FibroSpect, ELF Test, or LIVERFASt to produce a predictive score indicating the probability and/or degree of liver fibrosis does not meet member benefit certificate primary coverage criteria for evaluation and/or monitoring of chronic liver disease or any other medical condition.
 
For members with contracts without primary coverage criteria, the use of FibroSURE, FibroTest, FibroSpect, ELF Test, or LIVERFASt to produce a predictive score indicating the probability and/or degree of liver fibrosis is considered not medically necessary. Services that are not medically necessary are specific contract exclusions in most member benefit certificates of coverage.
 
*NOTE- The use of simple biomarkers (e.g., Fib4 and/or APRI) used in conjunction with transient elastography and acoustic radiation force impulse imaging is addressed in a separate policy #2016007.
 
Effective July 2020 through December 2021
 
The use of FibroSURE, FibroTest, FibroSpect, ELF Test, or LIVERFASt to produce a predictive score indicating the probability and/or degree of liver fibrosis does not meet member benefit certificate primary coverage criteria.
 
For members with contracts without primary coverage criteria, the use of FibroSURE, FibroTest, FibroSpect, ELF Test, or LIVERFASt to produce a predictive score indicating the probability and/or degree of liver fibrosis is considered not medically necessary. Services that are not medically necessary are specific contract exclusions in most member benefit certificates of coverage.
 
*NOTE- The use of simple biomarkers (e.g., Fib4 and/or APRI) used in conjunction with transient elastography and acoustic radiation force impulse imaging is addressed in a separate policy #2016007.
 
Effective Prior to July 2020
The use of FibroSURE, FibroTest or FibroSpect, to produce a predictive score indicating the probability of liver fibrosis does not meet member benefit certificate primary coverage criteria.
 
For members with contracts without primary coverage criteria, the use of FibroSURE, FibroTest or FibroSpect to produce a predictive score indicating the probability of liver fibrosis is considered not medically necessary.  Services that are not medically necessary are specific contract exclusions in most member benefit certificates of coverage.
 
*NOTE- The use of simple biomarkers (e.g., Fib4 and/or APRI) used in conjunction with transient elastography and acoustic radiation force impulse imaging is addressed in a separate policy #2016007.
 
Effective Prior to April 2016
 
Biomarkers of hepatic fibrosis, used to produce a predictive score indicating the probability of liver fibrosis does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.
 
For members with contracts without primary coverage criteria, the use of biomarkers of hepatic fibrosis used to produce a predictive score indicating the probability of liver fibrosis is considered investigational.  Investigational services are specific contract exclusions in most member benefit certificates of coverage.
 

Rationale:
Introduction
Validation of the clinical use of any diagnostic test focuses on 3 main principles: 1) technical feasibility of the test; 2) diagnostic performance of the test, such as sensitivity, specificity, and positive and negative predictive values in relevant populations of patients and compared to the gold standard; and 3) clinical utility of the test, i.e., how the results of the diagnostic test will be used to improve the management of the patient.
 
HCV FibroSure (FibroTest™)
 
Technical Feasibility
Measurement of the serum levels of liver function tests (i.e., alpha-2 macroglobulin, haptoglobin, gamma glutamyl transpeptidase [GGT], total bilirubin, and apolipoprotein A1) are readily available biochemical tests. However, measurement of serum factors that directly measure fibrogenesis are relatively novel, and not readily available.
 
Diagnostic Performance
Initial research into the HCV FibroSure algorithm involved testing an initial panel of 11 serum markers in 339 patients with liver fibrosis who had undergone liver biopsy. From the original group of 11 markers, 5 were selected as the most informative, based on logisitic regression, neural connection, and receiver operating characteristic (ROC) curves. Markers included alpha-2 macroglobulin, haptoglobin, gamma globulin, apolipoprotein A1, gamma glutamyl transpepetidase, and total bilirubin (Imbert-Bismut, 2001). Using an algorithm-derived scoring system ranging from 0–1.0, the authors reported that a score of less than 0.10 was associated with a negative predictive value of 100% (i.e., absence of fibrosis, as judged by liver biopsy scores of METAVIR F2 -F4). A score greater than 0.60 was associated with a 90% positive predictive value of fibrosis (i.e., METAVIR F2 - F4). The authors concluded that liver biopsy might be deferred in patients with a score less than 0.10.
 
The next step in the development of this test was the further evaluation of the algorithm in a cross section of patients, including patients with hepatitis C virus (HCV) participating in large clinical trials before and after the initiation of antiviral therapy. One study focused on patients with hepatitis C who were participating in a randomized study of peginterferon and ribavirin (Poynard, 2003). From the 1,530 participants, 352 patients with stored serum samples and liver biopsies at study entry and at 24-week follow-up were selected. The HCV FibroSure score was calculated and then compared to the METAVIR liver biopsy score. At a cutoff point of 0.30, the HCV FibroSure score had 90% sensitivity and 88% positive predictive value for the diagnosis of METAVIR F2-F4. The specificity was 36%, and the negative predictive value was 40%. There was a large overlap in scores for patients in the METAVIR F2-F4 categories, and thus the scoring system has been primarily used to subdivide patients with and without fibrosis (i.e., METAVIR F0-F1 vs. F2-F4). When used as a monitoring test, patients can serve as their own baseline. Patients with a sustained virological response to interferon also experienced reductions in the FibroTest and ActiTest scores.
 
Further studies were done to formally validate the parameters used to calculate the HCV FibroSure scores. Acceptable levels of intra-laboratory and intra-patient variability were reported (Halfon, 2002; Imbert-Bismut, 2004).  Poynard and colleagues also evaluated discordant results in 537 patients who underwent liver biopsy and the HCV FibroSure and Actitest on the same day; with the discordance attributed to either the limitations in the biopsy or serum markers (Poynard, 2004). In this study, cutoff values were used for the individual METAVIR scores (i.e., F0-F4) and also for combinations of METAVIR scores (i.e., F0-F1, F1-F2, etc.) The definition of a significant discordance between FibroTest and ActiTest and biopsy scores was a discordance of at least 2 stages or grades in the METAVIR system. Discordance was observed in 29% of patients. 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 HCV 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% of patients and to the biopsy in 18% and nonattributed in 8.2% of patients. The authors suggest that biopsy failure, frequently to the small size of the biopsy sample, is a common problem. The diagnostic value of FibroSure-Fibrotest has also been evaluated for the prediction of liver fibrosis in patients with alcoholic liver disease (ALD) and non-alcoholic fatty liver disease (NAFLD) (Naveau, 2005; Ratziu, 2006). As noted in 2 reviews, the bulk of the research regarding HCV FibroSure was conducted by researchers with an interest in the commercialization of the algorithm (Afdhal, 2004; Lichtinghagen, 2004).
 
One Australian study attempted to independently replicate the results of FibroSure in 125 patients with hepatitis C. (10) Using the cutoff point of less than 0.1 to identify lack of bridging fibrosis (i.e., Metavir stages F0-F1) and greater than 0.6 to identify fibrosis (i.e., Metavir 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 that 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.
 
Clinical Utility
The clinical utility of a test depends on the demonstration that the test can be used to improve patient management. The primary benefit of the HCV FibroSure-FibroTest is its ability to avoid liver biopsy in patients without significant fibrosis. Thus, empiric data are needed that demonstrate that the Fibrosure test impacts clinician decision making on whether a biopsy should be performed and that the net effect is to reduce the overall number of biopsies while achieving similar clinical outcomes. There are currently no such published studies to demonstrate clinical utility.
 
These tests also need to be adequately compared to other non-invasive tests of fibrosis to determine their comparative efficacy. In particular, the proprietary, algorithmic tests should demonstrate superiority to other readily available, non-proprietary scoring systems in order to demonstrate that the tests improve health outcomes.
 
The test also has potential clinical utility as a means to follow response to therapy. In this case, evidence needs to demonstrate that the use of the test for response to therapy impacts decision making and that these changes in management decisions lead to improved outcomes. Although the FibroSure-FibroTest is reported to be widely disseminated and accepted in France, literature searches of English language publications have not identified any clinical articles in which the HCV FibroSure was actively used in the management of the patient. It is not clear whether the HCV FibroSure could be used in lieu of an initial liver biopsy, or whether it could be used as an interval test in patients receiving therapy to determine whether an additional liver biopsy was necessary.
 
ASH FibroSure (ASH-Test)
Technical Feasibility
 
As above.
 
Diagnostic Performance
In 2006, Thabut et al. reported the development of a panel of biomarkers (ASH FibroSure-ASH Test) for the diagnosis of alcoholic steatohepatitis (ASH) in patients with chronic alcoholic liver disease (ALD) (Thabut, 2006). Biomarkers were initially assessed with a training group consisting of 70 patients, and a panel was constructed using a combination of the 6 biochemical components of the FibroTest-ActiTest plus aspartate aminotransferase (AST). The algorithm was subsequently studied in 2 validation groups (one prospective study for severe ALD and one retrospective study for non-severe ALD) that included 155 patients and 299 controls. The severity of ASH (none, mild, moderate, and severe) was blindly assessed from biopsy samples. In the validation groups there were 28 cases (18%) of discordance between the diagnosis of ASH predicted by the ASH-Test and biopsy; 10 (36%) were considered to be false negatives of the ASH-Test, and 11 were suspected to be failures of biopsy. Seven cases were indeterminate by biopsy. The area under the ROC curves was 0.88 and 0.89 in the validation groups. The median ASH-Test value was 0.005 in controls, 0.05 in patients without or with mild ASH, 0.64 in the moderate ASH grade, and 0.84 in severe ASH grade 3. Using a cut-off value of 0.50, the ASH-Test had sensitivity of 80% and specificity of 84%, with positive and negative predictive values of 72% and 89%, respectively.
 
Several of the authors have an interest in the commercialization of this test, and no independent studies on the diagnostic performance of ASH FibroSure-ASH Test were identified. In addition, it is not clear if the algorithm used in this study is the same as in the currently commercially available test that includes 10 biochemicals.
 
Clinical Utility
The issues of clinical utility are similar to those discussed for the FibroSure-Fibro test. No studies were identified that assessed clinical outcomes following use of ASH FibroSure-ASH Test.
 
NASH FibroSure (NASH-Test)
 
Technical Feasibility
As above.
 
Diagnostic Performance
In 2006, Poynard et al. reported the development of a panel of biomarkers (NASH FibroSure-NASH Test) for the prediction of non-alcoholic steatohepatitis (NASH) in patients with NAFLD (Poynard, 2006). Biomarkers were initially assessed with a training group consisting of 160 patients, and a panel was constructed using a combination of 13 of 14 parameters of the currently available test (see description). The algorithm was subsequently studied in a validation group of 97 patients and 383 controls. Patients in the validation group were from a prospective multicenter study with hepatic steatosis at biopsy and suspicion of NAFLD. Histological diagnoses used Kleiner et al.’s scoring system, with 3 classes for NASH (NASH, borderline NASH, or no NASH). The main endpoint was steatohepatitis, defined as a histological NASH score (NAS) of 5 or greater. The area under the ROC curve for the validation group was 0.79 for the diagnosis of NASH, 0.69 for the diagnosis of borderline NASH, and 0.83 for the diagnosis of no NASH. Results showed sensitivity of 33% and specificity of 94% for NASH with positive and negative predictive values of 66% and 81%, respectively. For borderline NASH or NASH there was sensitivity of 88%, specificity of 50% and positive and negative predictive values of 74% and 72%, respectively. Clinically significant discordance (2 class difference) was observed in 8 patients (8%). None of the 383 controls were considered to have NASH by NASH FibroSure-NASH Test. The authors propose that this test would be suitable for mass screening for NAFLD in patients with obesity and diabetes.
 
An independent study from France was a prospective validation of the NASH Test (along with the Fibrotest, Steatotest and Actitest) in a cohort of 288 patients treated with bariatric surgery (Lassailly, 2011). Included were patients with severe or morbid obesity (body mass index [BMI] >35 kg/m2), at least 1 comorbidity for at least 5 years, and resistance to medical treatment. Excluded were patients with current excessive drinking, long-term consumption of hepatotoxic drugs, and positive screening for chronic liver diseases including hepatitis. Histology and biochemical measurements were centralized and blinded to other characteristics. The NASH test provided a 3-category score for no NASH (0.25), possible NASH (0.50), and NASH (0.75). The prevalence of NASH was 6.9%, while the prevalence of NASH or possible NASH was 27%. The concordance rate between histological NAS and the NASH Test was 43.1% with a weak kappa-reliability test (0.14). In 183 patients who were categorized as possible-NASH by the NASH Test, 124 (68%) were classified as no NASH by biopsy. In 15 patients categorized as NASH by the NASH Test, 7 (47%) were no NASH and 4 (27%) were possible NASH by biopsy. The negative predictive value of the NASH Test for possible NASH or NASH was 47.5%. The authors suggest that the power of this study to validate agreement between the NASH Test and biopsy was low, due to the low prevalence of NASH. However, the results show poor concordance between the NASH Test and biopsy, particularly for intermediate values.
 
Clinical Utility
The issues of clinical utility are similar to those discussed for the FibroSure-Fibro Test. No studies were identified that assessed clinical outcomes following use of NASH FibroSure-NASH Test.
 
FibroSpect II
 
Technical Feasibility
As noted above, the FibroSpect test consists of measurements of hyaluronic acid, TIMP-1, and alpha 2 macroglobulin. In a 2004 review, Lichtinghagen and Bahr noted that the lack of standardization of assays of matrix metalloproteinases and tissue inhibitors of metalloproteinase (TIMP) limited the interpretation of studies (Lichtinghagen, 2004).
 
Diagnostic Performance
Patel and colleagues investigated the use of these serum markers in an initial training set of 294 patients with hepatitis C and further validated the resulting algorithm in a validation set of 402 patients (Patel, 2004). The algorithm was designed to distinguish between no/mild fibrosis (F0-F1) and moderate to severe fibrosis (F2-F4). With the prevalence of F2-F4 disease of 52% and a cutoff value of 0.36; the positive and negative predictive values were 74.3% and 75.8%, respectively. Using a FibroSpect II cutoff score of 0.42, Christensen and colleagues reported a sensitivity of 93%, specificity of 66%, overall accuracy of 76%, and a negative predictive value of 94% for advanced fibrosis in 136 patients with hepatitis C (Christensen, 2006).
 
The published studies for this combination of markers continue to focus on test characteristics such as sensitivity, specificity, and accuracy (Mehta, 2008; Patel, 2008; Snyder, 2007).
 
Clinical Utility
The issues of clinical utility are similar to those discussed for the FibroSure-Fibro Test. No studies were identified in the published literature in which results of the FibroSpect test were actively used in the management of the patient.
 
HepaScore®
In a retrospective study, Bourliere studied HepaScore as an alternative to liver biopsy and FT and the proposal of five optimized combination algorithms to improve diagnostic accuracy (Bourliere, 2008). The study included 467 patients with HCV. Hepascore AUC for =F2, F3F4 and F4 diagnosis were 0.82, 0.84 and 0.90 respectively, in the same range as FT. HepaScore and FT were concordant in 387/ 467 (82%) for fibrosis staging. Among these patients, 342 /387 (88%) were concordant with liver biopsy. AUCs of AST to APRI and Forns for =F2 were 0.76 and 0.73 (0.65–0.79) respectively. The algorithm combining APRI and HepaScore had the highest rate of avoided liver biopsies (45%) with a high diagnostic accuracy (91%). The authors reported that Hepascore is an accurate non-invasive marker for =F2 and F4 diagnosis in HCV patients. In a pragmatic approach, a stepwise optimized algorithm combining APRI and FT or HepaScore considerably increases diagnostic accuracy and avoided liver biopsies. One of the reported limitations of this study is the distribution of liver biopsies among the cohort, with 49% of patients with =F2, reflecting the fact that most centers were referral centers for liver disease. This may be a limitation of the study, as non-invasive markers of fibrosis may have different diagnostic accuracies depending on the prevalence of significant fibrosis in the studied population. The authors noted that before HS can be used in routine practice, HepaScore should be validated on blood donor populations and on a larger population.
 
In a prospective study, Adams and colleagues used the HepaScore model to predict liver fibrosis in HCV patients (n=117) (Adams, 2005). The model was validated I 104 paitents from other institutions . The HepaScore produced AUROC of 0.85, 0.96, and 0.94 for significant fibrosis, advanced fibrosis, and cirrhosis, respectively. The Hepascore provided information for all patients: a score = 0.5 was 89–92% specific for the presence of significant fibrosis (METAVIR F2); and a score = 0.5 was 88–95% sensitive for the absence of advanced fibrosis (METAVIR F3). In the training set, a score = 0.5 (range, 0.0–1.0) was 92% specific and 67% sensitive for significant fibrosis, a score < 0.5 was 81% specific and 95% sensitive for advanced fibrosis, and a score < 0.84 was 84% specific and 71% sensitive for cirrhosis. Among the validation set, the AUC for significant fibrosis, advanced fibrosis, and cirrhosis were 0.82, 0.90, and 0.89, respectively. A score = 0.5 provided a specificity and sensitivity of 89% and 63% for significant fibrosis, whereas scores < 0.5 had 74% specificity and 88% sensitivity for advanced fibrosis. Thus, a HepaScore = 0.5 provided high PPVs (87% and 88%) for the presence of significant fibrosis, a Hepascore < 0.5 provided NPVs of 95% and 98% for advanced fibrosis, and a HepaScore < 0.84 provided NPVs of 94% and 98% for cirrhosis. The authors noted that further validation is required in community-based patients versus tertiary referral centers. Also, longitudinal studies are needed to determine whether the model is responsive to fibrosis change in the same individual over time. This study had a small sample of patients with cirrhosis which limits conclusions regarding accuracy of the test in this population.
 
Other Scoring Systems
Other scoring systems have been developed. For example 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 non-proprietary 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 patients with hepatitis C, the authors reported that the negative predictive value for fibrosis was 86% and that the positive predictive value was 88%.
 
Rosenberg and colleagues developed a scoring system based on an algorithm combining hyaluronic acid, amino terminal propeptide of type III collagen, and TIMP-1 (Rosenberg, 2004). The algorithm was developed in a test set of 400 patients with a wide variety of chronic liver diseases and then validated in another 521 patients. The algorithm was designed to discriminate between no or mild fibrosis and moderate to severe fibrosis. The negative predictive value for fibrosis was 92%.
 
Giannini et al. reported that use of the AST to alanine aminotransferase ratio (AST/ALT ratio) ratio and platelet counts in a diagnostic algorithm would have avoided liver biopsy in 69% of their patients and would have correctly identified the absence/presence of significant fibrosis in 80.5% of these cases (Giannini, 2006).
 
While most of the studies to identify fibrosis have been in patients with hepatitis C, studies are also being conducted in patients with chronic hepatitis B (HBV) (Mohamadnejad, 2006; Zeng, 2005). There are no studies of the clinical utility for these patients. Of note, some researchers have noted that different markers (e.g., HBV FibroSure) may be needed for this assessment in patients with hepatitis B (Wai, 2006).
 
A number of studies have compared HCV FibroSure-FibroTest and other non-invasive tests of fibrosis with biopsy using ROC analysis. For example, Bourliere and colleagues reported validation of FibroSure-FibroTest and reported that based on ROC analysis that FibroSure-FibroTest was superior to APRI (AST to platelet ratio index) for identifying significant fibrosis with areas under the ROC curve of 0.81 and 0.71, respectively (Bourliere, 2006). A 2012 prospective multicenter study from France compared 9 of the best-evaluated blood tests in 436 patients with hepatitis C and found similar performance for HCV (hepatitis C virus) FibroSure-FibroTest, Fibrometer and Hepascore (ROC curve: 0.84, 0.86, 0.84, respectively) (Zarski, 2012). These 3 tests were significantly superior to the 6 other tests with 70-73% of patients considered well-classified according to a dichotomized score (F0/F1 vs. > F2). The number of “theoretically avoided liver biopsies” for the diagnosis of significant fibrosis was calculated to be 35.6% for HCV FibroSure-FibroTest. In order to improve diagnostic performance, algorithms that combine HCV FibroSure-FibroTest with other tests such as APRI are also being evaluated (Zarski, 2012; Sebastiani, 2009; Boursier, 2012).
 
Summary
The HCV FibroSure test has been developed and extensively tested as a non-invasive measure of fibrosis, with the main body of literature published by the same group of investigators who developed the test. Data on the diagnostic accuracy and predictive value is variable. Although the negative predictive value for the FibroSure was reported as 100% by the authors who developed the test, another group of investigators reported a 89% negative predictive value, suggesting that 11% of patients would potentially forego initial antiviral therapy. A few studies have compared the diagnostic accuracy of FibroSure with other non-invasive tests and report that the area under the curve on ROC analysis is higher than for non-proprietary tests.
 
There are less published data regarding the ASH FibroSure and NASH FibroSure tests and the FibroSpect test. In one study, the negative predictive value (NPV) of FibroSpect was 75.8%, which is substantially lower than that reported for FibroSure. Because of the limited evidence on these other tests, the diagnostic accuracy and predictive ability is uncertain.
 
There were no studies identified that actually used the results of any of the tests to reduce the number of biopsies, or in the management of patients who are being treated. Therefore, there are inadequate scientific data to permit conclusions on whether HCV FibroSure, ASH FibroSure, NASH FibroSure, or FibroSpect or HepaScore improve health outcomes.
 
2014 Update
A literature search was conducted through May 2014. There was no new information identified that would prompt a change in the coverage statement. A summary of the key identified literature is included below.
 
In a 2013 systematic review, Chou and Wasson evaluated the accuracy of a wide variety of blood tests in determining fibrosis and/or cirrhosis (Chou, 2013). Both “simple” tests such as platelet count, and more complex scoring systems such as the Fibrotest and FibroIndex 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.
 
In a 2013 study, Park and colleagues compared liver biopsy and the FibroTest results obtained on the same day from 330 patients with chronic HBV (Park, 2013). Discordance was found in 30 patients (9.1%) of which the FibroTest underestimated fibrosis in 25 patients and overestimated fibrosis in 5 patients. Those with liver fibrosis F3 - F4 had a significantly higher discordance rate than F1 - F2 (15.4% vs. 3.0%, respectively, p<0.001). The only independent factor for discordance on multivariate analysis was F3 - F4 on liver biopsy (p<0.001).
 
Ongoing Clinical Trials
A search of ClinicalTrials.gov on June 21, 2013 identified one study using the FibroTest and transient elastography for liver fibrosis screening in diabetic patients (NCT01306110). Another study will compare FibroTest to transient elastography in alcoholic liver disease (NCT00708617). No active Phase 3 or randomized studies were identified.
 
Practice Guidelines and Position Statements
The 2012 practice guidelines on the diagnosis and management of non-alcoholic fatty liver disease, developed by the American Gastroenterological Association, the American Association for the Study of Liver Diseases, and the American College of Gastroenterology, do not reference multianalyte assays for liver fibrosis evaluation and management (Chalasani, 2012). The 2010 American College of Gastroenterology guidelines on alcoholic liver disease also do not reference multianalyte assays (O’Shea, 2010). The 2009 American Association for the Study of Liver Diseases guidelines on the diagnosis, management, and treatment of hepatitis C indicate: “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- consensus opinion; efficacy less well established by evidence) (Ghany, 2009).
  
2015 Update
A literature search conducted through May 2015 did not reveal any new information that would prompt a change in the coverage statement.  The key identified literature is summarized below.
 
In 2014 Morling and colleagues performed the Edinburgh type 2 diabetes study: using non-invasive biomarkers to identify hepatic fibrosis in people with type 2 diabetes mellitus (Morling, 2014). In the Edinburgh Type 2 Diabetes Study, a population-based cohort aged 60-74 years with type 2 diabetes, 831 participants underwent ultrasound assessment for fatty liver and had serum aspartate aminotransferase to alanine aminotransferase ratio (AST/ALT), aspartate to platelet ratio index (APRI), European Liver Fibrosis panel (ELF), Fibrosis-4 Score (FIB4) and liver stiffness measurement (LSM) measured. Literature based cut-offs yielded marked differences in the proportions of the cohort with probable liver fibrosis in the full cohort. Agreement between the top 5% of the distribution for each biomarker pair was poor. APRI and FIB4 had the best positive agreement at 76.4%, but agreement for all of the other serum biomarker pairs was between 18% and 34%. Agreement with LSM was poor (9-16%). Poor correlation was found between the five biomarkers of liver fibrosis studied. Using the top 5% of each biomarker resulted in good agreement on the absence of advanced liver disease but poor agreement on the presence of advanced disease. Further work is required to validate these markers against liver biopsy and to determine their predictive value for clinical liver-related endpoints, in a range of different low and high risk population groups.
 
Pérez and colleagues did a Validation study of systems for noninvasive diagnosis of fibrosis in nonalcoholic fatty liver disease in Latin population (Pérez, 2013). The incidence of liver cirrhosis is significantly high in Latin population. The high prevalence of nonalcoholic fatty liver disease NAFLD is likely partially responsible for these figures. Liver biopsy is not a practical diagnostic option in this scenario. The validation of noninvasive markers of fibrosis is important in populations with a high prevalence of NAFLD. Aim was to compare the diagnostic value of noninvasive assessment systems to detect fibrosis in a cohort of Latin patients with biopsy-proven NAFLD. Material and methods. Patients with biopsy-proven NAFLD were included. Noninvasive evaluations included calculations of NAFLD fibrosis, FIB-4, BARD scores, APRI, and AST/ALT ratio. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver-operating characteristic curve (AUROC) were calculated.  Results were a total of 228 patients (mean age, 48.6 ± 12.7 years) were included. Fifty-one percent were women; 48% were overweight and 23% were obese. The severity of fibrosis was classified as G0, 56.6%; G1, 25%; G2, 6.6%; G3, 7%; and G4, 4.8%. The AUROC values for advanced fibrosis were 0.72 for the NAFLD fibrosis score, 0.74 for FIB-4 score, 0.67 for AST/ALT ratio, 0.66 for APRI score, and 0.65 for BARD score. In 54% of patients with undetermined FIB-4 score and in 60% of patients with undetermined NAFLD fibrosis score, fibrosis was observed in the liver biopsy. The conclusion was the NAFLD fibrosis, FIB-4, and APRI scores can be used for the noninvasive diagnosis of fibrosis. However, 25% of patients evaluated by these methods have an indeterminate degree of fibrosis.
 
2017 Update
A literature search conducted using the MEDLINE database through March 2017 did not reveal any new literature that would prompt a change in the coverage statement.
 
2018 Update
Annual policy review completed with a literature search using the MEDLINE database through February 2018. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
 
Magnetic Resonance Elastography
A 2014 phase 1 study examined the interobserver agreement between 2 pathologists who assessed with MRE using biopsy results from 103 patients with chronic hepatitis B and C (Runge, 2014). The intraclass correlation coefficient (ICC) was very high at 0.99 (95% CI, 0.98 to 1.00). For the same patients, the ICC for these 2 pathologists using Metavir was 0.91 (95% CI, 0.86 to 0.94; difference with 23 MRE, p<0.001). In a second phase 1 study of 110 patients and 10 normative volunteers, the ICC for 2 raters was 0.993 for MRE. The absolute differences in elasticity assigned by the 2 raters were less than 0.8 kPa for more than 95% of the subjects (Motosugi, 2010). Twenty-one patients had also undergone liver biopsy. Shi et al demonstrated that, in 22 healthy volunteers liver, MRE had good short and mid-term (within 6 mo) repeatability (Shi, 2014). Venkatesh et al showed that liver stiffness measurements on MRE performed 4 to 6 weeks apart in a study of 41 healthy Asian volunteers had an ICC of 0.9 (95% CI, 0.78 to 0.96) and a within-subject coefficient of variation of 2.2% to 11.4% (Venkatesh, 2017). Yin et al retrospectively analyzed 1377 consecutive MRE examinations performed between 2007 and 2010 for patients with various chronic liver diseases (Yin, 2014). MRE had a success rate of 94% and highly reproducible measurements (r=0.972, p<0.001). BMI was not associated with success.
 
PRACTICE GUIDELINES AND POSITION STATEMENTS
 
American College of Gastroenterology
Guidelines published by the American College of Gastroenterology in 2017 on the role of elastography in chronic liver disease indicated that, in adults with chronic hepatitis B virus and HCV, VCTE has better diagnostic performance for diagnosing cirrhosis than the aminotransferase to platelet ratio index and FIB-4 (moderate quality of evidence for HCV, low quality of evidence for hepatitis B virus) (Singh, 2017). In addition, the guidelines stated that, in adults with HCV, magnetic resonance guided elastography has little or no increased diagnostic accuracy for identifying cirrhosis compared with VCTE in patients who have cirrhosis, and has lower diagnostic accuracy than VCTE in patients who do not have cirrhosis (very low quality of evidence).
 
2019 Update
A literature search was conducted through March 2019.  There was no new information identified that would prompt a change in the coverage statement.  The key identified literature is summarized below.
 
American Gastroenterological Association et al
The practice guidelines on the diagnosis and management of nonalcoholic fatty liver disease (NAFLD), developed by the American Gastroenterological Association, the American Association for the Study of Liver Diseases, and the American College of Gastroenterology stated that “NFS [NAFLD fibrosis score] or FIB-4 [Fibrosis-4] index are clinically useful tools for identifying NAFLD patients with higher likelihood of having bridging fibrosis (stage 3) or cirrhosis (stage 4).” (AGA, 2018). It also cited VCTE [vibration-controlled transient elastography] and MRE [magnetic resonance elastography] as “clinically useful tools for identifying advanced fibrosis in patients with NAFLD.”
 
American Association for the Study of Liver Diseases and Infectious Diseases Society of America
The American Association for the Study of Liver Diseases and Infectious Diseases Society of America guidelines for testing, managing, and treating hepatitis C virus (HCV) recommended that, for counseling and pretreatment assessment purposes, the following should be completed:
 
“Evaluation for advanced fibrosis using liver biopsy, imaging, and/or noninvasive markers is recommended in all persons with HCV infection to facilitate an appropriate decision regarding HCV treatment strategy and 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 trials, or meta-analyses]” (AASLDIDSA, 2018).
 
The guidelines noted that there are several noninvasive tests to stage the degree of fibrosis in patients with hepatitis C. Tests included indirect serum biomarkers, direct serum biomarkers, and vibration-controlled liver elastography. The guidelines asserted that no single method is recognized to have high accuracy alone and careful interpretation of these tests is required.
 
2020 Update
A literature search was conducted through March 2020.  There was no new information identified that would prompt a change in the coverage statement.  
 
2020 Update (July)
 
Tanwar and colleagues 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 (Tanwar, 2017). 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).
 
Sanyal et al (2019) reported on findings of 2, phase 2b, placebo-controlled trials of simtuzumab in NASH in patients with bridging fibrosis (F3; n=217) or compensated cirrhosis (F4; n=258) that assessed patients with liver biopsy and serum biomarker tests, including ELF, APRI, FibroSure/FibroTest, and the FIB-4 index. Laboratory screening was conducted at baseline and at every three months during the course of the trials. The trials were terminated after 96 weeks due to simtuzumab inefficacy, at which point data from treatment groups were combined for analysis. In patients with bridging fibrosis, increased risk of progression to cirrhosis was observed with higher baseline levels of all serum fibrosis tests (p < 0.001). Change in the ELF score over time was also associated with progression to cirrhosis (p<0.001). For a cut-off score of 9.76, progression to cirrhosis had a reported hazard ratio of 4.12 (95% CI: 2.14 to 7.93; p<0.001). For patients with compensated cirrhosis, higher levels of baseline biomarker tests were also associated with liver-related clinical events in 19% of patients, such as ascites, hepatic encephalophathy, newly diagnosed varices, esophageal variceal bleed, increase in Child-Pugh and/or MELD score, or death ( p<0.001 to 0.006). While the manufacturer of the test differentiates moderate from severe fibrosis with a cut-off ELF score of 9.8, current National Institute for Health and Care Excellence guidelines for NAFLD recommend reserving a diagnosis of advanced fibrosis to NAFLD patients with an ELF score of 10.51 or greater, limiting the clinical significance of these findings. (NICE, 2019) Furthermore, serum fibrosis test results were not directly used in patient management in the simtuzumab trials.
 
2021 Update
Annual policy review completed with a literature search using the MEDLINE database through March 2021. No new literature was identified that would prompt a change in the coverage statement.
 
2022 Update
Annual policy review completed with a literature search using the MEDLINE database through March 2022. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
 
Castellana et al conducted a meta-analytic head-to-head comparison between FIB-4 and NFS and found no significant differences regarding relative diagnostic OR, positive likelihood ratio, and negative likelihood ratio (Castellana, 2021). FIB-4 was associated with fewer indeterminate findings compared to NFS. Mozes et al found that FibroScan, a transient elastography test, outperformed all of the serum-based tests (Mozes, 2021).
 
Younossi et al evaluated the diagnostic value of ELF to assess liver fibrosis in patients with NAFLD (Younossi, 2021). This was a retrospective, cross-sectional study including 829 patients; 462 had transient elastography data and 463 had liver biopsy data. A significant increase in ELF scores was correlated in patients with advanced fibrosis by biopsy or transient elastography. The AUROC for ELF for identifying fibrosis was 0.81 (95% CI, 0.77 to 0.85) with biopsy as the reference standard and 0.79 (95% CI, 0.75 to 0.82) with transient elastography as the reference standard. Predictive combinations of ELF and FIB-4 scores were additionally evaluated. For ELF score 7.2 with a FIB-4 score 0.74, the sensitivity and NPV were 92.5% (95% CI, 87.4% to 97.5%) and 95.1% (95% CI, 91.8% to 98.4%), respectively, for ruling out fibrosis. For ELF score 9.8 with a FIB-4 score 2.9, the specificity and PPV were 99.7% (95% CI, 99.1% to 100%) and 95.0% (95% CI, 85.5% to 100%), respectively, for ruling in fibrosis.
 
Liu et al conducted a meta-analysis to evaluate the use of noninvasive scoring systems and histological scores to predict clinical outcomes in patients with NAFLD (Liu, 2021). Nineteen prospective or retrospective observational trials were included the study. The cutoff points of each scoring system were the same in each included study. There were 4, 3, and 3 studies included in the meta-analysis for assessing the predictive value of NFS, FIB-4, and APRI, respectively, for all-cause mortality. Both NFS-high versus NFS-low (thresholds, -1.455 and 0.676; pooled hazard [HR], 1.44; 95% CI, 1.05 to 1.96) and FIB-4-intermediate versus FIB-4-low (thresholds, 1.30 and 2.67; pooled HR, 1.55; 95% CI, 1.16 to 2.06) demonstrated statistical significance for predicting all-cause mortality. APRI was not predictive for all-cause mortality.
 
Jayaswal et al compared the prognostic value of MRI cT1 measurements, transient elastography, and multianalyte serum assays in a cohort of 197 patients with compensated chronic liver disease (Jayaswal, 2020). Patients who were referred for a clinically indicated liver biopsy, or with a known diagnosis of liver cirrhosis, were eligible. At baseline, patients underwent multiparametric MRI scans, transient elastography, and blood tests. Additionally, all patients received a liver biopsy and had their fibrosis rated on the Ishak scale; results of the biopsies informed clinical care. The most common underlying disease states were NAFLD (n=85, 43%), viral hepatitis (n=50, 25%), and ALD (n=22, 11%). The primary endpoint was a composite of ascites, variceal bleeding, hepatic encephalopathy, hepatocellular carcinoma, liver transplantation and mortality. Binary cutoff values were predefined. Patients were followed for a median of 43 months. Over this period, 14 new clinical events were recorded, including 11 deaths. Technical failures were also reported (eg, poor quality scan); reliable measurements were obtained in 182 of 197 (92%) patients for multiparametric MRI and in 121 of 160 (76%) patients for transient elastography (transient elastography was additionally not attempted in 37 patients). The study was limited by having variable follow-up periods and the effect of patients being censored at different time points was not taken into account, so sensitivities, specificities, PPVs and NPVs should be interpreted cautiously. The CI for the survival analysis were wide likely due to the relatively small number of new clinical events observed.
 
Pavlides et al evaluated whether data obtained from multiparametric MRI was predictive of all-cause mortality and liver-related clinical events (Pavlides, 2016). Patients who were referred for a clinically indicated liver biopsy, or with a diagnosis of liver cirrhosis on MRI scan, were eligible. Liver-related clinical events were defined as liver-related death, hepatocellular carcinoma, and new hepatic decompensation (ie, clinically evident ascites, variceal bleeding, and hepatic encephalopathy). Patients received multiparametric MRI and liver cT1 values were mapped into a Liver Inflammation and Fibrosis (LIF) score. One hundred twenty three patients were recruited to the study; 6 were excluded due to claustrophobia or incomplete MRI data. Of the 117 patients who had complete MRI data, follow-up data were available for 112; the study reported outcomes on these 112 patients. The most common underlying disease states were NAFLD (35%), viral hepatitis (30%), and ALD (10%). Over a median follow-up time of 27 months, 10 patients had a liver-related clinical event and 6 patients died. No patients who had a LIF <2 (no or mild liver disease) developed a clinical event. Ten of 56 (18%) patients with a LIF 2 (moderate or severe liver disease) experienced a clinical event. A study limitation is the use of LIF scores, which are no longer used in clinical practice. The authors further described the study as a small proof of principle study.
 
Multiparametric MRI has been used as an alternative to biopsy for measuring fibrosis or cirrhosis in clinical trials. Phase 2 clinical trials have used multiparametric MRI to measure therapeutic efficacy of an investigational treatments for NASH and NAFLD (Harrison, 2018; Nakajima, 2021).
 
The utility of multiparametric MRI to provide clinically useful information on the presence and extent of liver fibrosis and inflammation has been evaluated in smaller prospective studies. Specifically, it has been evaluated in the setting of biochemical remission in liver diseases where noninvasive testing for continued disease activity could further aid in direct management of patients as a prognostic marker of future liver-related complications. Quantitative multiparametric MRI has been used to measure disease burden after treatment (ie, liver fibrosis and inflammation response to therapy) in patients with chronic HCV and pediatric autoimmune hepatitis (Jayaswal, 2021; Janowski, 2021; Arndtz, 2021; Bradley, 2019).

CPT/HCPCS:
0001MInfectious disease, chronic hepatitis C virus (HCV) infection, 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
0002MLiver 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)
0003MLiver 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)
0014MLiver disease, analysis of 3 biomarkers (hyaluronic acid [HA], procollagen III amino terminal peptide [PIIINP], tissue inhibitor of metalloproteinase 1 [TIMP-1]), using immunoassays, utilizing serum, prognostic algorithm reported as a risk score and risk of liver fibrosis and liver-related clinical events within 5 years
0166ULiver disease, 10 biochemical assays (a2 macroglobulin, haptoglobin, apolipoprotein A1, bilirubin, GGT, ALT, AST, triglycerides, cholesterol, fasting glucose) and biometric and demographic data, utilizing serum, algorithm reported as scores for fibrosis, necroinflammatory activity, and steatosis with a summary interpretation
81596Infectious disease, chronic hepatitis C virus (HCV) infection, 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
82172Apolipoprotein, each
82247Bilirubin; total
82465Cholesterol, serum or whole blood, total
82977Glutamyltransferase, gamma (GGT)
83010Haptoglobin; quantitative
83520Immunoassay for analyte other than infectious agent antibody or infectious agent antigen; quantitative, not otherwise specified
83883Nephelometry, each analyte not elsewhere specified
84450Transferase; aspartate amino (AST) (SGOT)
84460Transferase; alanine amino (ALT) (SGPT)
84478Triglycerides
84999Unlisted chemistry procedure

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