Minireviews Open Access
Copyright ©The Author(s) 2015. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Mar 21, 2015; 21(11): 3223-3231
Published online Mar 21, 2015. doi: 10.3748/wjg.v21.i11.3223
Biomarkers in nonalcoholic fatty liver disease-the emperor has no clothes?
Madhusudana Girija Sanal, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, United States
Author contributions: Sanal MG conceived the issues which formed the content of the manuscript and wrote the manuscript.
Supported by IIP fellowship (2013-2014), Albert Einstein College of Medicine, New York, through the generosity of the Gruss Lipper Family Foundation.
Conflict-of-interest: The author does not have any conflict of interest associated with this manuscript.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Madhusudana Girija Sanal, MBBS, PhD, IIP Research Fellow, Albert Einstein College of Medicine, Room#323, Ullmann Building, 1300 Morris Park Avenue, Bronx, NY 10461, United States. sanalmg@gmail.com
Telephone: +1-347-3894440 Fax: +1-718-4303099
Received: November 22, 2014
Peer-review started: November 23, 2014
First decision: December 26, 2014
Revised: January 16, 2015
Accepted: February 11, 2015
Article in press: February 11, 2015
Published online: March 21, 2015

Abstract

Fatty liver is present in over ten percentage of the world population and it is a growing public health problem. Nonalcoholic fatty liver disease (NAFLD) is not a single disease, but encompasses a spectrum of diseases of different etiologies. It is difficult to find highly specific and sensitive diagnostic biomarkers when a disease is very complex. Therefore, we should aim to find relevant prognostic markers rather than accurate diagnostic markers which will help to minimize the frequency of liver biopsies to evaluate disease progression. There are several biomarker panels commercially available, however, there is no clear evidence that more sophisticated panels are better compared to simple criteria such as, presence of diabetes over five years, metabolic syndrome, obesity, obstructive sleep apnea, aspartate transaminase/alanine transaminase (ALT) ratio > 0.8 or ferritin levels > 1.5 times normal in patients with over six month history of raised ALT and/or ultrasonological evidence of fat in the liver. Currently the biomarker panels are not a replacement for a liver biopsy. However the need and benefit of liver biopsy in NAFLD is questionable because there is no convincing evidence that biopsy and detailed staging of NAFLD improves the management of NAFLD and benefits the patient. After all there is no evidence based treatment for NAFLD other than management of lifestyle and components of “metabolic syndrome”.

Key Words: Nonalcoholic fatty liver disease, Biomarkers, Fibrosis, Cirrhosis, Steatohepatitis, Liver biopsy

Core tip: Nonalcoholic fatty liver disease (NAFLD) is not a single disease, but encompasses a spectrum of diseases and this makes it very difficult to find highly specific and sensitive biomarkers. We should therefore aim to find relevant prognostic markers rather than accurate diagnostic markers which will help to minimize the frequency of liver biopsies to evaluate disease progression. There is no evidence that biopsy and detailed staging of NAFLD is important in the NAFLD management and benefits patients. Finally, there is no evidence based treatment for NAFLD other than management of ‘metabolic syndrome’ by pharmacological or non-pharmacological (lifestyle management/surgical) approaches.



INTRODUCTION

Fatty liver can be a sign of an underlying disorder but by itself it is not a disease. Nonalcoholic fatty liver disease (NAFLD) is not a single disease but encompasses a spectrum of diseases. No wonder that efforts to find a highly specific and sensitive biomarker for NAFLD have not become successful. About a quarter of fatty livers develop liver inflammation [nonalcoholic steatohepatitis (NASH)] and over a quarter of NASH patients develop severe fibrosis. We need biomarkers for the excess fat in liver, inflammation and fibrosis of liver. It is less likely that we could find liver specific proteins/molecules which can be used in commercial settings for identifying fat in liver. While there are several markers for inflammation, but it is difficult to find markers which are liver specific but superior to classic liver enzymes such as alanine transaminase (ALT). Similarly, it is difficult to find biomolecules which are specific for fibrosis of liver. We should therefore aim to find relevant prognostic markers rather than accurate diagnostic markers which will help to minimize the frequency of liver biopsies to evaluate disease progression. Despite several years of research, there is no clear evidence in the literature that any of the sophisticated algorithms or proprietary biomarker panels are good enough to avoid a liver biopsy compared to simple criteria such as, presence of diabetes over five years, metabolic syndrome, obesity, obstructive sleep apnea, aspartate transaminase (AST)/ALT ratio > 0.8 or ferritin levels > 1.5 times normal in patients with over six months history of raised ALT and/or ultrasonological evidence of fat in liver. Therefore, “more” is not necessarily ‘the better’ when it comes to the number of biomarkers, accuracy of diagnosis and staging of NAFLD. Moreover, the performance of biomarkers depends on the etiology of NAFLD and the stage of the disease and compromising their reliability. After all there is no evidence based treatment for NAFLD other than management of lifestyle and components of “metabolic syndrome”. There is no convincing evidence that biopsy and detailed staging of NAFLD improves the management of NAFLD and benefits the patients. Appropriate combination of lifestyle adjustments, pharmacological and non-pharmacological (such as bariatric surgery) intervention to improve the underlying cause of NAFLD such as diabetes should be undertaken in all cases of NAFLD with diabetes over five years, metabolic syndrome, obesity, obstructive sleep apnea, AST/ALT ratio > 0.8 or ferritin levels > 1.5 times normal in patients with over six months history of raised ALT and/or ultrasonological evidence of fat in liver.

It is important to detect the development of inflammation in fatty liver because greater than a quarter of these patients develop fibrosis which is associated with a high mortality rate. Detection of inflammation requires microscopic examination of liver biopsy specimens. The diagnosis of nonalcoholic steatohepatitis (inflamed fatty liver) is therefore histological[1-3]. However, liver biopsy is an invasive procedure which involves some serious patient risk and suffers from sampling errors[3]. In association with liver biopsy, various studies have reported mortality as high as 2% in the literature[4]. Though liver biopsy is recommended for therapeutic decisions, clinical practice guidelines for NAFLD have been modified therefore to include noninvasive tests for diagnosis of NASH. The European Association for the Study of the Liver had a special topic conference in NAFLD which showed a renewed interest on noninvasive biomarkers[5]. The prospect of imaging techniques [such as real-time elastography, acoustic radiation force impulse elastography, magnetic resonance spectroscopy and certain magnetic resonance imaging (MRI) based techniques] are currently more promising when compared to the prospect of biomarkers in the evaluation of fibrosis. Many of the non-invasive diagnosis techniques now employed for NAFLD were actually developed for managing chronic hepatitis C. The most important criteria to be evaluated in hepatitis C virus (HCV) and NAFLD are inflammation and progression of fibrosis, the two most important turning points in the course of fatty liver disease progression.

While there are several markers for inflammation only liver enzymes are specific to liver and even few are sufficiently sensitive enough to be a serum biomarker for clinical use. For example cytokeratin-18 (CK-18) is a relatively useful marker to differentiate non-alcoholic steatohepatitis (NASH) from fatty liver without inflammation. However its plasma levels are altered in several inflammatory conditions involving apoptotic response such as chronic viral hepatitis, chronic lung and renal diseases. Therefore, CK-18 is not definitive enough for routine diagnostic use as a marker for staging NASH[6].

This review will focus on the limitations of biomarkers and diagnostic panels presently available in the diagnosis and management of NAFLD. Although tremendous advances are presently being made in non-invasive imaging methods and other non-biomarker based methods inclusive of ultrasound based methods such as transient ultrasound elastography, Doppler analysis, acoustic radiation force impulse (ARFI), real-time elastography, tissue strain imaging, supersonic shear imaging, magnetic resonance based techniques such as MRI, diffusion-weighted MRI, magnetic resonance spectroscopy, X-ray based imaging techniques such as computed tomography (CT) and radioisotope based imaging techniques such as positron emission tomography and single photon emission computed tomography (SPECT), however they are beyond the scope of this review.

There exists a plethora of panels and scoring systems and plenty of redundancy exists among these tests. We will only consider some of these panels or scoring systems as detailed discussion about these all is also beyond the scope of this review. There are already many good reviews on biomarkers and diagnostic panels used in NAFLD, NASH and fibrosis[7-12].

MicroRNAs are implicated in pathogenesis of NAFLD, however more research is required to confirm and validate their usefulness as diagnostic or prognostic markers to qualify them for clinical use[13].

QUESTION OF BECOMING BETTER THAN THE GOLD STANDARD

An important fact to note is that when we decide the quality of a non-invasive test or biomarker, all non-invasive tests or biomarkers are compared against the “gold standard” and for NASH diagnosis it is liver biopsy. It is well documented that liver biopsy suffers from sample variability and inter-observer variability[3]. It is possible that in a proportion of samples where liver biopsy results were inaccurate but the biomarkers were correct, the comparative performance of biomarker will be reported inferior despite the reality that they gave superior results.

MARKERS OF INFLAMMATION

Pro-inflammatory cytokines, such as tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6), are raised in plasma in NASH patients compared to patients who suffer from fatty liver without inflammation. There are several reports showing strong association between IL-6 and non-alcoholic steatohepatitis (NASH)[14]. However, IL-6 is raised in several inflammatory conditions including insulin resistance and triggers fibrosis in multiple organs[15] IL-6 is not only involved in inflammation and infection responses but also it has anti-inflammatory action, besides, it is also involved in the regulation of metabolic, regenerative, and neural processes[16]. TNF-α level is increased several fold in NASH, however it is also increased in several inflammatory diseases, cancer and infections. Obesity is characterized by increased plasma levels of TNF-α, IL-6 and acute phase reactant proteins like C-reactive protein (CRP). It may be noted that about 70% of adults age twenty years and over are overweight or obese according to Center for Disease Control and Prevention, United States[17]. Pentraxin-related protein (PTX3), also known as TNF-inducible gene 14 (TSG-14) protein is rapidly induced in many cell types, in particular by mononuclear phagocytes, fibroblasts and endothelial cells in response to inflammatory signals such as TNF-α[18]. To be useful, IL-6 and TNF-α, should be sufficiently specific and should be able to distinguish between a fatty liver without inflammation from one with inflammation. The same is true for markers such as CRP, adiponectin, resistin, leptin, visfatin or retinol-binding protein 4 and PTX3. Ferritin is an intracellular protein that binds to iron and releases it in a controlled fashion present in all cells. Ferritin level increases in response to infection and inflammation. Serum ferritin is an independent predictor of advanced hepatic fibrosis among patients with NAFLD[19]. Both inflammation and accumulated fat in liver creates oxidative stress. Partially oxidized fat causes cellular damage and is known to attract leukocytes resulting in inflammatory response. Measurement of oxidative stress therefore is an indirect predictor of inflammation. However, both obesity and diabetes are independently associated with oxidative stress and inflammation[20]. Accumulated fat in liver will undergo slow oxidation inside hepatocytes, generating free radicals which will initiate a cascade of free radical reactions. Several of the stable intermediates and final products of these reactions can be quantified. Products of free radical–mediated oxidation of linoleic acid (9- and 13-hydroxy octadecadienoic acid and 9-13-oxo-octadecadienoic acid) measured in plasma were significantly elevated in NASH patients with reference to patients with fatty liver without inflammation or patients with normal biopsies[21]. Several compounds such as oxidized low density lipoproteins, malonaldehyde, thiobarbituric acid reactive substances (TBARS) or compounds arising from oxidized tyrosine are useful markers of oxidative stress. However they are of limited use in clinical diagnosis or management of NASH[22,23].

The human body has an anti-free radical regimen to counteract oxidative/nitrosative stress which is depleted during chronic free radical stress conditions such as NASH. The degree of depletion of antioxidant components of mammalian systems, such as glutathione (which is considered the main regulator of redox balance) is a reasonable surrogate measure for oxidative stress[24]. However, oxidative/nitrosative stress is now recognized to be a common characteristic of many acute and chronic diseases in addition to the normal aging process[25].

MARKERS OF REPAIR AND REMODELING RESPONSE

Chronic inflammation results in cell death (apoptosis and necrosis) which in turn induces repair and remodeling responses. Liver has enormous regeneration potential[3,7,9] and during this process several biomolecules are released into the bloodstream mainly from damaged/dying cells, tissue matrix, infiltrated immune cells and possibly from regenerating cells. This includes, liver enzymes and other proteins such as aspartate transaminase (AST), alanine transaminase (ALT), gamma-glutamyl transpeptidase (GGT), α2 macroglobulin (an inhibitor of fibrinolysis), haptoglobin (a protein which binds to free hemoglobin), apolipoprotein A1 (component of high density lipoprotein), tissue inhibitor of metalloproteinase 1 (TIMP1), Chitinase-3-like protein 1 (CHI3L1 also known as YKL-40, is a secreted glycoprotein) and constituents of extracellular matrix such as hyaluronic acid (HA) , laminin ,type IV collagen 7S domain, Pro-collagen III (PIIINP), procollagen I carboxyl terminal peptide (PICP), procollagen IV C peptide, procollagen IV N peptide (7-S collagen), cytokeratin 18 (CK-18 or KRT18- a type I cytokeratin present in glandular epithelia of the digestive, respiratory and urogenital tracts etc.)[7-12].

PRIMARY ETIOLOGICAL MARKERS OF NAFLD AND INDIRECT MARKERS ASSOCIATED WITH DECLINING LIVER FUNCTION AND HEALTH

Type 2 diabetes mellitus and adipose tissue dysfunction results in deposition of fat in liver[3]. Insulin resistance, dyslipidemia and obesity are therefore markers of fatty liver disease. Similarly, dysfunction of other organ systems may result in liver pathology. Liver is a key organ in maintaining good health and liver damage results in secondary damage to other organ systems. Liver damage is associated with changes in platelet values, renal and nervous system pathology. NAFLD is associated with cardiovascular risk and events associated with primary arterial hypertension[1-3].

MICRORNAS AS BIOMARKERS IN NAFLD

Recently, certain microRNAs were implicated in NAFLD, however, the available data is not sufficient to suggest their diagnostic use as markers of steatosis, inflammation or fibrosis. miR-122 and miR-34a levels were positively correlated with disease severity from simple steatosis to steatohepatitis. In both chronic hepatitis C (CHC) and NAFLD patients serum levels of miR-122 and miR-34a correlated with serum lipids, liver enzymes levels, and fibrosis stage and inflammation activity[26]. In a recent study, serum levels of circulating miRNAs, miR-21, miR-34a, miR-122 and miR-451 were found associated with nonalcoholic fatty liver disease and the serum level of miR-122 was correlated with the severity of liver steatosis[27]. Over-expressed microRNA-27a and 27b influence fat accumulation and cell proliferation during rat hepatic stellate cell activation but corresponding data from human studies are not presently available or corroborative[28]. In another rat study, Venugopal et al[29], reported that liver fibrosis is associated with a down regulation of miRNA-150 and miRNA-194 in hepatic stellate cells and their overexpression causes decreased stellate cell activation. In a study by Alisi et al[30] in rats, the miRNAs analysis showed the significant down regulation of three miRNAs, (miR-122, miR-451 and miR-27) and the up regulation of three (miR-200a, miR-200b and miR-429) in high fat diet (standard diet with high fructose and high fat diet combined with high fructose).

NONALCOHOLIC STEATOHEPATITIS DIAGNOSTIC PANELS: THE MORE PARAMETERS THE BETTER?

Although, there exists a variety of scoring systems and panels for evaluating the progression of fatty liver to NASH and cirrhosis exists, none of these markers can be a replacement for liver biopsy. Some of these panels depend on a dozen or more variables to derive the scores while others depend only on three or four parameters (Table 1). Despite the difference in the number of factors and the complexity of the mathematics involved in the biomarker panel development, the difference in efficiency and accuracy in diagnosing and/or staging inflammation and fibrosis that is associated with fatty liver disease is not very much different between these tests (see below).

Table 1 Some of these panels depend on a dozen or more variables to derive the scores while others depend only on three or four parameters.
Noninvasive testParametersDiseaseAUCRef.
APRIAST, platelet countFibrosis, cirrhosis in mixed patient population0.82Adler et al[40], Hepatology (2008)
Enhanced liver fibrosis (ELF) testHyaluronic acid, tissue inhibitor of matrix metalloproteinase-1, amino terminal propeptide of procollagen type IIINAFLD in children0.92 to 0.99Nobili et al[50], Gastroenterology (2009)
Chronic liver disease0.80Nobili et al[50], Gastroenterology (2009)
HAIRHypertension, ALT, IR indexNAFLD0.90Dixon et al[31], Gastroenterology (2001)
NashTestAlpha2-macroglobulin, haptoglobin, apolipoprotein A1, total bilirubin, GGT, fasting glucose, triglycerides, cholesterol, ALT, AST, age, gender, weight, heightNAFLD0.79Poynard et al[34], BMC Gastroenterology (2006)
A commercial panel from Biopredictive, France
FIB-4Platelets, ALT, AST and ageHCV fibrosis0.76Vallet-Pichard et al[38], Hepatology 2006
NAFLD fibrosis0.80Shah et al[39], Clinical Gastroenterology and Hepatology (2009)
FibroTest/FibroSureα2-macroglobulin , apolipoprotein A1, haptoglobin, total bilirubin, GGTNAFLD fibrosis0.86Ratziu et al[37], BMC gastroenterology (2006)
A commercial panel from Biopredictive, France
Age, AST, plateletHCV fibrosis0.783Hsieh et al[41], Chang Gung Med J (2009)
FibroQCount, PT-INR(F2-4)
Lok indexPlatelet count, PT-INR, AST, ALTHCV fibrosis0.78Lok et al[42], Hepatology (2005)
Forns ScoreAge, platelet count,HCV fibrosis0.86Forns X et al, Hepatology (2002)
GGT, cholesterolFibrosis from all causes0.76Adler et al[40], Hepatology (2008)
BARD ScoreBody-mass index, AST/ALT ratio, type 2 diabetes mellitusNAFLD fibrosis0.67Ruffillo et al[47], Journal of Hepatology (2011)
NAFLD fibrosis scoreAge, hyperglycemia, body mass index, platelet count, albumin, and AST/ALT ratioNAFLD fibrosis0.82Angulo et al[45], Hepatology (2007)
0.68Ruffillo et al[47], Journal of Hepatology (2011)
FibrometerPlatelets, prothrombin index, aspartate aminotransferase, α2-macroglobulin (A2M), hyaluronate, urea, and ageViral and alcoholic chronic liver diseases fibrosis0.883Calès et al[43], Hepatology (2005)
NAFLD0.943Calès et al[44], Journal of Hepatology (2009)
Brief review on the biomarkers/panels in NAFLD

In a paper published in 2001 Dixon et al[31] found that: (1) a raised index of Insulin; Resistance (OR = 9.3); (2) systemic hypertension (OR = 5.2); and (3) raised alanine aminotransferase (OR = 8.6) were independent predictors of NASH. A combination of any two or all three of these predictors showed a sensitivity of 0.8 and specificity of 0.89 for NASH. The accuracy of the test was found by receiver operating characteristic (ROC) analysis. They reported an area under the curve (AUC) equal to 0.90 for the combination of these three predictors[31].

A composite index for distinguishing steatosis from NASH was formulated by Palekar et al[32] which included the risk factors, age > 50 years, female gender, AST 45 IU/L, BMI 30 kg/m2, AST/ALT ratio ≥ 0.80, and HA ≥ 55 mcg/L, and its accuracy was determined by ROC analysis to be 0.763. The presence of three or more risk factors had sensitivity and specificity of 73.7% and 65.7% respectively[32].

A commercial panel, the “NashTest” from BioPredictive a French company, combines α2-macroglobulin, haptoglobin, apolipoprotein A1, total bilirubin, GGT, fasting blood glucose (FBS), triglycerides (TG), cholesterol, ALT and AST, with parameters adjusted for patient’s age, gender, weight and height[33]. According to Thierry Poynard, the inventor of this patented test, the accuracy of NashTest was determined by ROC analysis. The AUC of the “NashTest” for diagnosing NASH in the training and validation groups were, 0.79 and 0.79 (P = 0.94) respectively[34]. Therefore the test result for “NashTest” was not quite as impressive; and we need several independent and international studies to prove the usefulness of the “NashTest”.

The “FibroTest” (in the United States it is marketed as “FibroSure”) is a hepatic damage score that is useful in a variety of diseases involving the liver. It is derived from age, gender and five serum markers[33]. The markers are α-2-macroglobulin, haptoglobin, apolipoprotein a1 (APOA1), GGT, total bilirubin. ALT is used in another sub-test called ActiTest, for measuring necro inflammatory activity in patients with chronic hepatitis C or B. The patented formula for calculating the FibroTest score logistic regression coefficient is the following or a variant which can be found in the public domain[35].

The “FibroTest” is well standardized, reproducible and commercially available. According to a report by Imbert-Bismut et al[36] the impact of parameter analytical variability on Fibrotest and Actitest results was less than 10% and intra-patient reproducibility was within acceptable limits[36]. FibroTest was evaluated in two groups, group 1 from a reference center and group 2 was a multicenter study. The ROCs for the diagnosis of advanced fibrosis (F2F3F4): 0.86 in group 1 and 0.75 in group 2[37].

Biopredictive also offers the “SteatoTest” which combines α 2-macroglobulin, haptoglobin, APOA1, total bilirubin, GGT, fasting glucose, triglycerides, cholesterol and ALT, parameters adjusted for patient’s age, gender, weight and height according to the company’s website. Fibromax is the combination of FibroTest, SteatoTest and NashTest, available from the same company, “Biopredictive”[33].

FIB-4 is “an inexpensive and accurate marker of fibrosis in HCV infection in comparison with liver biopsy and Fibrotest” according to Vallet-Pichard et al[38] in a paper published in 2006. FIB-4, depends common clinical parameters-platelets, ALT, AST and age. According to the authors, “FIB-4 value < 1.45 or > 3.25 (64.6% of the cases) was concordant with the FibroTest results in 92.1% and 76%, respectively” and AUC was 0.76. A 2009 study by Shah et al[39] compared the performance of the FIB4 index with six other non-invasive markers of fibrosis in patients with NAFLD. They found that the FIB4 index is superior to the other noninvasive markers of fibrosis in patients with NAFLD [the AUC was greatest for FIB4 (AUC = 0.802)]. The authors however highlighted the need for even better noninvasive markers for NAFLD.

The AST-to-platelet ratio index (APRI) was developed as a simple, easy to use method in clinics to predict, severe fibrosis or cirrhosis in both HCV mono-infected and co-infected (HCV and HIV) patients. According to a meta-analysis of twenty two studies with 4,266 subjects, the summary AUCs of the APRI for significant fibrosis and cirrhosis were 0.76 and 0.82, respectively. For significant fibrosis, an APRI threshold of 0.5 was 81% sensitive and 50% specific. The Forns Index is mathematically derived from four simple parameters, age, GGT, cholesterol and platelet count. This index is best studied in HCV related fibrosis and it is useful with AUC of 0.750 and 0.760 respectively for the prediction of significant fibrosis (F/S2-4) in HCV and fibrosis from all causes. Comparable values for FibroTest are AUC of 0.794 and 0.800 respectively[40].

AST level, platelet count and prothrombin time (PT) international normalized ratio (INR) and the at onset are the variables considered in “FibroQ”, another test for predicting fibrosis in HCV developed by a group in Taiwan in 2009. According to these investigators, FibroQ performed better than APRI, but was similar to ALT/AST ratio, in the prediction of significant fibrosis (it was possible to distinguish between patients with or without fibrosis in 77% of the patient population)[41].

Lok et al[42] proposed another simple formula for predicting fibrosis in chronic hepatitis C (CHC). The Lok index was based on platelet count, PT-INR, serum AST and ALT levels. Lok et al[42] studied a cohort of 1141 patients with CHC and reported an AUROC of 0.78-0.81 to detect cirrhosis. Calès et al[43] in 2005 reported a test which they named the “Fibrometer” to characterize different fibrosis parameters in viral and alcoholic chronic liver diseases. This test is based on the values platelets, prothrombin index, aspartate aminotransferase, α2-macroglobulin, hyaluronate, urea, and age. The AUC for Fibrometer was 0.883 compared with 0.808 for the Fibrotest. Recently the same group used Fibrometer to measure fibrosis in NAFLD. They found that it was superior to NAFLD fibrosis score (NFSA) and APRI. AUC for Fibrometer was 0.943 and for NFSA and APRI the values were 0.884 and 0.866, respectively[44]. The NAFLD fibrosis score was introduced by Angulo et al[45] in 2007 and includes routine clinical/lab variables such as age, hyperglycemia, body mass index, platelet count, albumin, and AST/ALT ratio. This scoring was efficient in predicting fibrosis and had an AUC of 0.82 in the validation group. Harrison et al[46] proposed an index, referred to as the BRAD score, which included- body-mass index (BMI), AST/ALT ratio (AAR), and presence of type 2 diabetes mellitus. They scored these variables as follows-BMI ≥ 28 kg/m2 = 1 point, BMI < 28 kg/m2 = 0 point; AST/ALT ratio ≥ 0.8 = 2 points, AST/ALT ratio < 0.8 = 0 points; freshly recognized or preexisting diabetes = 1 point. A total of 2-4 points meant significant fibrosis[46]. Ruffillo et al[47] evaluated the diagnostic accuracy of this score in NAFLD patients and concluded that this score is useful in identifying patients without severe fibrosis.

A total of 2411 patients with compensated CLD (HCV = 75.1%, HBV = 10.5%, NASH = 7.9%, HIV/HCV = 6.5%) were evaluated by APRI, Forns index, Lok index, AST/ALT ratio, Fib-4, platelets and Fibrotest-Fibrosure against liver biopsy, in a multicenter study. This study concluded that the diagnostic performance is better for significant fibrosis for CHC compared with NAFLD patients, but accuracy was relatively poor among CHC patients with ALT[48].

Enhanced liver fibrosis (ELF) is a modified version of the original European Liver Fibrosis panel[49]. The original panel includes hyaluronic acid, tissue inhibitor of matrix metalloproteinases-1, amino terminal propeptide of procollagen type III (which are involved in the synthesis and degradation of extracellular matrix) and age. Later the parameter “age” was removed from the panel establishing the enhanced liver fibrosis (ELF) test[49,50]. The test was effective in predicting NAFLD in children (AUC ranging from 0.92 to 0.99, from fibrosis stage 1 to stage 3)[50].

HOW IMPORTANT IS EXACT STAGE INFORMATION IN THE MANAGEMENT OF NAFLD?

It seems, rather than patient management, exact stage information is more important in academic research and in clinical trials (especially where different drugs are being tried on a limited number of patients). There may be only subtle differences between some of these drugs, which can only be better identified if there exists a good scoring system to evaluate the progress or regression of steatohepatitis.

The appearance and persistence of inflammation is an important turning point in the history of fatty liver disease. The presence of inflammation in “fatty liver” needs to be taken quite seriously because it can progress to fibrosis depending on the patient’s genome and epigenome over time[1-4]. The major deficiency of most of the panels is the inability to identify this critical point effectively. Current panels are not reliable in distinguishing fatty liver disease from NASH accurately, although they are good at deciding fibrosis. Identification of fatty liver disease is important because of the associated liver, cardiovascular and cerebrovascular risk[3,51]. However when it comes to the disease staging, it is hitherto not clear whether accurate staging of the disease has a role in the management and what is its implication in practice.

The usefulness of accurate staging and grading of steatosis, inflammation and fibrosis in the management of NAFLD is controversial because of the following reasons. Firstly, pharmacological treatment is not warranted for simple fatty liver (fatty liver without inflammation). Secondly, there are no approved drugs for NASH[5]. Finally, to date, anti-fibrotic treatment of fibrosis represents, an unsuccessful area, by and large, for drug development[52]. Currently therapy for NAFLD aims at achieving good control of diabetes, hypertension and body mass in diabetic, hypertensive and overweight/obese NASH patients through pharmacological, surgical or non-pharmacological methods such as lifestyle modification. There is no clear “evidence-based treatment” for NAFLD[53,54]. A literature search, didn’t reveal to date, any definite guidelines from professional organizations other than what is described (vide-supra) for management of inflammation and fibrosis associated with NAFLD in a stage specific manner. It is therefore difficult to decide the usefulness of staging information on steatosis, inflammation and fibrosis in the currently available treatment methods for NAFLD. This implies, as far as treatment and benefit to the patients is concerned, small differences in efficiency (calculated often in terms of AUC by ROC analysis) between sophisticated, proprietary and costly/commercial tests and scoring algorithms versus simple, inexpensive, easily available non-proprietary tests and scoring systems may be insignificant (Table 1). A simple criteria such as presence of diabetes over five years, metabolic syndrome, obesity, obstructive sleep apnea, AST/ALT ratio > 0.8 or ferritin levels > 1.5 times normal in patients with over six months history of raised ALT and/or ultrasonological evidence of fat in liver would identify patients who need special care and personalized treatment depending on the comorbidities and etiology of NAFLD.

CONCLUSION

Despite the extensive research, development and investment in the field of biomarkers for NAFLD, it is doubtful how much benefit this has brought to the patients. Commercial panels and scoring systems have not improved upon the simpler, widely available, cost effective tests and clinical parameters and they offer little benefit in the management of NAFLD. The performance to date of biomarkers depends very much on the patient, the etiology of NAFLD and the stages of the disease and cannot be considered as a replacement for liver biopsy. Biomarkers, therefore, should serve as a tool to optimize the selection of patients with NAFLD for liver biopsy. There is no clear evidence that liver biopsy and detailed staging of the disease significantly influences the management decisions and benefits the patient. After all, there is no “evidence based medicine” for NAFLD except the management of associated morbidities such as components of the “metabolic syndrome” or (the largely symptomatic management) of cirrhosis.

ACKNOWLEDGMENTS

The manuscript was edited by Mr. Alan Alfieri and proof read by both A.Alfieri and R.Khan.

Footnotes

P- Reviewer: Fierbinteanu-Braticevici C, Gong ZJ, Roncucci L S- Editor: Ma YJ L- Editor: A E- Editor: Liu XM

References
1.  Adams LA, Sanderson S, Lindor KD, Angulo P. The histological course of nonalcoholic fatty liver disease: a longitudinal study of 103 patients with sequential liver biopsies. J Hepatol. 2005;42:132-138.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 647]  [Cited by in F6Publishing: 626]  [Article Influence: 32.9]  [Reference Citation Analysis (1)]
2.  Sanal MG. The blind men ‘see’ the elephant-the many faces of fatty liver disease. World J Gastroenterol. 2008;14:831-844.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 34]  [Cited by in F6Publishing: 35]  [Article Influence: 2.2]  [Reference Citation Analysis (0)]
3.  Sanal MG. Nonalcoholic fatty liver disease: the concept and confusion. Minerva Gastroenterol Dietol. 2011;57:419-426.  [PubMed]  [DOI]  [Cited in This Article: ]
4.  Thampanitchawong P, Piratvisuth T. Liver biopsy: complications and risk factors. World J Gastroenterol. 1999;5:301-304.  [PubMed]  [DOI]  [Cited in This Article: ]
5.  Ratziu V, Bellentani S, Cortez-Pinto H, Day C, Marchesini G. A position statement on NAFLD/NASH based on the EASL 2009 special conference. J Hepatol. 2010;53:372-384.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 723]  [Cited by in F6Publishing: 743]  [Article Influence: 53.1]  [Reference Citation Analysis (0)]
6.  Cusi K, Chang Z, Harrison S, Lomonaco R, Bril F, Orsak B, Ortiz-Lopez C, Hecht J, Feldstein AE, Webb A. Limited value of plasma cytokeratin-18 as a biomarker for NASH and fibrosis in patients with non-alcoholic fatty liver disease. J Hepatol. 2014;60:167-174.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 178]  [Cited by in F6Publishing: 170]  [Article Influence: 17.0]  [Reference Citation Analysis (0)]
7.  Parsian H, Alizadeh M, Yahyapour Y.  Clinical Application of Non-Invasive Markers of Liver Fibrosis. 2013;.  [PubMed]  [DOI]  [Cited in This Article: ]
8.  Patel K, Shackel NA. Current status of fibrosis markers. Curr Opin Gastroenterol. 2014;30:253-259.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 34]  [Cited by in F6Publishing: 36]  [Article Influence: 3.6]  [Reference Citation Analysis (0)]
9.  Pearce SG, Thosani NC, Pan JJ. Noninvasive biomarkers for the diagnosis of steatohepatitis and advanced fibrosis in NAFLD. Biomark Res. 2013;1:7.  [PubMed]  [DOI]  [Cited in This Article: ]
10.  Lee HH, Seo YS, Um SH, Won NH, Yoo H, Jung ES, Kwon YD, Park S, Keum B, Kim YS. Usefulness of non-invasive markers for predicting significant fibrosis in patients with chronic liver disease. J Korean Med Sci. 2010;25:67-74.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 19]  [Cited by in F6Publishing: 20]  [Article Influence: 1.4]  [Reference Citation Analysis (0)]
11.  Castera L, Vilgrain V, Angulo P. Noninvasive evaluation of NAFLD. Nat Rev Gastroenterol Hepatol. 2013;10:666-675.  [PubMed]  [DOI]  [Cited in This Article: ]
12.  Vizzutti F, Arena U, Nobili V, Tarquini R, Trappoliere M, Laffi G, Marra F, Pinzani M. Non-invasive assessment of fibrosis in non-alcoholic fatty liver disease. Ann Hepatol. 2009;8:89-94.  [PubMed]  [DOI]  [Cited in This Article: ]
13.  Cheung O, Puri P, Eicken C, Contos MJ, Mirshahi F, Maher JW, Kellum JM, Min H, Luketic VA, Sanyal AJ. Nonalcoholic steatohepatitis is associated with altered hepatic MicroRNA expression. Hepatology. 2008;48:1810-1820.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 518]  [Cited by in F6Publishing: 513]  [Article Influence: 32.1]  [Reference Citation Analysis (0)]
14.  Wieckowska A, Papouchado BG, Li Z, Lopez R, Zein NN, Feldstein AE. Increased hepatic and circulating interleukin-6 levels in human nonalcoholic steatohepatitis. Am J Gastroenterol. 2008;103:1372-1379.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 395]  [Cited by in F6Publishing: 422]  [Article Influence: 26.4]  [Reference Citation Analysis (0)]
15.  Fielding CA, Jones GW, McLoughlin RM, McLeod L, Hammond VJ, Uceda J, Williams AS, Lambie M, Foster TL, Liao CT. Interleukin-6 signaling drives fibrosis in unresolved inflammation. Immunity. 2014;40:40-50.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 237]  [Cited by in F6Publishing: 257]  [Article Influence: 25.7]  [Reference Citation Analysis (0)]
16.  Scheller J, Chalaris A, Schmidt-Arras D, Rose-John S. The pro- and anti-inflammatory properties of the cytokine interleukin-6. Biochim Biophys Acta. 2011;1813:878-888.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1902]  [Cited by in F6Publishing: 2119]  [Article Influence: 163.0]  [Reference Citation Analysis (0)]
17.  CDC. National Center for Health Statistics.  Available from: http://www.cdc.gov/nchs/fastats/obesity-overweight.htm accessed 9/30/2014.  [PubMed]  [DOI]  [Cited in This Article: ]
18.  PTX3 pentraxin 3, long [Homo sapiens (human)]  Available from: http://www.ncbi.nlm.nih.gov/gene/5806accessedon9/30/2014.  [PubMed]  [DOI]  [Cited in This Article: ]
19.  Kowdley KV, Belt P, Wilson LA, Yeh MM, Neuschwander-Tetri BA, Chalasani N, Sanyal AJ, Nelson JE. Serum ferritin is an independent predictor of histologic severity and advanced fibrosis in patients with nonalcoholic fatty liver disease. Hepatology. 2012;55:77-85.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 322]  [Cited by in F6Publishing: 349]  [Article Influence: 29.1]  [Reference Citation Analysis (0)]
20.  Matsuda M, Shimomura I. Increased oxidative stress in obesity: implications for metabolic syndrome, diabetes, hypertension, dyslipidemia, atherosclerosis, and cancer. Obes Res Clin Pract. 2013;7:e330-e341.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 375]  [Cited by in F6Publishing: 399]  [Article Influence: 39.9]  [Reference Citation Analysis (0)]
21.  Feldstein AE, Lopez R, Tamimi TA, Yerian L, Chung YM, Berk M, Zhang R, McIntyre TM, Hazen SL. Mass spectrometric profiling of oxidized lipid products in human nonalcoholic fatty liver disease and nonalcoholic steatohepatitis. J Lipid Res. 2010;51:3046-3054.  [PubMed]  [DOI]  [Cited in This Article: ]
22.  Yesilova Z, Yaman H, Oktenli C, Ozcan A, Uygun A, Cakir E, Sanisoglu SY, Erdil A, Ates Y, Aslan M. Systemic markers of lipid peroxidation and antioxidants in patients with nonalcoholic Fatty liver disease. Am J Gastroenterol. 2005;100:850-855.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 199]  [Cited by in F6Publishing: 205]  [Article Influence: 10.8]  [Reference Citation Analysis (0)]
23.  Chalasani N, Deeg MA, Crabb DW. Systemic levels of lipid peroxidation and its metabolic and dietary correlates in patients with nonalcoholic steatohepatitis. Am J Gastroenterol. 2004;99:1497-1502.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 252]  [Cited by in F6Publishing: 244]  [Article Influence: 12.2]  [Reference Citation Analysis (0)]
24.  Sánchez-Gómez FJ, Espinosa-Díez C, Dubey M, Dikshit M, Lamas S. S-glutathionylation: relevance in diabetes and potential role as a biomarker. Biol Chem. 2013;394:1263-1280.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 26]  [Cited by in F6Publishing: 26]  [Article Influence: 2.6]  [Reference Citation Analysis (0)]
25.  Dalle-Donne I, Rossi R, Colombo R, Giustarini D, Milzani A. Biomarkers of oxidative damage in human disease. Clin Chem. 2006;52:601-623.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1075]  [Cited by in F6Publishing: 1071]  [Article Influence: 59.5]  [Reference Citation Analysis (0)]
26.  Cermelli S, Ruggieri A, Marrero JA, Ioannou GN, Beretta L. Circulating microRNAs in patients with chronic hepatitis C and non-alcoholic fatty liver disease. PLoS One. 2011;6:e23937.  [PubMed]  [DOI]  [Cited in This Article: ]
27.  Yamada H, Suzuki K, Ichino N, Ando Y, Sawada A, Osakabe K, Sugimoto K, Ohashi K, Teradaira R, Inoue T. Associations between circulating microRNAs (miR-21, miR-34a, miR-122 and miR-451) and non-alcoholic fatty liver. Clin Chim Acta. 2013;424:99-103.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 210]  [Cited by in F6Publishing: 234]  [Article Influence: 21.3]  [Reference Citation Analysis (0)]
28.  Ji J, Zhang J, Huang G, Qian J, Wang X, Mei S. Over-expressed microRNA-27a and 27b influence fat accumulation and cell proliferation during rat hepatic stellate cell activation. FEBS Lett. 2009;583:759-766.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 237]  [Cited by in F6Publishing: 261]  [Article Influence: 17.4]  [Reference Citation Analysis (0)]
29.  Venugopal SK, Jiang J, Kim TH, Li Y, Wang SS, Torok NJ, Wu J, Zern MA. Liver fibrosis causes downregulation of miRNA-150 and miRNA-194 in hepatic stellate cells, and their overexpression causes decreased stellate cell activation. Am J Physiol Gastrointest Liver Physiol. 2010;298:G101-G106.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 161]  [Cited by in F6Publishing: 178]  [Article Influence: 12.7]  [Reference Citation Analysis (0)]
30.  Alisi A, Da Sacco L, Bruscalupi G, Piemonte F, Panera N, De Vito R, Leoni S, Bottazzo GF, Masotti A, Nobili V. Mirnome analysis reveals novel molecular determinants in the pathogenesis of diet-induced nonalcoholic fatty liver disease. Lab Invest. 2011;91:283-293.  [PubMed]  [DOI]  [Cited in This Article: ]
31.  Dixon JB, Bhathal PS, O’Brien PE. Nonalcoholic fatty liver disease: predictors of nonalcoholic steatohepatitis and liver fibrosis in the severely obese. Gastroenterology. 2001;121:91-100.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 941]  [Cited by in F6Publishing: 868]  [Article Influence: 37.7]  [Reference Citation Analysis (0)]
32.  Palekar NA, Naus R, Larson SP, Ward J, Harrison SA. Clinical model for distinguishing nonalcoholic steatohepatitis from simple steatosis in patients with nonalcoholic fatty liver disease. Liver Int. 2006;26:151-156.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 157]  [Cited by in F6Publishing: 162]  [Article Influence: 9.0]  [Reference Citation Analysis (0)]
33.  NashTest. The NashTest is diagnostic for non-alcoholic steato hepatitis (NASH) in patients with metabolic steatosis (overweight, diabetes, hyperlipidemia).  Available from: http://www.biopredictive.com/services/tests-OLD/nashtest/nashtest-en/view?set_language=enaccessedon10/06/2014.  [PubMed]  [DOI]  [Cited in This Article: ]
34.  Poynard T, Ratziu V, Charlotte F, Messous D, Munteanu M, Imbert-Bismut F, Massard J, Bonyhay L, Tahiri M, Thabut D. Diagnostic value of biochemical markers (NashTest) for the prediction of non alcoholo steato hepatitis in patients with non-alcoholic fatty liver disease. BMC Gastroenterol. 2006;6:34.  [PubMed]  [DOI]  [Cited in This Article: ]
35.  Poynard T, inventor; Assistance Publique-Hopitaux De Paris (Ap-Hp), assignee Diagnosis method of inflammatory, fibrotic or cancerous disease using biochemical markers. United States patent US: 6631330 2003; Oct 7.  [PubMed]  [DOI]  [Cited in This Article: ]
36.  Imbert-Bismut F, Messous D, Thibault V, Myers RB, Piton A, Thabut D, Devers L, Hainque B, Mercadier A, Poynard T. 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;42:323-333.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 62]  [Cited by in F6Publishing: 80]  [Article Influence: 4.2]  [Reference Citation Analysis (0)]
37.  Ratziu V, Massard J, Charlotte F, Messous D, Imbert-Bismut F, Bonyhay L, Tahiri M, Munteanu M, Thabut D, Cadranel JF. Diagnostic value of biochemical markers (FibroTest-FibroSURE) for the prediction of liver fibrosis in patients with non-alcoholic fatty liver disease. BMC Gastroenterol. 2006;6:6.  [PubMed]  [DOI]  [Cited in This Article: ]
38.  Vallet-Pichard A, Mallet V, Pol S. FIB-4: a simple, inexpensive and accurate marker of fibrosis in HCV-infected patients. Hepatology. 2006;44:769; author reply 769-770.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 66]  [Cited by in F6Publishing: 69]  [Article Influence: 3.8]  [Reference Citation Analysis (0)]
39.  Shah AG, Lydecker A, Murray K, Tetri BN, Contos MJ, Sanyal AJ. Comparison of noninvasive markers of fibrosis in patients with nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol. 2009;7:1104-1112.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 864]  [Cited by in F6Publishing: 947]  [Article Influence: 63.1]  [Reference Citation Analysis (1)]
40.  Adler M, Gulbis B, Moreno C, Evrard S, Verset G, Golstein P, Frotscher B, Nagy N, Thiry P. The predictive value of FIB-4 versus FibroTest, APRI, FibroIndex and Forns index to noninvasively estimate fibrosis in hepatitis C and nonhepatitis C liver diseases. Hepatology. 2008;47:762-773; author reply 763.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 69]  [Cited by in F6Publishing: 74]  [Article Influence: 4.6]  [Reference Citation Analysis (0)]
41.  Hsieh YY, Tung SY, Lee IL, Lee K, Shen CH, Wei KL, Chang TS, Chuang CS, Wu CS, Lin YH. FibroQ: an easy and useful noninvasive test for predicting liver fibrosis in patients with chronic viral hepatitis. Chang Gung Med J. 2009;32:614-622.  [PubMed]  [DOI]  [Cited in This Article: ]
42.  Lok AS, Ghany MG, Goodman ZD, Wright EC, Everson GT, Sterling RK, Everhart JE, Lindsay KL, Bonkovsky HL, Di Bisceglie AM. Predicting cirrhosis in patients with hepatitis C based on standard laboratory tests: results of the HALT-C cohort. Hepatology. 2005;42:282-292.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 239]  [Cited by in F6Publishing: 230]  [Article Influence: 12.1]  [Reference Citation Analysis (0)]
43.  Calès P, Oberti F, Michalak S, Hubert-Fouchard I, Rousselet MC, Konaté A, Gallois Y, Ternisien C, Chevailler A, Lunel F. A novel panel of blood markers to assess the degree of liver fibrosis. Hepatology. 2005;42:1373-1381.  [PubMed]  [DOI]  [Cited in This Article: ]
44.  Calès P, Lainé F, Boursier J, Deugnier Y, Moal V, Oberti F, Hunault G, Rousselet MC, Hubert I, Laafi J. Comparison of blood tests for liver fibrosis specific or not to NAFLD. J Hepatol. 2009;50:165-173.  [PubMed]  [DOI]  [Cited in This Article: ]
45.  Angulo P, Hui JM, Marchesini G, Bugianesi E, George J, Farrell GC, Enders F, Saksena S, Burt AD, Bida JP. The NAFLD fibrosis score: a noninvasive system that identifies liver fibrosis in patients with NAFLD. Hepatology. 2007;45:846-854.  [PubMed]  [DOI]  [Cited in This Article: ]
46.  Harrison SA, Oliver D, Arnold HL, Gogia S, Neuschwander-Tetri BA. Development and validation of a simple NAFLD clinical scoring system for identifying patients without advanced disease. Gut. 2008;57:1441-1447.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 545]  [Cited by in F6Publishing: 553]  [Article Influence: 34.6]  [Reference Citation Analysis (0)]
47.  Ruffillo G, Fassio E, Alvarez E, Landeira G, Longo C, Domínguez N, Gualano G. Comparison of NAFLD fibrosis score and BARD score in predicting fibrosis in nonalcoholic fatty liver disease. J Hepatol. 2011;54:160-163.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 65]  [Cited by in F6Publishing: 63]  [Article Influence: 4.8]  [Reference Citation Analysis (0)]
48.  Sebastiani G, Castera L, Halfon P, Pol S, Mangia A, Di Marco V, Pirisi M, Voiculescu M, Bourliere M, Alberti A. 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;34:1202-1216.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 96]  [Cited by in F6Publishing: 80]  [Article Influence: 6.2]  [Reference Citation Analysis (0)]
49.  Parkes J, Guha IN, Roderick P, Harris S, Cross R, Manos MM, Irving W, Zaitoun A, Wheatley M, Ryder S. Enhanced Liver Fibrosis (ELF) test accurately identifies liver fibrosis in patients with chronic hepatitis C. J Viral Hepat. 2011;18:23-31.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 120]  [Cited by in F6Publishing: 132]  [Article Influence: 10.2]  [Reference Citation Analysis (0)]
50.  Nobili V, Parkes J, Bottazzo G, Marcellini M, Cross R, Newman D, Vizzutti F, Pinzani M, Rosenberg WM. Performance of ELF serum markers in predicting fibrosis stage in pediatric non-alcoholic fatty liver disease. Gastroenterology. 2009;136:160-167.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 190]  [Cited by in F6Publishing: 190]  [Article Influence: 12.7]  [Reference Citation Analysis (0)]
51.  Musso G, Gambino R, Cassader M, Pagano G. Meta-analysis: natural history of non-alcoholic fatty liver disease (NAFLD) and diagnostic accuracy of non-invasive tests for liver disease severity. Ann Med. 2011;43:617-649.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 886]  [Cited by in F6Publishing: 854]  [Article Influence: 65.7]  [Reference Citation Analysis (0)]
52.  Schuppan D, Kim YO. Evolving therapies for liver fibrosis. J Clin Invest. 2013;123:1887-1901.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 435]  [Cited by in F6Publishing: 462]  [Article Influence: 42.0]  [Reference Citation Analysis (0)]
53.  de Alwis NM, Day CP. Non-alcoholic fatty liver disease: the mist gradually clears. J Hepatol. 2008;48 Suppl 1:S104-S112.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 397]  [Cited by in F6Publishing: 399]  [Article Influence: 24.9]  [Reference Citation Analysis (0)]
54.  Chitturi S, Farrell GC, Hashimoto E, Saibara T, Lau GK, Sollano JD. Non-alcoholic fatty liver disease in the Asia-Pacific region: definitions and overview of proposed guidelines. J Gastroenterol Hepatol. 2007;22:778-787.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 221]  [Cited by in F6Publishing: 204]  [Article Influence: 12.0]  [Reference Citation Analysis (0)]