The Use of Current Knowledge and Non-Invasive Testing Modalities for Predicting At-Risk Non-Alcoholic Steatohepatitis and Assessing Fibrosis

Marcelo Kugelmas; Mazen Noureddin; Nadege Gunn; Kimberly Brown; Zobair Younossi; Manal Abdelmalek; Naim Alkhouri

Liver International. 2023;43(5):964-974.

Abstract and Introduction

Abstract

There is ongoing recognition of the burden of non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH), with fibrosis being the most important histological feature that is associated with progression to cirrhosis and the occurrence of major adverse liver outcomes. Liver biopsy is the gold standard applied to detect NASH and determine the stage of fibrosis, but its use is limited. There is a need for non-invasive testing (NIT) techniques to identify patients considered at-risk NASH (NASH with NAFLD activity score > 4 and ≥ F2 fibrosis). For NAFLD-associated fibrosis, several wet (serological) and dry (imaging) NITs are available and demonstrate a high negative predictive value (NPV) for excluding those with advanced hepatic fibrosis. However, identifying at-risk NASH is more challenging; there is little guidance on how to use available NITs for these purposes, and these NITs are not specifically designed to identify at-risk NASH patients. This review discusses the need for NITs in NAFLD and NASH and provides data to support the use of NITs, focusing on newer methods to non-invasively identify at-risk NASH patients. This review concludes with an algorithm that serves as an example of how NITs can be integrated into care pathways of patients with suspected NAFLD and potential NASH. This algorithm can be used for staging, risk stratification and the effective transition of patients who may benefit from specialty care.

Introduction

Non-alcoholic fatty liver disease (NAFLD) is defined as the presence of steatosis in ≥5% of hepatocytes, without significant alcohol consumption or other known causes of steatosis.^[1] NAFLD is subdivided into two primary subtypes, the fairly benign non-alcoholic fatty liver (NAFL) and the more severe, progressive form termed non-alcoholic steatohepatitis (NASH), defined histologically by steatosis in ≥5% of hepatocytes, lobular inflammation and liver cell injury (hepatocyte 'ballooning'), with or without fibrosis.^[1] Until recently, there was a lack of large prospective studies to establish the prevalence of NAFLD and NASH. A recent study used magnetic resonance imaging-based proton density fat fraction (MRI-PDFF) to screen for NAFLD and the gold standard reference biopsy^[1] to screen for NASH. The cohort included 664 asymptomatic, middle-aged adults (mean age: 56 ± 6.4 years, 50% male, mean body mass index [BMI]: 30.48 ± 5.46 kg/m², 52% obese). Investigators determined that the overall prevalence of NAFLD was 38% and that of NASH by biopsy was 14%.^[2] These estimates are higher than those previously reported; in 2016, the global prevalence rates of NAFLD and NASH were estimated at 25% and 1.5–6.45% respectively.^[3] A more recent meta-analysis suggests that the global prevalence of NAFLD is approximately 30%.^[4] The growing prevalence of NAFLD and NASH may partly be owing to the increasing prevalence of associated comorbidities. Metabolic comorbidities associated with NAFLD and NASH include obesity, type-2 diabetes mellitus (T2DM), dyslipidaemia, hypertension and metabolic syndrome (MetS).^[3,5] The prevalence of NAFLD in patients with T2DM or MetS is estimated at over 50%,^[6] but when confirmed using biopsy, it has been found to be over 90% in these populations.^[7]

There are significant knowledge gaps regarding the diagnosis, natural history and treatment of NAFLD, but it is known that NAFLD is considered 'dichotomous'. NAFL poses lower risk to the patient, from a liver-related perspective, while NASH may lead to progressive hepatic fibrosis, liver cirrhosis, liver failure and hepatocellular carcinoma (HCC).^[1,8,9] An analysis of Medicare claims between 1999 and 2012 found that NAFLD was the most common cause of chronic liver disease (CLD) in all ethnic groups combined (52%).^[9] The most important histological feature of NAFLD associated with long-term mortality is fibrosis,^[1] and NAFLD has been found to be one of the most common causes of cirrhosis leading to liver transplants, second only to alcohol-associated liver disease.^[10] Another study found that the number of new waitlisted liver transplant registrants with NAFLD increased by 170% from 2004 to 2013.^[11] NASH has become the most common cause of cirrhosis in adults,^[9] the second leading cause for waitlisting and liver transplants in all patients and the first leading cause for waitlisting and liver transplants among Asian, Hispanic and non-Hispanic white females.^[11]

Identifying the presence of significant fibrosis (≥F2 fibrosis, NAFLD activity score [NAS] > 4) as a result of NASH in high-risk patients is of utmost importance, given its prognostic value and correlation with progression to cirrhosis and major adverse liver outcomes (MALOs). Liver biopsy is the gold standard applied to detect fibrosis, but its use is limited. Several non-invasive tests (NITs) are available for this purpose, which include 'wet' (i.e., NITs that use serum biomarkers to identify fibrosis) and 'dry' (i.e., NITs that use imaging to identify fibrosis). These NITS demonstrate high accuracy when used in combination, but staging and risk stratification of NASH are more challenging; there is no guidance on how to use available NITs for these purposes. This review discusses the need for NITs in NAFLD and NASH and provides data to support the use of NITs, focusing on newer methods of non-invasively identifying at-risk NASH patients (≥F2 fibrosis, NAS ≥4). This review concludes with an algorithm that serves as an example of how NITs can be integrated into care pathways of patients with NAFLD for better staging and risk stratification, as well as inform the referral decision for further evaluation.

1 2 3 4

Next Section

Table 1. 'Wet' NITs that use serum biomarkers and algorithms to identify fibrosis.
Test	Factors used to identify fibrosis
FIB4³⁷	Age, platelets, AST and ALT
NFS³¹	Age, platelets, AST/ALT ratio, albumin, BMI, and whether the patient has impaired fasting glucose/diabetes
APRI³²	AST and upper limits of normal and platelet counts
Hepascore®³⁵	Bilirubin, gamma-glutamyltransferase, hyaluronic acid, alpha (2)-macroglobulin, age and sex
FibroTest® (FibroSure® in the US)³⁶	a2-macroglobulin, apolipoprotein A1, total bilirubin, haptoglobin and g-glutamyl transferase
FibroMeter®³⁴	Age, weight, platelet count, AST, ALT, ferritin and glucose
ELF³³	Tissue inhibitor of metalloproteinases 1, amino-terminal propeptide of type-III procollagen and hyaluronic acid
ELF³³	A specialized laboratory is needed to assess these analytes.

Abbreviations: APRI, aspartate aminotransferase to platelet ratio index; ELF, enhanced liver fibrosis; FIB4, Fibrosis-4 index; NFS, NAFLD fibrosis score.

Table 2. 'Dry' NITs that use imaging to identify fibrosis.
Test	Factors used to identify fibrosis	Advantages	Disadvantages
VCTE	The velocity of the wave that travels through the liver indicates LSM; the higher the LSM, the greater the degree of liver stiffness.	Widely used, broadly validated, well-defined quality criteria; good reproducibility; good performance in cirrhosis (AUROC > 0.9); prognostic value for compensated cirrhosis	Affected by obesity, ascites, operator experience; can only assess superficial liver regions; risk of false positives
SWE	The propagation velocity of the shear wave that travels through the liver is correlated with the elasticity of tissue; a higher velocity indicates increasing LSM.	Larger region of interest than VCTE, chosen by operator; measures liver stiffness in real time;	Affected by operator experience;
		Prognostic value for compensated cirrhosis;	Risk of false positives
		Detects significant fibrosis and cirrhosis	Risk of false positives
MRE	Propagates acoustic shear waves into the liver and computes cross-sectional images using a mathematical algorithm, thereby allowing detection of fibrosis	Performed on standard MR scanner; whole liver study; superior to TE in pts with ascites and obesity; performs well for early stages of fibrosis; predicts clinical outcomes;³⁸ can diagnose cirrhosis	Not useful in iron overload; expensive
ARFI	An ultrasound-based technique that evaluates the wave propagation speed and allows the assessment of tissue stiffness	Allows use of conventional ultrasound; shear wave can be localized to avoid blood vessels and ribs	Cut-off values for advanced fibrosis vary; obese patients demonstrate increased failures

Abbreviations: ARFI, acoustic radiation force impulse; AST, aspartate aminotransferase; AUROC, area under the receiver operating characteristic curve; CAP, controlled attenuation parameter; CT, computed tomography; FAST, FibroScan-AST; LSM, liver stiffness measurement; MRE, magnetic resonance elastography; SWE, shear wave elastography; TE, transient elastography.

Authors and Disclosures

Marcelo Kugelmas¹, Mazen Noureddin², Nadege Gunn³, Kimberly Brown⁴, Zobair Younossi⁵, Manal Abdelmalek⁶ and Naim Alkhouri⁷

¹South Denver Gastroenterology, Englewood, Colorado, USA
²Houston Research Institute, Houston, Texas, USA
³Impact Research Institute, Waco, Texas, USA
⁴Henry Ford Hospital, Detroit, Michigan, USA
⁵Inova Fairfax Medical Campus, Falls Church, Virginia, USA
⁶Mayo Clinic, Rochester, Minnesota, USA
⁷Arizona Liver Health, Chandler, Arizona, USA

Correspondence
Marcelo Kugelmas, South Denver Gastroenterology, Englewood, CO, USA. Email: kugelmas@gutfeelings.com

Conflict of Interest Statement
Marcelo Kugelmas; Advisory Board: Gilead, Abbvie, Echosens, Intercept, Madrigal; Speakers Bureau: Gilead, Abbvie, Echosens, Intercept; Consultant: Gilead, Abbvie, Echosens, Madrigal, Topography Health, Intercept; Grants/Research Support: Madrigal, Genentech, Intercept, Gilead, Ionis, Bio89, Akero, Genfit, Viking, NorthSea, Celgene, Enanta, HighTide, Novartis, Tobira. Mazen Noureddin; Advisory Board: Altimmune, BI, BMS, 89BIO, EchoSens, Gilead, GSK, Merck, Novo Nordisk, OWL, Pfizer, Roche diagnostic and Siemens, Terns and Takeda. Principal Investigator for a Drug Study: Allergan, Akero, BMS, Gilead, Galectin, Genfit, Conatus, Corcept, Enanta, Madrigal, Novartis, Novo Nordisk, Shire, Terns, Viking and Zydus. Stockholder: Anaetos, Rivus Pharma, CIMA, ChronWell and Viking. Editorial Board: Gastroenterology. Associate Editor: Clinical Gastroenterology and Hepatology. Federal funding: NIH/NIDDK. Nadege Gunn; Research funding: Axcella, Gilead, Novo Nordisk, Eli Lilly, 89bio, Sagimet, Merck, Novo Nordisk, Helio Health, Madrigal, Akero, Glympse Bio, Galectin. Manal Abdelmalek; Advisory role: Madrigal, Intercept, Bristol-Myers Squibb, NGM Bio, Merck, Inventiva, 89bio, SonicIncytes, Hanmi, Novo Nordisk. Consultant: Hanmi, Inventiva, 89bio. Research funding: Intercept, Allergan, Madrigal, Genfit, Viking, Hanmi, Bristol-Myers Squibb, NGM Bio, Celgene, Boehinger-Ingelheim, Genentech, Target NASH, Novo Nordisk, Inventiva, Enanta, Enyo, Poxel, Durect, Galmed. Honoraria: Clinical Care Options, Fishawack, Inc., Medscape, Terra Firma, Inc., CLDF. Editorial Board: Hepatology. Kimberly Brown; Advisory role: Madrigal, Intercept, Salix, Gilead, Mallinckrodt. Consultant: Abbvie. Research funding: Salix, Eurofins. Honoraria: CLDF, Gilead, Mallinckrodt, Salix, Intercept, Madrigal. Editorial Board: Liver Transplantation. Board Membership: AASLD Foundation Board. Zobair Younossi, MD; Research funding and/or consultant: Gilead Sciences, Intercept, BMS, NovoNordisk, AstraZeneca, Siemens, Quest, Madrigal, Merck, Abbott. Naim Alkhouri. Advisory role: AbbVie/Allergan, Altimmune, Boehringer Ingelheim, Echosens, Fibronostics, Galecto, Gilead, Intercept, Madrigal, NorthSea, Novo Nordisk, Perspectum, Pfizer and Zydus. Research funding: 89Bio, Akero, AbbVie/Allergan, Altimmune, Better Therapeutics, Boehringer Ingelheim, Bristol-Myers Squibb, Corcept, DSM, Galectin, Genentech, Genfit, Gilead, Hepagene, Healio, Intercept, Inventiva, Ionis, Madrigal, Merck, NGM, Noom, NorthSea, Novo Nordisk, Perspectum, Pfizer, Poxel, Terns, Viking and Zydus. Honoraria: AbbVie/Allergan, Alexion, Echosens, Eisai, Exelixis, Gilead, Intercept, Perspectum, Salix, Siemens, Sonic Incytes and Theratechnologies.