The Enhanced Liver Fibrosis test maintains its diagnostic and prognostic performance in alcohol-related liver disease: a cohort study

Noninvasive Assessment of Portal Hypertension

The progressive use of noninvasive tests (NITs) has changed the way hepatologists diagnose and manage patients with chronic liver disease, mainly because of their easiness to use and the ability to be repeated during follow-up. Liver stiffness measurement is the NIT with more scientific evidence. NITs have demonstrated to be useful to detect not only liver fibrosis but also the presence of clinically significant portal hypertension. Moreover, current evidence supports they can also be useful to evaluate the prognosis of patients with chronic liver disease.

Enhanced liver fibrosis (ELF) score predicts hepatic decompensation and mortality

Background & Aims

In community pathways for detection of liver disease the most common reason for referral is fibrosis assessment. We investigated the impact of adding the Enhanced Liver Fibrosis (ELF) score as a second-line test (subsequent to an indeterminate or high Fibrosis-4 index [FIB-4] and/or non-alcoholic fatty liver disease fibrosis score) to guide referral and prognostication in our multi-aetiology pathway.

Methods

Patients with ELF results from the intelligent Liver Function Testing (iLFT) pathway were recruited. Case note review was undertaken to compare ELF with endpoints of cirrhosis, hepatic decompensation, and mortality (liver-related and all-cause death).

Results

In total, 1,327 individuals were included with a median follow-up of 859 days and median ELF score of 10.2. Overall sensitivity for cirrhosis at the 9.8 threshold was 94% (100% for metabolic-associated steatotic liver disease, 89% for alcohol-related liver disease). Determination of the ELF score as a second-line test reduced the referral rate by 34%. ELF scores predicted hepatic outcomes; each unit change was associated with increased decompensation (adjusted Hazard Ratio [aHR] 2.215, 95% CI: 1.934-2.537) and liver-related mortality (aHR 2.024, 95% CI: 1.674-2.446). ELF outperformed FIB-4 for risk of liver-related mortality, particularly in the short-term (area under the curve [AUC] 94.3% vs. 82.8% at six months). Where FIB-4 was indeterminate, ELF had higher AUC for all outcomes within at least 2 years. ELF ≥13 was associated with particularly high rates of decompensation (26% within 90 days) and all-cause mortality (38% at 1 year).

Conclusions

The addition of ELF reduced the number of individuals referred for fibrosis assessment following iLFT pathway testing and provided useful prognostic information. Individuals with ELF scores ≥13 were considered at high-risk of negative outcomes warranting urgent clinical assessment.

Impact and implications

Primary care pathways for suspected liver disease are increasingly common and often lead to increased specialist hepatology referrals for fibrosis assessment. This study, using clinical follow-up for liver-related outcomes, provides further evidence supporting ELF testing to safely reduce referrals in a two-step approach when combined with other simple fibrosis markers. Additionally, ELF scores predict liver-related morbidity and mortality, with ELF scores ≥13 indicating particularly high-risk patients. This study may help inform the implementation of diagnostic pathways for early detection of liver disease and highlights the need for urgent review of individuals with very high ELF scores.

Derivation and validation of Transform equations to convert historical Enhanced liver fibrosis (ELF) scores to modern equivalents

BACKGROUND AND AIMS

The Siemens Healthineers ELF™ Test was designed in 2004 with 2 algorithms to allow choice in histological alignment. Consequently, historical and modern algorithms are not fully harmonized, complicating comparisons involving early datasets. We derived transform equations to equate all ELF score versions, allowing historical data to be used in systematic reviews and meta-analyses.

METHODS

Historical ELF equations were graphed pairwise versus their modern equivalent to assess correlation and derive four transforms. Transforms were validated using multiple datasets and evaluated for median absolute bias, number of samples reflecting clinically significant bias, number of discordant samples, bias at established cutoffs, and regression slope and y-intercept.

RESULTS

Three transforms were validated equating Scheuer-aligned and/or age-included historical ELF equations (Immuno 1) to later equations aligned to Ishak and omitting age. A fourth transform corrected ADVIA Centaur® / Atellica® IM ELF scores miscalculated using the Scheuer Immuno 1 equation. Transformed data were well within allowable ELF bias limits.

CONCLUSIONS

All transforms enabled accurate comparison of ELF scores generated by all historical algorithms to the current ADVIA Centaur / Atellica IM Analyzer ELF score. The transforms presented in this report should be used in systematic reviews and meta-analyses to facilitate comparisons to historical data.

Advances in the understanding and management of alcohol-related liver disease

Alcohol-related liver disease (ALD) is a major cause of liver-related morbidity and mortality. Epidemiological trends indicate recent and predicted increases in the burden of disease. Disease progression is driven by continued alcohol exposure on a background of genetic predisposition together with environmental cofactors. Most individuals present with advanced disease despite a long history of excessive alcohol consumption and multiple missed opportunities to intervene. Increasing evidence supports the use of non-invasive tests to screen for and identify disease at earlier stages. There is a definite role for public health measures to reduce the overall burden of disease. At an individual level, however, the ability to influence subsequent disease course by modifying alcohol consumption or the underlying pathogenic mechanisms remains limited due to a comparative lack of effective, disease-modifying medical interventions. Abstinence from alcohol is the key determinant of outcome in established ALD and the cornerstone of clinical management. In those with decompensated ALD, liver transplant has a clear role. There is consensus that abstinence from alcohol for an arbitrary period should not be the sole determinant in a decision to transplant. An increasing understanding of the mechanisms by which alcohol causes liver disease in susceptible individuals offers the prospect of new therapeutic targets for disease-modifying drugs. Successful translation will require significant public and private investment in a disease area which has traditionally been underfunded when compared to its overall prevalence.

Prognostication in NAFLD: physiological bases, clinical indicators, and newer biomarkers

Non-alcoholic fatty liver disease (NAFLD) is becoming an epidemic in Western countries. Notably, while the majority of NAFLD patients will not evolve until advanced liver disease, a minority of them will progress towards liver-related events. Therefore, risk stratification and prognostication are emerging as fundamental in order to optimize human and economic resources for the care of these patients.Liver fibrosis has been clearly recognized as the main predictor of poor hepatic and extrahepatic outcomes. However, a prediction based only on the stage of fibrosis is near-sighted and static, as it does not capture the propensity of disease to further progress, the speed of progression and their changes over time. These determinants, which result from the interaction between genetic predisposition and acquired risk factors (obesity, diabetes, etc.), express themselves in disease activity, and can be synthesized by biomarkers of hepatic inflammation and fibrogenesis.In this review, we present the currently available clinical tools for risk stratification and prognostication in NAFLD specifically with respect to the risk of progression towards hard hepatic outcomes, i.e., liver-related events and death. We also discuss about the genetic and acquired drivers of disease progression, together with the physiopathological bases of their come into action. Finally, we introduce the most promising biomarkers in the direction of repeatedly assessing disease activity over time, mainly in response to future therapeutic interventions.

Combined use of the ELF test and CLivD score improves prediction of liver-related outcomes in the general population

BACKGROUND AND AIMS

Effective and feasible population screening strategies are needed for the early detection of individuals at high risk of future severe liver-related outcomes. We evaluated the predictive performance of the combination of liver fibrosis assessment, phenotype profile, and genetic risk.

METHODS

Data from 5795 adults attending the Finnish Health 2000 Survey were linked with healthcare registers for liver-related outcomes (hospitalization, hepatocellular cancer, and death). Fibrosis was assessed using the enhanced liver fibrosis (ELF) test, phenotype profile by the chronic liver disease (CLivD) risk score, and genetic risk by a validated Polygenic Risk Score (PRS-5). Predictive performance was assessed by competing-risk analyses.

RESULTS

During a median 13-year follow-up, 64 liver-related outcome events were recorded. ELF, CLivD score, and PRS-5 were independently associated with liver-related outcomes. The absolute 10-year risk of liver-related outcomes at an ELF value of 11.3 ranged from 0.3% to 33% depending on the CLivD score. The CLivD score added 51% of new predictive information to the ELF test and improved areas under the curve (AUCs) from 0.91, 0.81, and 0.71 for ELF alone to 0.95, 0.85, and 0.80, respectively, for ELF combined with the CLivD score at 1, 5, and 10 years. The greatest improvement was for 10-year predictions (delta-AUC 0.097, p < .0001). Adding PRS-5 did not significantly increase predictive performance. Findings were consistent in individuals with obesity, diabetes, or alcohol risk use, and regardless of whether gamma-glutamyltransferase was used in the CLivD score.

CONCLUSION

A combination of ELF and CLivD score predicts liver-related outcomes significantly better than the ELF test alone.

Predictive risk markers in alcoholism

The medical disorders of alcoholism rank among the leading public health problems worldwide and the need for predictive and prognostic risk markers for assessing alcohol use disorders (AUD) has been widely acknowledged. Early-phase detection of problem drinking and associated tissue toxicity are important prerequisites for timely initiations of appropriate treatments and improving patient's committing to the objective of reducing drinking. Recent advances in clinical chemistry have provided novel approaches for a specific detection of heavy drinking through assays of unique ethanol metabolites, phosphatidylethanol (PEth) or ethyl glucuronide (EtG). Carbohydrate-deficient transferrin (CDT) measurements can be used to indicate severe alcohol problems. Hazardous drinking frequently manifests as heavy episodic drinking or in combinations with other unfavorable lifestyle factors, such as smoking, physical inactivity, poor diet or adiposity, which aggravate the metabolic consequences of alcohol intake in a supra-additive manner. Such interactions are also reflected in multiple disease outcomes and distinct abnormalities in biomarkers of liver function, inflammation and oxidative stress. Use of predictive biomarkers either alone or as part of specifically designed biological algorithms helps to predict both hepatic and extrahepatic morbidity in individuals with such risk factors. Novel approaches for assessing progression of fibrosis, a major determinant of prognosis in AUD, have also been made available. Predictive algorithms based on the combined use of biomarkers and clinical observations may prove to have a major impact on clinical decisions to detect AUD in early pre-symptomatic stages, stratify patients according to their substantially different disease risks and predict individual responses to treatment.

Meta-analysis: Enhanced liver fibrosis test to identify hepatic fibrosis in chronic liver diseases

BACKGROUND & AIMS

Patients with liver disease can be stratified for risk of liver-related ill health by degree of hepatic fibrosis. The Enhanced liver fibrosis (ELF) test was developed to quantify hepatic fibrosis non-invasively and is widely used. The objective of this review was to identify and synthesise the evidence on the diagnostic accuracy of the ELF test for staging of hepatic fibrosis.

APPROACH & RESULTS

Searches of PubMed and EMBASE were conducted between October 2020 and November 2021 to identify studies reporting the diagnostic accuracy of the ELF test compared to histology in liver disease patients. QUADAS-2 was used to assess risk of bias in each study. Meta-analysis using the multiple thresholds model described by Steinhauser S, Schumacher M, Rücker G. Modelling multiple thresholds in meta-analysis of diagnostic test accuracy studies. BMC Med. Res. Methodol. 2016;16. 10.1186/s12874-016-0196-1 allowed synthesis of 2 × 2 data at different cut-offs. Sixty-three studies were included in this review. These studies included 19,285 patients with or at risk of liver disease from viral hepatitis, Non-Alcoholic Fatty Liver Disease, Alcohol-related Liver Disease and other mixed chronic liver diseases. The prevalence of significant fibrosis, advanced fibrosis and cirrhosis was 47.5%, 39.2% and 4.4%, respectively. Cut-offs with maximal Youden index were generated with AUROC = 0.811 (95% CI: 0.736-0.870), 0.812 (95% CI: 0.758-0.856) and 0.810 (95% CI: 0.694-0.888) to detect significant fibrosis, advanced fibrosis or cirrhosis, respectively. Diagnostic accuracy of the ELF test varied between different liver diseases and cut-offs to detect each stage with 95% sensitivity or specificity were also generated.

CONCLUSIONS

Meta-analysis revealed considerable variability in the ability of ELF to stage fibrosis across disease aetiologies. Research has mostly focused on viral hepatitis and NAFLD. There is currently a lack of data on the value of the ELF test in Alcohol-related liver disease and patients in primary care settings.