Endohepatology: The endoscopic armamentarium in the hand of the hepatologist

ABSTRACT

Recent advances in the field of hepatology include new and effective treatments for viral hepatitis. Further effort is now being directed to other disease entities, such as non-alcoholic fatty liver disease, with an increased need for assessment of liver function and histology. In fact, with the evolving nomenclature of fat-associated liver disease and the emergence of the term "metabolic-associated fatty liver disease" (MAFLD), new diagnostic challenges have emerged as patients with histologic absence of steatosis can still be classified under the umbrella of MAFLD. Currently, there is a growing number of endoscopic procedures that are pertinent to patients with liver disease. Indeed, interventional radiologists mostly perform interventional procedures such as percutaneous and intravascular procedures, whereas endoscopists focus on screening for and treatment of esophageal and gastric varices. EUS has proven to be of value in many areas within the realm of hepatology, including liver biopsy, assessment of liver fibrosis, measurement of portal pressure, managing variceal bleeding, and EUS-guided paracentesis. In this review article, we will address the endoscopic applications that are used to manage patients with chronic liver disease.

Multicenter validation of FIB-6 as a novel machine learning non-invasive score to rule out liver cirrhosis in biopsy-proven MAFLD

BACKGROUND AND AIMS

We previously developed and validated a non-invasive diagnostic index based on routine laboratory parameters for predicting the stage of hepatic fibrosis in patients with chronic hepatitis C (CHC) called FIB-6 through machine learning with random forests algorithm using retrospective data of 7238 biopsy-proven CHC patients. Our aim is to validate this novel score in patients with metabolic dysfunction-associated fatty liver disease (MAFLD).

METHOD

Performance of the new score was externally validated in cohorts from one site in Egypt (n = 674) and in 5 different countries (n = 1798) in Iran, KSA, Greece, Turkey and Oman. Experienced pathologists using METAVIR scoring system scored the biopsy samples. Results were compared with FIB-4, APRI, and AAR.

RESULTS

A total of 2472 and their liver biopsy results were included, using the optimal cutoffs of FIB-6 indicated a reliable performance in diagnosing cirrhosis, severe fibrosis, and significant fibrosis with sensitivity = 70.5%, specificity = 62.9%. PPV = 15.0% and NPV = 95.8% for diagnosis of cirrhosis. For diagnosis of severe fibrosis (F3 and F4), the results were 86.5%, 24.0%, 15.1% and 91.9% respectively, while for diagnosis of significant fibrosis (F2, F3 and F4), the results were 87.0%, 16.4%, 24.8% and 80.0%). Comparing the results of FIB-6 rule-out cutoffs with those of FIB-4, APRI, and AAR, FIB-6 had the highest sensitivity and NPV (97.0% and 94.7%), as compared to FIB-4 (71.6% and 94.7%), APRI (36.4% and 90.7%), and AAR (61.2% and 90.9%).

CONCLUSION

FIB-6 score is an accurate, simple, NIT for ruling out advanced fibrosis and liver cirrhosis in patients with MAFLD.

Global prevalence, cascade of care, and prophylaxis coverage of hepatitis B in 2022: a modelling study

BACKGROUND

The 2016 World Health Assembly endorsed the elimination of hepatitis B virus (HBV) infection as a public health threat by 2030; existing therapies and prophylaxis measures make such elimination feasible, even in the absence of a virological cure. We aimed to estimate the national, regional, and global prevalence of HBV in the general population and among children aged 5 years and younger, as well as the rates of diagnosis, treatment, prophylaxis, and the future burden globally.

METHODS

In this modelling study, we used a Delphi process with data from literature reviews and interviews with country experts to quantify the prevalence, diagnosis, treatment, and prevention measures for HBV infection. The PRoGReSs Model, a dynamic Markov model, was used to estimate the country, regional, and global prevalence of HBV infection in 2022, and the effects of treatment and prevention on disease burden. The future incidence of morbidity and mortality in the absence of additional interventions was also estimated at the global level.

FINDINGS

We developed models for 170 countries which resulted in an estimated global prevalence of HBV infection in 2022 of 3·2% (95% uncertainty interval 2·7-4·0), corresponding to 257·5 million (216·6-316·4) individuals positive for HBsAg. Of these individuals, 36·0 million were diagnosed, and only 6·8 million of the estimated 83·3 million eligible for treatment were on treatment. The prevalence among children aged 5 years or younger was estimated to be 0·7% (0·6-1·0), corresponding to 5·6 million (4·5-7·8) children with HBV infection. Based on the most recent data, 85% of infants received three-dose HBV vaccination before 1 year of age, 46% had received a timely birth dose of vaccine, and 14% received hepatitis B immunoglobulin along with the full vaccination regimen. 3% of mothers with a high HBV viral load received antiviral treatment to reduce mother-to-child transmission.

INTERPRETATION

As 2030 approaches, the elimination targets remain out of reach for many countries under the current frameworks. Although prevention measures have had the most success, there is a need to increase these efforts and to increase diagnosis and treatment to work towards the elimination goals.

FUNDING

John C Martin Foundation, Gilead Sciences, and EndHep2030.

Development and multicenter validation of FIB-6: A novel, machine learning, simple bedside score to rule out liver cirrhosis and compensated advanced chronic liver disease in patients with chronic hepatitis C

BACKGROUND

Non-invasive tests (NITs), such as Fibrosis-4 index (FIB-4) and the aspartate aminotransferase-to-platelet ratio index (APRI), developed using classical statistical methods, are increasingly used for determining liver fibrosis stages and recommended in treatment guidelines replacing the liver biopsy. Application of conventional cutoffs of FIB-4 and APRI resulted in high rates of misclassification of fibrosis stages.

AIM

There is an unmet need for more accurate NITs that can overcome the limitations of FIB-4 and APRI.

PATIENTS AND METHODS

Machine learning with the random forest algorithm was used to develop a non-invasive index using retrospective data of 7238 patients with biopsy-proven chronic hepatitis C from two centers in Egypt; derivation dataset (n = 1821) and validation set in the second center (n = 5417). Receiver operator curve analysis was used to define cutoffs for different stages of fibrosis. Performance of the new score was externally validated in cohorts from two other sites in Egypt (n = 560) and seven different countries (n = 1317). Fibrosis stages were determined using the METAVIR score. Results were also compared with three established tools (FIB-4, APRI, and the aspartate aminotransferase-to-alanine aminotransferase ratio [AAR]).

RESULTS

Age in addition to readily available laboratory parameters such as aspartate, and alanine aminotransferases, alkaline phosphatase, albumin (g/dl), and platelet count (/cm³ ) correlated with the biopsy-derived stage of liver fibrosis in the derivation cohort and were used to construct the model for predicting the fibrosis stage by applying the random forest algorithm, resulting in an FIB-6 index, which can be calculated easily at http://fib6.elriah.info. Application of the cutoff values derived from the derivation group on the validation groups yielded very good performance in ruling out cirrhosis (negative predictive value [NPV] = 97.7%), compensated advance liver disease (NPV = 90.2%), and significant fibrosis (NPV = 65.7%). In the external validation groups from different countries, FIB-6 demonstrated higher sensitivity and NPV than FIB-4, APRI, and AAR.

CONCLUSION

FIB-6 score is a non-invasive, simple, and accurate test for ruling out liver cirrhosis and compensated advance liver disease in patients with chronic hepatitis C and performs better than APRI, FIB-4, and AAR.

Nonalcoholic fatty liver disease: Noninvasive methods of diagnosing hepatic steatosis

Hepatic steatosis is the buildup of lipids within hepatocytes. It is the simplest stage in nonalcoholic fatty liver disease (NAFLD). It occurs in approximately 30% of the general population and as much as 90% of the obese population in the United States. It may progress to nonalcoholic steatohepatitis, which is a state of hepatocellular inflammation and damage in response to the accumulated fat. Liver biopsy remains the gold standard tool to diagnose and stage NAFLD. However, it comes with the risk of complications ranging from simple pain to life-threatening bleeding. It is also associated with sampling error. For these reasons, a variety of noninvasive radiological markers, including ultrasound, computed tomography, magnetic resonance spectroscopy, and the controlled attenuation parameter using transient elastography and Xenon-133 scan have been proposed to increase our ability to diagnose NAFLD, hence avoiding liver biopsy. The aim of this review is to discuss the utility and accuracy of using available noninvasive diagnostic modalities for fatty liver in NAFLD.