A prognostic model for hepatitis B acute-on-chronic liver failure patients treated using a plasma exchange-centered liver support system

Serum Anti-Fumarate Hydratase Autoantibody as a Biomarker for Predicting Prognosis of Acute-on-Chronic Liver Failure

Background/Aims

To investigate the autoantibody against fumarate hydratase (FH), which is a specific liver failure-associated antigen (LFAA) and determine whether it can be used as a biomarker to evaluate the prognosis of acute-on-chronic liver failure (ACLF).

Methods

An immunoproteomic approach was applied to screen specific LFAAs related to differential prognosis of ACLF (n=60). Enzyme-linked immunosorbent assay (ELISA) technology was employed for the validation of the frequency and titer of autoantibodies against FH in ACLF patients with different prognoses (n=82). Moreover, we clarified the expression of autoantibodies against FH in patients with chronic hepatitis B (n=60) and hepatitis B virus-related liver cirrhosis (n=60). The dynamic changes in the titers of autoantibodies against FH were analyzed by sample collection at multiple time points during the clinical course of eight ACLF patients with different prognoses.

Results

Ultimately, 15 LFAAs were screened and identified by the immunoproteomic approach. Based on ELISA-based verification, anti-FH/Fumarate hydratase protein autoantibody was chosen to verify its expression in ACLF patients. ACLF patients had a much higher anti-FH autoantibody frequency (76.8%) than patients with liver cirrhosis (10%, p=0.000), patients with chronic hepatitis B (6.7%, p=0.022), and normal humans (0%, p=0.000). More importantly, the frequency and titer of anti-FH protein autoantibodies in the serum of ACLF patients with a good prognosis were much higher than that of patients with a poor prognosis (83.9% vs 61.5%, p=0.019; 1.41±0.85 vs 0.94±0.56, p=0.017, respectively). The titer of anti-FH autoantibodies showed dynamic changes in the clinical course of ACLF.

Conclusions

The anti-FH autoantibody in serum may be a potential biomarker for predicting the prognosis of ACLF.

EASL Clinical Practice Guidelines on acute-on-chronic liver failure

Acute-on-chronic liver failure (ACLF), which was described relatively recently (2013), is a severe form of acutely decompensated cirrhosis characterised by the existence of organ system failure(s) and a high risk of short-term mortality. ACLF is caused by an excessive systemic inflammatory response triggered by precipitants that are clinically apparent (e.g., proven microbial infection with sepsis, severe alcohol-related hepatitis) or not. Since the description of ACLF, some important studies have suggested that patients with ACLF may benefit from liver transplantation and because of this, should be urgently stabilised for transplantation by receiving appropriate treatment of identified precipitants, and full general management, including support of organ systems in the intensive care unit (ICU). The objective of the present Clinical Practice Guidelines is to provide recommendations to help clinicians recognise ACLF, make triage decisions (ICU vs. no ICU), identify and manage acute precipitants, identify organ systems that require support or replacement, define potential criteria for futility of intensive care, and identify potential indications for liver transplantation. Based on an in-depth review of the relevant literature, we provide recommendations to navigate clinical dilemmas followed by supporting text. The recommendations are graded according to the Oxford Centre for Evidence-Based Medicine system and categorised as 'weak' or 'strong'. We aim to provide the best available evidence to aid the clinical decision-making process in the management of patients with ACLF.

Artificial liver support systems for hepatitis B virus-associated acute-on-chronic liver failure: A meta-analysis of the clinical literature

To evaluate the short-term and long-term survival efficacy of an artificial liver support system (ALSS) in patients with acute-on-chronic liver failure (ACLF). A systematic search was performed for relevant published data in PubMed, Web of Science and Cochrane Library databases. Studies that evaluated the efficacy of ALSS in patients with ACLF and provided the short-term or long-term survival rate were included. A total of 10 studies involving 3685 patients were included in this analysis. The pooled 28-day survival rate and 90-day survival rate were 68.7% (95% CI: 64.5%-72.9%) and 53.4% (95% CI: 45.5%-61.4%), respectively. The pooled estimates of the OR for the 28-day and 90-day survival rates between the ALSS group and the control group were 1.91 (95% CI: 1.21-3.04) and 1.41 (95% CI: 1.17-1.70), respectively. Subgroup analysis showed that patients treated with lower levels of TBIL and MELD scores had a higher 28-day survival rate (χ²  = 15.75, p < 0.01; χ²  = 13.80, p < 0.01). The present meta-analysis suggests that ALSS treatment could remarkably improve short-term survival rates in HBV-ACLF patients, which implies that treatment with ALSS may help to reduce high mortality. Further prospective randomized trials are needed to validate these findings.

A multi-subgroup predictive model based on clinical parameters and laboratory biomarkers to predict in-hospital outcomes of plasma exchange-centered artificial liver treatment in patients with hepatitis B virus-related acute-on-chronic liver failure

Background

Postoperative risk stratification is challenging in patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) who undergo artificial liver treatment. This study characterizes patients' clinical parameters and laboratory biomarkers with different in-hospital outcomes. The purpose was to establish a multi-subgroup combined predictive model and analyze its predictive capability.

Methods

We enrolled HBV-ACLF patients who received plasma exchange (PE)-centered artificial liver support system (ALSS) therapy from May 6, 2017, to April 6, 2022. There were 110 patients who died (the death group) and 110 propensity score-matched patients who achieved satisfactory outcomes (the survivor group). We compared baseline, before ALSS, after ALSS, and change ratios of laboratory biomarkers. Outcome prediction models were established by generalized estimating equations (GEE). The discrimination was assessed using receiver operating characteristic analyses. Calibration plots compared the mean predicted probability and the mean observed outcome.

Results

We built a multi-subgroup predictive model (at admission; before ALSS; after ALSS; change ratio) to predict in-hospital outcomes of HBV-ACLF patients who received PE-centered ALSS. There were 110 patients with 363 ALSS sessions who survived and 110 who did not, and 363 ALSS sessions were analyzed. The univariate GEE models revealed that several parameters were independent risk factors. Clinical parameters and laboratory biomarkers were entered into the multivariate GEE model. The discriminative power of the multivariate GEE models was excellent, and calibration showed better agreement between the predicted and observed probabilities than the univariate models.

Conclusions

The multi-subgroup combined predictive model generated accurate prognostic information for patients undergoing HBV-ACLF patients who received PE-centered ALSS.

Critical Updates on Chronic Hepatitis B Virus Infection in 2021

Chronic hepatitis B virus (HBV) infection is a global healthcare burden in the form of chronic liver disease, cirrhosis, liver failure and liver cancer. There is no definite cure for the virus and even though extensive vaccination programs have reduced the burden of liver disease in the future population, treatment options to eradicate the virus from the host are still lacking. In this review, we discuss in detail current updates on the structure and applied biology of the virus in the host, examine updates to current treatment and explore novel and state-of-the-art therapeutics in the pipeline for management of chronic HBV. Furthermore, we also specifically review clinical updates on HBV-related acute on chronic liver failure (ACLF). Current treatments for chronic HBV infection have seen important updates in the form of considerations for treating patients in the immune tolerant phase and some clarity on end points for treatment and decisions on finite therapy with nucleos(t)ide inhibitors. Ongoing cutting-edge research on HBV biology has helped us identify novel target areas in the life cycle of the virus for application of new therapeutics. Due to improvements in the area of genomics, the hope for therapeutic vaccines, vector-based treatments and focused management aimed at targeting host integration of the virus and thereby a total cure could become a reality in the near future. Newer clinical prognostic tools have improved our understanding of timing of specific treatment options for the catastrophic syndrome of ACLF secondary to reactivation of HBV. In this review, we discuss in detail pertinent updates regarding virus biology and novel therapeutic targets with special focus on the appraisal of prognostic scores and treatment options in HBV-related ACLF.

A novel prognostic model to predict outcome of artificial liver support system treatment

The prognosis of Artificial liver support system (ALSS) for hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is hard to be expected, which results in multiple operations of ALSS and excessive consumption of plasma, increase in clinical cost. A total of 375 HBV-ACLF patients receiving ALSS treatment were randomly divided a train set and an independent test set. Logistic regression analysis was conducted and a decision tree was built based on 3-month survival as outcome. The ratio of total bilirubin before and after the first time of ALSS treatment was the most significant prognostic factor, we named it RPTB. Further, a decision tree based on the multivariate logistic regression model using CTP score and the RPTB was built, dividing patients into 3 main groups such as favorable prognosis group, moderate prognosis group and poor prognosis group. A clearly-presented and easily-understood decision tree was built with a good predictive value of prognosis in HBV-related ACLF patients after first-time ALSS treatment. It will help maximal the therapeutic value of ALSS treatment and may play an important role in organ allocation for liver transplantation in the future.

A prognostic model for hepatitis B acute-on-chronic liver failure patients treated using a plasma exchange-centered liver support system

Aim

To determine the prognostic risk factors of patients with hepatitis B virus related acute‐on‐chronic liver failure (HBV‐ACLF) treated with plasma exchange (PE)‐based artificial liver support system (ALSS), and create a prognostic predictive model.

Methods

A total of 304 HBV‐ACLF patients who received PE‐based ALSS were retrospectively analyzed. Potential prognostic factors on admission associated with survival were investigated. Of note, 101 additional patients were analyzed to validate the performance of the prognostic models.

Results

According to 28‐day survival, a total of 207 patients who survived and 97 non‐survivors were identified in the derivation group. Overall, 268 (88.2%) ACLF cases were caused by reactivation of HBV. Cox proportional hazards regression model revealed that age, total bilirubin, ln (alpha‐fetoprotein [AFP]), encephalopathy (HE) score, sodium level, and international normalized ratio (INR) were independent risk factors of short‐term prognosis. We built a model named ALSS‐prognosis model (APM) to predict the 28‐day survival of HBV‐ACLF patients with ALSS; the model APM showed potentially better predictive performance for both the derivation and validation groups than MELD, MELD‐Na, and CLIF‐C ACLF score.

Conclusions

Low AFP was found to be an independent risk factor for high mortality in HBV‐ACLF patients treated with PE‐based ALSS. We generated a new model containing AFP, namely APM, which showed potentially better prediction performance than MELD, MELD‐Na, and CLIF‐C ACLF score for short‐term outcomes, and could aid physicians in making optimal therapeutic decisions.