Diagnostic and Therapeutic Approaches to Hepatocellular Carcinoma: Understanding the Barcelona Clínic Liver Cancer Protocol

Use of machine learning models for the prognostication of liver transplantation: A systematic review

BACKGROUND

Liver transplantation (LT) is a life-saving intervention for patients with end-stage liver disease. However, the equitable allocation of scarce donor organs remains a formidable challenge. Prognostic tools are pivotal in identifying the most suitable transplant candidates. Traditionally, scoring systems like the model for end-stage liver disease have been instrumental in this process. Nevertheless, the landscape of prognostication is undergoing a transformation with the integration of machine learning (ML) and artificial intelligence models.

AIM

To assess the utility of ML models in prognostication for LT, comparing their per formance and reliability to established traditional scoring systems.

METHODS

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, we conducted a thorough and standardized literature search using the PubMed/MEDLINE database. Our search imposed no restrictions on publication year, age, or gender. Exclusion criteria encompassed non-English stu dies, review articles, case reports, conference papers, studies with missing data, or those exhibiting evident methodological flaws.

RESULTS

Our search yielded a total of 64 articles, with 23 meeting the inclusion criteria. Among the selected studies, 60.8% originated from the United States and China combined. Only one pediatric study met the criteria. Notably, 91% of the studies were published within the past five years. ML models consistently demonstrated satisfactory to excellent area under the receiver operating characteristic curve values (ranging from 0.6 to 1) across all studies, surpassing the performance of traditional scoring systems. Random forest exhibited superior predictive capa bilities for 90-d mortality following LT, sepsis, and acute kidney injury (AKI). In contrast, gradient boosting excelled in predicting the risk of graft-versus-host disease, pneumonia, and AKI.

CONCLUSION

This study underscores the potential of ML models in guiding decisions related to allograft allocation and LT, marking a significant evolution in the field of prognostication.

Acute-on-chronic liver failure is independently associated with higher mortality for cirrhotic patients with acute esophageal variceal hemorrhage: Retrospective cohort study

BACKGROUND

Acute esophageal variceal hemorrhage (AEVH) is a common complication of cirrhosis and might precipitate multi-organ failure, causing acute-on-chronic liver failure (ACLF).

AIM

To analyze if the presence and grading of ACLF as defined by European Society for the Study of the Liver-Chronic Liver Failure (EASL-CLIF) is able to predict mortality in cirrhotic patients presenting AEVH.

METHODS

Retrospective cohort study executed in Hospital Geral de Caxias do Sul. Data from medical records from 2010 to 2016 were obtained by searching the hospital electronic database for patients who received terlipressin. Medical records were reviewed in order to determine the diagnosis of cirrhosis and AEVH, including 97 patients. Kaplan-Meier survival analysis was used for univariate analysis and a stepwise approach to the Cox regression for multivariate analysis.

RESULTS

All- cause mortality for AEVH patients was 36%, 40.2% and 49.4% for 30-, 90- and 365-day, respectively. The prevalence of ACLF was 41.3%. Of these, 35% grade 1, 50% grade 2 and 15% grade 3. In multivariate analysis, the non-use of non-selective beta-blockers, presence and higher grading of ACLF and higher Model for End-Stage Liver Disease scores were independently associated with higher mortality for 30-day with the addition of higher Child-Pugh scores for 90-day period.

CONCLUSION

Presence and grading of ACLF according to the EASL-CLIF criteria was independently associated with higher 30- and 90-day mortality in cirrhotic patients admitted due to AEVH.

Clinical Management of Liver Cancer in India and Other Developing Nations: A Focus on Radiation Based Strategies

Hepatocellular carcinoma (HCC) is a global killer with preponderance in Asian and African countries. It poses a challenge for successful management in less affluent or developing nations like India, with large populations and limited infrastructures. This review aims to assess the available options and future directions for management of HCC applicable to such countries. While summarizing current and emerging clinical strategies for detection, staging and therapy of the disease, it highlights radioisotope- and radioactivity-based strategies as part of an overall program. Using the widely accepted Barcelona Clinic Liver Cancer (BCLC) staging system as a base, it evaluates the applicability of different therapeutic approaches and their synergistic combination(s) in the context of a patient-specific dynamic results-based strategy. It distills the conclusions of multiple HCC management-focused consensus recommendations to provide a picture of clinical strategies, especially radiation-related approaches. Additionally, it discusses the logistical and economic feasibility of these approaches in the context of the limitations of the burdened public health infrastructure in India (and like nations) and highlights possible strategies both at the clinical level and in terms of an administrative health policy on HCC to provide the maximum possible benefit to the widest swathe of the affected population.

ACUTE-ON-CHRONIC LIVER FAILURE IS INDEPENDENTLY ASSOCIATED WITH LOWER SURVIVAL IN PATIENTS WITH SPONTANEOUS BACTERIAL PERITONITIS

BACKGROUND

Spontaneous bacterial peritonitis (SBP) is a decompensation of cirrhosis with an in-hospital mortality ranging from 20% to 40%.

OBJECTIVE

The purpose of this study is to analyze if EASL-CLIF definition of acute-on-chronic liver failure (ACLF) is able to predict mortality in cirrhotic patients with SBP.

METHODS

Historical cohort study conducted in a public tertiary care teaching hospital. Data from medical records from January 2009 to July 2016 were obtained by searching the hospital electronic database for samples of ascites collected in the period. Electronic and physical medical records were analyzed and patients were included if they were over 18-years old, with cirrhosis and an ascites fluid compatible with SBP: 69 patients were included. Liver-specific scores were calculated and Kaplan-Meier survival analysis was used for univariate analysis and a stepwise approach to the Cox regression for multivariate analysis.

RESULTS

All cause mortality was 44%, 56.5% and 74% for 28-, 90- and 365-day, respectively. The prevalence of ACLF was 58%. Of these, 65% grade 1, 17.5% grade 2 and 17.5% grade 3. In multivariate analysis, the use of proton-pump inhi-bitors, alanine transaminase lower than 40 U/L, hemoglobin higher than 9 g/dL, absence of ACLF and lower CLIF-SOFA and MELD scores were independently associated with higher survival for both 28- and 90-day interval.

CONCLUSION

The presence of ACLF and higher CLIF-SOFA scores were independently associated with higher 28- and 90-day mortality in cirrhotic patients admitted due to SBP.

Deep learning applied to the imaging diagnosis of hepatocellular carcinoma

Each year, hepatocellular carcinoma is diagnosed in more than half a million people worldwide. It is the fifth most common cancer in men and the seventh most common cancer in women. Its diagnosis is currently made using imaging techniques, such as computed tomography and magnetic resonance imaging. For most cirrhotic patients, these methods are enough for diagnosis, foregoing the necessity of a liver biopsy. In order to improve outcomes and bypass obstacles, many companies and clinical centers have been trying to develop deep learning systems that could be able to diagnose and classify liver nodules in the cirrhotic liver, in which the neural networks are one of the most efficient approaches to accurately diagnose liver nodules. Despite the advances in deep learning systems for the diagnosis of imaging techniques, there are many issues that need better development in order to make such technologies more useful in daily practice.

Evidence-based protocol for diagnosis and treatment of hepatorenal syndrome is independently associated with lower mortality

BACKGROUND

Hepatorenal syndrome (HRS) is the deadliest complication of cirrhosis. The purpose of this study is to analyze if the use of a protocol for HRS is associated with higher survival in these patients.

METHODS

An evidence-based protocol for the diagnosis and treatment of HRS was instituted in 2013. Data from medical records from 2010 to 2016 were obtained by searching the hospital database for patients who received terlipressin, in the three years before and after the institution of the protocol. Data were reviewed to confirm the diagnosis of HRS and multiple variables were collected. Liver-specific scores were calculated and a stepwise Cox regression approach was used for univariate and multivariate analysis.

RESULTS

The study included 46 patients, 20 from the pre-protocol period and 26 from the post-protocol period. Respectively, mortality at 30 days, 90 days and 365 days was 75%, 75% and 90% for the pre-protocol period, and 61%, 69% and 80% for the post-protocol period. In the multivariate analysis, an aspartate aminotransferase (AST) of <40U/L, the pre-protocol period and higher Child-Turcotte-Pugh scores were associated with higher 30-day and 90-day mortality. The total mean dose of terlipressin and human albumin used per patient was reduced from 27mg to 22mg and from 236g to 144g, respectively, after the institution of the protocol. This was not associated with higher mortality.

CONCLUSION

The use of an evidence-based protocol for the treatment of HRS translated into a higher survival. The authors suggest that the use of evidence-based protocols for the diagnosis and treatment of HRS could reduce cost and mortality in tertiary hospitals.

Role of VEGF in metformin induced apoptosis of HepG2 cells

AIM

To investigate the molecular mechanism of metformin induced apoptosis of HepG2 cells.

METHODS

HepG2 cells were treated with different concentrations (0-20 mmol/L) of metformin (MET) for 24 h or 10 mmol/L MET for different times (0-48 h), and the effect of MET on cell proliferation was measured by MTT assay. Annexin V-FITC/PI flow cytometry was used to determine the apoptosis rate. RT-PCR was used to analyze the expression of vascular endothelial growth factor (VEGF) in HepG2 cells treated with MET.

RESULTS

MET had an obvious inhibitory effect on HepG2 cell proliferation. After treatment with 0, 5, 10, 15, and 20 mmol/L MET for 24 h, the relative cell viability rates of HepG2 cells were 100%, 80.56% ± 0.72%, 71.06% ± 0.70%, 64.73% ± 0.35%, and 54.73% ± 0.40%, respectively, showing a dose-dependent manner. After treatment with 10 mmol/L MET for 0, 12, 24, 36, and 48 h, the relative cell viability rates of HepG2 cells were 100%, 83.40% ± 0.70%, 69.86% ± 0.45%, 60.40% ± 0.88%, and 50.70% ± 0.45%, respectively, showing a time-dependent manner. Annexin V-FITC/PI flow cytometry revealed that the apoptosis rates of HepG2 cell were increased after treatment with 0, 5, 10, 15, and 20 mmol/L MET for 24 h, and the apoptosis rates were 2.78% ± 0.68%, 9.33% ± 0.22%, 17.13% ± 0.10%, 21.61% ± 0.20%, and 25.26% ± 1.09%, respectively, showing a dose-dependent manner. The apoptosis rates of HepG2 cells were increased after treatment with 10 mmol/L for 0, 12, 24, 36, 48 h, and the apoptosis rates were 2.05% ± 0.04%, 8.10% ± 0.08%, 16.53% ± 0.93%, 20.95% ± 0.16%, and 25.65% ± 0.44%, showing a time-dependent manner. The expression of VEGF decreased after treatment with different concentrations of MET for 24 h or 10 mmol/L MET for different times, showing a dose- and time-dependent manner.

CONCLUSION

MET can inhibit HepG2 cell proliferation via inducing apoptosis, which may involve the expression of VEGF.