Hepatocellular Carcinoma Risk Scores Predict Patients Under Surveillance at Low Risk of Benefit and High Risk of Harm

Enhancing hepatocellular carcinoma diagnosis in non-high-risk patients: a customized ChatGPT model integrating contrast-enhanced ultrasound

PURPOSE

This study aims to improve hepatocellular carcinoma (HCC) diagnostic accuracy in non-high-risk populations by utilizing GPTs that incorporate integrated risk coefficients, and to explore its feasibility.

MATERIAL AND METHODS

Between August 2016 and June 2019, patients with focal liver lesions (FLLs) in non-high-risk populations, confirmed by histopathology or clinical/imaging evidence, were retrospectively included. A logistic regression model was developed using baseline characteristics and contrast-enhanced ultrasound (CEUS) features to identify independent HCC risk factors. Three ChatGPT-based models were evaluated: ChatGPT 4o (a general-purpose model developed by OpenAI), BaseGPT (a customized model with HCC diagnostic knowledge), and RiskGPT (a further customized model integrating HCC knowledge and identified risk factors). Their intra-agreement and diagnostic performance were compared.

RESULTS

Logistic regression identified male, obesity, HBcAb or HBeAb positivity, elevated alpha-fetoprotein, and mild washout on CEUS as associated with HCC. RiskGPT achieved the highest area under a receiver operating characteristic curve (AUC) (0.89) and demonstrated superior accuracy (90.3%) in HCC identification; significantly outperforming both ChatGPT 4o (AUC 0.79, P = 0.002; accuracy 83.1%, P = 0.02) and BaseGPT (AUC 0.81, P = 0.008; accuracy 80.6%, P = 0.002). RiskGPT demonstrated superior sensitivity compared to ChatGPT 4o (85.5% vs. 66.3%) and outperformed BaseGPT in specificity (92.7% vs. 80.6%) and positive predictive value (85.5% vs. 67.7%) (all P < 0.001). Additionally, RiskGPT showed substantial intra-consistency in diagnosing FLLs, with a κ value of 0.78.

CONCLUSION

RiskGPT improves HCC diagnostic accuracy in non-high-risk patients by integrating clinical, imaging features, and risk coefficients, demonstrating significant diagnostic potential.

Assessing the Predictive Accuracy of the aMAP Risk Score for Hepatocellular Carcinoma (HCC): Diagnostic Test Accuracy and Meta-analysis

Purpose

We aimed to perform a meta-analysis with the intention of evaluating the reliability and test accuracy of the aMAP risk score in the identification of HCC.

Methods

A systematic search was performed in PubMed, Scopus, Cochrane, Embase, and Web of Science databases from inception to September 2023, to identify studies measuring the aMAP score in patients for the purpose of predicting the occurrence or recurrence of HCC. The meta-analysis was performed using the meta package in R version 4.1.0. The diagnostic accuracy meta-analysis was conducted using Meta-DiSc software.

Results

Thirty-five studies 102,959 participants were included in the review. The aMAP score was significantly higher in the HCC group than in the non-HCC group, with a mean difference of 6.15. When the aMAP score is at 50, the pooled sensitivity, specificity, negative likelihood ratio, and positive likelihood ratio with 95% CI was 0.961 (95% CI 0.936, 0.976), 0.344 (95% CI 0.227, 0.483), 0.114 (95% CI 0.087, 0.15), and 1.464 (95% CI 1.22, 1.756), respectively. At a cutoff value of 60, the pooled sensitivity, specificity, negative likelihood ratio, and positive likelihood ratio with 95% CI was 0.594 (95% CI 0.492, 0.689), 0.816 (95% CI 0.714, 0.888), 0.497 (95% CI 0.418, 0.591), and 3.235 (95% CI 2.284, 4.582), respectively.

Conclusion

The aMAP score is a reliable, accurate, and easy-to-use tool for predicting HCC patients of all stages, including early-stage HCC. Therefore, the aMAP score can be a valuable tool for surveillance of HCC patients and can help to improve early detection and reduce mortality.

Liver diseases and hepatocellular carcinoma in the Asia-Pacific region: burden, trends, challenges and future directions

Globally, nearly half of deaths from cirrhosis and chronic liver diseases (CLD) and three-quarters of deaths from hepatocellular carcinoma (HCC) occur in the Asia-Pacific region. Chronic hepatitis B is responsible for the vast majority of liver-related deaths in the region. Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common form of CLD, affecting an estimated 30% of the adult population. Compared with people of European descent, people from the Asia-Pacific region carry more genetic variants associated with MASLD and its progression. Alcohol is a fast-growing cause of CLD and HCC in Asia as a result of the rising per-capita consumption of alcohol. Drug-induced liver injury is under-recognized and probably has a high prevalence in this region. The epidemiological and outcome data of acute-on-chronic liver failure are heterogeneous, and non-unified definitions across regions contribute to this heterogeneity. CLDs are severely underdiagnosed, and effective treatments and vaccinations are underutilized. In this Review, we highlight trends in the burden of CLD and HCC in the Asia-Pacific region and discuss the rapidly changing aetiologies of liver disease. We examine the multiple gaps in the care cascade and propose mitigating strategies and future directions.

The challenges and potential in developing microRNA associated with regeneration as biomarkers to improve prognostication for liver failure syndromes and hepatocellular carcinoma

INTRODUCTION

Determining the need for liver transplantation remains critical in the management of hepatocellular carcinoma (HCC) and liver failure syndromes (including acute liver failure and decompensated cirrhosis states). Conventional prognostic models utilize biomarkers of liver and non-liver failure and have limitations in their application. Novel biomarkers which predict regeneration may fulfil this niche. microRNA are implicated in health and disease and are present in abundance in the circulation. Despite this, they have not translated into mainstream clinical biomarkers.

AREAS COVERED

We will discuss current challenges in the prognostication of patients with liver failure syndromes as well as for patients with HCC. We will discuss biomarkers implicated with liver regeneration. We then provide an overview of the challenges in developing microRNA into clinically tractable biomarkers. Finally, we will provide a scoping review of microRNA which may have potential as prognostic biomarkers in liver failure syndromes and HCC.

EXPERT OPINION

Novel biomarkers are needed to improve prognostic models in liver failure syndromes and HCC. Biomarkers associated with liver regeneration are currently lacking and may fulfil this niche. microRNA have the potential to be developed into clinically tractable biomarkers but a consensus on standardizing methodology and reporting is required prior to large-scale studies.