Various hepatocellular carcinoma (HCC) prediction models have been proposed for patients with chronic hepatitis B (CHB) using clinical variables. We aimed to develop an artificial intelligence (AI)-based HCC prediction model by incorporating imaging biomarkers derived from abdominal computed tomography (CT) images along with clinical variables.

An AI prediction model employing a gradient-boosting machine algorithm was developed utilizing imaging biomarkers extracted by DeepFore, a deep learning-based CT auto-segmentation software. The derivation cohort (n = 5,585) was randomly divided into the training and internal validation sets at a 3:1 ratio. The external validation cohort included 2,883 patients. Six imaging biomarkers (i.e. abdominal visceral fat-total fat volume ratio, total fat-trunk volume ratio, spleen volume, liver volume, liver-spleen Hounsfield unit ratio, and muscle Hounsfield unit) and eight clinical variables were selected as the main variables of our model, PLAN-B-DF.

In the internal validation set (median follow-up duration = 7.4 years), PLAN-B-DF demonstrated an excellent predictive performance with a c-index of 0.91 and good calibration function (p = 0.78 by the Hosmer-Lemeshow test). In the external validation cohort (median follow-up duration = 4.6 years), PLAN-B-DF showed a significantly better discrimination function compared to previous models, including PLAN-B, PAGE-B, modified PAGE-B, and CU-HCC (c-index, 0.89 vs. 0.65-0.78; all p <0.001), and maintained a good calibration function (p = 0.42 by the Hosmer-Lemeshow test). When patients were classified into four groups according to the risk probability calculated by PLAN-B-DF, the 10-year cumulative HCC incidence was 0.0%, 0.4%, 16.0%, and 46.2% in the minimal-, low-, intermediate-, and high-risk groups, respectively.

This AI prediction model, integrating deep learning-based auto-segmentation of CT images, offers improved performance in predicting HCC risk among patients with CHB compared to previous models.

The novel predictive model PLAN-B-DF, employing an automated computed tomography segmentation algorithm, significantly improves predictive accuracy and risk stratification for hepatocellular carcinoma in patients with chronic hepatitis B (CHB). Using a gradient-boosting algorithm and computed tomography metrics, such as visceral fat volume and myosteatosis, PLAN-B-DF outperforms previous models based solely on clinical and demographic data. This model not only shows a higher c-index compared to previous models, but also effectively classifies patients with CHB into different risk groups. This model uses machine learning to analyze the complex relationships among various risk factors contributing to hepatocellular carcinoma occurrence, thereby enabling more personalized surveillance for patients with CHB.

The hepatitis B virus (HBV) remains a global problem despite effective tools to prevent, diagnosis, and control it. Unmet needs are identifiable across its clinical care cascade, underlining the challenges providers face in delivering effective care for patients with chronic hepatitis B. The review herein will focus on three timely clinical issues in HBV. This includes efforts to optimize delivery of perinatal HBV care, improve HBV-related hepatocellular carcinoma risk stratification models, and clarify the role of finite therapy in the HBV treatment algorithm. Important developments within these three topics will be addressed with the goal to motivate further investigation and optimization of these treatment strategies for HBV.

Chronic hepatitis B (CHB) patients who do not meet any immunostaging criteria are categorized as the "grey zone" (GZ). However, there are discrepancies in the definition of the GZ in different areas.

To investigate the prevalence and clinical characteristics of Chinese GZ patients and to validate the application value of three international guidelines.

Data from 807 naïve CHB patients with liver biopsies from seven Chinese centres were retrospectively collected. GZ patients were defined and compared across four guidelines: the Chinese guidelines, the American Association for the Study of Liver Diseases (AASLD) guidelines, the European Association for the Study of the Liver (EASL) guidelines, and the Asian Pacific Association for the Study of the Liver (APASL) guidelines.

When the Chinese guidelines were used, 38.79% of patients were categorized into the GZ, 78.91% of whom were indicated for antiviral therapy. The EASL guidelines yielded a greater proportion of GZ patients (50.56%) than did the APSAL (36.68%) and AASLD guidelines (33.21%). The APASL guidelines yielded a lower proportion of GZ patients who were indicated for antiviral therapy (42.57%) than did the AASLD (47.76%) and EASL guidelines (60.54%). According to the AASLD, EASL, APASL and Chinese guidelines, if liver biopsy was not performed, 13.06%, 31.86%, 0% and 64.54% of GZ patients were indicated for antiviral therapy, respectively.

GZ patients account for a significant proportion of CHB patients, with approximately half of them requiring antiviral therapy.

NCT06041022.

The updated EASL Clinical Practice Guidelines on the management of hepatitis B virus (HBV) infection provide comprehensive, evidence-based recommendations for its management. Spanning ten thematic sections, the guidelines address diagnostics, treatment goals, treatment indications, therapeutic options, hepatocellular carcinoma surveillance, management of special populations, HBV reactivation prophylaxis, post-transplant care, HBV prevention strategies, and finally address open questions and future research directions. Chronic HBV remains a global health challenge, with over 250 million individuals affected and significant mortality due to cirrhosis and hepatocellular carcinoma. These guidelines emphasise the importance of early diagnosis, risk stratification based on viral and host factors, and tailored antiviral therapy. Attention is given to simplified algorithms, vaccination, and screening to support global HBV elimination targets. The guidelines also discuss emerging biomarkers and evolving definitions of functional and partial cure. Developed through literature review, expert consensus, and a Delphi process, the guidelines aim to equip healthcare providers across disciplines with practical tools to optimise HBV care and outcomes worldwide.

To identify risk factors associated with liver complications in patients with chronic hepatitis B infection in an unselected cohort of hepatitis B patients in southern Spain.

A prospective open-cohort study was conducted on 437 patients with uncomplicated chronic hepatitis B infection in two hospitals in Málaga, southern Spain. The follow-up time ranged from 0.5 to 31.5 years (mean: 13.8±9.5 years; median: 11.4 years). The aim of this study was to evaluate the occurrence of the initial liver complication during follow-up, which is defined as the emergence of liver cancer or complications resulting from portal hypertension. Survival curves were obtained using a time-to-event method through Kaplan-Meier analysis. Multivariate Cox regression was conducted to estimate the hazard ratios of risk factors associated with complications after adjusting for multiple variables. The follow-up of the patients was carried out under conditions of usual clinical practice. Based on the weighted adjustment of these factors, we developed a Hepatitis B Complication Score (HBCS) from which it was possible to identify patients with low and high risk of complications during follow-up.

33 out of 437 patients (7.55%) experienced liver complications, 12 (36.3%) were secondary to portal hypertension, and 21 patients (63.7%) developed liver cancer. A Multivariate Cox regression identified the following independent risk factor: Age above 45 years: HR 7.10 (2.9-17.3); low platelet count: HR 4.88 (2.1-10.9); hepatitis C coinfection: HR 4.68 (2.0-10.9); Male gender: HR 4.64 (1.5-14.2); alkaline phosphatase above 147 UI/mL: HR 4.33 (2.0-8.9); and Child score above 5 points: HR 3.83 (1.7-8.4). The Risk of Complications Score (HBCS) was developed with a high predictive capacity AUROC 0.92 (0.87-0.97).

An HBCS score greater than 3.07 points identifies patients at high risk of developing complications and with an increased risk of liver and all-cause mortality.

Liver stiffness measurement (LSM) via vibration-controlled transient elastography accurately assesses fibrosis. We aimed to develop a universal risk score for predicting hepatocellular carcinoma (HCC) development in patients with chronic hepatitis.

We systematically selected predictors and developed the risk prediction model (HCC-LSM) in the hepatitis B virus (HBV) training cohort (n = 2251, median follow-up of 3.2 years). The HCC-LSM model was validated in an independent HBV validation cohort (n = 1191, median follow-up of 5.7 years) and a non-viral chronic liver disease (CLD) extrapolation cohort (n = 1189, median follow-up of 3.3 years). An HCC risk score was then constructed based on a nomogram. An online risk evaluation tool Liver Elastography-Based Hepatocellular Carcinoma Risk Score (LEBER) was developed using ChatGPT4.0.

Eight routinely available predictors were identified, with LSM levels showing a significant dose-response relationship with HCC incidence (P < .001 by log-rank test). The HCC-LSM model exhibited excellent predictive performance in the HBV training cohort (C-index = 0.866) and the HBV validation cohort (C-index = 0.852), with good performance in the extrapolation CLD cohort (C-index = 0.769). The model demonstrated significantly superior discrimination compared to 6 previous models across the 3 cohorts. Cut-off values of 87.2 and 121.1 for the HCC-LSM score categorized participants into low-, medium-, and high-risk groups. An online public risk evaluation tool (LEBER; http://ccra.njmu.edu.cn/LEBER669.html) was developed to facilitate the use of HCC-LSM.

The accessible, reliable risk score based on LSM accurately predicted HCC development in patients with chronic hepatitis, providing an effective risk assessment tool for HCC surveillance strategies.

Current guidelines to prevent hepatocellular carcinoma (HCC) by chronic hepatitis B virus (HBV) infection are based on risk assessments that include age, sex, and virological and biochemical parameters. The study aim was to investigate the impact of predictive markers on long-term outcomes. The clinical outcomes of 100 patients with chronic hepatitis B were investigated 30 years after a baseline assessment that included liver biopsy. A favourable outcome-HBsAg loss or HBeAg-negative infection (ENI; previously termed 'inactive carrier')-was observed in 74% of all patients, whereas 7% developed HCC. HBsAg loss was observed in 75% of patients with genotype A, compared with 42%, 33% and 0% with genotypes D, B and C, respectively (p < 0.0001). HCC developed in 3 patients (33%) with genotype C as compared with 3 (17%), 1 (2%) and 0 patients with genotypes B, D and A, respectively (p < 0.0001). In multiple logistic regression analysis, both HBsAg loss and HCC were associated with HBV genotype and baseline HBV DNA level, and HCC also with histological score. The results suggest that genotyping and histological assessment may improve outcome prediction and help decisions about HCC screening, particularly in populations with HBV-infected individuals of mixed geographic origin.

Chronic hepatitis B (CHB) infection is the major risk factor for hepatocellular carcinoma (HCC).

To develop machine-learning models for predicting an individual risk of HCC development in CHB-infected patients.

Machine learning models were constructed using features from follow-up visits of CHB patients to predict the diagnosis of HCC development within 6 months after each index follow-up. We developed 4 model variants using all features, with alpha fetoprotein (AFP) (AF A ) and without AFP (AFN ); and selected features, with AFP (SF A ) and without AFP (SFN ). Performance was evaluated using 10-fold cross-validation on a derivation cohort and further validated on an independent cohort.

In the derivation cohort of 2,382 patients, of whom 117 developed HCC, AFA achieved higher sensitivity (0.634, 95% confidence interval [CI]: 0.559-0.708) and specificity (0.836; 0.830-0.842) than AF N (sensitivity 0.553; 0.476-0.630 and specificity 0.786; 0.779-0.792). SFA also achieved higher sensitivity (0.683; 0.611-0.755 vs. 0.658; 0.585-0.732) and specificity (0.756; 0.749-0.763 vs. 0.744; 0.737-0.751) than SFN . Performance of SFA and SFN were tested in another cohort of 162 patients in which 57 patients developed HCC. SFA achieved sensitivity and specificity of 0.634 (0.522-0.746) and 0.657 (0.615-0.699), while sensitivity and specificity of SFN were 0.690 (0.583-0.798) and 0.651 (0.609-0.693), respectively.

The machine learning models demonstrate good performance for predicting short-term risk for HCC development and may potentially be used for tailoring surveillance interval for CHB patients.

Chronic hepatitis B and cirrhosis pose significant global health threats. Few studies have explored the disease burden and mortality trend of cirrhosis caused by hepatitis B virus infection among adolescents and young adults (AYAs, aged 15-39 years). This study aimed to assess the disease burden and trends.

Publicly available data were obtained from the 2021 GBD database. The rates of incidence, mortality, and disability-adjusted life years were calculated at the global, regional, and national levels. Temporal trends were assessed using joinpoint regression analysis, while the Bayesian age-period-cohort model was used to predict future trends.

From 1990 to 2021, the global incidence rate of hepatitis B-related cirrhosis decreased from 111.33 (95% uncertainty interval: 89.18 to 134.98) to 67.75 (54.06 to 82.71) per 100,000 with an average annual percentage change of -1.58 (95% confidence interval: -1.66 to -1.51, p < 0.001). However, between 1990 and 2021, the incidence numbers in the 30-34 and 35-39 age groups increased by 23.75 and 21.24%, respectively. The number of deaths in low and low-middle Socio-demographic Index (SDI) areas increased by 79.51 and 20.62%, respectively. Moreover, it is predicted that the numbers of incidences and deaths will continue to rise in areas with low SDI. At the regional level, Central Sub-Saharan Africa had the highest incidence and mortality rates. In 2021, Somalia and the Democratic Republic of Congo had the highest incidence rates, whereas Kiribati and Cambodia had the highest mortality rates.

The overall burden of hepatitis B-related cirrhosis among AYAs has decreased over the past three decades. Nevertheless, there was a slight increase in the incidence number among individuals aged 30-39 years. The substantial burden and predicted rise in the numbers of incidences and deaths in low SDI areas underscore the need for sustained and targeted public health interventions.

Risk prediction models can identify individuals at high risk of chronic liver disease (CLD), but there is limited evidence on the performance of various models in diverse populations. We aimed to systematically review CLD prediction models, meta-analyze their performance, and externally validate them in 0.5 million Chinese adults in the China Kadoorie Biobank (CKB).

Models were identified through a systematic review and categorized by the target population and outcomes (hepatocellular carcinoma [HCC] and CLD). The performance of models to predict 10-year risk of CLD was assessed by discrimination (C-index) and calibration (observed vs predicted probabilies).

The systematic review identified 57 articles and 114 models (28.4% undergone external validation), including 13 eligible for validation in CKB. Models with high discrimination (C-index ≥ 0.70) in CKB were as follows: (1) general population: Li-2018 and Wen 1-2012 for HCC, CLivD score (non-lab and lab) and dAAR for CLD; (2) hepatitis B virus (HBV) infected individuals: Cao-2021 for HCC and CAP-B for CLD. In CKB, all models tended to overestimate the risk (O:E ratio 0.55-0.94). In meta-analysis, we further identified models with high discrimination: (1) general population (C-index ≥ 0.70): Sinn-2020, Wen 2-2012, and Wen 3-2012 for HCC, and FIB-4 and Forns for CLD; (2) HBV infected individuals (C-index ≥ 0.80): RWS-HCC and REACH-B IIa for HCC and GAG-HCC for HCC and CLD.

Several models showed good discrimination and calibration in external validation, indicating their potential feasibility for risk stratification in population-based screening programs for CLD in Chinese adults.

Patients with advanced chronic liver disease (ACLD) are at high risk of developing hepatocellular carcinoma (HCC). Therefore, biannual surveillance is recommended. This large-scale multicenter study aimed to stratify the risk of HCC development in ACLD.

From 3016 patients with ACLD screened in 17 European and Chinese centers, 2340 patients with liver stiffness measurement (LSM) determined using different techniques (two-dimensional shear-wave elastography [2D-SWE], transient elastography, and point shear-wave elastography) and with different disease severities were included. Cox regression was used to explore risk factors for HCC. We used these data to create an algorithm, named PLEASE, but referred to in this manuscript as "the algorithm"; the algorithm was validated in internal and two external cohorts across elastography techniques.

HCC developed in 127 (5.4%) patients during follow-up. LSM by 2D-SWE (hazard ratio: 2.28) was found to be associated with developing HCC, alongside age, sex, etiology, and platelet count (C-index: 0.8428). We thus established the algorithm with applicable cutoffs, assigning a maximum of six points: platelet count less than 150×109/l, LSM greater than or equal to 15 kPa, age greater than or equal to 50 years, male sex, controlled/uncontrolled viral hepatitis, or presence of steatotic liver diseases. Within 2 years, with a median follow-up of 13.7 months, patients in the high-risk group (≥4 points) had an HCC incidence of 15.6% (95% confidence interval [CI], 12.1% to 18.7%) compared with the low-risk group, at 1.7% (95% CI, 0.9% to 2.5%).

Our algorithm stratified patients into two groups: those at higher risk of developing HCC and those at lower risk. Our data provide equipoise to test the prospective utility of the algorithm with respect to clinical decisions about screening patients with ACLD for incident HCC. (Funded by the German Research Foundation and others; ClinicalTrials.gov number, NCT03389152.).

Over 300 million individuals worldwide are chronically infected with hepatitis B virus and at risk for progressive liver disease. Due to the lack of a therapy that reliably achieves viral elimination and the variability of liver disease progression, treatment decisions are guided by the degree of liver disease and viral biomarkers as the viral life-cycle is well characterized and largely conserved between individuals. In contrast, the immunological landscape is much more heterogeneous and diverse and the measurement of its components is less well standardized. Due to the lack of a universal and easily measurable set of biomarkers, clinical practice guidelines remain controversial, aiming for a balance between simplifying treatment decisions by reducing biomarker requirements and using all available biomarkers to avoid overtreatment of patients with low risk for disease progression. While approved therapies such as nucleos(t)ide analogs improve patient outcomes, the inability to achieve a complete cure highlights the need for novel therapies. Since no treatment candidate has demonstrated universal efficacy, biomarkers will remain important for treatment stratification. Here, we summarize the current knowledge on virological and immunological biomarkers with a specific focus on how they might be beneficial in guiding treatment decisions in chronic hepatitis B.

A nonlinear association between serum hepatitis B virus (HBV) DNA levels and hepatocellular carcinoma (HCC) risk has been suggested in patients with chronic hepatitis B (CHB).

To develop and externally validate a prognostic model for HCC risk in noncirrhotic adult patients with CHB and no notable alanine aminotransferase (ALT) elevation.

Multinational cohort study.

A community-based cohort in Taiwan (REVEAL-HBV [Risk Evaluation of Viral Load Elevation and Associated Liver Disease/Cancer-Hepatitis B Virus]; REACH-B [Risk Estimation for HCC in CHB] model cohort) and 8 hospital-based cohorts from Korea and Hong Kong (GAG-HCC [Guide with Age, Gender, HBV DNA-HCC] and CU-HCC [Chinese University-HCC] cohorts).

Model development: 6949 patients with CHB from a Korean hospital-based cohort. External validation: 7429 patients with CHB combined from the Taiwanese cohort and 7 cohorts from Korea and Hong Kong.

Incidence of HCC.

Over median follow-up periods of 10.0 and 12.2 years, the derivation and validation cohorts identified 435 and 467 incident HCC cases, respectively. Baseline HBV DNA level was one of the strongest predictors of HCC development, demonstrating a nonlinear parabolic association in both cohorts, with moderate viral loads (around 6 log10 IU/mL) showing the highest HCC risk. Additional predictors included in the new model (Revised REACH-B) were age, sex, platelet count, ALT levels, and positive hepatitis B e antigen result. The model exhibited satisfactory discrimination and calibration, with c-statistics of 0.844 and 0.813 in the derivation and validation cohorts with multiple imputation, respectively. The model yielded a greater positive net benefit compared with other strategies in the 0% to 18% threshold.

Validation in cohorts of other races and receiving antiviral treatment was lacking.

Our new prognostic model, based on the nonlinear association between HBV viral loads and HCC risk, provides a valuable tool for predicting and stratifying HCC risk in noncirrhotic patients with CHB who are not currently indicated for antiviral treatment.

Korean government.

Hepatocellular carcinoma (HCC) represents a significant global health burden, with its incidence and mortality rates varying significantly across different geographic regions. This variance is largely attributed to differences in the prevalence of risk factors such as hepatitis B and C infections, and alcohol consumption, as well as genetic predispositions that are distinct between Eastern and Western populations. Moreover, the impact of racial and ethnic diversity on the disease's epidemiology further complicates the global understanding and prediction of HCC. Such disparities highlight the critical need to evaluate the applicability of predictive models across diverse populations, acknowledging that a model developed in one region may not necessarily translate with the same accuracy or effectiveness when applied to another, because of these underlying epidemiologic and genetic differences. In this study, we aimed to assess the cross-regional applicability and accuracy of an HCC prediction model (Texas hepatocellular carcinoma risk index [THCC-RI] predictive model) originally developed in Western populations, within an Eastern context.1,2.

Chronic hepatitis B (CHB) infection is responsible for 40% of the global burden of hepatocellular carcinoma (HCC) with a high case fatality rate. The risk of HCC differs among CHB subjects owing to differences in host and viral factors. Modifiable risk factors include viral load, use of antiviral therapy, co-infection with other hepatotropic viruses, concomitant metabolic dysfunctionassociated steatotic liver disease or diabetes mellitus, environmental exposure, and medication use. Detecting HCC at early stage improves survival, and current practice recommends HCC surveillance among individuals with cirrhosis, family history of HCC, or above an age cut-off. Ultrasonography with or without serum alpha feto-protein (AFP) every 6 months is widely accepted strategy for HCC surveillance. Novel tumor-specific markers, when combined with AFP, improve diagnostic accuracy than AFP alone to detect HCC at an early stage. To predict the risk of HCC, a number of clinical risk scores have been developed but none of them are clinically implemented nor endorsed by clinical practice guidelines. Biomarkers that reflect viral transcriptional activity and degree of liver fibrosis can potentially stratify the risk of HCC, especially among subjects who are already on antiviral therapy. Ongoing exploration of these novel biomarkers is required to confirm their performance characteristics, replicability and practicability.

It is generally acknowledged that antiviral therapy can reduce the incidence of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC), there remains a subset of patients with chronic HBV infection who develop HCC despite receiving antiviral treatment. This study aimed to develop a model capable of predicting the long-term occurrence of HCC in patients with chronic HBV infection before initiating antiviral therapy. A total of 1450 patients with chronic HBV infection, who received initial antiviral therapy between April 2006 and March 2023 and completed long-term follow-ups, were nonselectively enrolled in this study. Least absolute shrinkage and selection operator (LASSO) and Cox regression analysis was used to construct the model. The results were validated in an external cohort (n = 210) and compared with existing models. The median follow-up time for all patients was 60 months, with a maximum follow-up time of 144 months, during which, 32 cases of HCC occurred. The nomogram model for predicting HCC based on GGT, AFP, cirrhosis, gender, age, and hepatitis B e antibody (TARGET-HCC) was constructed, demonstrating a good predictive performance. In the derivation cohort, the C-index was 0.906 (95% CI = 0.869-0.944), and in the validation cohort, it was 0.780 (95% CI = 0.673-0.886). Compared with existing models, TARGET-HCC showed promising predictive performance. Additionally, the time-dependent feature importance curve indicated that gender consistently remained the most stable predictor for HCC throughout the initial decade of antiviral therapy. This simple predictive model based on noninvasive clinical features can assist clinicians in identifying high-risk patients with chronic HBV infection for HCC before the initiation of antiviral therapy.

We evaluated the association of hepatitis B virus (HBV) treatment with all-cause, and liver-related mortality among individuals with HBV and cirrhosis in British Columbia (BC), Canada.

This analysis included people diagnosed with HBV and had cirrhosis in the BC Hepatitis Testers Cohort, including data on all individuals diagnosed with HBV from 1990 to 2015 in BC and integrated with healthcare administrative data. We followed people with cirrhosis from the first cirrhosis diagnosis date until death or December 31, 2020. We compared all-cause and liver related mortality between those who received treatment and those who did not. HBV treatment was considered a time-varying variable. We performed multivariable Cox proportional hazards model and competing risk regression models to assess the association of HBV treatment with all causes, and liver-related mortality respectively using inverse probability of treatment weighted population.

Among 4962 individuals with HBV and cirrhosis, 48.1% received HBV treatment. Treated individuals had a median follow-up of 2.97 years, compared to 2.87 years for untreated individuals. The treated group was older (median age 57 vs 54 years), had higher proportion of treated of males [1802 (75.50%) vs 1766 (68.8%)], from urban area [2318 (97.2%) vs 2355 (91.8%)], and from East and South Asian ethnicity [1506 (63.1%) vs 709 (27.5%)] compared to untreated group. Untreated people experienced higher all-cause mortality (115.47 vs. 35.72 per 1000 person-years) and liver-related mortality (49.86 vs. 11.39 per 1000 person-years). Multivariable models showed that HBV treatment significantly lowered the risk of all-cause mortality (adjusted hazard ratio (aHR) 0.74; 95% CI: 0.65, 0.84) and liver-related mortality (adjusted subdistribution hazard ratio (asHR) 0.72; 95% CI: 0.58, 0.89) compared to untreated individuals. Among untreated individuals with HBV, those with HCV coinfection had a higher risk of both all-cause and liver-related mortality (aHR 1.57; 95% CI: 1.22, 2.04, and asHR 1.60; 95% CI: 1.25, 2.05, respectively).

HBV treatment was associated with a significant reduction in all-cause and liver-related mortality among individuals with cirrhosis. The findings highlight the need for treatment among individuals with HBV related cirrhosis especially those with coinfection with hepatitis C virus.

This work was supported by the BC Centre for Disease Control and the Canadian Institutes of Health Research (CIHR) [Grant # NHC-142832, PJT-156066, and SC1 -178736]. JDM has received doctoral fellowship from the Canadian Network on Hepatitis C (CanHepC). DJ has received Doctoral Research Award (#201910DF1-435705-64343) from the Canadian Institutes of Health Research (CIHR) and doctoral fellowship from the CanHepC. CanHepC is funded by a joint initiative of the Canadian Institutes of Health Research (CIHR) (NHC-142832) and the Public Health Agency of Canada (PHAC).

Several studies have indicated that BALAD score which includes the HCC tumor markers of HCC, AFP, AFP-L3%, DCP, and serum albumin and bilirubin value were good predictors of HCC patients for all treatment modalities. In this study, we aim to clarify the impact of BALAD score as the prognostic factor for HCC patients after curative surgery.

This study investigated 578 patients who underwent hepatectomy for HCC between January 2003 and May 2013. Cumulative recurrence rate, overall survival (OS), and clinicopathological parameters were analyzed according to the level of BALAD score.

In patients with higher BALAD score, recurrence rate and OS was poor (p = 0.0015 and p < 0.0001, respectively). Multivariate analyses revealed independent risk factors for recurrence to be male (hazard ratio [HR] 1.52, P = 0.011), HCV-antibody positive (HR 1.33, P = 0.019), multiple tumors (HR 2.16, P < 0.0001), microvascular invasion (HR 1.45, P = 0.0035) and higher BALAD score (RR 1.70, P = 0.015). The independent risk factors for OS were multiple tumors (HR 1.52, P = 0.014), microvascular invasion (HR 1.53, P = 0.012), and higher BALAD score (RR 2.51, P = 0.0012).

BALAD score is associated with high recurrence rate and poor overall survival of the patients who underwent curative liver resection for HCC.

Surveillance for hepatocellular carcinoma (HCC) has been proven to increase the proportion of tumors detected at early stages and the chance of receiving curative therapies, reducing mortality by about 30%.

Current recommendations consist of a semi-annual abdominal ultrasound with or without serum alpha-fetoprotein measurement in patients with cirrhosis and specific subgroups of populations with chronic viral hepatitis. Antiviral therapies, such as nucleot(s)ide analogs that efficiently suppress the replication of hepatitis B virus (HBV) and direct-acting antiviral drugs able to eliminate the hepatitis C virus (HCV) in >90% of patients, have radically changed the outcomes of viral liver disease and decreased, but not eliminated, the risk of HCC in both cirrhotic and non-cirrhotic patients. HCC risk is a key starting point for implementing a cost-effective surveillance and should also guide the decision-making process concerning its modality. As the global number of effectively treated viral patients continues to rise, there is a pressing need to identify those for whom the benefit-to-harm ratio of surveillance is favorable and to determine how to conduct cost-effective screening on such patients.

This article addresses this topic and attempts to determine which patients should continue HCC surveillance after HBV suppression or HCV eradication, based on cost-effectiveness principles and the fact that HCC risk declines over time. We also formulate a proposal for a surveillance algorithm that switches the use of surveillance for HCC from the "one-size-fits-all" approach to individualized programs based on oncologic risk (precision surveillance).

Chronic hepatitis B (CHB) infection constitutes a leading cause of hepatocellular carcinoma (HCC) development. The identification of HCC risk factors and the development of prognostic risk scores are essential for early diagnosis and prognosis. The aim of this observational, retrospective study was to evaluate baseline risk factors associated with HCC in CHB. Six hundred thirty-two consecutive adults with CHB (n = 632) [median age: 46 (IQR: 24)], attending the outpatients' Hepatology clinics between 01/1993-09/2020 were evaluated. Core promoter mutations and cirrhosis-HCC (GAG-HCC), Chinese University-HCC (CU-HCC), risk estimation for hepatocellular carcinoma in chronic hepatitis B (REACH-B), Fibrosis-4 (FIB-4), and Platelet Age Gender-HBV (PAGE-B) prognostic scores were calculated, and receiver operating curves were used to assess their prognostic performance. HCC was developed in 34 (5.38%) patients. In the multivariable Cox regression analysis, advanced age (HR: 1.086, 95% CI: 1.037-1.137), male sex (HR: 7.696, 95% CI: 1.971-30.046), alcohol abuse (HR: 2.903, 95% CI: 1.222-6.987) and cirrhosis (HR: 21.239, 95% CI: 6.001-75.167) at baseline were independently associated with the development of HCC. GAG-HCC and PAGE-B showed the highest performance with c-statistics of 0.895 (95% CI: 0.829-0.961) and 0.857 (95% CI: 0.791-0.924), respectively. In the subgroup of patients with cirrhosis, the performance of all scores declined. When treated and untreated patients were studied separately, the discriminatory ability of the scores differed. In conclusion, HCC development was independently associated with advanced age, male sex, alcohol abuse, and baseline cirrhosis among a diverse population with CHB. GAG-HCC and PAGE-B showed high discriminatory performance to assess the risk of HCC development in these patients, but these performances declined in the subgroup of patients with cirrhosis. Further research to develop scores more specific to certain CHB subgroups is needed.

Hepatitis B virus (HBV) RNA and hepatitis B core-related antigen (HBcrAg) have been reported to reflect the transcriptional activity of covalently closed circular HBV DNA. We retrospectively investigated the proportions of quantifiable serum HBV RNA and immunoassay for total antigen including complex via pretreatment-hepatitis B core-related antigen (iTACT-HBcrAg) in chronic hepatitis B patients negative for hepatitis B e antigen (HBeAg) and/or with hepatitis B surface antigen (HBsAg) seroclearance. This study included 246 HBeAg-negative HBV-infected patients, who comprised 13 with liver cirrhosis (LC, the LC group), 118 chronic hepatitis (CH, the CH group), and 115 inactive carriers (IC, the IC group), and 44 patients with HBsAg seroclearance. iTACT-HBcrAg and HBV RNA levels were determined using stored serum samples. Higher proportions of the patients had quantifiable iTACT-HBcrAg than HBV RNA in all groups of HBeAg-negative patients (iTACT-HBcrAg: 84.6%, 90.7%, 35.7%, HBV RNA: 23.1%, 26.3%, 14.8%, for the LC, CH, IC groups). With HBsAg seroclearance (HBsAg <0.05 IU/mL), the proportions of quantifiable samples for HBV RNA were also lower than iTACT-HBcrAg (0% for HBV RNA). Thus, iTACT-HBcrAg was more often detectable than circulating HBV RNA in this study population. Further long-term prospective evaluation of iTACT-HBcrAg is desirable for its utilization in clinical practice.

This study aimed to evaluate the efficacy of the aMAP score and compare it with other risk scores for predicting hepatocellular carcinoma (HCC) development in Thai patients with chronic hepatitis B (CHB). We retrospectively analyzed patients with CHB between 1 January 2008 and 31 December 2019. Data on demographics, clinical parameters, cirrhosis status, HCC imaging, and alpha fetoprotein surveillance were collected to calculate the aMAP score (0-100) based on age, sex, albumin-bilirubin level, and platelet count. Of the 1060 patients analyzed, 789 were eligible, of whom 51 developed HCC. The cumulative HCC incidences in the low-, moderate-, and high-risk groups at 3, 5, and 10 years were significantly different (log-rank, p < 0.0001). The area under the receiver operating characteristic curves (AUROCs) of the aMAP scores for predicting HCC at 3, 5, and 10 years were 0.748, 0.777, and 0.784, respectively. Among the risk scores, the CU-HCC score had the highest AUROCs (0.823) for predicting 5-year HCC development. The aMAP score is a valuable tool for predicting HCC risk in Thai patients with CHB and can enhance surveillance strategies. However, its performance is inferior to that of the CU-HCC score, suggesting the need for new predictive tools for HCC surveillance.

Clinical research has suggested that chronic HBV infection exerts a certain effect on the occurrence of cardiovascular disease by regulating cholesterol metabolism in liver cells. High serum apolipoprotein B/apolipoprotein A1 (ApoB/ApoA1) ratio plays a certain role in the above regulation, and it serves as a risk factor for cardiovascular disease. However, whether the ApoB/ApoA1 ratio is correlated with chronic HBV infection and its disease progression remains unclear. In accordance with the inclusion and exclusion criteria, all 378 participants administrated at Renmin Hospital of Wuhan University from March 2021 to March 2022, fell into Healthy Control (HC) group (50 participants), Hepatocellular carcinoma (HCC) group (107 patients), liver cirrhosis (LC) group (64 patients), chronic hepatitis B (CHB) group (62 patients), chronic hepatitis C (CHC) group (46 patients) and Hepatitis E Virus (HEV) group (49 patients). Serum ApoA1 and ApoB concentrations were measured at admission, and the ApoB/ApoA1 ratio was determined. The levels of laboratory parameters in the respective group were compared and ApoB/ApoA1 ratios in HCC patients and LC patients with different severity were further analyzed. ROC curves were plotted to analyze the early diagnostic ability of ApoB/ApoA1 ratio for HBV-associated HCC. Logistic regression and restricted cubic spline analysis were used to explore the correlation between ApoB/ApoA1 ratio and LC and HCC risk. A comparison was drawn in terms of ApoB/ApoA1 ratio between the groups, and the result was expressed in descending sequence: HEV group > CHB group > LC group > HCC group > CHC group > HC group, early-stage HCC < middle-stage HCC < advanced-stage HCC, Class A LC < Class B LC < Class C LC. Serum ApoB/ApoA1 ratio combined diagnosis with AFP exhibited the capability of increasing the detection efficacy and specificity of AFP for HCC and AFP-negative HCC. The incidence of LC and HCC in the respective logistic regression model showed a negative correlation with the serum ApoB/ApoA1 ratio in CHB patients (P < 0.05). After all confounding factors covered in this study were regulated, the result of the restricted cubic spline analysis suggested that in a certain range, serum ApoB/ApoA1 ratio showed an inverse correlation with the prevalence of LC or HCC in CHB patients. Serum ApoB/ApoA1 ratio in CHB patients may be conducive to identifying high-risk patients for HCC or LC, such that LC and HCC can be early diagnosed and treated.

Evidence shows people living with CHB even with a normal ALT (40U/L as threshold) suffer histological disease and there is still little research to evaluate the potential benefit of antiviral benefits in them.

We retrospectively examined 1352 patients who underwent liver biopsy from 2017 to 2021 and then obtained their 1-year follow-up data to analyze.

ALT levels were categorized into high and low, with thresholds set at >29 for males and >15 for females through Youden's Index. The high normal ALT group showed significant histological disease at baseline (56.43% vs 43.82%, p< 0.001), and better HBV DNA clearance from treatment using PSM (p=0.005). Similar results were obtained using 2016 AASLD high normals (male >30, female >19). Further multivariate logistic analysis showed that high normal ALT (both criterias) was an independent predictor of treatment (OR 1.993, 95% CI 1.115-3.560, p=0.020; OR 2.000, 95% CI 1.055-3.793, p=0.034) Both of the models had higher AUC compared with current scoring system, and there was no obvious difference between the two models (AUC:0.8840 vs 0.8835).

Male >30 or female >19 and Male >29 or female>15 are suggested to be better thresholds for normal ALT. Having a high normal ALT in CHB provides a potential benefit in antiviral therapy.