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.

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.

Antiviral therapy (AVT) reduces the risk of hepatitis B virus-related hepatocellular carcinoma (HCC).

The difference in risk of HCC after hepatitis B surface antigen (HBsAg) seroclearance to the AVT status was explored.

Patients with chronic hepatitis B who achieved HBsAg seroclearance were retrospectively evaluated. The primary outcome was the development of HCC after HBsAg seroclearance.

Of the study population, 1280 (84.2%) and 241 (15.8%) patients achieved HBsAg seroclearance without (spontaneous clearance group) and with AVT (AVT-induced clearance group), respectively. HCC cumulative incidence was comparable between the two groups (hazard ratio [HR] = 0.461; log-rank test, p = 0.197), whereas it was significantly lower in the AVT-induced HBsAg clearance group than in the spontaneous HBsAg clearance group in inverse probability of treatment weighting analysis (HR = 0.442; log-rank test, p = 0.004). In multivariate analysis, spontaneous HBsAg clearance, albumin-bilirubin (ALBI) grade ≥ 2, cirrhosis, and platelet count < 50 × 109/L were independently associated with the increased risk of HCC. The newly established antiviral therapy, cirrhosis, ALBI, and platelet count (ACAP) scores had a C-index of 0.765, and the time-dependent areas under the curve of HCC prediction at 5 and 8 years were 0774 and 0.823, respectively.

The risk of HCC differed according to the AVT status after HBsAg seroclearance.

Objective The progression of liver fibrosis and a male sex are risk factors for hepatocarcinogenesis under nucleos(t)ide analog (NA) therapy. Metabolic dysfunction-associated fatty liver disease (MAFLD) is a risk factor for hepatocarcinogenesis. This study aimed to investigate the factors involved in hepatocarcinogenesis during NAs therapy, including MAFLD. Methods This study is a retrospective study [observation period: median 9.4 years (2.1-19.6 years)]. The subjects were 164 patients taking NAs for more than 2 years and were hepatitis B envelope antigen (HBeAg)-negative with undetectable hepatitis B virus (HBV)-DNA. The patient had no history of hepatocellular carcinoma (HCC). We investigated the profile of HCC onset after NAs therapy using a decision tree analysis Results HCC developed in 20.7% (34/164) of the patients during the observation period. The prevalence of MAFLD was significantly higher in the HCC group than in the non-HCC group (64.7% vs. 43.9%, p=0.03). In particular, in the low-medium risk group classified by PAGE-B, MAFLD increased the risk of HCC development. According to a multivariate analysis, fibrosis-4 (FIB-4) index≥2.67, a male sex, and MAFLD (OR 2.4, 95%CI 1.0-6.0, p=0.04) were independent factors associated with the onset of HCC. In a decision tree analysis, MAFLD was the second classifier for the onset of HCC, next to the FIB-4 index (MAFLD 62.5%, non-MAFLD 28.5%). Conclusions We found that MAFLD was an independent risk factor for HCC in HBeAg-negative patients with undetectable HBV-DNA after NAs therapy. We further revealed that MAFLD was the second-best classifier for hepatocarcinogenesis, next to the FIB-4 index. MAFLD therefore appears to have a synergistic effect on hepatocarcinogenesis with hepatic fibrosis.

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.

To investigate the association between air pollution and hepatocellular carcinoma (HCC) in chronic hepatitis B (CHB) patients treated with nucleotide/nucleoside analogues.

We enrolled 1298 CHB patients treated with nucleotide/nucleoside analogues and analysed the incidence and risk factors for HCC. Daily estimates of air pollutants were estimated since the previous year from the enrolment date.

The annual incidence of HCC was 2.1/100 person-years after a follow-up period of over 4840.5 person-years. Factors with the strongest association with HCC development were liver cirrhosis (hazard ratio [HR]/95% confidence interval [CI]: 3.00/1.55-5.81; p = 0.001), male sex (2.98/1.51-5.90; p = 0.02), body mass index (1.11/1.04-1.18; p = 0.002) and age (1.06/1.04-1.09; p < 0.001). Among patients with cirrhosis, the factors associated with HCC development were male sex (HR/95% CI: 2.10/1.00-4.25; p = 0.04) and NO2 (per one-unit increment, parts per billion; 1.07/1.01-1.13; p = 0.01). Moreover, patients with the highest quartile of annual NO2 exposure had more than a three-fold risk of HCC than those with the lowest quartile of annual exposure (HR/95% CI: 3.26/1.34-7.93; p = 0.01). Among patients without cirrhosis, the strongest factors associated with HCC development were male sex (HR/95% CI: 5.86/1.79-19.23; p = 0.004), age (1.12/1.07-1.17; p < 0.001) and platelet count (0.99/0.98-1.00; p = 0.04).

Air pollution influences HCC development in CHB patients who receive nucleotide/nucleoside analogue therapy. Long-term NO2 exposure might accelerate HCC development in CHB patients with cirrhosis receiving nucleotide/nucleoside analogue treatment.

Identifying hepatitis B virus (HBV) patients eligible for safe nucleos(t)ide analogues (NAs) discontinuation remains challenging. Discrepant data on combined HBV DNA and quantitative HBV surface antigen (qHBsAg) assessments are available. This study aimed to identify potential predictors for safe treatment discontinuation by evaluating clinical/virological outcomes in patients on long-term NA therapy.

A retrospective cohort of 139 chronic hepatitis B (CHB) patients - who consecutively started Entecavir or Tenofovir from 2007 to 2011 - was evaluated. The study population was selected based on anti-HBe positivity, absence of prior antiviral treatment, absence of non-HBV-related liver diseases or hepatocellular carcinoma (HCC), and long-term clinical/ultrasonographic/laboratory evaluations post-NA initiation. Serum samples collected before starting NA (T0) and over ten years (T1-T10) were tested for HBV DNA and qHBsAg.

Twenty-two/139 (15.8 %) CHB patients (12 chronic hepatitis, 10 cirrhosis) met the inclusion criteria. All patients showed a significant decrease in liver stiffness values in the ten years of follow-up (p = 0.001), and no hepatic decompensation occurred. Three/22 (13.6 %) patients developed HCC. Ten/22 patients (45.5 %; group-A) had fluctuating HBV DNA, while other 10/22 (45.5 %; group-B) showed undetectable HBV DNA for 5-9 years with more significant qHBsAg decline (p = 0.04) than group-A. Two/22 (9.1 %) patients showed a critical qHBsAg decline up to seroconversion together with undetectable HBV DNA.

Persistent undetectable HBV DNA levels correlate with qHBsAg reduction and the potential HBsAg seroclearance, suggesting that long-term HBV DNA monitoring in NA-treated CHB patients might help identify candidates for treatment discontinuation.

Early assessment of hepatocellular carcinoma (HCC) risk could improve long-term outcomes in people with chronic hepatitis B virus (HBV) infection. Some existing HCC predictive scores are not easily implementable. We developed easy-to-use HCC predictive scores based on behavioural and routine bio-clinical data in people with chronic HBV infection.

Eight-year follow-up data was analysed from people with chronic HBV infection enrolled in the French ANRS CO22 HEPATHER cohort. Patients were randomly split into two samples (training/testing). A multivariable Cox model for time to HCC was estimated on the training sample. The HCC predictive score was computed by summing the points assigned to model predictors, normalising their coefficients over a 10-year age increment, and rounding to the nearest integer. The Youden index identified the score's optimal risk threshold. Comparisons with existing predictive scores were performed on the testing sample.

In the study population (N = 4370; 63% of men; 65% of < 50 years old), 56 HCC cases occurred during 25,900 follow-up person-years. Two HCC predictive scores were defined: SADAPTT (daily soft drink consumption, age, hepatitis Delta infection, unhealthy alcohol use, platelet count, heavy tobacco smoking, and HBV treatment) and ADAPTT (the same predictors except for daily soft drink consumption), with ranges 0-13 and 0-14, respectively, and values ≥ 3 indicating a high HCC risk. Their performances were similar to existing scores.

We developed two effective behaviour-based HCC predictive scores, implementable in many settings, including primary care and decentralised areas. Further studies are needed to validate these scores in other datasets.

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.

Successful antiviral therapy significantly decreases the incidence of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB). Alpha-fetoprotein (AFP) in the serum is a valuable early indicator of HCC. However, it is unclear whether different antiviral medications have varying effects on AFP levels. The purpose of this study was to evaluate this issue in those treated with entecavir (ETV) versus tenofovir disoproxil fumarate (TDF).

We prospectively enrolled treatment-naive CHB adults who commenced treatment with ETV or TDF. Their changes in biochemical, virological, and fibrosis parameters and the elevation of AFP or development of HCC during follow-up were analyzed.

A total of 1942 CHB patients were included (10-90% follow-up time 3-60 months), and 104 patients with elevated AFP (5.3%) and 27 patients with HCC development (1.4%) were identified during the follow-up. The difference in the cumulative incidence of AFP abnormalities and HCC was statistically significant between patients who received ETV or TDF therapy. Multivariate Cox regression showed that elevated liver stiffness with shear wave elastography (Hazard ratio (HR) = 1.05, 95% Confidence interval (CI) 1.03-1.08, P < 0.001) and abnormal AFP at baseline (HR = 1.00, 95% CI 1.00-1.00, P < 0.001) were independent risk factors for abnormal AFP in CHB patients, while shear wave elastography (HR = 1.07, 95% CI 1.02-1.12, P < 0.001) was also independent risk factor for HCC. Similar results were obtained after propensity score matching (PSM) analysis. The combination of shear wave elastography (SWE), mPage-B score, age and type 2 diabetes mellitus had an area under the curve of 0.838 (P < 0.001) in predicting the occurrence of HCC.

Similar AFP elevation and HCC development rates were observed in CHB patients treated with ETV or TDF. Elevated SWE and abnormal AFP at baseline were independent risk factors for abnormal AFP in CHB patients.

The risk of hepatocellular carcinoma (HCC) and hepatic decompensation persists after hepatitis B surface antigen (HBsAg) seroclearance. This study aimed to develop and validate a machine learning model to predict the risk of liver-related outcomes (LROs) following HBsAg seroclearance.

A total of 4,787 consecutive patients who achieved HBsAg seroclearance between 2000 and 2022 were enrolled from six centers in South Korea and a territory-wide database in Hong Kong, comprising the training (n = 944), internal validation (n = 1,102), and external validation (n = 2,741) cohorts. Three machine learning-based models were developed and compared in each cohort. The primary outcome was the development of any LRO, including HCC, decompensation, and liver-related death.

During a median follow-up of 55.2 (IQR 30.1-92.3) months, 123 LROs were confirmed (1.1%/person-year) in the Korean cohort. The model with the best predictive performance in the training cohort was selected as the final model (designated as PLAN-B-CURE), which was constructed using a gradient boosting algorithm and seven variables (age, sex, diabetes, alcohol consumption, cirrhosis, albumin, and platelet count). Compared to previous HCC prediction models, PLAN-B-CURE showed significantly superior accuracy in the training cohort (c-index: 0.82 vs. 0.63-0.70, all p <0.001; area under the receiver-operating characteristic curve: 0.86 vs. 0.62-0.72, all p <0.01; area under the precision-recall curve: 0.53 vs. 0.13-0.29, all p <0.01). PLAN-B-CURE showed a reliable calibration function (Hosmer-Lemeshow test p >0.05) and these results were reproduced in the internal and external validation cohorts.

This novel machine learning model consisting of seven variables provides reliable risk prediction of LROs after HBsAg seroclearance that can be used for personalized surveillance.

Using large-scale multinational data, we developed a machine learning model to predict the risk of liver-related outcomes (i.e., hepatocellular carcinoma, decompensation, and liver-related death) after the functional cure of chronic hepatitis B (CHB). The new model named PLAN-B-CURE was constructed using seven variables (age, sex, alcohol consumption, diabetes, cirrhosis, serum albumin, and platelet count) and a gradient boosting machine algorithm, and it demonstrated significantly better predictive accuracy than previous models in both the training and validation cohorts. The inclusion of diabetes and significant alcohol intake as model inputs suggests the importance of metabolic risk factor management after the functional cure of CHB. Using seven readily available clinical factors, PLAN-B-CURE, the first machine learning-based model for risk prediction after the functional cure of CHB, may serve as a basis for individualized risk stratification.

Hepatocellular carcinoma (HCC) risk prediction models established in patients with chronic hepatitis B receiving nucleos(t)ide analogue (NA) rarely include viral factors because of mediocre predictability of traditional viral markers. Here, we investigate the role of serum hepatitis B virus (HBV) RNA, a novel biomarker, in predicting HCC risk in NA-treated patients.

A total of 1374 NA-treated patients were enrolled from 2 prospective chronic hepatitis B cohorts. Serum HBV RNA was detected at baseline, year 1, 2 and 3 of treatment. Cox proportional-hazard model was used to investigate the association of HBV RNA kinetics with HCC risk.

After a median follow-up of 5.4 years, 76 patients developed HCC. HBV RNA declines at year 1 (adjusted hazard ratio, 0.70; P = .009) and 2 (adjusted hazard ratio, 0.71; P = .016) were independently associated with HCC risk. Patients with less HBV RNA decline at year 1 (≤0.4 log10 copies/mL) or 2 (≤0.6 log10 copies/mL) had 2.22- and 2.09-folds higher HCC risk, respectively, than those with more declines. When incorporating these early on-treatment HBV RNA declines into existing HCC risk scores, including PAGE-B (age, sex, and platelets), modified PAGE-B (mPAGE-B) (age, sex, platelets, and albumin), and aMAP (age, sex, platelets, and albumin-bilirubin score) score, they could enhance their predictive performance (ie, C-index 0.814 vs 0.78 [model (PAGE-B + year-1 HBV RNA decline) vs PAGE-B score based on baseline parameters]).

Serum HBV RNA declines at year 1 and 2 were significantly associated with on-treatment HCC risk. Incorporating early on-treatment HBV RNA declines into HCC risk prediction models can be useful tools to guide appropriate surveillance strategies in NA-treated patients.

Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide and the third leading cause of cancer-related death, with a 5-year survival rate of 10%-12%. It usually develops in the setting of chronic liver disease (CLD), with chronic viral hepatitis, alcohol, and non-alcoholic fatty liver disease (NAFLD) being the most common risk factors. Some patients are at higher risk of developing hepatocellular cancer, so it is important to screen them regularly to diagnose the disease at an early stage and improve their chances for curative treatment. Six-monthly ultrasound with or without alpha-fetoprotein (AFP) is the currently recommended surveillance method. AFP has been used as a biomarker for liver cancer; however, it has low sensitivity and specificity, which necessitates the search for other, more accurate biomarkers. Promising biomarkers include lens culinaris agglutinin-reactive AFP, des-gamma-carboxy prothrombin, methylated DNA markers, plasma microRNA expression, circulating tumor DNA, and circulating tumor cells. In addition, combinations of biomarkers, like the GALAD score and the Doylestown algorithm, may help in the early detection of HCC. In this review, we summarize the screening tests for early detection of HCC that have been studied over the last decade.

Hepatocellular carcinoma (HCC) risk prediction models may provide a more personalised approach to surveillance for HCC among patients with cirrhosis. This systematic review aims to summarise the performance of HCC prediction models in patients with non-viral chronic liver disease.

The study was prospectively registered with PROSPERO (ID: CRD42022370078) and reported in accordance with PRISMA guidelines. MEDLINE and Embase databases were searched using a validated search filter for prediction model studies. Two reviewers independently assessed studies for inclusion and risk of bias. Measures of model performance (discrimination and calibration) to assess the risk of HCC at specified time points were identified. A random effects meta-analysis was performed on a subset of studies that reported performance of the same model.

A total of 7,854 studies were identified. After review, 14 studies with a total of 94,014 participants were included; 45% of patients had viral hepatitis, 27% ALD (alcohol-related liver disease) and 19% MASLD (metabolic dysfunction-associated steatotic liver disease). Follow-up ranged from 15.1-138 months. Only one model was developed using a competing risk approach. Age (7 models) and sex (6 models) were the most frequently included predictors. Model discrimination (AUROC or c-statistic) ranged from 0.61-0.947. Only the 'aMAP' score (age, male sex, albumin, bilirubin, and platelets) had sufficient external validation for quantitative analysis, with a pooled c-statistic of 0.81 (95% CI 0.80-0.83). Calibration was reported in only 9 of 14 studies. All studies were rated at high risk of bias.

Studies describing risk prediction of HCC in non-viral chronic liver disease are poorly reported, have a high risk of bias and do not account for competing risk events. Patients with ALD and MASLD are underrepresented in development and validation cohorts. These factors remain barriers to the clinical utility and uptake of HCC risk models for those with the most common liver diseases.

The recent EASL policy statement emphasises the potential of risk-based surveillance to reduce both hepatocellular carcinoma (HCC)-related deaths and surveillance costs. This study addresses the gap in understanding the performance of current HCC risk models in patients with non-viral liver diseases, reflecting the epidemiological landscape of liver disease in Western countries. In our review of these models we identified several key concerns regarding reporting standards and risk of bias and confirmed that patients with alcohol-related liver disease and metabolic dysfunction-associated steatotic liver disease are underrepresented in model development and validation cohorts. Additionally, most models fail to account for the significant risk of competing events, leading to potential overestimation of true HCC risk. This study highlights these critical issues that may hinder the implementation of risk models in clinical practice and offers key recommendations for future model development studies.

The most common cause of hepatocellular carcinoma (HCC) worldwide is chronic hepatitis B virus (HBV) infection (CHB). Long-term suppression of HBV replication by antiviral treatment reduces the risk of HCC and mortality. Nonetheless, only 2.2% of CHB patients globally received the treatment in 2019. Current international CHB guidelines recommend antiviral treatment only in subsets of patients with clear evidence of liver damage as evidenced by elevation of alanine aminotransferase (ALT). This review aims to provide existing evidence that the risk of HCC is significantly associated with serum levels of HBV DNA, and the association is non-linear parabolic, in both untreated and treated CHB patients, regardless of HBeAg status or ALT levels. Therefore, the decision for the antiviral treatment should be based on serum HBV DNA levels and age, rather than ALT levels or liver biopsy, to reduce or prevent the risk of HCC in CHB patients. The potential impact and cost-effectiveness data on early antiviral treatment initiation were also collated.

Liver stiffness measurements (LSMs) are promising for monitoring disease progression or regression. We assessed the prognostic significance of dynamic changes in LSM over time on liver-related events (LREs) and death in patients with chronic hepatitis B (CHB) and compensated advanced chronic liver disease (cACLD).

This retrospective study included 1272 patients with CHB and cACLD who underwent at least two measurements, including LSM and fibrosis score based on four factors (FIB-4). ΔLSM was defined as [(follow-up LSM - baseline LSM)/baseline LSM × 100]. We recorded LREs and all-cause mortality during a median follow-up time of 46 months. Hazard ratios (HRs) and confidence intervals (CIs) for outcomes were calculated using Cox regression.

Baseline FIB-4, baseline LSM, ΔFIB-4, ΔLSM, and ΔLSM/year were independently and simultaneously associated with LREs (adjusted HR, 1.04, 95% CI, 1.00-1.07; 1.02, 95% CI, 1.01-1.03; 1.06, 95% CI, 1.03-1.09; 1.96, 95% CI, 1.63-2.35, 1.02, 95% CI, 1.01-1.04, respectively). The baseline LSM combined with the ΔLSM achieved the highest Harrell's C (0.751), integrated AUC (0.776), and time-dependent AUC (0.737) for LREs. Using baseline LSM and ΔLSM, we proposed a risk stratification method to improve clinical applications. The risk proposed stratification based on LSM performed well in terms of prognosis: low risk (n = 390; reference), intermediate risk (n = 446; HR = 3.38), high risk (n = 272; HR = 5.64), and extremely high risk (n = 164; HR = 11.11).

Baseline and repeated noninvasive tests measurement allow risk stratification of patients with CHB and cACLD. Combining baseline and dynamic changes in the LSM improves prognostic prediction.

To develop and evaluate a mobile health application, the Cancer Risk Calculator (CRC), aimed at improving public health literacy by providing personalized information on cancer risks and preventive measures.

The CRC was developed through a comprehensive process involving the identification of necessary content, integration of average cancer risks using data from reliable sources, creation of a novel risk model emphasizing modifiable factors, and the application's development for easy access. The application covers 38 cancer types, 18 subtypes, and approximately 790 risk factors, utilizing data from the Surveillance, Epidemiology, and End Results Program and scientific literature.

CRC offers users personalized risk assessments across a broad range of cancers, emphasizing modifiable risk factors to encourage preventive behaviors. It distinguishes itself by covering more cancer types and risk factors than existing tools, with preliminary user feedback indicating its utility in promoting health literacy and lifestyle changes.

The CRC application stands out as an innovative tool in health informatics, significantly enhancing public understanding of cancer risks. Its development underscores the potential of digital health technologies to bolster preventive healthcare strategies through improved health literacy.

The Cancer Risk Calculator is a pivotal development in mobile health technology, offering comprehensive and personalized insights into cancer risks and prevention. It serves as a valuable resource for public health education, facilitating informed decisions and lifestyle modifications for cancer prevention.

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.

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.

A single-nation study reported that pretreatment HBV viral load is associated with on-treatment risk of HCC in patients who are HBeAg-positive without cirrhosis and with chronic hepatitis B initiating antiviral treatment. We aimed to validate the association between baseline HBV viral load and on-treatment HCC risk in a larger, multinational cohort.

Using a multinational cohort from Korea, Hong Kong, and Taiwan involving 7545 adult patients with HBeAg-positive, without cirrhosis and with chronic hepatitis B who started entecavir or tenofovir treatment with baseline HBV viral load ≥5.00 log 10 IU/mL, HCC risk was estimated by baseline viral load. HBV viral load was analyzed as a categorical variable. During continuous antiviral treatment (median, 4.28 y), HCC developed in 200 patients (incidence rate, 0.61 per 100 person-years). Baseline HBV DNA level was independently associated with on-treatment HCC risk in a nonlinear pattern. HCC risk was lowest with the highest baseline viral load (≥8.00 log 10 IU/mL; incidence rate, 0.10 per 100 person-years), but increased sharply as baseline viral load decreased. The adjusted HCC risk was 8.05 times higher (95% CI, 3.34-19.35) with baseline viral load ≥6.00 and <7.00 log 10 IU/mL (incidence rate, 1.38 per 100 person-years) compared with high (≥8.00 log 10 IU/mL) baseline viral load ( p <0.001).

In a multinational cohort of adult patients with HBeAg-positive without cirrhosis and with chronic hepatitis B, baseline HBV viral load was significantly associated with HCC risk despite antiviral treatment. Patients with the highest viral load who initiated treatment had the lowest long-term risk of HCC development.

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).

Integrating conventional ultrasound features with 2D shear wave elastography (2D-SWE) can potentially enhance preoperative hepatocellular carcinoma (HCC) predictions.

To develop a 2D-SWE-based predictive model for preoperative identification of HCC.

A retrospective analysis of 884 patients who underwent liver resection and pathology evaluation from February 2021 to August 2023 was conducted at the Oriental Hepatobiliary Surgery Hospital. The patients were divided into the modeling group (n = 720) and the control group (n = 164). The study included conventional ultrasound, 2D-SWE, and preoperative laboratory tests. Multiple logistic regression was used to identify independent predictive factors for malignant liver lesions, which were then depicted as nomograms.

In the modeling group analysis, maximal elasticity (Emax) of tumors and their peripheries, platelet count, cirrhosis, and blood flow were independent risk indicators for malignancies. These factors yielded an area under the curve of 0.77 (95% confidence interval: 0.73-0.81) with 84% sensitivity and 61% specificity. The model demonstrated good calibration in both the construction and validation cohorts, as shown by the calibration graph and Hosmer-Lemeshow test (P = 0.683 and P = 0.658, respectively). Additionally, the mean elasticity (Emean) of the tumor periphery was identified as a risk factor for microvascular invasion (MVI) in malignant liver tumors (P = 0.003). Patients receiving antiviral treatment differed significantly in platelet count (P = 0.002), Emax of tumors (P = 0.033), Emean of tumors (P = 0.042), Emax at tumor periphery (P < 0.001), and Emean at tumor periphery (P = 0.003).

2D-SWE's hardness value serves as a valuable marker for enhancing the preoperative diagnosis of malignant liver lesions, correlating significantly with MVI and antiviral treatment efficacy.

The association between hepatitis B envelope antigen (HBeAg) seroclearance during long-term nucleos(t)ide analogue (NA) treatment and the risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB) remains unclear. Here, we aimed to investigate the association of HBeAg seroclearance during potent NA treatment with the development of HCC and decompensated cirrhosis.

Using a multicenter historical cohort including 2,392 non-cirrhotic adult patients with HBeAg-positive CHB who initiated NA treatment with tenofovir or entecavir, the risk of HCC and decompensated cirrhosis was compared between patients who achieved HBeAg seroclearance within 36 months of NA treatment (the HBeAg-loss group) and those who did not (the HBeAg-maintained group), using inverse probability of treatment weighting.

Over a median of 6.6 years of NA treatment, 1,077 patients achieved HBeAg seroclearance (HBeAg loss rate = 6.0 per 100 person-years), 64 patients developed HCC (HCC incidence rate = 0.39 per 100 person-years), and 46 patients developed decompensated cirrhosis (decompensation incidence rate = 0.28 per 100 person-years). The HBeAg-loss and HBeAg-maintained groups had a similar risk of developing HCC (hazard ratio 0.89; 95% CI 0.47-1.68; p = 0.72) and decompensated cirrhosis (hazard ratio 0.98; 95% CI 0.48-1.81; p = 0.91). Compared with delayed HBeAg seroclearance beyond 10 years of NA treatment, the risk of HCC was comparable in those who achieved earlier HBeAg seroclearance at any time point within 10 years, regardless of baseline age and fibrotic burden.

Early HBeAg seroclearance during NA treatment was not associated with a reduced risk of development of HCC or decompensated cirrhosis in non-cirrhotic HBeAg-positive patients with CHB.

The association between hepatitis B envelope antigen (HBeAg) seroclearance during long-term nucleos(t)ide analogue treatment and the risk of hepatocellular carcinoma in patients with chronic hepatitis B remains unclear. Our findings indicate that early on-treatment HBeAg seroclearance within 3 years was not associated with the development of hepatocellular carcinoma or decompensated cirrhosis. Achieving HBeAg seroclearance may not be an appropriate surrogate endpoint for preventing the development of liver-related outcomes in non-cirrhotic patients with HBeAg-positive chronic hepatitis B treated with nucleos(t)ide analogues.

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.

Chronic hepatitis B (CHB) constitutes a major global public health issue, affecting millions of individuals. Despite the implementation of robust vaccination programs, the hepatitis B virus (HBV) significantly influences morbidity and mortality rates. CHB emerges as one of the leading causes of hepatocellular carcinoma (HCC), introducing a major challenge in the effective management of CHB patients. Therefore, it is of utmost clinical importance to diligently monitor individuals with CHB who are at high risk of HCC development. While various prognostic scores have been developed for surveillance and screening purposes, their accuracy in predicting HCC risk may be limited, particularly in patients under treatment with nucleos(t)ide analogues. The PAGE-B model, incorporating age, gender, and platelet count, has exhibited remarkable accuracy, validity, and reliability in predicting HCC occurrence among CHB patients receiving HBV treatment. Its predictive performance stands out, whether considered independently or in comparison to alternative HCC risk scoring systems. Furthermore, the introduction of targeted adjustments to the calculation of the PAGE-B score might have the potential to further improve its predictive accuracy. This review aims to evaluate the efficacy of the PAGE-B score as a dependable tool for accurate prediction of the development of HCC in CHB patients. The evidence discussed aims to provide valuable insights for guiding recommendations on HCC surveillance within this specific population.

This study aimed to investigate whether peginterferon-α (IFN) add-on nucleos(t)ide analogs(NAs) can further reduce hepatocellular carcinoma(HCC) risk compared with NAs monotherapy in NA-treated patients with chronic hepatitis B(CHB). In this multi-center randomized controlled trial "PARADISE study" (NCT05671315), CHB patients with intermediate to high risk of HCC after more than 24-week NAs pretreatment were recruited, randomized to two groups at a ratio of 1:2 and followed up for 240 weeks. NAs group maintained NAs monotherapy, while IFN + NAs group received IFN add-on NAs therapy for 48 weeks, then switched to NAs monotherapy. Totally, 196 patients were included in interim analysis (NAs group 68, IFN + NAs group 128). The 96-week cumulative HCC incidence was lower in IFN + NAs group than NAs group (0% vs. 4.5%, p < 0.05). Compared with NAs group, IFN + NAs group had significantly higher rates of HBsAg loss at week 48 and 96 (22.7% vs. 0%; 16.7% vs. 0%, both p < 0.05). A new scoring system was established to predict HBsAg decline >2log10 IU/ml, HBsAg <10 IU/ml or HBsAg loss at the end of 48-week IFN treatment. The area under ROC curve was 0.914, 0.922 or 0.905 in the original cohort (n = 128) and 0.896, 0.896 or 0.864 in the external validation cohort (n = 162) for the aforementioned three outcomes, respectively. IFN add-on NAs therapy may suggest the dual benefits of reducing HCC development and facilitating HBsAg loss among NA-treated CHB patients with intermediate to high risk of HCC. The new scoring system helps to make the most of IFN treatment for a higher cost-effectiveness in healthcare.

A diagnosis of cirrhosis initiates a shift in the management of chronic liver disease and affects the diagnostic workflow and treatment decision of primary liver cancer. Liver biopsy remains the gold standard for cirrhosis diagnosis, but it is invasive and susceptible to sampling bias and observer variability. Various qualitative and quantitative imaging biomarkers based on ultrasound, CT and MRI have been proposed for noninvasive diagnosis of cirrhosis. Qualitative imaging features are easy to apply but have moderate diagnostic sensitivity. Elastography techniques allow quantitative assessment of liver stiffness and are highly accurate for cirrhosis diagnosis. Ultrasound elastography are widely used in clinical practice, while MR elastography has narrower availability. Although not applicable in clinical practice yet, other quantitative imaging features, including liver surface nodularity, linear and volumetric measurement, extracellular volume fraction, liver enhancement on hepatobiliary phase, and parameters derived from diffusion-weighted imaging, can provide additional information of liver morphology, perfusion, and function, thus may increase diagnosis performance. The introduction of radiomics and deep learning has further improved diagnostic accuracy while reducing subjectivity. Several imaging features may also help to assess liver function and outcomes in patients with cirrhosis. In this review, we summarize the qualitative and quantitative imaging biomarkers for noninvasive cirrhosis diagnosis, and the assessment of liver function and outcomes, and discuss the challenges and future directions in this field.

The application of antifibrotic drugs to treat patients with chronic liver diseases who are receiving antiviral therapies for hepatocellular carcinoma (HCC) has not been established. Here, we aimed to assess the impact of the Traditional Chinese Medicine Fuzheng Huayu (FZHY) on the occurrence of HCC in patients with hepatitis B virus-related compensated cirrhosis receiving the antiviral drug entecavir (ETV).

A multicenter retrospective cohort study was performed. Compensated liver cirrhosis patients were divided into the ETV+FZHY group or the ETV group according to treatment. The cumulative incidence of HCC was analyzed using Kaplan-Meier and log-rank tests. Propensity score matching was used for confounding factors. Stratified analysis and Cox regression were used to determine the effects of FZHY on the occurrence of HCC and liver function decompensation.

Out of 910 chronic hepatitis B patients, 458 were in the ETV+FZHY group and 452 were in the ETV group. After propensity score matching, the 5-year cumulative incidence of HCC was 9.8% in the ETV+FZHY group and 21.8% in the ETV group (p<0.01). The adjusted hazard ratio for HCC was 0.216 (0.108, 0.432) when FZHY treatment was >36 months. Age, diabetes, alanine aminotransferase, γ-glutamyl transpeptidase, albumin, hepatitis B e-antigen, and fibrosis 4 score were associated with the occurrence of HCC. FZHY decreased the risk of HCC in patients aged >45 years with a hepatitis B virus DNA level of ≥2,000 IU/l.

Adjunctive FZHY treatment reduced HCC occurrence in patients with hepatitis B virus cirrhosis who were treated with ETV, possibly due to the antifibrotic properties of FZHY.

Risk of hepatocellular carcinoma (HCC) persists after hepatitis B surface antigen (HBsAg) seroclearance in patients with chronic hepatitis B (CHB).

To identify risk factors and construct a predictive model for HCC development.

We retrospectively analysed patients with CHB with HBsAg seroclearance. Primary outcome was HCC development. Factors identified from a multivariate Cox model in the training cohort, consisting of 3476 patients from two Korean hospitals, were used to construct the prediction model. External validation was performed using data from 5255 patients in Hong Kong.

In the training cohort, HCC occurred in 102 patients during 24,019 person-years of observation (0.43%/year). Risk scores were assigned to cirrhosis (C:3), age ≥50 years (A:2), male sex (M:3) and platelet count <150,000/mm3 (P:1); all were independently associated with an increased risk of HCC in multivariate analysis The time-dependent area under receiver operating characteristic curves for 5, 10 and 15 years in the training and validation cohorts were 0.782, 0.817 and 0.825 and 0.785, 0.771 and 0.796, respectively. In the validation cohort, 85 patients developed HCC (0.24%/year). The corresponding incidence of HCC in the low-, intermediate- and high-risk groups were 0.07%, 0.37% and 0.90%, respectively.

The CAMP-B score (cirrhosis, age ≥50 years, male sex and platelet count <150,000/mm3/L) was significantly associated with HCC development after HBsAg seroclearance. CAMP-B score can be easily implemented in real-world clinical practice and helps stratify HCC risk in patients with CHB following HBsAg seroclearance.

Hepatitis C patients with advanced fibrosis or cirrhosis are at high risk of developing hepatocellular carcinoma (HCC), even after sustained virological response (SVR). Clinical recommendations impose a significant burden on patients by recommending lifelong screening for HCC every six months. The goals of this study were to develop a nomogram that accurately stratifies risk of HCC and improve the screening approach that is currently in use.

Risk factors for HCC were identified using univariate and multivariate analyses in this prospective study. We developed and validated a nomogram for assessing hepatocellular carcinoma risk after SVR in patients with advanced fibrosis and cirrhosis.

During the median follow-up period of 61.00 (57.00-66.00) months in the derivation cohort, 37 patients (9.61%) developed HCC. Older age (HR = 1.08, 95% CI 1.02-1.14, p = 0.009), male gender (HR = 2.38, 95% CI 1.10-5.13, p = 0.027), low serum albumin levels (HR = 0.92, 95% CI 0.86-1.00, p = 0.037), and high liver stiffness measurement (LSM) (HR = 1.03, 95% CI 1.01-1.06, p = 0.001) were found to be independent predictors of HCC development. Harrell's C-index for the derivation cohort was 0.81. The nomogram's 3-, 5- and 7-years time-dependent AUROCSs were 0.84 (95% CI 0.80-0.88), 0.83 (95% CI 0.79-0.87), and 0.81 (95% CI 0.77-0.85), respectively (all p > 0.05). According to the nomogram, patients are categorized as having low, intermediate, or high risk. The annual incidence rates of HCC in the three groups were 0.18%, 1.29%, and 4.45%, respectively (all p < 0.05).

Older age, male gender, low serum albumin levels, and high LSM were risk factors for HCC after SVR in hepatitis C patients with advanced fibrosis and cirrhosis. We used these risk factors to establish a nomogram. The nomogram can identify a suitable screening plan by classifying hepatitis C patients according to their risk of HCC.