Impact of nationwide hepatocellular carcinoma surveillance on the prognosis in patients with chronic liver disease

Changes in the ultrasound presentation of hepatocellular carcinoma: a center's three decades of experience

PURPOSE

Ultrasound (US) surveillance is a cornerstone for early diagnosis of HCC, anyway US presentation has undergone significant changes. With the aim of evaluating the effects of US surveillance program in the real-world clinical practice, we wanted to evaluate US presentation of HCCs over the last 30 years and the differences of HCCs presentation according to etiology.

METHODS

174 patients diagnosed between 1993 and 98 (G1), 96 between 2003 and 08 (G2), 102 between 2013 and 18 (G3), were compared. US patterns were: single, multiple or diffuse nodules. The echo-patterns: iso-, hypo-, hyper-echoic, or mixed. In G1, the HCC diagnosis was mainly histologic; in G2 by EASL 2001 and AASLD 2005, in G3 AASLD 2011, EASL 2012, and AISF 2013 guidelines.

RESULTS

HCV was the most frequent etiology, dropping between G1 (81%) and G3 (66%) (P < 0.01), metabolic increased between G1 (5%) and G3 (14%) (P < 0.01). Single HCC was more prevalent in G3 vs G1 (65.6% vs 40%) (P < 0.0001), multiple nodules in G1 (50%) vs G3 (33.3%) (P < 0.02) and diffuse in G1 (16%) vs G2 (2%) and vs G3 (1%) (P < 0.001). The most frequent echo-pattern was hypo-echoic G1 (50%) vs G2 (79%) and G1 vs G3 (65%) (P < 0.01). Iso-echoic pattern was the least frequent (7-12%). Mixed pattern decreased from G1 (28%) to G3 (12%) (P < 0.002). In G3 there were more multiple or diffuse HCCs in metabolic (P < 0.03).

CONCLUSION

US presentation became less severe due to surveillance programs. HCV remains the most frequent cause, an increase in metabolic etiology has been shown throughout the decades.

PAGE-B incorporating moderate HBV DNA levels predicts risk of HCC among patients entering into HBeAg-positive chronic hepatitis B

BACKGROUND & AIMS

Recent studies reported that moderate HBV DNA levels are significantly associated with hepatocellular carcinoma (HCC) risk in hepatitis B e antigen (HBeAg)-positive, non-cirrhotic patients with chronic hepatitis B (CHB). We aimed to develop and validate a new risk score to predict HCC development using baseline moderate HBV DNA levels in patients entering into HBeAg-positive CHB from chronic infection.

METHODS

This multicenter cohort study recruited 3,585 HBeAg-positive, non-cirrhotic patients who started antiviral treatment with entecavir or tenofovir disoproxil fumarate at phase change into CHB from chronic infection in 23 tertiary university-affiliated hospitals of South Korea (2012-2020). A new HCC risk score (PAGED-B) was developed (training cohort, n = 2,367) based on multivariable Cox models. Internal validation using bootstrap sampling and external validation (validation cohort, n = 1,218) were performed.

RESULTS

Sixty (1.7%) patients developed HCC (median follow-up, 5.4 years). In the training cohort, age, gender, platelets, diabetes and moderate HBV DNA levels (5.00-7.99 log10 IU/ml) were independently associated with HCC development; the PAGED-B score (based on these five predictors) showed a time-dependent AUROC of 0.81 for the prediction of HCC development at 5 years. In the validation cohort, the AUROC of PAGED-B was 0.85, significantly higher than for other risk scores (PAGE-B, mPAGE-B, CAMD, and REAL-B). When stratified by the PAGED-B score, the HCC risk was significantly higher in high-risk patients than in low-risk patients (sub-distribution hazard ratio = 8.43 in the training and 11.59 in the validation cohorts, all p <0.001).

CONCLUSIONS

The newly established PAGED-B score may enable risk stratification for HCC at the time of transition into HBeAg-positive CHB.

IMPACT AND IMPLICATIONS

In this study, we developed and validated a new risk score to predict hepatocellular carcinoma (HCC) development in patients entering into hepatitis B e antigen (HBeAg)-positive chronic hepatitis B (CHB) from chronic infection. The newly established PAGED-B score, which included baseline moderate HBV DNA levels (5-8 log10 IU/ml), improved on the predictive performance of prior risk scores. Based on a patient's age, gender, diabetic status, platelet count, and moderate DNA levels (5-8 log10 IU/ml) at the phase change into CHB from chronic infection, the PAGED-B score represents a reliable and easily available risk score to predict HCC development during the first 5 years of antiviral treatment in HBeAg-positive patients entering into CHB. With a scoring range from 0 to 12 points, the PAGED-B score significantly differentiated the 5-year HCC risk: low <7 points and high ≥7 points.

Prediction model of hepatitis B virus-related hepatocellular carcinoma in patients receiving antiviral therapy

Chronic hepatitis B virus (HBV) infection, which ultimately leads to liver cirrhosis, hepatic decompensation, and hepatocellular carcinoma (HCC), remains a significant disease burden worldwide. Despite the use of antiviral therapy (AVT) using oral nucleos(t)ide analogs (NUCs) with high genetic barriers, the risk of HCC development cannot be completely eliminated. Therefore, bi-annual surveillance of HCC using abdominal ultrasonography with or without tumor markers is recommended for at-risk populations. For a more precise assessment of future HCC risk at the individual level, many HCC prediction models have been proposed in the era of potent AVT with promising results. It allows prognostication according to the risk of HCC development, for example, low-vs. intermediate-vs. high-risk groups. Most of these models have the advantage of high negative predictive values for HCC development, allowing exemption from biannual HCC screening. Recently, non-invasive surrogate markers for liver fibrosis, such as vibration-controlled transient elastography, have been introduced as integral components of the equations, providing better predictive performance in general. Furthermore, beyond the conventional statistical methods that primarily depend on multi-variable Cox regression analyses based on the previous literature, newer techniques using artificial intelligence have also been applied in the design of HCC prediction models. Here, we aimed to review the HCC risk prediction models that were developed in the era of potent AVT and validated among independent cohorts to address the clinical unmet needs, as well as comment on future direction to establish the individual HCC risk more precisely.

Risk factors associated with late hepatocellular carcinoma detection in patients undergoing regular surveillance

Hepatocellular carcinoma (HCC) has a very poor prognosis with a 5-year survival rate of < 20%; hence, early diagnosis is crucial. Despite regular checkups for high-risk groups of HCC, there are a few cases in which it is discovered as a late-stage HCC. Therefore, this study aimed to investigate the characteristics of patients with delayed HCC detection during regular surveillance. Between January 2010 and December 2020, we analyzed patients with newly diagnosed HCCs who underwent HCC surveillance by ultrasound or computed tomography scan at least twice and were followed up for more than 1 year for hepatitis B, hepatitis C, and chronic liver disease. The mean age of 223 HCC patients was 70 years, of which 152 were male, accounting for 68.1%. Among them, 196 patients (87%) were diagnosed with Barcelona clinic liver cancer stage 0 or A, while 27 (13%) were diagnosed with Barcelona clinic liver cancer stages B and C. When classified according to the TNM criteria, 154 patients (69%) were in stage I, and 69 (31%) were in stage II or higher. Multivariate analysis was performed to identify the risk factors for patients diagnosed with late-stage HCC. The Child-Turcotte-Pugh (CTP) score was identified as a highly significant factor (P = .002, HR 1.547, 95% CI 1.177-2.032), whereas the presence of cirrhosis, body mass index, and sex had no significant effect. We found that in patients with chronic liver disease who were screened regularly, those with higher CTP scores were more likely to be diagnosed with HCC in the late-stages. Therefore, although the presence of cirrhosis is also important for HCC surveillance, careful attention is needed in patients with high CTP scores.

Compared with CT/MRI LI-RADS, whether CEUS LI-RADS is worth popularizing in diagnosis of hepatocellular carcinoma?-a direct head-to-head meta-analysis

Background

Until now, there has been no systematic review or meta-analysis of direct head-to-head studies that compare two liver imaging reporting and data system (LI-RADS) algorithms, contrast-enhanced ultrasound (CEUS) LI-RADS and contrast-enhanced computed tomography/magnetic resonance imaging (CT/MRI) LI-RADS, for the diagnostic efficacy of hepatocellular carcinoma. The purpose of this study was to identify and head-to-head compare the diagnostic performance of both LI-RADS algorithms for hepatocellular carcinoma.

Methods

We searched the PubMed, EMBASE, Web of Science, and Cochrane Library databases from the inception of each database to April 26, 2022, to find the comparative study of both LI-RADS algorithms for hepatocellular carcinoma at risk of patients who underwent both LI-RADS algorithms. Eligibility criteria included only studies published in English, full reports published, both retrospective and prospective studies. Liver histology or imaging follow-up results served as the reference standard. We analyzed the sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and summary receiver operating characteristic curve to determine summary estimates. The Quality Assessment of Diagnostic Accuracy Studies was utilized to assess the methodological quality.

Results

In 5 included studies (831 patients, 877 lesions), the pooled sensitivity and pooled specificity of CEUS LR-5 were 0.79, 0.81, and 0.78, 0.79 in CT/MRI LR-5, respectively. The pooled sensitivity and pooled specificity of CEUS LR-4/5 were 0.86, 0.70, and 0.93, 0.59 in CT/MRI LR-4/5, respectively. There was no obvious difference between the two LI-RADS algorithms for hepatocellular carcinoma, and there was no significant statistical difference between two LR-M algorithms for non-hepatocellular carcinoma malignancies.

Conclusions

The results of our analysis demonstrated that CEUS LI-RADS has satisfactory diagnostic performance similar to that of CT/MRI LI-RADS, which provides a theoretical basis for the popularization of CEUS LI-RADS for diagnosing HCC. This work was supported by Sichuan Science and Technology Program (No. 2020YFS0211). We registered this study on the international prospective register of systematic reviews (PROSPERO, CRD42022328107) before the search step.

A machine learning model for predicting hepatocellular carcinoma risk in patients with chronic hepatitis B

BACKGROUND

Machine learning (ML) algorithms can be used to overcome the prognostic performance limitations of conventional hepatocellular carcinoma (HCC) risk models. We established and validated an ML-based HCC predictive model optimized for patients with chronic hepatitis B (CHB) infections receiving antiviral therapy (AVT).

METHODS

Treatment-naïve CHB patients who were started entecavir (ETV) or tenofovir disoproxil fumarate (TDF) were enrolled. We used a training cohort (n = 960) to develop a novel ML model that predicted HCC development within 5 years and validated the model using an independent external cohort (n = 1937). ML algorithms consider all potential interactions and do not use predefined hypotheses.

RESULTS

The mean age of the patients in the training cohort was 48 years, and most patients (68.9%) were men. During the median 59.3 (interquartile range 45.8-72.3) months of follow-up, 69 (7.2%) patients developed HCC. Our ML-based HCC risk prediction model had an area under the receiver-operating characteristic curve (AUC) of 0.900, which was better than the AUCs of CAMD (0.778) and REAL B (0.772) (both p < .05). The better performance of our model was maintained (AUC = 0.872 vs. 0.788 for CAMD and 0.801 for REAL B) in the validation cohort. Using cut-off probabilities of 0.3 and 0.5, the cumulative incidence of HCC development differed significantly among the three risk groups (p < .001).

CONCLUSIONS

Our new ML model performed better than models in terms of predicting the risk of HCC development in CHB patients receiving AVT.

A new model predicts hepatocellular carcinoma in patients with HBV-related decompensated liver cirrhosis and long-term antiviral therapy: a prospective study

Background

We aimed to evaluate the prediction values of non-invasive models for hepatocellular carcinoma (HCC) development in patients with HBV-related liver cirrhosis (LC) and long-term NA treatment.

Methods

Patients with compensated or decompensated cirrhosis (DC), who achieved long-term virological response, were enrolled. DC and its stages were defined by the complications including ascites, encephalopathy, variceal bleeding, or renal failure. Prediction accuracy of several risk scores, including ALBI, CAMD, PAGE-B, mPAGE-B and aMAP, was compared.

Results

The median follow-up duration was 37 (28-66) months. Among the 229 patients, 9 (9.57%) patients in the compensated LC group and 39 (28.89%) patients in the DC group developed HCC. The incidence of HCC was higher in the DC group ( X ² = 12.478, P < 0.01). The AUROC of ALBI, aMAP, CAMD, PAGE-B and mPAGE-B scores were 0.512, 0.667, 0.638, 0.663, 0.679, respectively. There was no significant difference in AUROC between CAMD, aMAP, PAGE-B and mPAGE-B (all P > 0.05). Univariable analysis showed that age, DC status and platelet were associated with HCC development, and multivariable analysis showed that age and DC status (both P < 0.01) were independent risk factors for HCC development, then Model (Age_DC) was developed and its AUROC was 0.718. Another model, Model (Age_DC_PLT_TBil) consisting of age, DC stage, PLT, TBil was also developed, and its AUROC was larger than that of Model (Age_DC) (0.760 vs. 0.718). Moreover, AUROC of Model (Age_DC_PLT_TBil) was larger than the other five models (all P < 0.05). With an optimal cut-off value of 0.236, Model (Age_DC_PLT_TBil) achieved 70.83% sensitivity, 76.24% specificity.

Conclusion

There is a lack of non-invasive risk scores for HCC development in HBV-related DC, and a new model consisting of age, DC stage, PLT, TBil may be an alternative.

Suboptimal Performance of Hepatocellular Carcinoma Prediction Models in Patients with Hepatitis B Virus-Related Cirrhosis

This study aimed to evaluate the predictive performance of pre-existing well-validated hepatocellular carcinoma (HCC) prediction models, established in patients with HBV-related cirrhosis who started potent antiviral therapy (AVT). We retrospectively reviewed the cases of 1339 treatment-naïve patients with HBV-related cirrhosis who started AVT (median period, 56.8 months). The scores of the pre-existing HCC risk prediction models were calculated at the time of AVT initiation. HCC developed in 211 patients (15.1%), and the cumulative probability of HCC development at 5 years was 14.6%. Multivariate Cox regression analysis revealed that older age (adjusted hazard ratio [aHR], 1.023), lower platelet count (aHR, 0.997), lower serum albumin level (aHR, 0.578), and greater LS value (aHR, 1.012) were associated with HCC development. Harrell’s c-indices of the PAGE-B, modified PAGE-B, modified REACH-B, CAMD, aMAP, HCC-RESCUE, AASL-HCC, Toronto HCC Risk Index, PLAN-B, APA-B, CAGE-B, and SAGE-B models were suboptimal in patients with HBV-related cirrhosis, ranging from 0.565 to 0.667. Nevertheless, almost all patients were well stratified into low-, intermediate-, or high-risk groups according to each model (all log-rank p < 0.05), except for HCC-RESCUE (p = 0.080). Since all low-risk patients had cirrhosis at baseline, they had unneglectable cumulative incidence of HCC development (5-year incidence, 4.9−7.5%). Pre-existing risk prediction models for patients with chronic hepatitis B showed suboptimal predictive performances for the assessment of HCC development in patients with HBV-related cirrhosis.