Prediction Model for Familial Aggregated HBV‐Associated Hepatocellular Carcinoma Based on Serum Biomarkers Linmei Zhong, Guole Nie, Qiaoping Wu, Honglong Zhang, Haiping Wang, Jun Yan Cancer Reports.2025;[Epub] CrossRef
Reply to correspondence on “Hepatocellular carcinoma prediction model performance decreases with long-term antiviral therapy in chronic hepatitis B patients” Beom Kyung Kim Clinical and Molecular Hepatology.2024; 30(4): 1044. CrossRef
Hepatitis B virus (HBV) infection was highly endemic in China, where the prevalence of HBsAg was 9.7% in 1992. Comprehensive strategies, including universal infant hepatitis B vaccination with emphasis on timely birth-dose and 3-dose coverage, dramatically reduced the mother-to-infant transmission and early childhood acquisition of HBV, resulting in estimated HBsAg prevalence rates of 5.6% and 0.1% in the general population and among children aged <5 years in 2022, respectively. Clinical guidelines on the prevention and treatment of chronic hepatitis B have been periodically updated based on emerging evidence from clinical research. The continuously improved reimbursement policy and the massively reduced price of antiviral drugs through government negotiation and central procurement have increased treatment accessibility and affordability. However, due to the low rates of diagnosis and treatment, China still faces a large challenge in achieving the 2030 goal of lowering HBV-related mortality by 65%. A public health approach involving concerted efforts from the government, medical community, industry, and society as a whole would be necessary to increase the uptake of HBV tests and treatment to achieve the global goal of eliminating viral hepatitis as a public health threat by 2030.
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Background/Aims Existing hepatocellular carcinoma (HCC) prediction models are derived mainly from pretreatment or early on-treatment parameters. We reassessed the dynamic changes in the performance of 17 HCC models in patients with chronic hepatitis B (CHB) during long-term antiviral therapy (AVT).
Methods Among 987 CHB patients administered long-term entecavir therapy, 660 patients had 8 years of follow-up data. Model scores were calculated using on-treatment values at 2.5, 3, 3.5, 4, 4.5, and 5 years of AVT to predict threeyear HCC occurrence. Model performance was assessed with the area under the receiver operating curve (AUROC). The original model cutoffs to distinguish different levels of HCC risk were evaluated by the log-rank test.
Results The AUROCs of the 17 HCC models varied from 0.51 to 0.78 when using on-treatment scores from years 2.5 to 5. Models with a cirrhosis variable showed numerically higher AUROCs (pooled at 0.65–0.73 for treated, untreated, or mixed treatment models) than models without (treated or mixed models: 0.61–0.68; untreated models: 0.51–0.59). Stratification into low, intermediate, and high-risk levels using the original cutoff values could no longer reflect the true HCC incidence using scores after 3.5 years of AVT for models without cirrhosis and after 4 years of AVT for models with cirrhosis.
Conclusions The performance of existing HCC prediction models, especially models without the cirrhosis variable, decreased in CHB patients on long-term AVT. The optimization of existing models or the development of novel models for better HCC prediction during long-term AVT is warranted.
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