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
Backgrounds/Aims Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model.
Methods Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort.
Results In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM).
Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.
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Endoscopic variceal ligation combined with carvedilol versus endoscopic variceal ligation combined with propranolol for the treatment of oesophageal variceal bleeding in cirrhosis: study protocol for a multicentre, randomised controlled trial Yiling Li, Li Du, Shuairan Zhang, Chuan Liu, Chao Ma, Xiaochao Liu, Huanhai Xu, Zhixu Fan, Shengjuan Hu, Jing Wang, Lichun Shao, Lijun Peng, Huiling Xiang, Xuan Liang, Wenhui Zhang, Hongyun Zhao, Pengyuan He, Jingyi Xu, Qianlong Li, Ling Yang, Yunhai Wu, BMJ Open.2025; 15(4): e093866. CrossRef
Relative change rate of liver stiffness measurements predicts the risk of liver decompensation in compensated advanced chronic liver disease Yanqiu Li, Zihang Qiao, Jinze Li, Bingbing Zhu, Yu Lu, Ying Feng, Xianbo Wang Clinical and Experimental Medicine.2025;[Epub] CrossRef
Revolutionising portal hypertension diagnosis: the rise of non-invasive techniques in liver cirrhosis Bocheng Gao, Yumeng Lin, Huimin Zhang, Yulin Li, Shuhua Gou, Peiling Ma, Xueni Zhao, Yue Zhou, Qian Chen, Lan Yuan, Zhongyu Han, Chang Yu Frontiers in Medicine.2025;[Epub] CrossRef
Editorial: Non‐selective beta‐blockers: A lifesaving shield for critically ill patients with acute decompensation of cirrhosis? Ling Yang, Chuan Liu, Jimmy Che‐To Lai, Xiaolong Qi Alimentary Pharmacology & Therapeutics.2024; 60(7): 965. CrossRef
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.
Citations
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Racing toward the future of chronic hepatitis B management: Achieving functional cure and enhancing hepatocellular carcinoma surveillance through precision medicine Yaru Shi, Rong Fan Interdisciplinary Medicine.2025;[Epub] CrossRef
La prise en charge de l'hépatite B chronique: mise à jour 2025 des lignes directrices de l'Association canadienne pour l'étude du foie et de l'Association pour la microbiologie médicale et l'infectiologie Canada Carla Osiowy, Fernando Alvarez, Carla S. Coffin, Curtis L. Cooper, Scott K. Fung, Hin Hin Ko, Sébastien Poulin, Jennifer van Gennip Canadian Liver Journal.2025; 8(2): 402. CrossRef
The management of chronic hepatitis B: 2025 Guidelines update from the Canadian Association for the Study of the Liver and Association of Medical Microbiology and Infectious Disease Canada Carla Osiowy, Fernando Alvarez, Carla S Coffin, Curtis L Cooper, Scott K Fung, Hin Hin Ko, Sébastien Poulin, Jennifer van Gennip Canadian Liver Journal.2025; 8(2): 368. CrossRef
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
LEAST as a novel prediction model of hepatocellular carcinoma development in patients with chronic hepatitis B: a multi-center study Jingjing Song, Jie Li, Zhigang Ren, Wen Xie, Jinhua Shao, Xiaoxiao Zhang, Yang Zhou, Fajuan Rui, Xiaoqing Wu, Qiuling Wang, Zuxiong Huang, Chao Sun, Yuemin Nan BMC Medicine.2025;[Epub] CrossRef
Validation of the Texas Hepatocellular Carcinoma Risk Index Predictive Model for Hepatocellular Carcinoma in Asian Cohort Jeong-Ju Yoo, Young-Gi Song, Ji Eun Moon, Young Seok Kim, Sang Gyune Kim Clinical Gastroenterology and Hepatology.2024; 22(9): 1953. CrossRef
Risk predictive model for the development of hepatocellular carcinoma before initiating long‐term antiviral therapy in patients with chronic hepatitis B virus infection Junjie Chen, Tienan Feng, Qi Xu, Xiaoqi Yu, Yue Han, Demin Yu, Qiming Gong, Yuan Xue, Xinxin Zhang Journal of Medical Virology.2024;[Epub] CrossRef
Correspondence to editorial on “Hepatocellular carcinoma prediction model performance decreases with long-term antiviral therapy in chronic hepatitis B patients” Xiaoqian Xu, Hong You, Jidong Jia, Yuanyuan Kong Clinical and Molecular Hepatology.2024; 30(4): 994. CrossRef
Decreasing performance of HCC prediction models during antiviral therapy for hepatitis B: what else to keep in mind: Editorial on “Hepatocellular carcinoma prediction model performance decreases with long-term antiviral therapy in chronic hepatitis B pati Beom Kyung Kim Clinical and Molecular Hepatology.2024; 30(4): 656. 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
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