Risk predictive model for the development of hepatocellular carcinoma before initiating long-term antiviral therapy in patients with chronic hepatitis B virus infection
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引用次数: 0
Abstract
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.
期刊介绍:
The Journal of Medical Virology focuses on publishing original scientific papers on both basic and applied research related to viruses that affect humans. The journal publishes reports covering a wide range of topics, including the characterization, diagnosis, epidemiology, immunology, and pathogenesis of human virus infections. It also includes studies on virus morphology, genetics, replication, and interactions with host cells.
The intended readership of the journal includes virologists, microbiologists, immunologists, infectious disease specialists, diagnostic laboratory technologists, epidemiologists, hematologists, and cell biologists.
The Journal of Medical Virology is indexed and abstracted in various databases, including Abstracts in Anthropology (Sage), CABI, AgBiotech News & Information, National Agricultural Library, Biological Abstracts, Embase, Global Health, Web of Science, Veterinary Bulletin, and others.