丙型肝炎相关肝硬化的危险因素及预测模型研究进展
Research Progress on Risk Factors and Prediction Models of Hepatitis C-Related Liver Cirrhosis
摘要: 丙型肝炎病毒(HCV)感染是导致肝硬化的主要病因之一，肝硬化的发生不仅加重患者病情，还显著影响其预后及治疗选择。尽管近年来抗病毒治疗取得了较大进展，但其发生率仍然较高，并且发生机制较为复杂，受病毒学特征、宿主遗传及免疫反应、生活方式及环境等因素的影响。因此，应进一步加强对丙型肝炎相关肝硬化高危人群的判定和鉴别。本文通过系统综述丙型肝炎相关肝硬化的主要危险因素和作用机制，同时结合各类预测模型的构建方法及其临床应用现状，旨在为临床识别丙型肝炎相关肝硬化高风险人群提供依据。
Abstract: Hepatitis C virus (HCV) infection is one of the main causes of liver cirrhosis. The occurrence of liver cirrhosis not only aggravates the patient’s condition but also significantly affects their prognosis and treatment options. Although significant progress has been made in antiviral treatment in recent years, its incidence remains high, and the underlying mechanism is rather complex, being influenced by factors such as viral characteristics, host genetics and immune response, lifestyle, and environment. Therefore, it is necessary to further strengthen the identification and differentiation of high-risk groups for hepatitis C-related liver cirrhosis. This article conducts a systematic review of the main risk factors and mechanism of hepatitis C-related liver cirrhosis, and at the same time, combines the construction methods of various predictive models and their current clinical application status, aiming to provide a basis for clinical identification of high-risk populations for hepatitis C-related liver cirrhosis.
文章引用：谭泽鸿, 秦波. 丙型肝炎相关肝硬化的危险因素及预测模型研究进展[J]. 临床医学进展, 2026, 16(1): 2024-2029. https://doi.org/10.12677/acm.2026.161255

参考文献

[1] 中华医学会肝病学分会, 中华医学会感染病学分会. 丙型肝炎防治指南(2022年版) [J]. 中华传染病杂志, 2023, 41(1): 29-46.
[2] Hsu, W., Tsai, P., Chen, C., Tseng, K., Lai, H., Kuo, H., et al. (2021) Hepatitis C Virus Eradication Decreases the Risks of Liver Cirrhosis and Cirrhosis‐Related Complications (Taiwanese Chronic Hepatitis C Cohort). Journal of Gastroenterology and Hepatology, 36, 2884-2892. [Google Scholar] [CrossRef] [PubMed]
[3] Singh, V., Goyal, S., Gupta, T. and Aggarwal, H.K. (2020) Prediction of Cirrhosis in Patients with Chronic Hepatitis C by Genotype 3. Euroasian Journal of Hepato-Gastroenterology, 10, 7-10. [Google Scholar] [CrossRef] [PubMed]
[4] Westin, J., Nordlinder, H., Lagging, M., Norkrans, G. and Wejstål, R. (2002) Steatosis Accelerates Fibrosis Development over Time in Hepatitis C Virus Genotype 3 Infected Patients. Journal of Hepatology, 37, 837-842. [Google Scholar] [CrossRef] [PubMed]
[5] Galli, A. and Bukh, J. (2023) Mechanisms and Consequences of Genetic Variation in Hepatitis C Virus (HCV). In: Domingo, E., et al., Eds., Viral Fitness and Evolution, Springer International Publishing, 237-264. [Google Scholar] [CrossRef] [PubMed]
[6] Senkerikova, R., Frankova, S., Jirsa, M., Kreidlova, M., Merta, D., Neroldova, M., et al. (2019) PNPLA3 Rs738409 G Allele Carriers with Genotype 1b HCV Cirrhosis Have Lower Viral Load but Develop Liver Failure at Younger Age. PLOS ONE, 14, e0222609. [Google Scholar] [CrossRef] [PubMed]
[7] de Bitencorte, J.T., Rech, T.F., Lunge, V.R., dos Santos, D.C., Álvares-da-Silva, M.R. and Simon, D. (2021) Association of Interferon Lambda-4 Rs12979860 Polymorphism with Hepatocellular Carcinoma in Patients with Chronic Hepatitis C Infection. World Journal of Hepatology, 13, 109-119. [Google Scholar] [CrossRef] [PubMed]
[8] Zhang, N., Yao, H., Zhang, Z., Li, Z., Chen, X., Zhao, Y., et al. (2023) Ongoing Involvers and Promising Therapeutic Targets of Hepatic Fibrosis: The Hepatic Immune Microenvironment. Frontiers in Immunology, 14, Article ID: 1131588. [Google Scholar] [CrossRef] [PubMed]
[9] Martínez-Esparza, M., et al. (2015) Inflammatory Status in Human Hepatic Cirrhosis. World Journal of Gastroenterology, 21, 11522-11541. [Google Scholar] [CrossRef] [PubMed]
[10] Gonzalez-Aldaco, K., Torres-Reyes, L.A., Ojeda-Granados, C., Leal-Mercado, L., Roman, S. and Panduro, A. (2024) Metabolic Dysfunction-Associated Steatotic Liver Disease in Chronic Hepatitis C Virus Infection: From Basics to Clinical and Nutritional Management. Clinics and Practice, 14, 2542-2558. [Google Scholar] [CrossRef] [PubMed]
[11] Fernandez, C.J., Alkhalifah, M., Afsar, H. and Pappachan, J.M. (2024) Metabolic Dysfunction-Associated Fatty Liver Disease and Chronic Viral Hepatitis: The Interlink. Pathogens, 13, Article No. 68. [Google Scholar] [CrossRef] [PubMed]
[12] Kondili, L.A., Taliani, G., Cerga, G., Tosti, M.E., Babameto, A. and Resuli, B. (2005) Correlation of Alcohol Consumption with Liver Histological Features in Non-Cirrhotic Patients. European Journal of Gastroenterology & Hepatology, 17, 155-159. [Google Scholar] [CrossRef] [PubMed]
[13] Liu, T., Zhang, F., Feng, Y., Han, P. and Gao, Y. (2025) Alcohol-Metabolizing Enzymes, Liver Diseases and Cancer. Seminars in Liver Disease, 45, 99-113. [Google Scholar] [CrossRef] [PubMed]
[14] Osna, N.A., Thomes, P.G. and Donohue, T.M. (2011) Involvement of Autophagy in Alcoholic Liver Injury and Hepatitis C Pathogenesis. World Journal of Gastroenterology, 17, 2507-2514. [Google Scholar] [CrossRef] [PubMed]
[15] El-Zayadi, A.R. (2006) Heavy Smoking and Liver. World Journal of Gastroenterology, 12, 6098-6101. [Google Scholar] [CrossRef] [PubMed]
[16] Liu, Y., Dai, M., Bi, Y., Xu, M., Xu, Y., Li, M., et al. (2013) Active Smoking, Passive Smoking, and Risk of Nonalcoholic Fatty Liver Disease (NAFLD): A Population-Based Study in China. Journal of Epidemiology, 23, 115-121. [Google Scholar] [CrossRef] [PubMed]
[17] Ferreira, L.G., Anastácio, L.R., Lima, A.S. and Touslon Davisson Correia, M.I. (2013) Predictors of Mortality in Patients on the Waiting List for Liver Transplantation. Nutrición Hospitalaria, 28, 914-919.
[18] Goldberg, D., Ross-Driscoll, K. and Lynch, R. (2021) County Differences in Liver Mortality in the United States: Impact of Sociodemographics, Disease Risk Factors, and Access to Care. Gastroenterology, 160, 1140-1150.e1. [Google Scholar] [CrossRef] [PubMed]
[19] Åberg, F., Danford, C.J., Thiele, M., Talbäck, M., Rasmussen, D.N., Jiang, Z.G., et al. (2021) A Dynamic Aspartate‐to‐alanine Aminotransferase Ratio Provides Valid Predictions of Incident Severe Liver Disease. Hepatology Communications, 5, 1021-1035. [Google Scholar] [CrossRef] [PubMed]
[20] Ismaiel, A., Katell, E., Leucuta, D., Popa, S., Catana, C.S., Dumitrascu, D.L., et al. (2025) The Impact of Non-Invasive Scores and Hemogram-Derived Ratios in Differentiating Chronic Liver Disease from Cirrhosis. Journal of Clinical Medicine, 14, Article No. 3072. [Google Scholar] [CrossRef] [PubMed]
[21] Hsu, C., Parikh, N.D., Huo, T. and Tapper, E.B. (2021) Comparison of Seven Noninvasive Models for Predicting Decompensation and Hospitalization in Patients with Cirrhosis. Digestive Diseases and Sciences, 66, 4508-4517. [Google Scholar] [CrossRef] [PubMed]
[22] Cai, H., Zhang, J., Chen, C., Shen, J., Zhang, X., Peng, W., et al. (2025) Prognostic Assessment of Early-Stage Liver Cirrhosis Induced by HCV Using an Integrated Model of CX3CR1-Associated Immune Infiltration Genes. Scientific Reports, 15, Article No. 1771. [Google Scholar] [CrossRef] [PubMed]
[23] Abdel-Azeez, H.A., Elhady, H.A. and Fikry, A.A. (2022) Cartilage Oligomeric Matrix Protein as a Non-Invasive Biomarker for Diagnosis of Hepatocellular Carcinoma in Patients with Liver Cirrhosis. Gastroenterology and Hepatology from Bed to Bench, 15, 139-145.
[24] Aierken, A., Azhati, Y., Wu, J., Zhang, Y., Mamuti, A., Maimaiti, M., et al. (2025) The Insight to History and Trends of Transient Elastography for Assessing Liver Fibrosis—A Bibliometric Analysis. Quantitative Imaging in Medicine and Surgery, 15, 2971-2986. [Google Scholar] [CrossRef] [PubMed]
[25] Bi, J., Liu, L. and Qin, T. (2021) Comparison of Magnetic Resonance Elastography and Transient Elastography in the Diagnosis of Hepatic Fibrosis: A Systematic Review and Meta-Analysis. Annals of Palliative Medicine, 10, 8692-8700. [Google Scholar] [CrossRef] [PubMed]
[26] Su, P.Y., Shih, H.J. and Xu, J.L. (2025) Rapid Liver Fibrosis Evaluation Using the UNet-ResNet50-32 × 4d Model in Magnetic Resonance Elastography: Retrospective Study. JMIR Medical Informatics, 13, e80351. [Google Scholar] [CrossRef] 
[27] Liu, C., Sun, Y., Yang, Y., Feng, Y., Xie, X., Qi, L., et al. (2021) Gadobenate Dimeglumine-Enhanced Biliary Imaging from the Hepatobiliary Phase Can Predict Progression in Patients with Liver Cirrhosis. European Radiology, 31, 5840-5850. [Google Scholar] [CrossRef] [PubMed]
[28] Zhang, K., Qi, M., Jian, J., Li, Z., Wang, H., Liu, Y., et al. (2025) A Study of [18f]fluoro-L-Dopa PET/Computed Tomography Imaging to Evaluate the Extent of Liver Fibrosis. Nuclear Medicine Communications, 46, 884-894. [Google Scholar] [CrossRef] [PubMed]
[29] Li, H., Dai, R., Huang, Y., Zhong, J., Yan, Q., Yang, J., et al. (2024) [18F]AlF-ND-bisFAPI PET Imaging of Fibroblast Activation Protein as a Biomarker to Monitor the Progression of Liver Fibrosis. Hepatology Communications, 8, e0407. [Google Scholar] [CrossRef] [PubMed]
[30] Ioannou, G.N., Tang, W., Beste, L.A., Tincopa, M.A., Su, G.L., Van, T., et al. (2020) Assessment of a Deep Learning Model to Predict Hepatocellular Carcinoma in Patients with Hepatitis C Cirrhosis. JAMA Network Open, 3, e2015626. [Google Scholar] [CrossRef] [PubMed]
[31] Beste, L.A., Zhang, X., Su, G.L., Van, T., Ioannou, G.N., Oselio, B., et al. (2021) Adapted Time-Varying Covariates Cox Model for Predicting Future Cirrhosis Development Performs Well in a Large Hepatitis C Cohort. BMC Medical Informatics and Decision Making, 21, Article No. 347. [Google Scholar] [CrossRef] [PubMed]
[32] Ahn, J.C., Rattan, P., Starlinger, P., Juanola, A., Moreta, M.J., Colmenero, J., et al. (2025) AI-Cirrhosis-ECG (ACE) Score for Predicting Decompensation and Liver Outcomes. JHEP Reports, 7, Article ID: 101356. [Google Scholar] [CrossRef] [PubMed]

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