Department of Internal Medicine, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA.
Therap Adv Gastroenterol. 2009 Sep;2(5):287-302. doi: 10.1177/1756283X09339079.
Hepatitis C virus (HCV) is a major cause of chronic liver disease infecting more than 170 million people worldwide. HCV produces a wide gamut of manifestations varying from mild self-limiting disease to cirrhosis and hepatocellular carcinoma. A variety of viral, environmental and host genetic factors contribute to the clinical spectrum of patients infected with HCV and influence response to interferon (IFN) therapy. Predicting the probable outcome of treatment in patients with HCV infection has always been a challenging task. Treatment of HCV by pegylated interferon (peg-IFN) plus ribavirin eradicates the virus in approximately 60% of patients - HCV genotype 1 (42-51% response rates) and genotypes 2 and 3 (76-84% response rates); however, a significant number of patients do not respond to therapy or relapse following discontinuation of treatment or have significant side effects that preclude further treatment. Accurately predicting the patients who will respond to therapy is becoming increasingly important, both from the point of patient care and also with respect to the healthcare cost as clinicians need to continue treatment in patients who will respond and stop treatment in patients who are unlikely to respond. Viral RNA measurements and genotyping are used to optimize treatment as a low viral load and nongenotype 1 is more likely to be associated with sustained virological response (SVR). Rapid virological response (RVR) defined by undetectable HCV RNA at 4 weeks of treatment is increasingly being recognized as a powerful tool for predicting treatment response. A variety of host factors including single nuclear polymorphisms (SNPs) of IFN response genes, insulin resistance, obesity, ethnicity, human leukocyte antigens and difference in T-cell immune response has been found to modulate the response to antiviral treatment. The presence of severe fibrosis/cirrhosis on pretreatment liver biopsy predicts a poor response to treatment. Recent studies on gene expression profiling and characterization of the liver and serum proteome provide options to accurately predict the outcome of patients infected with HCV in the future. Future studies on the factors that predict treatment response and tailoring treatment based on this is required if we are to conquer this disease.
丙型肝炎病毒（HCV）是一种主要的慢性肝病病原体，全球有超过 1.7 亿人感染。HCV 可引起广泛的临床表现，从轻症自限性疾病到肝硬化和肝细胞癌不等。多种病毒、环境和宿主遗传因素导致感染 HCV 的患者临床表现多样化，并影响干扰素（IFN）治疗的反应。预测 HCV 感染患者的治疗结果一直是一项具有挑战性的任务。聚乙二醇干扰素（peg-IFN）联合利巴韦林治疗可清除约 60%的 HCV 患者的病毒 - HCV 基因型 1（42-51%的应答率）和基因型 2 和 3（76-84%的应答率）；然而，相当数量的患者对治疗无反应或停药后复发，或有严重的副作用而无法进一步治疗。准确预测哪些患者对治疗有反应变得越来越重要，不仅从患者护理的角度，而且从医疗保健成本的角度来看，因为临床医生需要继续对有反应的患者进行治疗，而对无反应的患者停止治疗。病毒 RNA 测量和基因分型用于优化治疗，因为低病毒载量和非基因型 1更有可能与持续病毒学应答（SVR）相关。治疗 4 周时 HCV RNA 不可检测的快速病毒学应答（RVR）越来越被认为是预测治疗反应的有力工具。宿主因素包括 IFN 反应基因的单核苷酸多态性（SNP）、胰岛素抵抗、肥胖、种族、人类白细胞抗原和 T 细胞免疫反应的差异，已被发现可调节抗病毒治疗的反应。治疗前肝活检中存在严重纤维化/肝硬化预示着对治疗的反应不佳。最近关于基因表达谱分析和肝及血清蛋白质组学特征的研究为未来准确预测 HCV 感染患者的治疗结果提供了选择。如果我们要征服这种疾病，就需要研究预测治疗反应的因素，并根据这些因素来调整治疗方案。
