Unit of Infectious Diseases and Microbiology, Hospital Universitario de Valme, Seville, Spain.
J Hepatol. 2012 Apr;56(4):788-94. doi: 10.1016/j.jhep.2011.11.008. Epub 2011 Dec 13.
BACKGROUND & AIMS: This study aimed at developing a predictive algorithm based on interleukin 28B (IL28B) genotype, hepatitis C virus (HCV) genotype, and plasma HCV-RNA load, which could accurately allow us to define the probability of response to pegylated interferon (Peg-IFN) plus ribavirin (RBV) therapy in HIV/HCV-coinfected patients.
Five hundred and twenty-one treatment-naive HIV-infected patients, who initiated HCV therapy with Peg-IFN/RBV, were analysed in an on-treatment basis. Patients were categorized as unlikely responders, uncertain responders, and anticipated responders (<20%, 20-60%, and >60% probability to achieve SVR, respectively).
HCV genotype, baseline HCV-RNA load, and IL28B genotype were confirmed as independent predictors of SVR in a logistic regression analysis. A stepwise algorithm based on these three variables was created based on 321 patients and evaluated in the remaining 200 patients. Unlikely responders included patients with genotype 1 or 4, HCV-RNA load ≥600,000IU/ml, and rs12979860 non-CC (rate of SVR: 17.3%). Anticipated responders were those with HCV genotype 2-3, patients harboring HCV genotype 4 and IL28B CC, as well as those who simultaneously bore HCV genotype 1, HCV-RNA load <600,000IU/ml, and IL28B CC (rate of SVR 74.1%, 77.8%, and 64.4%, respectively). The area under the receiver operating characteristic curve of the model was 0.77 (0.733-0.814).
The combined use of IL28B genotype, HCV genotype, and HCV-RNA load enables to easily identify patients with a high and very low likelihood of SVR. HCV therapy could be deferred in the latter patients, until more effective options are available, at least if they do not show advanced liver fibrosis.
本研究旨在开发一种基于白细胞介素 28B(IL28B)基因型、丙型肝炎病毒(HCV)基因型和血浆 HCV-RNA 载量的预测算法,以便准确预测 HIV/HCV 合并感染患者对聚乙二醇干扰素(Peg-IFN)联合利巴韦林(RBV)治疗的反应概率。
对 521 例初治的 HIV 感染患者进行了基于治疗的分析,这些患者接受了 Peg-IFN/RBV 治疗 HCV。患者被分为不太可能应答者、不确定应答者和预期应答者(分别为 SVR 概率<20%、20-60%和>60%)。
在逻辑回归分析中,HCV 基因型、基线 HCV-RNA 载量和 IL28B 基因型被确认为 SVR 的独立预测因子。基于这三个变量的逐步算法是在 321 例患者的基础上建立的,并在其余 200 例患者中进行了评估。不太可能应答者包括基因型 1 或 4、HCV-RNA 载量≥600,000IU/ml 和 rs12979860 非 CC 患者(SVR 率:17.3%)。预期应答者为 HCV 基因型 2-3、携带 HCV 基因型 4 和 IL28B CC 的患者,以及同时携带 HCV 基因型 1、HCV-RNA 载量<600,000IU/ml 和 IL28B CC 的患者(SVR 率分别为 74.1%、77.8%和 64.4%)。模型的受试者工作特征曲线下面积为 0.77(0.733-0.814)。
联合使用 IL28B 基因型、HCV 基因型和 HCV-RNA 载量,可以方便地识别 SVR 可能性高和极低的患者。对于后者患者,可以推迟 HCV 治疗,直到有更有效的治疗方法可用,至少如果他们没有出现晚期肝纤维化。