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Several factors including ITPA polymorphism influence ribavirin-induced anemia in chronic hepatitis C

机译:包括ITPA多态性在内的多种因素影响利巴韦林引起的慢性丙型肝炎贫血

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AIM: To construct formulae for predicting the likelihood of ribavirin-induced anemia in pegylated interferon α plus ribavirin for chronic hepatitis C.METHODS: Five hundred and sixty-one Japanese patients with hepatitis C virus genotype 1b who had received combination treatment were enrolled and assigned randomly to the derivation and confirmatory groups. Single nucleotide polymorphisms at or nearby ITPA were genotyped by real-time detection polymerase chain reaction. Factors influencing significant anemia (hemoglobin concentration < 10.0 g/dL at week 4 of treatment) and significant hemoglobin decline (declining concentrations > 3.0 g/dL at week 4) were analyzed using multiple regression analyses. Prediction formulae were constructed by significantly independent factors.RESULTS: Multivariate analysis for the derivation group identified four independent factors associated with significant hemoglobin decline: hemoglobin decline at week 2 [P = 3.29 × 10-17, odds ratio (OR) = 7.54 (g/dL)], estimated glomerular filtration rate [P = 2.16 × 10-4, OR = 0.962 (mL/min/1.73 m2)], rs1127354 (P = 5.75 × 10-4, OR = 10.94) and baseline hemoglobin [P = 7.86 × 10-4, OR = 1.50 (g/dL)]. Using the model constructed by these factors, positive and negative predictive values and predictive accuracy were 79.8%, 88.8% and 86.2%, respectively. For the confirmatory group, they were 83.3%, 91.0% and 88.3%. These factors were closely correlated with significant anemia. However, the model could not be constructed, because no patients with rs1127354 minor genotype CA/AA had significant anemia.CONCLUSION: Reliable formulae for predicting the likelihood of ribavirin-induced anemia were constructed. Such modeling may be useful in developing individual tailoring and optimization of ribavirin dosage.
机译:目的:建立预测聚乙二醇化干扰素α和利巴韦林治疗利巴韦林引起的慢性丙型肝炎的可能性的计算公式。方法:招募并分配了561名接受联合治疗的日本丙型肝炎病毒基因型患者随机到派生和确认组。通过实时检测聚合酶链反应对ITPA或其附近的单核苷酸多态性进行基因分型。使用多重回归分析分析了影响显着贫血(治疗第4周血红蛋白浓度<10.0 g / dL)和显着血红蛋白下降(第4周浓度下降> 3.0 g / dL)的因素。结果:派生组的多变量分析确定了与血红蛋白显着下降有关的四个独立因素:第2周血红蛋白下降[P = 3.29×10 -17 ,优势比(OR)= 7.54(g / dL)],估计的肾小球滤过率[P = 2.16×10 -4 ,OR = 0.962(mL / min / 1.73 m 2 )],rs1127354(P = 5.75×10 -4 ,OR = 10.94)和基线血红蛋白[P = 7.86×10 -4 ,OR = 1.50(g / dL )]。使用这些因素构建的模型,阳性和阴性预测值和预测准确性分别为79.8%,88.8%和86.2%。确认组分别为83.3%,91.0%和88.3%。这些因素与严重的贫血密切相关。但是,由于没有rs1127354轻型基因型CA / AA患者没有明显的贫血,因此无法建立该模型。结论:构建了可靠的公式来预测利巴韦林引起的贫血的可能性。这样的模型可用于开发利巴韦林剂量的个体调整和优化。

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