Larrat Sylvie, Vallet Sophie, David-Tchouda Sandra, Caporossi Alban, Margier Jennifer, Ramière Christophe, Scholtes Caroline, Haïm-Boukobza Stéphanie, Roque-Afonso Anne-Marie, Besse Bernard, André-Garnier Elisabeth, Mohamed Sofiane, Halfon Philippe, Pivert Adeline, LeGuillou-Guillemette Hélène, Abravanel Florence, Guivarch Matthieu, Mackiewicz Vincent, Lada Olivier, Mourez Thomas, Plantier Jean-Christophe, Baazia Yazid, Alain Sophie, Hantz Sebastien, Thibault Vincent, Gaudy-Graffin Catherine, Bouvet Dorine, Mirand Audrey, Henquell Cécile, Gozlan Joel, Lagathu Gisèle, Pronier Charlotte, Velay Aurélie, Schvoerer Evelyne, Trimoulet Pascale, Fleury Hervé, Bouvier-Alias Magali, Brochot Etienne, Duverlie Gilles, Maylin Sarah, Gouriou Stéphanie, Pawlotsky Jean-Michel, Morand Patrice
Centre Hospitalier Universitaire Grenoble, Pôle Biologie, Laboratoire de Virologie, Département des Agents Infectieux, Grenoble, France Université Grenoble Alpes, Unit of Virus Host Cell Interactions UMI 3265 UJF-EMBL-CNRS, Grenoble, France
Université Européenne de Bretagne, UFR Médecine et des Sciences de la Santé, LUBEM, Brest, France Laboratoire de Virologie, Centre Hospitalier Régional Universitaire, Brest, France.
J Clin Microbiol. 2015 Jul;53(7):2195-202. doi: 10.1128/JCM.03633-14. Epub 2015 Apr 29.
The pretherapeutic presence of protease inhibitor (PI) resistance-associated variants (RAVs) has not been shown to be predictive of triple-therapy outcomes in treatment-naive patients. However, they may influence the outcome in patients with less effective pegylated interferon (pegIFN)-ribavirin (RBV) backbones. Using hepatitis C virus (HCV) population sequence analysis, we retrospectively investigated the prevalence of baseline nonstructural 3 (NS3) RAVs in a multicenter cohort of poor IFN-RBV responders (i.e., prior null responders or patients with a viral load decrease of <1 log IU/ml during the pegIFN-RBV lead-in phase). The impact of the presence of these RAVs on the outcome of triple therapy was studied. Among 282 patients, the prevalances (95% confidence intervals) of baseline RAVs ranged from 5.7% (3.3% to 9.0%) to 22.0% (17.3% to 27.3%), depending to the algorithm used. Among mutations conferring a >3-fold shift in 50% inhibitory concentration (IC50) for telaprevir or boceprevir, T54S was the most frequently detected mutation (3.9%), followed by A156T, R155K (0.7%), V36M, and V55A (0.35%). Mutations were more frequently found in patients infected with genotype 1a (7.5 to 23.6%) than 1b (3.3 to 19.8%) (P = 0.03). No other sociodemographic or viroclinical characteristic was significantly associated with a higher prevalence of RAVs. No obvious effect of baseline RAVs on viral load was observed. In this cohort of poor responders to IFN-RBV, no link was found with a sustained virological response to triple therapy, regardless of the algorithm used for the detection of mutations. Based on a cross-study comparison, baseline RAVs are not more frequent in poor IFN-RBV responders than in treatment-naive patients and, even in these difficult-to-treat patients, this study demonstrates no impact on treatment outcome, arguing against resistance analysis prior to treatment.
蛋白酶抑制剂(PI)耐药相关变异(RAV)的治疗前存在情况尚未被证明可预测初治患者的三联疗法疗效。然而,它们可能会影响聚乙二醇化干扰素(pegIFN)-利巴韦林(RBV)治疗效果欠佳患者的治疗结果。我们通过丙型肝炎病毒(HCV)群体序列分析,回顾性研究了多中心队列中对IFN-RBV反应不佳患者(即既往无反应者或在pegIFN-RBV导入期病毒载量下降 <1 log IU/ml的患者)基线非结构3(NS3)RAV的流行情况。研究了这些RAV的存在对三联疗法结果的影响。在282例患者中,根据所使用的算法,基线RAV的流行率(95%置信区间)在5.7%(3.3%至9.0%)至22.0%(17.3%至27.3%)之间。在导致替拉普韦或博赛匹韦50%抑制浓度(IC50)出现>3倍变化的突变中,T54S是最常检测到的突变(3.9%),其次是A156T、R155K(0.7%)、V36M和V55A(0.35%)。感染1a基因型的患者(7.5%至23.6%)比感染1b基因型的患者(3.3%至19.8%)更频繁地出现突变(P = 0.03)。没有其他社会人口统计学或病毒临床特征与RAV的较高流行率显著相关。未观察到基线RAV对病毒载量有明显影响。在这个对IFN-RBV反应不佳的队列中,无论用于检测突变的算法如何,均未发现与三联疗法的持续病毒学应答有联系。基于跨研究比较,对IFN-RBV反应不佳的患者中基线RAV并不比初治患者更常见,而且即使在这些难以治疗的患者中,本研究也表明其对治疗结果没有影响,这表明反对在治疗前进行耐药性分析。