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Modelled in vivo HIV fitness under drug selective pressure and estimated genetic barrier towards resistance are predictive for virological response.

机译:在药物选择压力下对体内HIV适应度进行建模,并估算出抗药性的遗传障碍可预测病毒学应答。

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BACKGROUND: A method has been developed to estimate a fitness landscape experienced by HIV-1 under treatment selective pressure as a function of the genotypic sequence thereby also estimating the genetic barrier to resistance. METHODS: We evaluated the performance of two estimated fitness landscapes (nelfinavir [NFV] and zidovudine [AZT] plus lamivudine [3TC]) to predict week 12 viral load (VL) change for 176 treatment change episodes (TCEs) and probability of week 48 virological failure for 90 TCEs, in treatment experienced patients starting these drugs in combination. RESULTS: A higher genetic barrier for AZT plus 3TC, (quantified per additional mutation required to develop resistance against these drugs) was associated with a 0.54 (95% confidence interval [CI] 0.30-0.77) larger log10 VL reduction at 12 weeks (P < 0.0001) and a 0.39 (95%/ CI 0.23-0.66) lower odds of virological failure at 48 weeks (P = 0.0005), in analyses adjusting for the pre-TCE VL and the exact time-lag between the TCE and the date of determining response VL. The strength of these associations was comparable with those seen with expert interpretation systems (Rega, ANRS and HIVDB). A higher genetic barrier to NFV resistance was the only genotypic predictor that tended to be associated with a 0.19 (95% CI 0-0.39) higher log10 VL reduction at 12 weeks (P = 0.05) and a 0.63 (95% CI 0.36-1.09) lower odds of virological failure at 48 weeks ( P = 0.10) per additional mutation. CONCLUSIONS: These results suggest that an estimated genetic barrier derived from fitness landscapes may contribute to an improvement of predicted treatment outcome for NFV and this approach should be explored for other drugs.
机译:背景:已经开发出一种方法来估计HIV-1在治疗选择压力下根据基因型序列所经历的健康状况,从而也可以估计抗药性的遗传障碍。方法:我们评估了两种估计的适应状况(纳非那韦[NFV]和齐多夫定[AZT]加拉米夫定[3TC])的性能,以预测176次治疗变化发作(TCE)的第12周病毒载量(VL)变化和第48周的可能性在治疗中,经验丰富的患者开始联合使用这些药物,导致90个TCE发生病毒学失败。结果:AZT + 3TC的更高遗传障碍(对这些药物产生耐药性所需要的每个额外突变进行量化),与12周时log10 VL降低0.54(95%置信区间[CI] 0.30-0.77)相关(P <0.0001),并且在校正了TCE VL前和TCE与日期之间的确切时滞的分析中,在48周时病毒学失败的几率降低了0.39(95%/ CI 0.23-0.66)(P = 0.0005)确定响应VL。这些协会的实力与专家解释系统(Rega,ANRS和HIVDB)看到的实力相当。较高的NFV耐药性遗传障碍是唯一的基因型预测因子,在12周时与log10 VL降低相关(0.19(95%CI 0-0.39)较高(P = 0.05),0.63(95%CI 0.36-1.09) )每增加一个突变,在48周时发生病毒学失败的几率较低(P = 0.10)。结论:这些结果表明,从健康状况中获得的估计遗传障碍可能有助于改善NFV的预期治疗结果,对于其他药物,应探索这种方法。

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