Dynamic treatment model to examine the association between phenotypic drug resistance and duration of HIV viral suppression.
Dynamic treatment model to examine the association between phenotypic drug resistance and duration of HIV viral suppression.
复制标题
动态治疗模型检查表型耐药性与 HIV 病毒抑制持续时间之间的关联。
DOI：
10.1016/j.bulm.2005.02.004
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发表时间：
2005
期刊：
影响因子：
--
通讯作者：
Snedecor,SonyaJ
中科院分区：
文献类型：
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作者：
Snedecor,SonyaJ
HIV感染化疗的最新进展成功地延缓了许多患者的疾病进展，并导致美国与HIV相关的死亡人数下降。然而，许多患者在治疗中未能维持抑制的病毒载量。扩大现有药物效用的方法包括开发改进的方法来评估耐药变异的治疗影响。创建了一个将耐药突变的存在与一级或二级分类相结合的数学模型，作为探索表型耐药性与病毒治疗反应持续时间之间关系的一种手段。该模型包括每个病毒突变体的表型和基因型抗性信息，此处提供了简化的五密码子基因组。然而，随着额外的实验数据和计算资源变得可用，未来用户可能会调整模型以使其更大、更准确。二次分析表明，在该模型中，具有中等数量突变的菌株的耐药表型是单次治疗的病毒抑制总持续时间以及两种治疗的正向和反向顺序给药的抑制持续时间之间的差异的主要决定因素。这些发现意味着，包含耐药表型和基因型耐药病毒株体内反应的模型可能会导致对携带耐药病毒的个体成功选择抗 HIV 药物的先验预测。
Recent advances in the chemotherapy of HIV infection have been successful in delaying the progression of disease in many patients and are responsible for the decline in HIV-related deaths in the United States. Yet, there are many patients who fail to maintain suppressed viral loads on treatment. Means to extend the utility of currently available drugs include developing improved ways to assess the therapeutic impact of drug-resistant variants. A mathematical model to incorporate the presence of resistance mutations with either primary or secondary classifications is created as a means to explore the association between phenotypic resistance and duration of viral response to therapy. The model, which includes phenotypic and genotypic resistance information for each viral mutant, is presented here with a simplified five-codon genome. However, as additional experimental data and computational resources become available future users may adapt the model to be larger and more accurate. Secondary analyses suggest that, in this model, the resistance phenotypes of the strains with an intermediate number of mutations are the primary determinants of both the total duration of viral suppression with a single treatment and the difference between the durations of suppression of the forward and reverse sequential administrations of two treatments. These findings imply that a model including the resistance phenotype and in vivo response of genotypically-resistant viral strains may lead to a priori prediction of successful anti-HIV drug selection for an individual harboring drug-resistant virus.