Kirschner D E, Webb G F
Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor 48109-0620, USA.
Bull Math Biol. 1997 Jul;59(4):763-85. doi: 10.1007/BF02458429.
The purpose of this study was to investigate strategies in the monotherapy treatment of HIV infection in the presence of drug-resistant (mutant) strains. A mathematical system is developed to model resistance in HIV chemotherapy. It includes the key players in the immune response to HIV infection: virus and both uninfected CD4+ and infected CD4+ T-cell populations. We model the latent and progressive stages of the disease, and then introduce monotherapy treatment. The model is a system of differential equations describing the interaction of two distinct classes of HIV--drug-sensitive (wild type) and drug-resistant (mutant)--with lymphocytes in the peripheral blood. We then introduce chemotherapy effects. In the absence of treatment, the model produces the three types of qualitative clinical behavior--an uninfected steady state, an infected steady state (latency), and progression to AIDS. Simulation of treatment is provided for monotherapy, during the progression to AIDS state, in the consideration of resistance effects. Treatment benefit is based on an increase or retention in CD4+ T-cell counts together with a low viral titer. We explore the following treatment approaches: an antiviral drug which reduces viral infectivity that is administered early--when the CD4+ T-cell count is > or = 300/mm3, and the late--when the CD4+ T-cell count is less than 300/mm3. We compare all results with data. When treatment is initiated during the progression to AIDS state, treatment prevents T-cell collapse, but gradually loses effectiveness due to drug resistance. We hypothesize that it is the careful balance of mutant and wild-type HIV strains which provides the greatest prolonged benefit from treatment. This is best achieved when treatment is initiated when the CD4+ T-cell counts are greater than 250/mm3, but less than 400/mm3 in this model (i.e. not too early, not too late). These results are supported by clinical data. The work is novel in that it is the first model to accurately simulate data before, during and after monotherapy treatment. Our model also provides insight into recent clinical results, as well as suggests plausible guidelines for clinical testing in the monotherapy of HIV infection.
本研究的目的是探讨在存在耐药（突变）毒株的情况下，单药治疗HIV感染的策略。开发了一个数学系统来模拟HIV化疗中的耐药性。该系统包括HIV感染免疫反应中的关键参与者：病毒以及未感染的CD4+和感染的CD4+ T细胞群体。我们对疾病的潜伏和进展阶段进行建模，然后引入单药治疗。该模型是一个微分方程组系统，描述了外周血中两类不同的HIV（药物敏感型（野生型）和耐药型（突变型））与淋巴细胞之间的相互作用。接着我们引入化疗效果。在未进行治疗的情况下，该模型产生三种定性的临床行为——未感染稳态、感染稳态（潜伏期）以及进展为艾滋病。在考虑耐药效应的情况下，针对进展为艾滋病状态期间的单药治疗提供了模拟。治疗效果基于CD4+ T细胞计数的增加或维持以及低病毒载量。我们探索了以下治疗方法：一种降低病毒感染性的抗病毒药物，在CD4+ T细胞计数≥300/mm³时早期给药，以及在CD4+ T细胞计数小于300/mm³时晚期给药。我们将所有结果与数据进行比较。当在进展为艾滋病状态期间开始治疗时，治疗可防止T细胞崩溃，但由于耐药性会逐渐失去效力。我们假设正是突变型和野生型HIV毒株之间的精确平衡使得治疗能带来最大的长期益处。在该模型中，当CD4+ T细胞计数大于250/mm³但小于400/mm³时开始治疗（即不太早也不太晚），能最好地实现这一点。这些结果得到了临床数据的支持。这项工作具有创新性，因为它是第一个能准确模拟单药治疗前、治疗期间和治疗后数据的模型。我们的模型还为近期临床结果提供了见解，并为HIV感染单药治疗的临床试验提出了合理的指导原则。
