Wu Hulin, Huang Yangxin, Acosta Edward P, Rosenkranz Susan L, Kuritzkes Daniel R, Eron Joseph J, Perelson Alan S, Gerber John G
Department of Biostatistics and Computational Biology, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA.
J Acquir Immune Defic Syndr. 2005 Jul 1;39(3):272-83. doi: 10.1097/01.qai.0000165907.04710.da.
We propose a long-term HIV-1 dynamic model by considering drug potency, drug exposure, and drug susceptibility. Using a Bayesian approach, HIV-1 dynamic parameters were estimated by fitting the model to viral load data from a phase 1/2 randomized clinical study of 2 indinavir (IDV)/ritonavir (RTV)-containing highly active antiretroviral (ARV) therapy regimens in HIV-infected subjects who had previously failed protease inhibitor-containing ARV therapies. A large between-subject variation in estimated viral dynamic parameters was observed, even after accounting for variations in drug exposure and drug susceptibility, suggesting that characteristics of HIV-1 dynamics are host dependent. Significant correlations of baseline factors such as HIV-1 RNA levels and CD4 cell counts with viral dynamic parameters were found. These correlations coincide with biologic interaction mechanisms between HIV and the host immune system and also provide an explanation for the correlations between the baseline viral load and phase 1 viral decay rate, for which inconsistent results have been reported in the literature. The relations between viral dynamic parameters and virologic response were established, and these results suggest that viral dynamic parameters may play an important role in determining treatment success or failure. In particular, we estimated a drug efficacy threshold for each patient that can be used to assess whether an ARV regimen is potent enough to suppress HIV viruses in the individual patient. Our findings indicate that it is necessary to individualize the ARV regimen to treat HIV-1-infected patients. The proposed mathematic models and statistical techniques may provide a framework to simulate and predict antiviral response for individual patients.
我们通过考虑药物效力、药物暴露和药物敏感性，提出了一个长期的HIV-1动力学模型。采用贝叶斯方法，通过将模型拟合到来自一项1/2期随机临床研究的病毒载量数据，对HIV-1动力学参数进行了估计，该研究针对的是先前含蛋白酶抑制剂的抗逆转录病毒（ARV）治疗失败的HIV感染受试者，采用了两种含茚地那韦（IDV）/利托那韦（RTV）的高效抗逆转录病毒（ARV）治疗方案。即使在考虑了药物暴露和药物敏感性的差异之后，仍观察到估计的病毒动力学参数存在较大的个体间差异，这表明HIV-1动力学特征取决于宿主。发现了基线因素如HIV-1 RNA水平和CD4细胞计数与病毒动力学参数之间存在显著相关性。这些相关性与HIV和宿主免疫系统之间的生物学相互作用机制一致，也为基线病毒载量与1期病毒衰减率之间的相关性提供了解释，对此文献中报道的结果并不一致。建立了病毒动力学参数与病毒学反应之间的关系，这些结果表明病毒动力学参数可能在决定治疗成败中起重要作用。特别是，我们为每位患者估计了一个药物疗效阈值，可用于评估一种ARV方案是否有足够的效力在个体患者中抑制HIV病毒。我们的研究结果表明，有必要对ARV方案进行个体化，以治疗HIV-1感染患者。所提出的数学模型和统计技术可能为模拟和预测个体患者的抗病毒反应提供一个框架。
