Evaluation of HIV-1 kinetic models using quantitative discrimination analysis
Evaluation of HIV-1 kinetic models using quantitative discrimination analysis
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DOI：
10.1093/bioinformatics/bti230
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发表时间：
2005-04
期刊：
影响因子：
5.8
通讯作者：
Andrea L. Knorr;R. Srivastava
中科院分区：
文献类型：
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作者：
Andrea L. Knorr;R. Srivastava
动机 自二十多年前人类免疫缺陷病毒 (HIV) 被识别以来，人们提出了许多 HIV 动力学的数学模型。本研究的目的是评估细胞内和细胞间规模的 HIV 模型，该模型最好地描述了一个人的病毒和细胞滴度的动态，其中参数是使用通常可用的患者数据确定的。在这种情况下，“最佳”被定义为最能够描述实验患者数据的模型，并由基于贝叶斯的模型判别分析和提供真实结果的能力确定。结果 最初评估了 20 个 HIV-1 病毒动力学模型，以确定是否可以从病情稳定的 HIV-1 患者的现成临床数据中获得参数。基于此分析，选择了三种模型进行进一步的检验和比较。使用对 338 人进行长达 2484 天监测的实验数据来估计参数。使用贝叶斯技术评估模型以确定哪个模型最有可能。相对于其余两个模型，最终被选为最可能的模型是压倒性的，它考虑了未感染细胞、感染细胞和细胞毒性 T 淋巴细胞动力学。作者结合原始三个模型的特征，开发了第四个模型用于比较。估计了新模型的参数，并对所有四个模型重复了统计分析。经过模型判别分析，再次选择最初青睐的模型。联系 srivasta@engr.uconn.edu。
MOTIVATION Since the identification of human immunodeficiency virus (HIV) over twenty years ago, many mathematical models of HIV dynamics have been proposed. The purpose of this study was to evaluate intracellular and intercellular scale HIV models that best described the dynamics of viral and cell titers of a person, where parameters were determined using typically available patient data. In this case, 'best' was defined as the model most capable of describing experimental patient data and was determined by Bayesian-based model discrimination analysis and the ability to provide realistic results. RESULTS Twenty models of HIV-1 viral dynamics were initially evaluated to determine whether parameters could be obtained from readily available clinical data from established HIV-1 patients with stable disease. Based on this analysis, three models were chosen for further examination and comparison. Parameters were estimated using experimental data from a cohort of 338 people monitored for up to 2484 days. The models were evaluated using a Bayesian technique to determine which model was most probable. The model ultimately selected as most probable was overwhelmingly favored relative to the remaining two models, and it accounted for uninfected cells, infected cells and cytotoxic T lymphocyte dynamics. The authors developed a fourth model for comparison purposes by combining the features of the original three models. Parameters were estimated for the new model and the statistical analysis was repeated for all four models. The model that was initially favored was selected again upon model discrimination analysis. CONTACT srivasta@engr.uconn.edu.