Xiao Yanni, Sun Xiaodan, Tang Sanyi, Zhou Yicang, Peng Zhihang, Wu Jianhong, Wang Ning
Department of Applied Mathematics, Xi'an Jiaotong University, Xianning West Road, Xi'an, 710049, China.
College of Mathematics and Information Science, Shaanxi Normal University, West Chang'an Avenue, Xi'an, 710119, China.
Theor Biol Med Model. 2017 Jan 18;14(1):1. doi: 10.1186/s12976-016-0047-0.
The progression of Human Immunodeficiency Virus (HIV) within host includes typical stages and the Antiretroviral Therapy (ART) is shown to be effective in slowing down this progression. There are great challenges in describing the entire HIV disease progression and evaluating comprehensive effects of ART on life expectancy for HIV infected individuals on ART.
We develop a novel summative treatment benefit index (TBI), based on an HIV viral dynamics model and linking the infection and viral production rates to the Weibull function. This index summarizes the integrated effect of ART on the life expectancy (LE) of a patient, and more importantly, can be reconstructed from the individual clinic data.
The proposed model, faithfully mimicking the entire HIV disease progression, enables us to predict life expectancy and trace back the timing of infection. We fit the model to the longitudinal data in a cohort study in China to reconstruct the treatment benefit index, and we describe the dependence of individual life expectancy on key ART treatment specifics including the timing of ART initiation, timing of emergence of drug resistant virus variants and ART adherence.
We show that combining model predictions with monitored CD4 counts and viral loads can provide critical information about the disease progression, to assist the design of ART regimen for maximizing the treatment benefits.
人类免疫缺陷病毒(HIV)在宿主体内的进展包括典型阶段,抗逆转录病毒疗法(ART)已被证明能有效减缓这一进展。描述整个HIV疾病进展以及评估ART对接受ART治疗的HIV感染者预期寿命的综合影响面临巨大挑战。
我们基于HIV病毒动力学模型,将感染率和病毒产生率与威布尔函数相联系,开发了一种新型的综合治疗效益指数(TBI)。该指数总结了ART对患者预期寿命(LE)的综合影响,更重要的是,可以从个体临床数据中重建。
所提出的模型忠实地模拟了整个HIV疾病进展,使我们能够预测预期寿命并追溯感染时间。我们将该模型应用于中国一项队列研究的纵向数据,以重建治疗效益指数,并描述个体预期寿命对关键ART治疗细节的依赖性,包括ART开始时间、耐药病毒变体出现时间和ART依从性。
我们表明,将模型预测与监测的CD4细胞计数和病毒载量相结合,可以提供有关疾病进展的关键信息,以协助设计ART方案,使治疗效益最大化。