在观察性研究中估计HAART对CD4影响的动态模型：应用于阿基坦队列研究和瑞士HIV队列研究
Dynamic models for estimating the effect of HAART on CD4 in observational studies: application to the Aquitaine Cohort study and the Swiss HIV Cohort Study
摘要：
在许多随机临床试验中，高效抗逆转录病毒治疗（HAART）已被证明在增加CD 4计数方面有效。因为随机试验有一些局限性（例如，持续时间短，高度选择的受试者），使用观察性研究来评估它是很有趣的。这是具有挑战性的，因为治疗优先在患有重度疾病的受试者中开始，特别是在具有低CD 4计数的受试者中。这个一般性问题已经用依赖于反事实表述的边际结构模型（MSM）来处理。因果关系的另一种方法是基于动态模型。首先，我们提出了三个离散时间动态模型的基础上线性增量（LIM）：最简单的模型是由一个差分方程CD 4计数;第二个有一个平衡点;第三个模型是基于一个系统的两个差分方程，允许联合建模CD 4计数和病毒载量。然后，我们考虑连续时间模型的基础上常微分方程的随机效应（ODE-NLME）。这些机制模型允许在可用时并入生物学知识，这导致用于检测处理效应的能力增加。然而，在ODE-NLME模型中的推断从数值的角度来看是具有挑战性的，并且需要特定的方法和软件。LIM在一致性、精确性和复杂性方面是一个有价值的中间选择。不同的方法进行了比较，在模拟和适用于艾滋病毒队列（ANRS CO 3阿基坦队列和瑞士艾滋病毒队列研究）。
英文摘要：
Highly active antiretroviral therapy (HAART) has proved efficient in increasing CD4 counts in many randomized clinical trials. Because randomized trials have some limitations (e.g., short duration, highly selected subjects), it is interesting to assess it using observational studies. This is challenging because treatment is started preferentially in subjects with severe conditions, in particular in subjects with low CD4 counts. This general problem had been treated using Marginal Structural Models (MSM) relying on the counterfactual formulation. Another approach to causality is based on dynamical models. First, we present three discrete-time dynamic models based on linear increments (LIM): the simplest model is described by one difference equation for CD4 counts; the second has an equilibrium point; the third model is based on a system of two difference equations which allows jointly modeling CD4 counts and viral load. Then we consider continuous time models based on ordinary differential equations with random effects (ODE-NLME). These mechanistic models allow incorporating biological knowledge when available, which leads to increased power for detecting treatment effect. Inference in ODE-NLME models, however, is challenging from a numerical point of view, and requires specific methods and softwares. LIMs are a valuable intermediary option in terms of consistency, precision and complexity. The different approaches are compared in simulation and applied to HIV cohorts (the ANRS CO3 Aquitaine Cohort and the Swiss HIV Cohort Study).
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