Department of Mathematical Statistics and Actuarial Sciences, Faculty of Natural and Agricultural Sciences, University of the Free State, Bloemfontein, South Africa; Department of Mathematics and Computer Sciences, Faculty of Agriculture and Natural Sciences, Great Zimbabwe University, Zimbabwe.
S Afr Med J. 2020 Mar 30;110(4):313-319. doi: 10.7196/SAMJ.2020.v110i4.13934.
The goal of antiretroviral therapy (ART) is to suppress viral replication to undetectable levels. These low viral load (VL) levels may not be attained in some patients, a situation representing potential virological failure during the course of treatment.
To present the results of a Markov model exploring how virological failure and active tuberculosis (TB) affect the progression of HIV in patients on ART.
A continuous-time non-homogeneous Markov model was used to model the progression of HIV/AIDS in patients on combination ART (cART). We define seven states in our model. The first five states are based on VL levels and the other two are absorbing states: death and withdrawal from the study. The effects of TB co-infection, baseline VL, lactic acidosis and treatment failure on transition intensities were assessed.
The model shows that VL-based transition intensities do not follow a constant rate; rather, there are two different trends in HIV/AIDS progression. The first trend is an increase in the prevalence of state 1 (undetectable VL levels) in the first 0.5 years of treatment. The second trend follows thereafter and shows a slow decrease. Within the first 0.5 years of therapeutic intervention, the undetectable VL state is therefore attainable from any VL state. However, when virological failure occurs, there is an increased risk of death. Developing active TB while on cART increases the risk of viral rebound from undetectable levels to VLs between 50 and 10 000 copies/mL by ~1.03-fold. From a VL between 10 000 and 100 000 copies/mL, developing TB while on cART increases the rate of viral rebound by ~2.5-fold. However, if TB is detected and treated at enrolment, rates of viral rebound from undetectable levels are reduced.
The model confirms that virological failure, coupled with developing active TB while on cART, increases mortality rates irrespective of patient CD4+ count status. It also suggests that while TB at the time of cART initiation does not increase the risk of viral rebound, development of active TB after cART initiation does increase this risk. These findings highlight the importance of strengthening VL monitoring, which should be performed every 2 months, especially in patients with TB, and addressing unsuppressed VLs appropriately if they are detected.
抗逆转录病毒疗法（ART）的目标是抑制病毒复制至无法检测的水平。但在某些患者中可能无法达到这种低病毒载量（VL）水平，这种情况下代表着治疗过程中存在潜在的病毒学失败。
介绍一个马尔可夫模型的结果，该模型探讨了病毒学失败和活动性结核病（TB）如何影响接受 ART 的 HIV 患者的进展。
我们使用连续时间非齐次马尔可夫模型来对接受联合抗逆转录病毒治疗（cART）的患者的 HIV/AIDS 进展进行建模。我们在模型中定义了七个状态。前五个状态基于 VL 水平，另外两个是吸收状态：死亡和退出研究。评估了 TB 合并感染、基线 VL、乳酸酸中毒和治疗失败对转移强度的影响。
该模型表明，基于 VL 的转移强度不遵循恒定速率；相反，HIV/AIDS 进展存在两种不同的趋势。第一种趋势是在治疗的前 0.5 年内，状态 1（无法检测到 VL 水平）的流行率增加。第二种趋势随后出现，并且显示出缓慢的下降。在治疗干预的前 0.5 年内，因此可以从任何 VL 状态达到无法检测到 VL 的状态。但是，发生病毒学失败时，死亡的风险会增加。在接受 cART 的同时发生活动性 TB 会使从无法检测到的 VL 水平到 50 至 10,000 拷贝/mL 之间的 VL 发生病毒反弹的风险增加约 1.03 倍。从 10,000 至 100,000 拷贝/mL 的 VL 开始，在接受 cART 的同时发生 TB 会使病毒反弹的速度增加约 2.5 倍。但是，如果在登记时检测到并治疗了 TB，则从无法检测到的 VL 水平发生病毒反弹的速度会降低。
该模型证实，病毒学失败加上在接受 cART 的同时发生活动性 TB，会增加死亡率，无论患者的 CD4+计数状态如何。它还表明，cART 启动时的 TB 不会增加病毒反弹的风险，但 cART 启动后发生活动性 TB 会增加这种风险。这些发现强调了加强 VL 监测的重要性，应每两个月进行一次监测，特别是在患有 TB 的患者中，并且如果检测到未被抑制的 VL，则应适当地进行处理。
