CD4 cell and viral load count are highly correlated surrogate markers of human immunodeficiency virus (HIV) disease progression. In modelling the progression of HIV, previous studies mostly dealt with either CD4 cell counts or viral load alone. In this work, both biomarkers are in included one model, in order to study possible factors that affect the intensities of immune deterioration, immune recovery and state-specific duration of HIV-infected women. The data is from an ongoing prospective cohort study conducted among antiretroviral treatment (ART) naïve HIV-infected women in the province of KwaZulu-Natal, South Africa. Participants were enrolled in the acute HIV infection phase, then followed-up during chronic infection up to ART initiation. Full-parametric and semi-parametric Markov models were applied. Furthermore, the effect of the inclusion and exclusion viral load in the model was assessed. Inclusion of a viral load component improves the efficiency of the model. The analysis results showed that patients who reported a stable sexual partner, having a higher educational level, higher physical health score and having a high mononuclear component score are more likely to spend more time in a good HIV state (particularly normal disease state). Patients with TB co-infection, with anemia, having a high liver abnormality score and patients who reported many sexual partners, had a significant increase in the intensities of immunological deterioration transitions. On the other hand, having high weight, higher education level, higher quality of life score, having high RBC parameters, high granulocyte component scores and high mononuclear component scores, significantly increased the intensities of immunological recovery transitions. Inclusion of both CD4 cell count based disease progression states and viral load, in the time-homogeneous Markov model, assisted in modeling the complete disease progression of HIV/AIDS. Higher quality of life (QoL) domain scores, good clinical characteristics, stable sexual partner and higher educational level were found to be predictive factors for transition and length of stay in sequential adversity of HIV/AIDS.

中文翻译：

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通过病毒载量调整对 HIV 感染女性的免疫恶化、免疫恢复和州特定持续时间进行建模：使用参数多状态模型。

CD4 细胞和病毒载量计数是人类免疫缺陷病毒 (HIV) 疾病进展的高度相关替代标记。在对 HIV 进展进行建模时，之前的研究大多仅涉及 CD4 细胞计数或病毒载量。在这项工作中，这两种生物标志物都包含在一个模型中，以研究影响艾滋病毒感染女性免疫恶化、免疫恢复和特定状态持续时间强度的可能因素。这些数据来自一项正在进行的前瞻性队列研究，该研究针对南非夸祖鲁-纳塔尔省未接受过抗逆转录病毒治疗 (ART) 的艾滋病毒感染女性。参与者在急性艾滋病毒感染阶段入组，然后在慢性感染期间进行随访，直至开始抗逆转录病毒治疗。应用全参数和半参数马尔可夫模型。此外，还评估了模型中包含和排除病毒载量的效果。包含病毒载量成分可以提高模型的效率。分析结果显示，自称有稳定性伴侣、受教育程度较高、身体健康评分较高以及单核成分评分较高的患者更有可能处于良好的HIV状态（尤其是正常疾病状态）。结核病合并感染、贫血、肝脏异常评分高以及性伴侣较多的患者的免疫恶化转变强度显着增加。另一方面，高体重、较高教育水平、较高生活质量评分、高红细胞参数、高粒细胞成分评分和高单核成分评分，显着增加免疫恢复转变的强度。将基于 CD4 细胞计数的疾病进展状态和病毒载量纳入时间均质马尔可夫模型中，有助于对 HIV/AIDS 的完整疾病进展进行建模。研究发现，较高的生活质量（QoL）领域得分、良好的临床特征、稳定的性伴侣和较高的教育水平是艾滋病毒/艾滋病连续逆境转变和停留时间的预测因素。