Modelling HIV disease process and progression in seroconversion among South Africa women: using transition-specific parametric multi-state model.

Q1 Mathematics
Zelalem G Dessie, Temesgen Zewotir, Henry Mwambi, Delia North
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引用次数: 2

Abstract

Background: HIV infected patients may experience many intermediate events including between-event transition throughout their follow up. Through modelling these transitions, we can gain a deeper understanding of HIV disease process and progression and of factors that influence the disease process and progression pathway. In this work, we present transition-specific parametric multi-state models to describe HIV disease process and progression.

Methods: The data is from an ongoing prospective cohort study conducted amongst adult women who were HIV-infected in KwaZulu-Natal, South Africa. Participants were enrolled during the acute HIV infection phase and then followed up during chronic infection, up to ART initiation.

Results: Transition specific distributions for multi-state models, including a variety of accelerated failure time (AFT) models and proportional hazards (PH) models, were presented and compared in this study. The analysis revealed that women enrolling with a CD4 count less than 350 cells/mm3 (severe and advanced disease stages) had a far lower chance of immune recovery, and a considerably higher chance of immune deterioration, compared to women enrolling with a CD4 count of 350 cells/mm3 or more (normal and mild disease stages). Our analyses also showed that older age, higher educational levels, higher scores for red blood cell counts, higher mononuclear scores, higher granulocytes scores, and higher physical health scores, all had a significant effect on a shortened time to immunological recovery, while women with many sex partners, higher viral load and larger family size had a significant effect on accelerating time to immune deterioration.

Conclusion: Multi-state modelling of transition-specific distributions offers a flexible tool for the study of demographic and clinical characteristics' effects on the entire disease progression pathway. It is hoped that the article will help applied researchers to familiarize themselves with the models, including interpretation of results.

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模拟南非妇女血清转化中的艾滋病毒疾病过程和进展:使用过渡特异性参数多状态模型
背景:HIV感染患者在随访过程中可能会经历许多中间事件,包括事件之间的过渡。通过对这些转变进行建模,我们可以更深入地了解HIV的疾病过程和进展,以及影响疾病过程和进展途径的因素。在这项工作中,我们提出了过渡特异性参数多状态模型来描述HIV疾病的过程和进展。方法:数据来自一项正在进行的前瞻性队列研究,研究对象是南非夸祖鲁-纳塔尔省感染艾滋病毒的成年妇女。参与者在急性HIV感染阶段被招募,然后在慢性感染期间随访,直到ART开始。结果:本研究给出并比较了多状态模型(包括各种加速失效时间(AFT)模型和比例危害(PH)模型)的过渡特定分布。分析显示,与CD4细胞计数为350细胞/毫米3或更高(正常和轻度疾病阶段)的妇女相比,CD4细胞计数低于350细胞/毫米3(严重和晚期疾病阶段)的妇女免疫恢复的机会要低得多,免疫恶化的机会要高得多。我们的分析还显示,年龄越大、受教育程度越高、红细胞计数得分越高、单核细胞得分越高、粒细胞得分越高、身体健康得分越高,都对缩短免疫恢复时间有显著影响,而性伴侣多、病毒载量高、家庭规模大的女性对加速免疫退化时间有显著影响。结论:过渡特异性分布的多状态建模为研究人口统计学和临床特征对整个疾病进展途径的影响提供了一种灵活的工具。希望本文能帮助应用研究者熟悉模型,包括对结果的解释。
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来源期刊
Theoretical Biology and Medical Modelling
Theoretical Biology and Medical Modelling MATHEMATICAL & COMPUTATIONAL BIOLOGY-
自引率
0.00%
发文量
0
审稿时长
6-12 weeks
期刊介绍: Theoretical Biology and Medical Modelling is an open access peer-reviewed journal adopting a broad definition of "biology" and focusing on theoretical ideas and models associated with developments in biology and medicine. Mathematicians, biologists and clinicians of various specialisms, philosophers and historians of science are all contributing to the emergence of novel concepts in an age of systems biology, bioinformatics and computer modelling. This is the field in which Theoretical Biology and Medical Modelling operates. We welcome submissions that are technically sound and offering either improved understanding in biology and medicine or progress in theory or method.
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