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

Autor: Delia North, Zelalem G. Dessie, Temesgen Zewotir, Henry Mwambi
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Adult
medicine.medical_specialty
Health Informatics
HIV Infections
Accelerated failure time model
lcsh:Computer applications to medicine. Medical informatics
01 natural sciences
010104 statistics & probability
03 medical and health sciences
South Africa
0302 clinical medicine
Immune system
Internal medicine
medicine
Humans
030212 general & internal medicine
Longitudinal Studies
Prospective Studies
0101 mathematics
Seroconversion
Prospective cohort study
Latent variables
lcsh:QH301-705.5
Probability
Multi state
business.industry
Research
AFT models
Viral Load
Transitions and quality of life domain scores
Markov model
CD4 Lymphocyte Count
Waiting probabilities
Chronic infection
Sexual Partners
lcsh:Biology (General)
Modeling and Simulation
Disease Progression
lcsh:R858-859.7
Female
Factor analysis
business
Viral load
Hiv disease
Zdroj: Theoretical Biology and Medical Modelling, Vol 17, Iss 1, Pp 1-13 (2020)
Theoretical Biology & Medical Modelling
ISSN: 1742-4682
Popis: BackgroundHIV 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.MethodsThe 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.ResultsTransition 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/mm3or 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.ConclusionMulti-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.
Databáze: OpenAIRE
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