Evidence map›Paper›PMID 37880600›Full record

ArticleBMC public health2023

A joint survival model for estimating the association between viral load outcome and survival time to death among HIV/AIDS patients attending health care and treatment centers in Tanzania.

Habiel Benjamin Luvanda, Elevatus Nkebukwa Mukyanuzi, Rocky R J Akarro

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Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

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6citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  6. Joint modeling of longitudinal CD4 count data and time to first occurrence of composite outcome.Journal of clinical tuberculosis and other mycobacterial diseases · 2024
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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Habiel Benjamin LuvandaDepartment of Mathematics and Statistics, University of Dodoma, Dodoma, Tanzania. luvanda09@gmail.com.
Elevatus Nkebukwa MukyanuziDepartment of Statistics, University of Dar es Salaam, Dar es Salaam, Tanzania.
Rocky R J AkarroDepartment of Statistics, University of Dar es Salaam, Dar es Salaam, Tanzania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGlobally, HIV/AIDS is one of the diseases that have a huge burden in terms of cost and health of individuals; and Sub-Sahara Africa is the highly affected region by the pandemic. Tanzania is among the countries that have a higher prevalence of HIV/AIDS-related mortality. This study aimed at using the joint survival model to estimate the association between viral load outcome and survival outcome to death adjusting for age, sex, adherence, and visit date.

methodsSecondary data from a retrospective cohort of HIV patients attending health care and treatment centers were used to analyze the association between the longitudinal viral load and time-to-death outcomes. The three-step analysis was based on the individual mixed effects linear model and the Cox proportional hazards models to estimate the significance of the independent outcomes, and the joint survival model as a final model. The joint model was used to estimate the factors affecting the average change in log viral load over time and the risk factors for the survival time of HIV patients. The exposures for both models were ART adherence status, age, male, and visit date whereas the outcome for the LMM was log viral load and the outcome for the Cox PH model was time-to-death in years.

resultsThe joint survival model results revealed that a 10-year increase in age was associated with a 37% increased risk of death (HR = 1.369, 95% CI: 1.253-1.844), and being male was associated with a 49% higher risk of death (HR = 1.489, 95% CI: 1.202-1.844) compared to females. The results also provided evidence of an association between the longitudinal log viral load and the survival time to death ) whereby a unit increase in the log viral load was associated with a 26% increase in the risk of death (HR = 1.262, 95% CI: 1.226-1.301).

conclusionThe joint survival model analysis provided valuable insights into the associations between time to death and log viral load with adherence to ART, age, visit date, and sex of the patients. This implies that viral load suppression, as well as sex and age-specific interventions, are necessary for reducing HIV/AIDS-related deaths.

Indexed as

Acquired Immunodeficiency SyndromeAnti-HIV AgentsHIV InfectionsDelivery of Health CareFemaleHumansMaleRetrospective StudiesTanzaniaViral LoadAnti-HIV AgentsCox proportional hazards modelHIV/AIDSJoint survival modelLinear mixed modelMortality

Identifiers

PMID37880600
PMCPMC10598891

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