Department of Mathematics and Statistics, University of Dodoma, Dodoma, Tanzania.
Department of Statistics, University of Dar es Salaam, Dar es Salaam, Tanzania.
BMC Public Health. 2023 Oct 25;23(1):2091. doi: 10.1186/s12889-023-16977-x.
Globally, 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.
Secondary 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.
The 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).
The 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.
在全球范围内，艾滋病毒/艾滋病是个人成本和健康负担最大的疾病之一；而撒哈拉以南非洲是受该大流行病影响最严重的地区。坦桑尼亚是艾滋病毒/艾滋病死亡率较高的国家之一。本研究旨在使用联合生存模型估计病毒载量结果和调整年龄、性别、依从性和就诊日期后与死亡相关的生存结果之间的关联。
使用参加医疗保健和治疗中心的艾滋病毒患者回顾性队列的二级数据来分析纵向病毒载量与死亡时间结果之间的关联。三步分析基于个体混合效应线性模型和 Cox 比例风险模型来估计独立结果的显著性，以及最终模型联合生存模型。联合模型用于估计影响平均对数病毒载量随时间变化的因素以及艾滋病毒患者生存时间的危险因素。两个模型的暴露因素均为抗逆转录病毒治疗的依从性状况、年龄、男性和就诊日期，而 LMM 的结果是病毒载量的对数，Cox PH 模型的结果是死亡时间（以年为单位）。
联合生存模型的结果表明，年龄每增加 10 岁，死亡风险增加 37%（HR=1.369，95%CI：1.253-1.844），与女性相比，男性死亡风险增加 49%（HR=1.489，95%CI：1.202-1.844）。结果还提供了纵向对数病毒载量与死亡时间之间关联的证据，即对数病毒载量增加一个单位，死亡风险增加 26%（HR=1.262，95%CI：1.226-1.301）。
联合生存模型分析提供了有关时间到死亡和对数病毒载量与患者对 ART 的依从性、年龄、就诊日期和性别的关联的有价值的见解。这意味着需要进行病毒载量抑制以及针对性别和年龄的干预措施，以减少与艾滋病毒/艾滋病相关的死亡。
