Gebre Tamrat Endebu, Taye Girma, Deressa Wakgari
Department of Epidemiology and Biostatistics, School of Public Health, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia.
PLoS One. 2025 Jul 24;20(7):e0329132. doi: 10.1371/journal.pone.0329132. eCollection 2025.
Loss to follow-up (LTFU) remains a major challenge in HIV care, particularly in resource-limited settings. While several studies have identified its predictors, many have neglected the competing risks of transfer out and death, as well as the dynamic influence of these predictors over time. A retrospective cohort study was conducted among adult HIV patients who initiated antiretroviral therapy (ART) between 2019 and 2024. LTFU was a primary outcome, whereas transfer out and death were competing risks. A Fine‒Gray subdistribution hazard ratio (SHR) regression analysis identified LTFU predictors within a competing risk framework. An extended SHR model with a time‒covariate interaction term was used to examine the predictors' time‒varying effects on LTFU risk. Data analysis was performed via STATA 17 and Python 3.9. In a cohort of 4,135 HIV patients (8,521.54 person-years of follow-up), the overall incidence of LTFU was 13.10 per 100 person-years (95% CI: 12.35-13.89), with cumulative risks of 15%, 25%, and 35% at 1, 3, and 5 years post-ART, respectively. The predictors of LTFU included younger age (15-24 years: aSHR = 1.51), male sex (aSHR = 1.24), incomplete address details (aSHR = 1.72), noninitiation/noncompletion of TPT (aSHR = 2.16), poor adherence (aSHR = 2.54), and undernutrition (aSHR = 2.03). While younger age (e.g., 15-24 years) was associated with an increased risk of LTFU at baseline (baseline aSHR = 1.36, p = 0.014), this association diminished over time (interaction aSHR = 0.54, p = 0.001). Undernutrition consistently predicted LTFU (baseline aSHR = 1.64, p < 0.001), with no significant time-dependent effect (interaction aSHR = 1.01, p = 0.903). In conclusion, this study highlights the high incidence of LTFU among HIV patients and its key predictors. Notably, age has a significant time-dependent effect, with its influence on the risk of LTFU being most pronounced during the early stage of ART initiation, whereas nutritional status remains a consistent predictor of LTFU over time.
失访在艾滋病护理中仍然是一项重大挑战,在资源有限的环境中尤为如此。虽然多项研究已确定了失访的预测因素,但许多研究都忽略了转出和死亡的竞争风险,以及这些预测因素随时间的动态影响。对2019年至2024年开始接受抗逆转录病毒治疗(ART)的成年艾滋病患者进行了一项回顾性队列研究。失访是主要结局,而转出和死亡是竞争风险。采用Fine-Gray亚分布风险比(SHR)回归分析在竞争风险框架内确定失访的预测因素。使用带有时间协变量交互项的扩展SHR模型来检验预测因素对失访风险的时间变化影响。数据分析通过STATA 17和Python 3.9进行。在一个包含4135名艾滋病患者的队列中(随访8521.54人年),失访的总体发生率为每100人年13.10例(95%置信区间:12.35 - 13.89),在ART治疗后1年、3年和5年的累积风险分别为15%、25%和35%。失访的预测因素包括年龄较小(15 - 24岁:aSHR = 1.51)、男性(aSHR = 1.24)、地址信息不完整(aSHR = 1.72)、未开始/未完成结核病预防性治疗(aSHR = 2.16)、依从性差(aSHR = 2.54)和营养不良(aSHR = 2.03)。虽然年龄较小(如15 - 24岁)在基线时与失访风险增加相关(基线aSHR = 1.36,p = 0.014),但这种关联随时间减弱(交互作用aSHR = 0.54,p = 0.001)。营养不良一直是失访的预测因素(基线aSHR = 1.64,p < 0.001),且无显著的时间依赖性效应(交互作用aSHR = 1.01,p = 0.903)。总之,本研究突出了艾滋病患者中失访的高发生率及其关键预测因素。值得注意的是,年龄具有显著的时间依赖性效应,其对失访风险的影响在ART治疗开始的早期最为明显,而营养状况一直是失访的预测因素。
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