Second-line anti-retroviral treatment failure and its predictors among patients with HIV in Ethiopia: A systematic review and meta-analysis

埃塞俄比亚艾滋病患者二线抗逆转录病毒治疗失败及其预测因素:系统评价和荟萃分析

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Abstract

Antiretroviral therapy (ART) treatment failure remains a major public health concern, with multidimensional consequences, including an increased risk of drug resistance, compromised quality of life, and high healthcare costs. However, little is known about the outcomes of second-line ART in Ethiopia. Therefore, this systematic review and meta-analysis aimed to determine the incidence and determinants of second-line ART treatment failure. Articles published in PubMed, Google Scholar, Science Direct, and Scopus databases were systematically searched. All observational studies on the incidence and predictors of treatment failure among patients with HIV on second-line ART were included. A random-effects model was used to estimate the pooled incidence, and subgroup analysis was performed to identify the possible sources of heterogeneity. Publication bias was checked using forest plot, Begg's test, and Egger's test. The pooled odds ratio was also computed for associated factors. Seven studies with 3,962 study participants were included in this study. The pooled incidence of second-line antiretroviral treatment failure was 5.98 (95% CI: 4.32, 7.63) per 100 person-years of observation. Being in the advanced WHO clinical stage at switch (AHR = 2.98, 95% CI: 2.11, 4.25), having a CD4 count <100 cells/mm3 (AHR = 2.14, 95% CI: 1.57, 2.91), poor drug adherence (AHR = 1.78, 95% CI: 1.4, 2.25), and tuberculosis co-infection (AHR = 2.93, 95% CI: 1.93, 4.34) were risk factors for treatment failure. In conclusion, this study revealed that that out of 100 person-years of follow-up, an estimated six patients with HIV who were on second-line antiretroviral therapy experienced treatment failure. The risk of treatment failure was higher in patients who were in an advanced WHO clinical stage, CD4 count <100 cells/mm3, and presence tuberculosis co-infection. Therefore, addressing predictors reduces the risk of treatment failure and maximizes the duration of stay in second-line regimens.

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