Predictors Of Viral Rebound Among Adolescents At An Urban Clinic In Kampala Using Repeated Events Survival Analysis

BackgroundA suppressed HIV viral load below 1000 copies/ml is mark of HIV treatment success because it is associated with reduced risk of transmission of HIV. However, following viral suppression, some people experience viral rebound which may occur multiple times. We used repeated events survival analysis to assess the predictors of viral rebound among adolescents (aged 10-19 years) at an urban clinic in Kampala, Uganda. MethodsThe study was a retrospective cohort design conducted at Baylor-Uganda, an HIV care facility. The Lognormal model was used to estimate time from viral suppression to viral rebound (in months) and to determine factors associated with time to first viral rebound. The Prentice, Williams, and Peterson (PWP) model was used to determine the factors associated with repetitive viral rebound. ResultsData from 219 participants were included in the study; 160 (73.06%) were female, and 117 (53.42%) were aged 15-19 years. The overall proportion of viral rebound was 31.5% (31.51/100); 23.29% (23.29/100) experienced one rebound whereas 8.22% (8.22/100) had multiple rebounds. The probability of viral rebound did not reach 50%, so the median time from viral suppression to viral rebound could not be estimated. The 25th percentile survival time to first viral rebound was 34.1 months. The incidence rate of first viral rebound was 84.7 (95%CI, 66.9 - 107.2) per 10,000-person months of observation. The predictors of first viral rebound included; duration on ART (adjusted Time Ratio (TR), 1.04; 95%CI, 1.04-1.05; p<0.001), having psychosocial issues (adjusted TR, 0.67; 95%CI, 0.58-0.77; p<0.001), baseline viral load of <1000 (adjusted TR, 0.85; 95%CI, 0.72-0.99; p=0.008) and protease inhibitors (PI) based ART regimens (adjusted TR, 0.67; 95%CI, 0.49-0.92; p=0.012). The predictors of multiple rebounds included duration on ART (adjusted Hazard Ratio (HR), 0.86, 95%CI, 0.84-0.89; p<0.001), having psychosocial issues (adjusted HR, 11.04, 95%CI, 6.09-20.0; p<0.001), WHO clinical stage II (adjusted HR, 2.28, 95%CI, 1.22-4.25; p=0.002), and WHO clinical stage III (adjusted HR, 2.17, 95%CI, 1.14-4.14; p=0.005) ConclusionIn an urban HIV care facility in Kampala, we found an overall proportion of viral rebound among the adolescents of 31.5%. Occurrence of multiple viral rebounds was associated with duration on ART, psychosocial issues, and WHO clinical staging. Therefore, there is need to incorporate screening of adolescents for psychosocial challenges into the routine programming of HIV care and treatment so as identify and appropriately support those affected in time.