Viraemic-time predicts mortality among people living with HIV on second-line antiretroviral treatment in Myanmar: A retrospective cohort study

Abstract

Introduction: Despite HIV viral load (VL) monitoring being serial, most studies use a cross-sectional design to evaluate the virological status of a cohort. The objective of our study was to use a simplified approach to calculate viraemic-time: the proportion of follow-up time with unsuppressed VL above the limit of detection. We estimated risk factors for higher viraemic-time and whether viraemic-time predicted mortality in a second-line antiretroviral treatment (ART) cohort in Myanmar.

Methods: We conducted a retrospective cohort analysis of people living with HIV (PLHIV) who received second-line ART for a period >6 months and who had at least two HIV VL test results between 01 January 2014 and 30 April 2018. Fractional logistic regression assessed risk factors for having higher viraemic-time and Cox proportional hazards regression assessed the association between viraemic-time and mortality. Kaplan-Meier curves were plotted to illustrate survival probability for different viraemic-time categories.

Results: Among 1,352 participants, 815 (60.3%) never experienced viraemia, and 172 (12.7%), 214 (15.8%), and 80 (5.9%) participants were viraemic <20%, 20-49%, and 50-79% of their total follow-up time, respectively. Few (71; 5.3%) participants were ≥80% of their total follow-up time viraemic. The odds for having higher viraemic-time were higher among people with a history of injecting drug use (aOR 2.01, 95% CI 1.30-3.10, p = 0.002), sex workers (aOR 2.10, 95% CI 1.11-4.00, p = 0.02) and patients treated with lopinavir/ritonavir (vs. atazanavir; aOR 1.53, 95% CI 1.12-2.10, p = 0.008). Viraemic-time was strongly associated with mortality hazard among those with 50-79% and ≥80% viraemic-time (aHR 2.92, 95% CI 1.21-7.10, p = 0.02 and aHR 2.71, 95% CI 1.22-6.01, p = 0.01). This association was not observed in those with viraemic-time <50%.

Conclusions: Key populations were at risk for having a higher viraemic-time on second-line ART. Viraemic-time predicts clinical outcomes. Differentiated services should target subgroups at risk for a higher viraemic-time to control both HIV transmission and mortality.

Fig 1. Example of allocation of unsuppressed and suppressed time.

Cumulative unsuppressed or suppressed time was the time during which we assumed that a patient had HIV VL above or below the limit of detection, respectively. Follow-up time was defined as a sum of cumulative unsuppressed and suppressed time and started on the date of the first VL test and ended on the date of the last VL test plus 183 days. When two consecutive VL tests showed the same result, either viraemia or suppression, the time in between both tests was considered unsuppressed or suppressed. When two consecutive VL tests showed different results, the time in between both tests was divided in half, adding both unsuppressed and suppressed time. When the time between two VL tests was more than 365 days, a maximum of 183 days was added to either unsuppressed or suppressed time.

Fig 2. Flowchart for inclusion of participants in the study.

^aPLHIV: People living with HIV, ^bSL ART: Second-line antiretroviral treatment, ^c HIV VL: HIV viral load.

Fig 3. Distribution of participants by viraemic-time among those who experienced viraemia (N = 537).

Fig 4. Kaplan-Meier survival estimates by viraemic-time.