PLoS ONE (Jan 2022)

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

  • Anita Mesic,
  • Tom Decroo,
  • Htay Thet Mar,
  • Bart K M Jacobs,
  • Moe Pyae Thandar,
  • Thin Thin Thwe,
  • Aung Aung Kyaw,
  • Mitchell Sangma,
  • David Beversluis,
  • Elkin Bermudez-Aza,
  • Alexander Spina,
  • Darli Po Po Aung,
  • Erwan Piriou,
  • Koert Ritmeijer,
  • Josefien Van Olmen,
  • Htun Nyunt Oo,
  • Lutgarde Lynen

DOI
https://doi.org/10.1371/journal.pone.0271910
Journal volume & issue
Vol. 17, no. 7
p. e0271910

Abstract

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IntroductionDespite 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.MethodsWe 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.ResultsAmong 1,352 participants, 815 (60.3%) never experienced viraemia, and 172 (12.7%), 214 (15.8%), and 80 (5.9%) participants were viraemic ConclusionsKey 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.