Review 3: "Population Dynamics of HIV Drug Resistance among Pre-treatment and Treatment-experienced Persons with HIV during Treatment Scale-up in Uganda: A Population-based Longitudinal Study"

Anne–Mieke Vandamme; George Bwire

doi:doi:10.1162/2e3983f5.264e9c32

Population dynamics of HIV drug resistance among pre-treatment and treatment-experienced persons with HIV during treatment scale-up in Uganda: a population-based longitudinal study

by Michael A. Martin, Steven James Reynolds, Charles Ssuuna, Brian T. Foley, Fred Nalugoda, Thomas C. Quinn, Steven A. Kemp, Margaret Nakalanzi, Edward Nelson Kankaka, Godfrey Kigozi, Robert Ssekubugu, Ravindra K. Gupta, Lucie Abeler-Dörner, Joseph Kagaayi, Oliver Ratmann, Christophe Fraser, Ronald Moses Galiwango, David Bonsall, M. Kate Grabowski, and the PANGEA-HIV Consortium and the Rakai Health Sciences Program

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Published on Oct 15, 2023
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Abstract Background Longitudinal data on the population prevalence of HIV drug resistance during scale-up of HIV treatment in Africa are extremely limited. We estimated trends in HIV drug resistance prevalence during ART program expansion from a population-based surveillance cohort in southern Uganda.Methods We analyzed data from Rakai Community Cohort Study participants aged 15-49 during four survey rounds conducted between 2012 (round 15) and 2019 (round 19). Consenting participants were tested for HIV and completed questionnaires. Persons living with HIV (PLHIV) provided samples for viral load quantification and virus deep-sequencing. Sequence data were used to predict resistance profiles. The prevalence of class-specific resistance and resistance-conferring substitutions were estimated using robust log-Poisson regression.Findings 93,659 participant visits were contributed between 2012 and 2019, including 17,471 (18.65%) from PLHIV. Using deep-sequencing data from 3,713 pre-treatment participant-visits we estimated that the population prevalence of viremic NNRTI, NRTI, and PI resistance decreased significantly between 2012 and 2017 (PR = 0.38, 95% CI 0.25 – 0.57; 0.20, 95% CI 0.09 – 0.45; 0.19, 95% CI 0.09 – 0.39, respectively) with increasing viral suppression. Among viremic pre-treatment PLHIV, the prevalence of NNRTI resistance increased two-fold (PR = 1.96, 95% CI 1.31-2.95) to 9.77% (7.35% - 12.97%) over the same time period. We did not observe an increase in NRTI or PI resistance in this population. The 2017 prevalence of NNRTI and NRTI resistance among viremic treatment-experienced PLHIV was 47.67% (95% CI 40.94% - 55.50%) and 36.55% (95% CI 30.14% - 44.31%), respectively. Single-class resistance predominated among resistant pre-treatment PLHIV (83.05%) whereas most treatment-experienced resistance was multi-class (76.65%). In 2017, 10.13% (95% CI 7.83%-13.63%) and 9.98% (95% CI 6.43%-15.51%) of viremic pre-treatment and treatment-experienced PLHIV harbored the inT97A mutation.Interpretation Prevalence of HIV drug resistance among viremic PLHIV significantly increased with scale-up of ART programs. The prevalence of inT97A is potentially concerning considering the recent roll-out of dolutegravir-based regimens.Funding National Institutes of Health, the Bill & Melinda Gates Foundation, and the U.S. President’s Emergence Plan for AIDS Relief through the Centers for Disease Control and Prevention.Research in context Evidence before the study We searched PubMed for studies matching the keywords “hiv” “resistance” “longitudinal” “cohort” “population” published since 2004 (the beginning of antiretroviral therapy (ART) availability in sub-Saharan Africa) and identified 48 studies. We excluded 33 studies not based in sub-Saharan Africa, four studies primarily concerned with coinfection with other pathogens (e.g. HBV, M. tuberculosis), two studies concerned with insulin resistance, one sequencing-methods paper, and one paper concerned with host susceptibility to HIV infection. The remaining seven studies were not population-based meaning that the study population was not all persons but e.g. people living with HIV enrolled in care at a given clinic. We identified no previous longitudinal population-based cohort studies of HIV ART resistance in sub-Saharan Africa.Added value of this study We estimated the prevalence of drug resistance over four survey rounds of a population-based open-cohort study in southern Uganda between 2012 and 2019 during a period of intense treatment scale-up. We show that pre-treatment resistance to non-nucleoside reverse transcriptase inhibitors (NNRTIs) among pre-treatment PLHIV increased significantly during the scale-up of ART. We further show that among viremic treatment-experienced individuals 48% and 37% harbored resistance to NNRTIs and nucleoside-reverse transcriptase inhibitors (NRTIs), the majority of which harbored multiclass resistance. While drug resistance among people living with viremic HIV increased, the overall prevalence of viremic HIV drug resistance in the population decreased by about two-thirds due to increasing population viral load suppression. The most common resistance mutation in our population was inT97A, a known compensatory mutation for integrase strand transfer inhibitor (INSTI) resistance. In contrast to other mutations, presence of inT97A did not depend on treatment status.These results provide the first longitudinal population-based estimates of temporal trends in the prevalence of drug resistance during ART program expansion in a high-burden setting. Further, they provide critical insight into the landscape of prevalent drug resistance substitutions circulating in this population.Implications of all the available evidence Scale-up of HIV treatment has increased the prevalence of drug resistance mutations among viremic people living with HIV in sub-Saharan Africa. The relatively high prevalence of NNRTI resistance has prompted a recent shift to first-line regimens including dolutegravir (an INSTI) in combination with NRTIs. The high prevalence of an INSTI compensatory mutation in our population further warrants continuing monitoring of treatment failures and the prevalence of drug resistance in high burden settings.

RR:C19 Evidence Scale rating by reviewer:

Potentially informative. The main claims made are not strongly justified by the methods and data, but may yield some insight. The results and conclusions of the study may resemble those from the hypothetical ideal study, but there is substantial room for doubt. Decision-makers should consider this evidence only with a thorough understanding of its weaknesses, alongside other evidence and theory. Decision-makers should not consider this actionable, unless the weaknesses are clearly understood and there is other theory and evidence to further support it.

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Review:

As reviewers assessing the manuscript on the population dynamics of HIV drug resistance in Uganda, we find this work to be a commendable contribution to the field. The analysis of HIV drug resistance in pre-treatment and treatment-experienced individuals during the scale-up of treatment offers valuable insights into the complex landscape of HIV care and drug resistance in the region. Moreover, the contextualization of the study within Uganda’s treatment scale-up efforts adds substantial relevance to the broader discourse on HIV management strategies, both locally and the region.

We do have one major remark that is affecting all calculations and conclusions. Almost half of viral load measurements of round 15 are lacking while for the other rounds this is less than 1%. It is assumed that pre-treatment viral load for these missing data is viremic. This assumption influences the conclusions about trends in viremia and in drug resistance. The authors failed to make clear what the impact is of this assumption on the conclusions of this study.

Abstract

The interpretation section is the first instance where T97A and dolutegravir are mentioned together, without clarifying what the problem is with this variant. So from the abstract it is not clear why this variant is concerning. Perhaps clarify in the abstract somewhere that this variant is related to dolutegravir resistance as a polymorphic resistance-enhancing mutation, not as a major dolutegravir resistance mutation

Research in context

We find this section excellent.

Introduction

We find this section well written, structured, and provides the rationale for conducting this study.

Methods

Line 50, page 5: The authors should write the long form of RCCS as it appears for the first time.
Line 72 to 78, page 5: The authors should provide a sentence to justify the high missing rate. To what extent did these missing viral loads influence the results? 1,783/2,380 is not 100%, yet 100% of pre-treatment samples were assumed to be viraemic for the missing data of round 15, so how solid were these assumptions?
Were the missing viral loads missing samples? Or bad quality of the samples? Or missing information in the patient clinical records? Given that there is a mention of missing viral load, and not of missing samples to do viral load testing, this raises the doubt whether some of the data were retrospectively retrieved from patient clinical records rather than prospectively collected as part of the longitudinal study. If so, this needs to be clearly stated. In addition, if the problem is bad quality of samples, how did this impact the genetic testing of the same round, were these sample of sufficient quality?

Results

The authors should perform a sensitivity analysis for assuming the missing viral load for pre-treatment PLHIV in round 15 as viraemic.
The association between missing genotype data and missing viral loads would suggest that there may be a problem with the assumption that all pre-treatment viral loads in round 15 are viraemic. How solid then is the observation that population prevalence of pre-treatment viremia is decreasing between rounds 15 and 18 (line 208)? Would it not be better to just discard the pre-treatment viral load data for round 15? What would remain of the statement “These declines were accompanied by a nearly nine-fold decrease in the population prevalence of pre-treatment viremia over the study” (line 174-175). What would remain of the decrease in population prevalence of resistance (lines 209-2011) and of prevalence of resistance among PLHIV (lines 228-230)?

Discussion

The authors should include in the limitations of the study the impact of the missing viral loads for round 15, and of the assumption that missing viral load for pre-treatment PLHIV in round 15 were viraemic. How solid are the main conclusions if the round 15 pre-treatment viral load data are excluded?
Considering the timeline of data collection in relation to the introduction or changes in treatment protocols, the authors should add to the limitations of the study a remark about how representative or applicable the data are to the present scenario involving dolutegravir-based regimen
The authors should add considerations of the meaning of the results in the context of the introduction of dolutegravir based regimen in the study area. The reader might not know to what extent dolutegravir is used and which drugs are combined with dolutegravir. For example, data on NNRTI resistance is not relevant for a dolutegravir-containing regimen as NNRTIs are not used in such a combination. In other neighboring countries, all first line regimens currently contain dolutegravir.

Review 3: "Population Dynamics of HIV Drug Resistance among Pre-treatment and Treatment-experienced Persons with HIV during Treatment Scale-up in Uganda: A Population-based Longitudinal Study"

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