METHODS AND FINDINGS: We reviewed all GenBank submissions of HIV-1 reverse transcriptase sequences with or without protease and identified 287 studies published between March 1, 2000, and December 31, 2013, with more than 25 recently or chronically infected ARV-naïve individuals. These studies comprised 50,870 individuals from 111 countries. Each set of study sequences was analyzed for phylogenetic clustering and the presence of 93 surveillance drug-resistance mutations (SDRMs). The median overall TDR prevalence in sub-Saharan Africa (SSA), south/southeast Asia (SSEA), upper-income Asian countries, Latin America/Caribbean, Europe, and North America was 2.8%, 2.9%, 5.6%, 7.6%, 9.4%, and 11.5%, respectively. In SSA, there was a yearly 1.09-fold (95% CI: 1.05-1.14) increase in odds of TDR since national ARV scale-up attributable to an increase in non-nucleoside reverse transcriptase inhibitor (NNRTI) resistance. The odds of NNRTI-associated TDR also increased in Latin America/Caribbean (odds ratio [OR] = 1.16; 95% CI: 1.06-1.25), North America (OR = 1.19; 95% CI: 1.12-1.26), Europe (OR = 1.07; 95% CI: 1.01-1.13), and upper-income Asian countries (OR = 1.33; 95% CI: 1.12-1.55). In SSEA, there was no significant change in the odds of TDR since national ARV scale-up (OR = 0.97; 95% CI: 0.92-1.02). An analysis limited to sequences with mixtures at less than 0.5% of their nucleotide positions—a proxy for recent infection—yielded trends comparable to those obtained using the complete dataset. Four NNRTI SDRMs—K101E, K103N, Y181C, and G190A—accounted for >80% of NNRTI-associated TDR in all regions and subtypes. Sixteen nucleoside reverse transcriptase inhibitor (NRTI) SDRMs accounted for >69% of NRTI-associated TDR in all regions and subtypes. In SSA and SSEA, 89% of NNRTI SDRMs were associated with high-level resistance to nevirapine or efavirenz, whereas only 27% of NRTI SDRMs were associated with high-level resistance to zidovudine, lamivudine, tenofovir, or abacavir. Of 763 viruses with TDR in SSA and SSEA, 725 (95%) were genetically dissimilar; 38 (5%) formed 19 sequence pairs. Inherent limitations of this study are that some cohorts may not represent the broader regional population and that studies were heterogeneous with respect to duration of infection prior to sampling.
CONCLUSIONS: Most TDR strains in SSA and SSEA arose independently, suggesting that ARV regimens with a high genetic barrier to resistance combined with improved patient adherence may mitigate TDR increases by reducing the generation of new ARV-resistant strains. A small number of NNRTI-resistance mutations were responsible for most cases of high-level resistance, suggesting that inexpensive point-mutation assays to detect these mutations may be useful for pre-therapy screening in regions with high levels of TDR. In the context of a public health approach to ARV therapy, a reliable point-of-care genotypic resistance test could identify which patients should receive standard first-line therapy and which should receive a protease-inhibitor-containing regimen.
METHODS: Of the 37 sites that participated in the randomised, open-label, non-inferiority SECOND-LINE study, eight sites from five countries (Argentina, India, Malaysia, South Africa, and Thailand) participated in the body composition substudy. All sites had a dual energy x-ray absorptiometry (DXA) scanner and all participants enrolled in SECOND-LINE were eligible for inclusion in the substudy. Participants were randomly assigned (1:1), via a computer-generated allocation schedule, to receive either ritonavir-boosted lopinavir plus raltegravir (raltegravir group) or ritonavir-boosted lopinavir plus two or three N(t)RTIs (N[t]RTI group). Randomisation was stratified by site and screening HIV-1 RNA. Participants and investigators were not masked to group assignment, but allocation was concealed until after interventions were assigned. DXA scans were done at weeks 0, 48, and 96. The primary endpoint was mean percentage and absolute change in peripheral limb fat from baseline to week 96. We did intention-to-treat analyses of available data. This substudy is registered with ClinicalTrials.gov, number NCT01513122.
FINDINGS: Between Aug 1, 2010, and July 10, 2011, we recruited 211 participants into the substudy. The intention-to-treat population comprised 102 participants in the N(t)RTI group and 108 participants in the raltegravir group, of whom 91 and 105 participants, respectively, reached 96 weeks. Mean percentage change in limb fat from baseline to week 96 was 16·8% (SD 32·6) in the N(t)RTI group and 28·0% (37·6) in the raltegravir group (mean difference 10·2%, 95% CI 0·1-20·4; p=0·048). Mean absolute change was 1·04 kg (SD 2·29) in the N(t)RTI group and 1·81 kg (2·50) in the raltegravir group (mean difference 0·6, 95% CI -0·1 to 1·3; p=0·10).
INTERPRETATION: Our findings suggest that for people with virological failure of a first-line regimen containing efavirenz plus tenofovir and lamivudine or emtricitabine, the WHO-recommended switch to a ritonavir-boosted protease inhibitor plus zidovudine (a thymidine analogue nucleoside reverse transcriptase inhibitor) and lamivudine might come at the cost of peripheral lipoatrophy. Further study could help to define specific groups of people who might benefit from a switch to an N(t)RTI-sparing second-line ART regimen.
FUNDING: The Kirby Institute and the Australian National Health and Medical Research Council.
DESIGN: We analyzed data from a community-recruited prospective cohort in Vancouver, Canada (n = 623), from 2014 to 2017.
METHODS: We used multivariable generalized mixed-effects analyses to estimate longitudinal factors associated with mean material security score. We then estimated the association between achieving at least 95% adherence to ART and overall mean material score, as well as mean score for three factors derived from a factor analysis. The three-factor structure, employed in the current analyses, were factor 1 (basic needs); factor 2 (housing-related variables) and factor 3 (economic resources).
RESULTS: Recent incarceration [β-coefficient (β) = -0.176, 95% confidence interval (95% CI): -0.288 to -0.063], unmet health needs [β = -0.110, 95% CI: -0.178 to -0.042), unmet social service needs (β = -0.264, 95% CI: -0.336 to -0.193) and having access to social services (β= -0.102, 95% CI: -0.1586 to -0.0465) were among the factors associated with lower material security scores. Contrary to expectations that low levels of material security in this population would lead to poor ART adherence, we did not observe a significant relationship between adherence and overall material security score, or for each factor individually.
CONCLUSION: Our findings highlight the potentially important role of no-cost, universal access to HIV prevention and treatment, in mitigating the impact of socioeconomic disadvantage on ART adherence.