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  1. Phanuphak P, Sirivichayakul S, Jiamsakul A, Sungkanuparph S, Kumarasamy N, Lee MP, et al.
    J Acquir Immune Defic Syndr, 2014 May 01;66(1):74-9.
    PMID: 24413039 DOI: 10.1097/QAI.0000000000000108
    BACKGROUND: We compared treatment outcomes of transmitted drug resistance (TDR) in patients on fully or partially sensitive drug regimens.

    METHODS: Factors associated with survival and failure were analyzed using Cox proportional hazards and discrete time conditional logistic models.

    RESULTS: TDR, found in 60 (4.1%) of 1471 Asian treatment-naive patients, was one of the significant predictors of failure. Patients with TDR to >1 drug in their regimen were >3 times as likely to fail compared to no TDR.

    CONCLUSIONS: TDR was associated with failure in the context of non-fully sensitive regimens. Efforts are needed to incorporate resistance testing into national treatment programs.

  2. Sungkanuparph S, Oyomopito R, Sirivichayakul S, Sirisanthana T, Li PC, Kantipong P, et al.
    Clin Infect Dis, 2011 Apr 15;52(8):1053-7.
    PMID: 21460324 DOI: 10.1093/cid/cir107
    Of 682 antiretroviral-naïve patients initiating antiretroviral therapy in a prospective, multicenter human immunodeficiency virus type 1 (HIV-1) drug resistance monitoring study involving 8 sites in Hong Kong, Malaysia, and Thailand, the prevalence of patients with ≥1 drug resistance mutation was 13.8%. Primary HIV drug resistance is emerging after rapid scaling-up of antiretroviral therapy use in Asia.
  3. Jiamsakul A, Chaiwarith R, Durier N, Sirivichayakul S, Kiertiburanakul S, Van Den Eede P, et al.
    J Med Virol, 2016 Feb;88(2):234-43.
    PMID: 26147742 DOI: 10.1002/jmv.24320
    HIV drug resistance assessments and interpretations can be obtained from genotyping (GT), virtual phenotyping (VP) and laboratory-based phenotyping (PT). We compared resistance calls obtained from GT and VP with those from PT (GT-PT and VP-PT) among CRF01_AE and subtype B HIV-1 infected patients. GT predictions were obtained from the Stanford HIV database. VP and PT were obtained from Janssen Diagnostics BVBA's vircoType(TM) HIV-1 and Antivirogram®, respectively. With PT assumed as the "gold standard," the area under the curve (AUC) and the Bland-Altman plot were used to assess the level of agreement in resistance interpretations. A total of 80 CRF01_AE samples from Asia and 100 subtype B from Janssen Diagnostics BVBA's database were analysed. CRF01_AE showed discordances ranging from 3 to 27 samples for GT-PT and 1 to 20 samples for VP-PT. The GT-PT and VP-PT AUCs were 0.76-0.97 and 0.81-0.99, respectively. Subtype B showed 3-61 discordances for GT-PT and 2-75 discordances for VP-PT. The AUCs ranged from 0.55 to 0.95 for GT-PT and 0.55 to 0.97 for VP-PT. Didanosine had the highest proportion of discordances and/or AUC in all comparisons. The patient with the largest didanosine FC difference in each subtype harboured Q151M mutation. Overall, GT and VP predictions for CRF01_AE performed significantly better than subtype B for three NRTIs. Although discrepancies exist, GT and VP resistance interpretations in HIV-1 CRF01_AE strains were highly robust in comparison with the gold-standard PT.
  4. Rhee SY, Blanco JL, Jordan MR, Taylor J, Lemey P, Varghese V, et al.
    PLoS Med, 2015 Apr;12(4):e1001810.
    PMID: 25849352 DOI: 10.1371/journal.pmed.1001810
    BACKGROUND: Regional and subtype-specific mutational patterns of HIV-1 transmitted drug resistance (TDR) are essential for informing first-line antiretroviral (ARV) therapy guidelines and designing diagnostic assays for use in regions where standard genotypic resistance testing is not affordable. We sought to understand the molecular epidemiology of TDR and to identify the HIV-1 drug-resistance mutations responsible for TDR in different regions and virus subtypes.

    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.

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