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Human Immunodeficiency Virus Drug Resistance: 2018 Recommendations of the International Antiviral Society–USA Panel

Huldrych F Günthard, Vincent Calvez, Roger Paredes and 5 more

Clinical Infectious Diseases · 2018 · CC BY

doi:10.1093/cid/ciy463

Abstract

Background. Contemporary antiretroviral therapies (ART) and management strategies have diminished both human immunodeficiency virus (HIV) treatment failure and the acquired resistance to drugs in resource-rich regions, but transmission of drug-resistant viruses has not similarly decreased. In low- and middle-income regions, ART roll-out has improved outcomes, but has resulted in increasing acquired and transmitted resistances. Our objective was to review resistance to ART drugs and methods to detect it, and to provide updated recommendations for testing and monitoring for drug resistance in HIV-infected individuals.

Methods. A volunteer panel of experts appointed by the International Antiviral (formerly AIDS) Society–USA reviewed relevant peer-reviewed data that were published or presented at scientific conferences. Recommendations were rated according to the strength of the recommendation and quality of the evidence, and reached by full panel consensus.

Results. Resistance testing remains a cornerstone of ART. It is recommended in newly-diagnosed individuals and in patients in whom ART has failed. Testing for transmitted integrase strand-transfer inhibitor resistance is currently not recommended, but this may change as more resistance emerges with widespread use. Sanger-based and next-generation sequencing approaches are each suited for genotypic testing. Testing for minority variants harboring drug resistance may only be considered if treatments depend on a first-generation nonnucleoside analogue reverse transcriptase inhibitor. Different HIV-1 subtypes do not need special considerations regarding resistance testing.

Conclusions. Testing for HIV drug resistance in drug-naive individuals and in patients in whom antiretroviral drugs are failing, and the appreciation of the role of testing, are crucial to the prevention and management of failure of ART.

Full text

From PubMed Central, U.S. National Library of Medicine, as current on Oct 22, 2026. Paragraph numbers are ours, so an answer can point at one.

Human immunodeficiency virus (HIV) drug resistance is an important contributor to failure of antiretroviral therapies (ART). In resource-rich regions, acquired HIV drug resistance as a result of treatment failure has diminished with the availability of better drugs and better monitoring for treatment failure and drug resistant viruses. Transmission of drug-resistant virus, however, persists at prevalences of around 10% in resource-rich countries. The rollout of ART in low- and middle-income countries (LMIC) reduced morbidity and mortality, but over the last few years prevalences of 10% or higher of transmitted drug resistance (TDR) have been reached in some countries.

This report examines recent information regarding HIV drug resistance in resource-rich and LMIC, and provides updated recommendations. Drug-resistant mutations (DRMs) that impact treatment responses are updated regularly. Implementation of next-generation sequencing methods is increasing and has changed approaches to drug resistance testing. These new approaches, and the insights they provide (eg, minority drug-resistant variants), are also addressed. Table 1 provides a summary of definitions of terms relevant for HIV drug resistance.

Prevalence of Transmitted Drug Resistance in Resource-rich Countries

Recommendations are provided in Appendix Box 1. TDR has been observed in virtually all countries where drug-resistance testing has been performed. Frequencies vary substantially over time and by country. The prevalence of TDR is highest for nucleoside analogue reverse transcriptase inhibitors (nRTIs) and nonnucleoside analogue reverse transcriptase inhibitors (NNRTIs); is lower for protease inhibitors (PIs); and, so far, is rare for integrase strand transfer inhibitors (InSTIs). Frequencies may vary by location and time of testing. Table 2 summarizes the prevalence of TDR in some recent studies in seroconverter cohorts or in drug-naive individuals.

The prevalence of TDR ranged from 6.6% to 11% and time trends seem to be rather stable, except in the United Kingdom, where TDR prevalence peaked in 2002 at 14% and dropped to 8% to 9% in 2009 and to 6.6% in 2013. In the Swiss HIV Cohort Study, the yearly TDR prevalence in recently infected patients fluctuated between 2.2% and 15.5% from 2000 to 2013, attributed in part to the introduction of new drugs (eg, boosted PIs in 2000 and InSTIs in 2008), after which substantial transient declines occurred. Data on the transmission of InSTI resistances are scant. The larger studies, to date from the Swiss HIV Cohort Study and the United Kingdom, did not find any transmitted major InSTI DRMs since the class was introduced in 2007, despite the fact that thousands of patients are being treated with these drugs. Anecdotal cases, however, have been reported. Thus, as seen for all drugs used at high frequency, InSTI TDR likely will increase over time.

Prevalence of Transmitted or Pretreatment Drug Resistance in Low- and Middle-income Countries

With expanding use of ART in LMIC, acquired and transmitted drug resistance have increased. It is increasingly recognized that a considerable proportion of detected DRMs in individuals in LMIC, previously assumed to be ART-naive, resulted from undisclosed exposure to earlier ART, rather than TDR. Thus in LMIC, pretreatment drug resistance (PDR) data are more feasible to collect than TDR data, and remain important for treatment decisions.

Table 3 summarizes selected recent studies of PDR in LMIC. Surveillance conducted by the World Health Organization (WHO) between 2015 and 2016 in 11 countries from Africa, middle/south America, and Asia found that Uganda, Namibia, Zimbabwe, Nicaragua, Guatemala, and Argentina were above the critically-defined NNRTI TDR/PDR threshold of 10%. A meta-analysis of 56044 adults with HIV infection from 64 LMIC estimated annual increases of the odds of PDR for NNRTIs of 23% (95% confidence interval [CI], 16–29) in southern Africa, 17% (95% CI, 5–30) in eastern Africa, 17% (95% CI, 6–29) in western and central Africa, 11% (95% CI, 5–18) in Latin America and the Caribbean, and 11% (95% CI, 2–20) in Asia. Estimated absolute increases in prevalence of PDR between 2015 and 2016 ranged from 0.3% in Asia to 1.8% in southern Africa.

A meta-analysis that included 19 studies, representing 2617 children from 13 countries, found a prevalence of PDR of 42.7% in children exposed to ART as treatment for prevention of mother-to-child transmission (PMTCT) and 12.7% among children not exposed to PMTCT treatment. The prevalence of TDR in children not exposed rose from 0% in 2004 to 26.8% in 2013. NNRTI mutations were found in 32.4% of PMTCT treatment–exposed and in 9.7% of PMTCT treatment–unexposed children. Representative data on PDR prevalences are limited in LMIC, and thus prevalences are likely underestimated.

Factors Associated With Transmission

In Switzerland and the United Kingdom, the major source of TDR in men who have sex with men are ART-naïve, HIV-1–infected individuals. This unexpected finding is due to some DRMs with low fitness cost; fitness cost is defined as reduced ability of a virus to replicate in the absence of the drug. For example, both the DRM L90M, conferring resistance to PIs, and the DRM K103N, conferring resistance to NNRTIs, have low fitness costs and persist for prolonged periods after transmission; they are prevalent in this population. Generally, drug-resistant viruses will be gradually replaced by fitter viruses in the absence of drug pressure; the rate of replacement depends on the degree of the fitness cost. The sources of most transmissions are individuals with acute or recent infections. Recommendations to treat all HIV-1–infected individuals, including patients diagnosed early after infection, have been inadequately implemented to optimally reduce new transmissions.

Transmission of Minority Variants Harboring Drug-resistant Mutations

Recommendations are given in Appendix Box 2. In 70% to 90% of acute HIV-1 infections, single-virus variants are detected. However, in 10% to 30%, minority variants are transmitted, often at very low frequencies. Minority variants harboring DRMs have been identified in drug-naive and primary infection populations.

Minority variants harboring DRMs have not been shown to negatively affect treatment responses in acutely-infected patients; however, in some studies they modestly reduced treatment success in chronically-infected drug-naive patients receiving first-generation NNRTI (efavirenz or nevirapine)-based treatment. More information on minority variants and the relevance of cut-offs to detect different frequencies of variants harboring DRMs is available in the Supplementary Data.

EMERGENCE OF RESISTANCE WITH LOW-LEVEL VIREMIA

Recommendations are given in Appendix Box 3. Suppression of HIV ribonucleic acid (RNA) below limits of quantification is the objective of ART. Detectable viremia during ART between the limits of the assay quantification (20 to 50 copies/mL) and 1000 copies/mL is generally referred to as a low-level viremia (LLV). An LLV that is transient and only observed in a single measurement followed by subsequent undetectable viral load is termed a viral blip. A detectable viremia below the limit of quantification is referred to as a residual viremia or very LLV. The source and clinical relevance of very LLV and viral blips are unknown. LLV and blips may reflect technical variability or real biologic processes. A proposed mechanism is the release of a virus from activated, latently-infected cells that, in the presence of ART, does not result in active rounds of virus replication. Low levels of ongoing virus replication due to poor adherence or insufficient drug penetration in certain tissues and anatomical compartments may also occur.

Drug resistance can emerge in patients with an HIV-1 RNA below 1000 copies/mL. Studies have utilized different thresholds for LLV and different criteria for resistance; however, each confirmed that drug resistance can emerge at low levels of HIV replication, in the range of 50 to 200 copies/mL, with increased risk at higher levels in the presence of the selective pressure of ART.

Although resistance assay kits are only approved by the Food and Drug Administration for HIV RNA levels above 1000 copies/mL, resistance testing is feasible at lower ranges of viremia. During polymerase chain reaction amplification, more plasma can be used to increase the amount of HIV RNA extracted. The Supplementary Data summarizes existing data on the relevance of LLV and blips in treated individuals in more detail.

EFFECT OF SUBTYPE ON HIV-1 DRUG RESISTANCE

Recommendations are given in Appendix Box 4. HIV-1 group M viruses have evolved into numerous subtypes and circulating recombinant forms, differing from each other by approximately 12% in HIV-1 pol. Subtype B viruses account for about 10% overall, but have been disproportionately studied, as they are the predominant subtype in North America and Europe. As ART has expanded globally, the effect of subtype on HIV-1 drug resistance has received increasing attention.

Virtually all amino acid differences between subtypes are polymorphisms: variants that occur commonly in the absence of therapy and have little, if any, phenotypic or clinical effect on antiretroviral drugs (ARVs). Thus, most studies suggest that individual ARVs and standard ART regimens are similarly active, regardless of subtype. Increased risk of virologic failure has been associated with particular subtypes, but most studies are confounded by geographic location, treatment facilities, and clinical, social, and economic statuses that could affect outcome differences among individuals infected with different subtypes.

HIV-2 infects more than 1 million persons, most of whom reside in or have emigrated from West Africa. It differs from HIV-1 by more than 50% of its genome. HIV-2 is intrinsically resistant to NNRTIs and is variably susceptible to PIs. The potential impact of different subtypes on ART outcomes is discussed in the Supplementary Data.

METHODS FOR HIV-1 RESISTANCE TESTING

Recommendations are given in Appendix Box 5.

Resistance Test Options

In most situations, genotypic testing for resistance is the test of choice because it is faster, less expensive, and sufficient to predict drug susceptibility. Phenotypic testing is more expensive, technically demanding, and requires a highly-specialized laboratory infrastructure, but is recommended in certain situations. Methodologic aspects and challenges of resistance testing are described in the Supplementary Data.

The bulk of evidence associating resistance with clinical outcomes has been generated with sequencing of plasma HIV RNA. For individuals with LLV (ie, <200 copies/mL), sequencing of peripheral blood mononuclear cell (PBMC) DNA is technically feasible and more likely to provide an HIV genotype than plasma. However, PBMCs contain HIV DNA that has been archived throughout the patient’s infection, and may be discordant with plasma testing. Clinicians should judge results from PBMC testing with caution. More detailed discussion on proviral DNA sequencing is provided in the Supplementary Data.

Recommended Genomic Regions for Sequencing

To determine what new regimen to use for patients in whom ART is failing, the protease and the first half of the reverse transcriptase (up to at least nucleotide 215) should be sequenced. If an InSTI-containing treatment has failed, integrase should be sequenced. Although of interest for better understanding of patterns at time of failure, baseline InSTI resistance testing is currently not cost-effective, as transmitted InSTI resistance is infrequent. Baseline InSTI resistance testing should be considered, however, in select patients with evidence of TDR, such as those with nRTI- or multi-class resistances. In such patients, the risk of also having transmitted InSTI resistance is likely to be higher than in patients without TDR, and the consequences of virologic failure on an InSTI-containing initial regimen may be more severe.

Sequencing of other regions (C-terminus of reverse transcriptase, group-specific antigen) or even a near-full length of HIV-1 might be useful in research settings. Sequencing of the third variable loop (V3) of the envelope glycoprotein, gp120, can determine whether a virus is R5 tropic, and thus might respond to inclusion of a chemokine receptor 5 (CCR5) antagonist in ART. Genotypic tropism testing performance might be comparable to phenotypic tropism assays, particularly when NGS is used. However, testing for genotypic tropism from the PBMC compartment is less accurate than plasma testing. A more detailed discussion of entry inhibitor resistance and novel drug formulations is available in the Supplementary Data.

Genotypic Resistance Test Interpretation

Genotypic test results require an interpretation, because there are many DRMs that often arise in complex patterns and cause varying levels of reduced drug susceptibilities. Genotypic test interpretation systems are either rule-based or machine-learning systems. Rule-based systems require a knowledge base and a set of derived rules. The knowledge base usually comprises studies of whether a drug selects a DRM in vitro or in patients, whether a DRM reduces drug susceptibility in site-directed mutants or clinical isolates, and whether a DRM is associated with reduced virologic response to a regimen containing a specific ARV. Virologic response studies have usually been performed in the context of clinical trials. Such studies have assessed the effect of nRTI-associated DRMs on virologic responses to regimens containing abacavir or tenofovir disoproxil fumarate; PI-associated DRMs on responses to regimens containing lopinavir/ritonavir and darunavir/ritonavir; NNRTI-associated DRMs on responses to regimens containing etravirine; and InSTI-associated DRMs on responses to regimens containing dolutegravir.

Rule-based systems are more commonly used for interpretation, because they consider diverse forms of data and incorporate expert opinions. These systems are reproducible, transparent, and educational, but subjective. Well-described rule-based systems include those from the French National Agency for Research on AIDS and Viral Hepatitis, Rega, HIV Genotypic Resistance-Algorithm Deutschland, and the Stanford HIV Drug Resistance Database. Although these systems may produce somewhat different estimates of drug resistance for the same drug, their predictive ability generally has been similar. An online system for interpreting HIV-2 sequences has also been developed.

Machine-learning systems use datasets containing large amounts of data; for example, correlating DRMs in a sequence with reduced susceptibility or with virologic response to a new treatment regimen. With sufficiently large numbers of such correlations, these systems can use genotypic data to predict fold-reductions in susceptibility or the likelihood of virologic suppression with a new regimen.

Interpretation of Phenotypic Resistance Tests

Phenotypic test results require interpretation, because the clinical significance of fold-change reductions in susceptibility differs among drugs. Interpretation of these results usually requires studies that indicate cutoff values for each drug: the fold-reduction in drug susceptibility that exceeds the uppermost values for wild-type viruses (biologic cutoff); the lowest fold-reduction in susceptibility that indicates reduced likelihood of responding to therapy with a drug (lower clinical cutoff); and the lowest fold-reduction in susceptibility that indicates a drug will likely be completely inactive (upper clinical cutoff). Clinical cutoff values for an ARV are assay-dependent, and therefore need to be established for each phenotypic assay used in a clinical setting.

Limitations of Drug Resistance Interpretation Systems

Genotypic and phenotypic test interpretations cannot provide specific treatment recommendations, because they do not integrate all data required for therapy selection, such as treatment history, previous resistance test results, minority variants harboring DRM archived in the latent reservoirs, plasma HIV-1 RNA level, CD4+ cell count, pharmacologic interactions, hepatic and renal status, or the likelihood of adherence. Interpretation systems vary in how they account for differences in potencies of different ARVs, and do not incorporate fundamental principles of how specific regimens should be constructed. Therefore, clinicians must either have a sound understanding of the principles of therapy to optimally use results of drug resistance tests or have access to expertise. An extended discussion on interpretation systems is available in the Supplementary Data.

CLINICAL APPLICATIONS AND RECOMMENDATIONS

Table 4 summarizes in whom and when genotypic resistance testing should be performed. With the recent recommendations to initiate therapy with an InSTI, the current likelihood of a compromising DRM is low. Regardless, even if treatment is initiated quickly, adjustments can be made within days if test results so indicate. The HIV-1 RNA threshold of 200 copies/mL is a technical limit; that is, the minimum copy number at which the likelihood of obtaining a test result is above 70%. HIV genotyping below 200 copies/mL may produce clinically meaningful data, but the chance of obtaining an interpretable genotype may be too low for routine clinical use. Access to drug resistance testing may be limited by economic constraints or local technical capacity

USE OF GENETIC SEQUENCES FOR OTHER PURPOSES

With routine use of resistance testing for clinical purposes in the late 1990s, it became possible to establish large sequence databases. Linking sequences to clinical and epidemiologic data provides a public health infrastructure to monitor transmission of drug resistance and the risk conferred by the emergence of resistance on therapy. These approaches have also defined and validated clinical interpretations of drug resistance, such as those described earlier.

Large HIV genetic databases have also facilitated the application of increasingly sophisticated phylogenetic-based analyses to assess dynamics of virus spread, taking advantage of the inherent variation between sampled viral sequences. This approach has uncovered key characteristics of the epidemic, particularly where the density of sampling (eg, the proportion of infected individuals represented by viral sequence) has been high. Use of large-scale viral sequences for purposes other than resistance testing is described in the Supplementary Data.

SUMMARY AND FUTURE DIRECTIONS

Despite the unprecedented global rollout and success of ART, drug resistance continues to emerge with treatment failure, and TDR persists. Divergent patterns of resistance between resource-rich and -limited settings have evolved. In the former, resistance testing, viral load monitoring, and access to care and to ART have resulted in a continuing decrease of acquired drug resistance and stable rates of TDR. In contrast, in LMIC, limited availability of drugs and inadequate monitoring of and acting on viral load and drug resistance has contributed to a steep increase in drug resistance. New strategies, such as starting with regimens with greater potency and genetic barriers (eg, with InSTIs), providing increased options for second- and third-line regimens, implementing viral load testing to identify virologic failures early, and raising capacities for resistance testing at baseline and after treatment failure are prerequisites to secure long-term global success of ART.

Since the last report, recommendations to initiate ART have fundamentally changed; all individuals with HIV infections should be treated as early as possible after infection, regardless of CD4+ count. Concerns that large-scale earlier treatment initiation would give rise to more resistance has not been confirmed in resource-rich settings; in fact, resistance emergence decreases with earlier treatment initiation.

This report is primarily written for settings that have access to resistance testing for HIV patient management, whereas most people with HIV live in LMIC, where most HIV drug resistance testing is applied to epidemiologic monitoring. Available data on prevalence and TDR or PDR in LMIC are limited and delayed, thus often underestimating those numbers.

In conclusion, testing for HIV drug resistance, and the appreciation of its role, is crucial to the prevention and management of failure of ART.

Supplementary Data

Supplementary materials are available at Clinical Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.

References 113

  1. 1.

    Scherrer AU, von Wyl V, Yang WL, et al; Swiss HIV Cohort Study. Emergence of acquired HIV-1 drug resistance almost stopped in Switzerland: a 15-year prospective cohort analysis. Clin Infect Dis2016; 62:1310–7.

    Not in our library10.1093/cid/ciw128

  2. 2.

    World Health Organization. Consolidated guidelines on the use of antiretroviral drugs for treating and preventing HIV infection. Recommendations for a public health approach Available at: http://www.who.int/hiv/pub/arv/arv-2016/en/. Accessed 4 January 2017.

    Not in our library

  3. 3.
  4. 4.

    Gupta RK, Jordan MR, Sultan BJ, et al Global trends in antiretroviral resistance in treatment-naive individuals with HIV after rollout of antiretroviral treatment in resource-limited settings: a global collaborative study and meta-regression analysis. Lancet2012; 380:1250–8.

    Not in our library10.1016/s0140-6736(12)61038-1

  5. 5.
  6. 6.

    Stadeli KM, Richman DD Rates of emergence of HIV drug resistance in resource-limited settings: a systematic review. Antivir Ther2013; 18:115–23.

    Not in our library10.3851/imp2437

  7. 7.

    Hamers RL, Wallis CL, Kityo C, et al; PharmAccess African Studies to Evaluate Resistance HIV-1 drug resistance in antiretroviral-naive individuals in sub-Saharan Africa after rollout of antiretroviral therapy: a multicentre observational study. Lancet Infect Dis2011; 11:750–9.

    Not in our library10.1016/s1473-3099(11)70149-9

  8. 8.

    Hirsch MS, Günthard HF, Schapiro JM, et al Antiretroviral drug resistance testing in adult HIV-1 infection: 2008 recommendations of an International AIDS Society–USA panel. Clin Infect Dis2008; 47:266–85.

    Not in our library10.1086/589297

  9. 9.

    Wensing AM, Calvez V, Günthard HF, et al 2017 Update of the drug resistance mutations in HIV-1. Top Antivir Med2017; 24:132–3.

    Not in our library

  10. 10.

    Hofstra LM, Sauvageot N, Albert J, et al; SPREAD Program Transmission of HIV drug resistance and the predicted effect on current first-line regimens in Europe. Clin Infect Dis2016; 62:655–63.

    Not in our library10.1093/cid/civ963

  11. 11.

    Hauser A, Hofmann A, Hanke K, et al National molecular surveillance of recently acquired HIV infections in Germany, 2013 to 2014. Euro Surveill2017; 22:30436.

    Not in our library10.2807/1560-7917.es.2017.22.2.30436

  12. 12.

    Tostevin A, White E, Dunn D, et al; UK HIV Drug Resistance Database Recent trends and patterns in HIV-1 transmitted drug resistance in the United Kingdom. HIV Med2017; 18:204–13.

    Not in our library10.1111/hiv.12414

  13. 13.

    Frange P, Assoumou L, Descamps D, et al; French ANRS CO 6 PRIMO Cohort, the ANRS 147 OPTIPRIM Clinical Trial and the AC11 Resistance Study Groups; French ANRS CO 6 PRIMO Cohort the ANRS 147 OPTIPRIM Clinical Trial and the AC11 Resistance Study Groups HIV-1 subtype B-infected MSM may have driven the spread of transmitted resistant strains in France in 2007-12: impact on susceptibility to first-line strategies. J Antimicrob Chemother2015; 70:2084–9.

    Not in our library10.1093/jac/dkv049

  14. 14.

    Baxter JD, Dunn D, White E, et al; International Network for Strategic Initiatives in Global HIV Trials (INSIGHT) START Study Group Global HIV-1 transmitted drug resistance in the INSIGHT Strategic Timing of AntiRetroviral Treatment (START) trial. HIV Med2015; 16(Suppl 1):77–87.

    Not in our library10.1111/hiv.12236

  15. 15.

    Olson A, Bannert N, Sönnerborg A, et al; for CASCADE Collaboration in EuroCoord Temporal trends of transmitted HIV drug resistance in a multinational seroconversion cohort. AIDS2018; 32:161–9.

    Not in our library10.1097/qad.0000000000001689

  16. 16.

    Scherrer AU, Yang WL, Kouyos RD, et al; Swiss HIV Cohort Study Successful prevention of transmission of integrase resistance in the Swiss HIV Cohort Study. J Infect Dis2016; 214:399–402.

    Not in our library10.1093/infdis/jiw165

  17. 17.

    Stekler JD, McKernan J, Milne R, et al Lack of resistance to integrase inhibitors among antiretroviral-naive subjects with primary HIV-1 infection, 2007-2013. Antivir Ther2015; 20:77–80.

    Not in our library10.3851/imp2780

  18. 18.

    Mourad R, Chevennet F, Dunn DT, et al; UK HIV Drug Resistance Database & the Collaborative HIV, Anti-HIV Drug Resistance Network A phylotype-based analysis highlights the role of drug-naive HIV-positive individuals in the transmission of antiretroviral resistance in the UK. AIDS2015; 29:1917–25.

    Not in our library10.1097/qad.0000000000000768

  19. 19.

    Dolling D, Sabin C, Delpech V, et al Time trends in drug resistant HIV-1 infections in the United Kingdom up to 2009: multicentre observational study. BMJ2012; 345:e5253.

    Not in our library10.1136/bmj.e5253

  20. 20.

    Yang WL, Kouyos R, Scherrer AU, et al; Swiss HIV Cohort Study Assessing the paradox between transmitted and acquired HIV Type 1 drug resistance mutations in the Swiss HIV Cohort Study from 1998 to 2012. J Infect Dis2015; 212:28–38.

    Not in our library10.1093/infdis/jiv012

  21. 21.

    Boyd SD, Maldarelli F, Sereti I, et al Transmitted raltegravir resistance in an HIV-1 CRF_AG-infected patient. Antivir Ther2011; 16:257–61.

    Not in our library10.3851/imp1749

  22. 22.

    Hernandez AL, Ocfemia MCB, Saduvala N, et al HIV integrase genotypic testing and resistance in the United States--9 jurisdictions (abstract 478). In: Program and Abstracts of the Conference on Retroviruses and Opportunistic Infections (2017) Seattle, Washington.

    Not in our library

  23. 23.

    World Health Organization. Guidelines on the public health response to pretreatment HIV drug resistance: supplement to the 2016 consolidated guidelines on the use of antiretroviral drugs for treating and preventing HIV infection. 2nd ed. 2016 Available at: http://apps.who.int/iris/bitstream/10665/255880/1/9789241550055-eng.pdf?ua=1. Accessed 6 September 2017.

    Not in our library

  24. 24.

    Boerma RS, Sigaloff KC, Akanmu AS, et al Alarming increase in pretreatment HIV drug resistance in children living in sub-Saharan Africa: a systematic review and meta-analysis. J Antimicrob Chemother2017; 72:365–71.

    Not in our library10.1093/jac/dkw463

  25. 25.

    Drescher SM, von Wyl V, Yang WL, et al; Swiss HIV Cohort Study Treatment-naive individuals are the major source of transmitted HIV-1 drug resistance in men who have sex with men in the Swiss HIV Cohort Study. Clin Infect Dis2014; 58:285–94.

    Not in our library10.1093/cid/cit694

  26. 26.

    Yang WL, Kouyos RD, Böni J, et al; Swiss HIV Cohort Study Persistence of transmitted HIV-1 drug resistance mutations associated with fitness costs and viral genetic backgrounds. PLoS Pathog2015; 11:e1004722.

    Not in our library10.1371/journal.ppat.1004722

  27. 27.

    Marzel A, Shilaih M, Yang WL, et al; Swiss HIV Cohort Study HIV-1 transmission during recent infection and during treatment interruptions as major drivers of new infections in the Swiss HIV Cohort Study. Clin Infect Dis2016; 62:115–22.

    Not in our library10.1093/cid/civ732

  28. 28.

    Brenner BG, Roger M, Routy JP, et al; Quebec Primary HIV Infection Study Group High rates of forward transmission events after acute/early HIV-1 infection. J Infect Dis2007; 195:951–9.

    Not in our library10.1086/512088

  29. 29.

    Hollingsworth TD, Anderson RM, Fraser C HIV-1 transmission, by stage of infection. J Infect Dis2008; 198:687–93.

    Not in our library10.1086/590501

  30. 30.

    Thompson MA, Aberg JA, Cahn P, et al; International AIDS Society–USA. Antiretroviral treatment of adult HIV infection: 2010 recommendations of the International AIDS Society–USA panel. JAMA2010; 304:321–33.

    Not in our library10.1001/jama.2010.1004

  31. 31.

    Thompson MA, Aberg JA, Hoy JF, et al Antiretroviral treatment of adult HIV infection: 2012 recommendations of the International Antiviral Society–USA panel. JAMA2012; 308:387–402.

    Not in our library10.1001/jama.2012.7961

  32. 32.

    Günthard HF, Aberg JA, Eron JJ, et al; International Antiviral Society–USA Panel Antiretroviral treatment of adult HIV infection: 2014 recommendations of the International Antiviral Society–USA Panel. JAMA2014; 312:410–25.

    Not in our library10.1001/jama.2014.8722

  33. 33.

    Günthard HF, Saag MS, Benson CA, et al Antiretroviral drugs for treatment and prevention of HIV infection in adults: 2016 recommendations of the International Antiviral Society–USA panel. JAMA2016; 316:191–210.

    Not in our library10.1001/jama.2016.8900

  34. 34.

    Ryom L, Boesecke C, Gisler V, et al; EACS Governing Board Essentials from the 2015 European AIDS Clinical Society (EACS) guidelines for the treatment of adult HIV-positive persons. HIV Med2016; 17:83–8.

    Not in our library10.1111/hiv.12322

  35. 35.

    Panel on Antiretroviral Guidelines for Adults and Adolescents. Guidelines for the use of antiretroviral agents in HIV-1-infected adults and adolescents. Department of Health and Human Services Available at: http://aidsinfo.nih.gov/contentfiles/lvguidelines/adultandadolescentgl.pdf. Accessed 20 February 2018.

    Not in our library

  36. 36.

    Abrahams MR, Anderson JA, Giorgi EE, et al; CAPRISA Acute Infection Study Team; Center for HIV-AIDS Vaccine Immunology Consortium Quantitating the multiplicity of infection with human immunodeficiency virus type 1 subtype C reveals a non-poisson distribution of transmitted variants. J Virol2009; 83:3556–67.

    Not in our library10.1128/jvi.02132-08

  37. 37.

    Keele BF, Giorgi EE, Salazar-Gonzalez JF, et al Identification and characterization of transmitted and early founder virus envelopes in primary HIV-1 infection. Proc Natl Acad Sci USA2008; 105:7552–7.

    Not in our library10.1073/pnas.0802203105

  38. 38.

    Rieder P, Joos B, Scherrer AU, et al Characterization of human immunodeficiency virus type 1 (HIV-1) diversity and tropism in 145 patients with primary HIV-1 infection. Clin Infect Dis2011; 53:1271–9.

    Not in our library10.1093/cid/cir725

  39. 39.

    Cozzi-Lepri A, Noguera-Julian M, Di Giallonardo F, et al; CHAIN Minority HIV-1 Variants Working Group Low-frequency drug-resistant HIV-1 and risk of virological failure to first-line NNRTI-based ART: a multicohort European case-control study using centralized ultrasensitive 454 pyrosequencing. J Antimicrob Chemother2015; 70:930–40.

    Not in our library10.1093/jac/dku426

  40. 40.

    Gianella S, Delport W, Pacold ME, et al Detection of minority resistance during early HIV-1 infection: natural variation and spurious detection rather than transmission and evolution of multiple viral variants. J Virol2011; 85:8359–67.

    Not in our library10.1128/jvi.02582-10

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