Global epidemiology of drug resistance after failure of WHO recommended first-line regimens for adult HIV-1 infection: a multicentre retrospective cohort study
Identifieur interne : 002755 ( Pmc/Corpus ); précédent : 002754; suivant : 002756Global epidemiology of drug resistance after failure of WHO recommended first-line regimens for adult HIV-1 infection: a multicentre retrospective cohort study
Auteurs :Source :
- The Lancet. Infectious Diseases [ 1473-3099 ] ; 2016.
Abstract
Antiretroviral therapy (ART) is crucial for controlling HIV-1 infection through wide-scale treatment as prevention and pre-exposure prophylaxis (PrEP). Potent tenofovir disoproxil fumarate-containing regimens are increasingly used to treat and prevent HIV, although few data exist for frequency and risk factors of acquired drug resistance in regions hardest hit by the HIV pandemic. We aimed to do a global assessment of drug resistance after virological failure with first-line tenofovir-containing ART.
The TenoRes collaboration comprises adult HIV treatment cohorts and clinical trials of HIV drug resistance testing in Europe, Latin and North America, sub-Saharan Africa, and Asia. We extracted and harmonised data for patients undergoing genotypic resistance testing after virological failure with a first-line regimen containing tenofovir plus a cytosine analogue (lamivudine or emtricitabine) plus a non-nucleotide reverse-transcriptase inhibitor (NNRTI; efavirenz or nevirapine). We used an individual participant-level meta-analysis and multiple logistic regression to identify covariates associated with drug resistance. Our primary outcome was tenofovir resistance, defined as presence of K65R/N or K70E/G/Q mutations in the reverse transcriptase (
We included 1926 patients from 36 countries with treatment failure between 1998 and 2015. Prevalence of tenofovir resistance was highest in sub-Saharan Africa (370/654 [57%]). Pre-ART CD4 cell count was the covariate most strongly associated with the development of tenofovir resistance (odds ratio [OR] 1·50, 95% CI 1·27–1·77 for CD4 cell count <100 cells per μL). Use of lamivudine versus emtricitabine increased the risk of tenofovir resistance across regions (OR 1·48, 95% CI 1·20–1·82). Of 700 individuals with tenofovir resistance, 578 (83%) had cytosine analogue resistance (M184V/I mutation), 543 (78%) had major NNRTI resistance, and 457 (65%) had both. The mean plasma viral load at virological failure was similar in individuals with and without tenofovir resistance (145 700 copies per mL [SE 12 480] versus 133 900 copies per mL [SE 16 650; p=0·626]).
We recorded drug resistance in a high proportion of patients after virological failure on a tenofovir-containing first-line regimen across low-income and middle-income regions. Effective surveillance for transmission of drug resistance is crucial.
The Wellcome Trust.
Url:
DOI: 10.1016/S1473-3099(15)00536-8
PubMed: 26831472
PubMed Central: 4835583
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Global epidemiology of drug resistance after failure of WHO recommended first-line regimens for adult HIV-1 infection: a multicentre retrospective cohort study</title></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">26831472</idno><idno type="pmc">4835583</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4835583</idno><idno type="RBID">PMC:4835583</idno><idno type="doi">10.1016/S1473-3099(15)00536-8</idno><date when="2016">2016</date><idno type="wicri:Area/Pmc/Corpus">002755</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">002755</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Global epidemiology of drug resistance after failure of WHO recommended first-line regimens for adult HIV-1 infection: a multicentre retrospective cohort study</title></analytic><series><title level="j">The Lancet. Infectious Diseases</title><idno type="ISSN">1473-3099</idno><idno type="eISSN">1474-4457</idno><imprint><date when="2016">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><title>Summary</title><sec><title>Background</title><p>Antiretroviral therapy (ART) is crucial for controlling HIV-1 infection through wide-scale treatment as prevention and pre-exposure prophylaxis (PrEP). Potent tenofovir disoproxil fumarate-containing regimens are increasingly used to treat and prevent HIV, although few data exist for frequency and risk factors of acquired drug resistance in regions hardest hit by the HIV pandemic. We aimed to do a global assessment of drug resistance after virological failure with first-line tenofovir-containing ART.</p></sec><sec><title>Methods</title><p>The TenoRes collaboration comprises adult HIV treatment cohorts and clinical trials of HIV drug resistance testing in Europe, Latin and North America, sub-Saharan Africa, and Asia. We extracted and harmonised data for patients undergoing genotypic resistance testing after virological failure with a first-line regimen containing tenofovir plus a cytosine analogue (lamivudine or emtricitabine) plus a non-nucleotide reverse-transcriptase inhibitor (NNRTI; efavirenz or nevirapine). We used an individual participant-level meta-analysis and multiple logistic regression to identify covariates associated with drug resistance. Our primary outcome was tenofovir resistance, defined as presence of K65R/N or K70E/G/Q mutations in the reverse transcriptase (<italic>RT</italic>) gene.</p></sec><sec><title>Findings</title><p>We included 1926 patients from 36 countries with treatment failure between 1998 and 2015. Prevalence of tenofovir resistance was highest in sub-Saharan Africa (370/654 [57%]). Pre-ART CD4 cell count was the covariate most strongly associated with the development of tenofovir resistance (odds ratio [OR] 1·50, 95% CI 1·27–1·77 for CD4 cell count <100 cells per μL). Use of lamivudine versus emtricitabine increased the risk of tenofovir resistance across regions (OR 1·48, 95% CI 1·20–1·82). Of 700 individuals with tenofovir resistance, 578 (83%) had cytosine analogue resistance (M184V/I mutation), 543 (78%) had major NNRTI resistance, and 457 (65%) had both. The mean plasma viral load at virological failure was similar in individuals with and without tenofovir resistance (145 700 copies per mL [SE 12 480] versus 133 900 copies per mL [SE 16 650; p=0·626]).</p></sec><sec><title>Interpretation</title><p>We recorded drug resistance in a high proportion of patients after virological failure on a tenofovir-containing first-line regimen across low-income and middle-income regions. Effective surveillance for transmission of drug resistance is crucial.</p></sec><sec><title>Funding</title><p>The Wellcome Trust.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Granich, Rm" uniqKey="Granich R">RM Granich</name></author><author><name sortKey="Gilks, Cf" uniqKey="Gilks C">CF Gilks</name></author><author><name sortKey="Dye, C" uniqKey="Dye C">C Dye</name></author><author><name sortKey="De Cock, Km" uniqKey="De Cock K">KM De Cock</name></author><author><name sortKey="Williams, Bg" uniqKey="Williams B">BG Williams</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Hankins, Ca" uniqKey="Hankins C">CA Hankins</name></author><author><name sortKey="Dybul, Mr" uniqKey="Dybul M">MR Dybul</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Garforth, Sj" uniqKey="Garforth S">SJ 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Lancet Infect Dis</journal-id><journal-id journal-id-type="iso-abbrev">Lancet Infect Dis</journal-id><journal-title-group><journal-title>The Lancet. Infectious Diseases</journal-title></journal-title-group><issn pub-type="ppub">1473-3099</issn><issn pub-type="epub">1474-4457</issn><publisher><publisher-name>Elsevier Science ;, The Lancet Pub. Group</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">26831472</article-id><article-id pub-id-type="pmc">4835583</article-id><article-id pub-id-type="publisher-id">S1473-3099(15)00536-8</article-id><article-id pub-id-type="doi">10.1016/S1473-3099(15)00536-8</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group></article-categories><title-group><article-title>Global epidemiology of drug resistance after failure of WHO recommended first-line regimens for adult HIV-1 infection: a multicentre retrospective cohort study</article-title></title-group><contrib-group><contrib contrib-type="author"><collab>The TenoRes Study Group</collab><xref rid="fn1" ref-type="fn">†</xref></contrib></contrib-group><author-notes><fn id="fn1"><label>†</label><p id="cenpara20">Members listed at the end of the report</p></fn></author-notes><pub-date pub-type="pmc-release"><day>1</day><month>5</month><year>2016</year></pub-date><pmc-comment> PMC Release delay is 0 months and 0 days and was based on .</pmc-comment>
<pub-date pub-type="ppub"><month>5</month><year>2016</year></pub-date><volume>16</volume><issue>5</issue><fpage>565</fpage><lpage>575</lpage><permissions><copyright-statement>© 2016 The TenoRes Study Group. Open Access article distributed under the terms of CC BY</copyright-statement><copyright-year>2016</copyright-year><license license-type="CC BY" xlink:href="http://creativecommons.org/licenses/by/4.0/"><license-p>This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).</license-p></license></permissions><related-article related-article-type="article-reference" id="d32e12" ext-link-type="doi" xlink:href="10.1016/S1473-3099(16)00013-X"></related-article><abstract><title>Summary</title><sec><title>Background</title><p>Antiretroviral therapy (ART) is crucial for controlling HIV-1 infection through wide-scale treatment as prevention and pre-exposure prophylaxis (PrEP). Potent tenofovir disoproxil fumarate-containing regimens are increasingly used to treat and prevent HIV, although few data exist for frequency and risk factors of acquired drug resistance in regions hardest hit by the HIV pandemic. We aimed to do a global assessment of drug resistance after virological failure with first-line tenofovir-containing ART.</p></sec><sec><title>Methods</title><p>The TenoRes collaboration comprises adult HIV treatment cohorts and clinical trials of HIV drug resistance testing in Europe, Latin and North America, sub-Saharan Africa, and Asia. We extracted and harmonised data for patients undergoing genotypic resistance testing after virological failure with a first-line regimen containing tenofovir plus a cytosine analogue (lamivudine or emtricitabine) plus a non-nucleotide reverse-transcriptase inhibitor (NNRTI; efavirenz or nevirapine). We used an individual participant-level meta-analysis and multiple logistic regression to identify covariates associated with drug resistance. Our primary outcome was tenofovir resistance, defined as presence of K65R/N or K70E/G/Q mutations in the reverse transcriptase (<italic>RT</italic>) gene.</p></sec><sec><title>Findings</title><p>We included 1926 patients from 36 countries with treatment failure between 1998 and 2015. Prevalence of tenofovir resistance was highest in sub-Saharan Africa (370/654 [57%]). Pre-ART CD4 cell count was the covariate most strongly associated with the development of tenofovir resistance (odds ratio [OR] 1·50, 95% CI 1·27–1·77 for CD4 cell count <100 cells per μL). Use of lamivudine versus emtricitabine increased the risk of tenofovir resistance across regions (OR 1·48, 95% CI 1·20–1·82). Of 700 individuals with tenofovir resistance, 578 (83%) had cytosine analogue resistance (M184V/I mutation), 543 (78%) had major NNRTI resistance, and 457 (65%) had both. The mean plasma viral load at virological failure was similar in individuals with and without tenofovir resistance (145 700 copies per mL [SE 12 480] versus 133 900 copies per mL [SE 16 650; p=0·626]).</p></sec><sec><title>Interpretation</title><p>We recorded drug resistance in a high proportion of patients after virological failure on a tenofovir-containing first-line regimen across low-income and middle-income regions. Effective surveillance for transmission of drug resistance is crucial.</p></sec><sec><title>Funding</title><p>The Wellcome Trust.</p></sec></abstract></article-meta></front><body><sec id="cesec10"><title>Introduction</title><p>More than 35 million people worldwide are living with HIV-1.<xref rid="bib1" ref-type="bibr"><sup>1</sup></xref> There is no effective vaccine and therefore control of the HIV pandemic relies heavily on combination antiretroviral therapy (cART). WHO treatment guidelines for adult HIV-1 infection recommend the nucleotide reverse-transcriptase inhibitor (NRTI) tenofovir for first-line ART, in combination with lamivudine or emtricitabine and the non-nucleoside reverse-transcriptase inhibitor (NNRTI) efavirenz.<xref rid="bib2" ref-type="bibr"><sup>2</sup></xref> Older NRTIs such as the thymidine analogue drugs are being replaced by tenofovir and the NNRTI nevirapine, although mentioned in WHO guidelines, is being phased out from first-line regimens.<xref rid="bib2" ref-type="bibr"><sup>2</sup></xref></p><p>The global scale-up of cART has now reached 15 million treated individuals.<xref rid="bib1" ref-type="bibr"><sup>1</sup></xref> The administration of cART at the time individuals with HIV-1 are initially diagnosed prevents immunological deterioration as early as possible and interrupts the spread of HIV-1 from newly diagnosed individuals.<xref rid="bib3" ref-type="bibr"><sup>3</sup></xref> This strategy, referred to as treatment as prevention, is being studied especially in high-incidence regions and nearly always includes the use of first-line tenofovir-containing ART regimens. Likewise, the strategy of pre-exposure prophylaxis (PrEP) depends entirely on the administration of tenofovir or tenofovir and emtricitabine to uninfected individuals at high risk of HIV-1 infection.<xref rid="bib4" ref-type="bibr"><sup>4</sup></xref></p><p>In individuals receiving tenofovir, HIV-1 develops phenotypically and clinically significant resistance usually as a result of one mutation at position 65 (lysine to arginine; K65R) in the reverse transcriptase (<italic>RT</italic>) gene.<xref rid="bib5" ref-type="bibr"><sup>5</sup></xref> Data from clinical trials and cohorts in high-income settings using tenofovir combined with NNRTI have reported low prevalence of tenofovir resistance at viral failure,<xref rid="bib6" ref-type="bibr">6</xref>, <xref rid="bib7" ref-type="bibr">7</xref>, <xref rid="bib8" ref-type="bibr">8</xref> in stark contrast with reports from low-income and middle-income countries where prevalence seems to be much higher.<xref rid="bib9" ref-type="bibr">9</xref>, <xref rid="bib10" ref-type="bibr">10</xref> Similarly, high-level resistance to NNRTI and the cytosine analogue component (emtricitabine and lamivudine) arise through changes to one aminoacid, which suggests a low genetic barrier to resistance for these drugs as well. In view of the pivotal role of tenofovir-containing ART as both treatment and prophylaxis, and the striking potential for drug resistance, we did a global assessment of drug resistance after virological failure with first-line tenofovir-containing ART.</p><p><boxed-text id="cetextbox10"><caption><title>Research in context</title></caption><p><bold>Evidence before this study</bold></p><p>We searched PubMed for studies of the prevalence of tenofovir resistance after failure of first-line antiretroviral therapy with efavirenz or nevirapine (non-nucleoside reverse-transcriptase inhibitors [NNRTIs]) in patients with HIV-1, published between January, 1999, and June, 2015, using the search terms “HIV” AND “tenofovir” AND “resistance”. We identified studies done in untreated adults (age >15 years) in which either efavirenz or nevirapine was combined with tenofovir and either emtricitabine or lamivudine as first line antiretroviral therapy. Several studies reported resistance data for tenofovir when the drug was started after initial use of stavudine or zidovudine; these studies were not reviewed further. We also excluded studies that reported tenofovir use without NNRTI because standard first-line antiretroviral therapy under a public health approach is based on NNRTI in adults.</p><p>We identified randomised controlled trials and a meta-analysis comparing NNRTI with protease inhibitors, in combination with tenofovir, which reported resistance data. Patients in high-income settings reported tenofovir resistance in 0–25% of virological failures and those in sub-Saharan Africa in 28–50%. The only other prospective study in sub-Saharan Africa was PASER-M, and was limited by few resistance data for patients given tenofovir plus NNRTI-based combination antiretroviral therapy (cART). The remaining studies were largely from South Africa and reported a wide range of prevalence (between 23% and 70%) of tenofovir resistance after virological failure. In west Africa, one study reported that 57% of virological failures were tenofovir resistant in a very small sample of 23 patients. Although aforementioned studies also reported NNRTI and cytosine analogue resistance, they were unable to quantify to what extent tenofovir resistance was a marker for high-level compromise of the regimen. We found no studies that specifically reported resistance data for patients given first-line tenofovir in east Africa. No study reported resistance data from more than one continent, and none seemed adequately powered to establish the effect of co-administered reverse-transcriptase inhibitors on the emergence of tenofovir resistance.</p><p><bold>Added value of this study</bold></p><p>This study reports the most comprehensive assessment of HIV-1 drug resistance after scale-up of first-line WHO recommended tenofovir-based antiretroviral regimens, showing that tenofovir resistance is surprisingly common in patients with treatment failure across many studies in all low-income regions. Importantly, these individuals also have notable resistance to other drugs in their regimen, leading to almost complete compromise of combination treatment. Challenging current perceptions in the specialty, our findings show that tenofovir resistant viruses have substantial transmission potential. Furthermore, our results show that viral strain affects tenofovir resistance in Europe but is not the main driver for resistance in viruses circulating in sub-Saharan Africa. Newly identified risk factors for resistance to tenofovir and NNRTI drugs include pre-treatment CD4 cell count (but not viral load) and co-administered antiretrovirals.</p><p><bold>Implications of all the available evidence</bold></p><p>Improvements in the quality of HIV care and viral load monitoring could mitigate the emergence and spread of tenofovir resistance, thereby prolonging the lifetime of tenofovir-containing regimens for both treatment and prophylaxis. Surveillance of tenofovir and NNRTI resistance should be a priority both in untreated and treated populations.</p></boxed-text></p></sec><sec id="cesec20"><title>Methods</title><sec id="cesec30"><title>Study population and design</title><p>The TenoRes collaboration comprises adult HIV treatment cohorts and clinical trials from Europe, Latin and North America, sub-Saharan Africa, and Asia. Cohorts and trials were identified by RWS and RKG as those known to do genotypic resistance testing through previous collaborations, the WHO HIV Drug Resistance Network, and through the International HIV Drug Resistance Workshop. Moreover, we did a systematic review using the keywords “HIV”, AND “tenofovir” AND “resistance” in PubMed for articles published between January, 1999, and June, 2015. We identified 44 studies suitable for the reported analysis after applying the following inclusion criteria: documented virological failure after first-line ART comprising tenofovir plus either lamivudine or emtricitabine plus either efavirenz or nevirapine (virological failure was defined by local viral load thresholds or surveillance protocols); a successful resistance test result associated with virological failure of cART; tenofovir-based ART for at least 4 months before virological failure; and absence of thymidine analogue mutations at resistance testing (<xref rid="sec1" ref-type="sec">appendix</xref>). Exclusion criteria were: studies reporting resistance data after tenofovir that was started after initial use of stavudine or zidovudine; and studies reporting tenofovir use without NNRTI. Data were extracted and harmonised by RWS, RKG, MT, and JG and stored in a central database.</p><p>We collected individual-level data for a predefined set of covariates: age at first-line ART initiation, sex, frequency of viral load monitoring (number of tests per year), urban versus rural setting for HIV clinics, viral load threshold for virological failure and genotyping, co-administered antiretrovirals, duration of treatment, viral load and CD4 cell count before the start of first-line ART (baseline) and at time of viral failure, and resistance mutations based on the <ext-link ext-link-type="uri" xlink:href="http://hivdb.stanford.edu" id="interrefs10">Stanford HIV Drug Resistance Database</ext-link>.</p></sec><sec id="cesec40"><title>Statistical analysis</title><p>Our primary outcome was tenofovir resistance, defined as presence of K65R/N or K70E/G/Q mutations in the RT gene. Our secondary outcomes were resistance to first generation NNRTI (efavirenz and nevirapine), defined as specific mutations at aminoacid positions 100, 103, 106, 108, 181, 188, 190, and 225,<xref rid="bib11" ref-type="bibr"><sup>11</sup></xref> and cytosine analogue resistance, defined as presence of M184V/I. Our main exposures of interest were baseline CD4 cell count (<100 <italic>vs</italic> ≥100 cells per μL), baseline viral load (<100 000 <italic>vs</italic> ≥100 000 copies HIV-1 RNA per mL; this cutoff was chosen because of findings from previous studies<xref rid="bib12" ref-type="bibr"><sup>12</sup></xref>), nevirapine versus efavirenz, and lamivudine versus emtricitabine. For our primary analysis, we estimated the odds ratios (ORs) for tenofovir resistance within each study before pooling estimates across studies using a random-effects meta-analysis with DerSimonian-Laird weighting and estimates of heterogeneity taken from the Mantel-Haenszel model. We chose this method to ensure that we only compared patients in the same study and country, thereby minimising confounding by differences in care at the study or country level. Findings were not sensitive to the choice of method used for the meta-analysis (ie, fixed or random effects). We also used a continuity correction of 0·5 for counts of 0, although findings were not sensitive to this choice.</p><p>We did sensitivity analyses to investigate whether associations changed when adjusted for possible confounders. Because of the sparseness of data in many studies, we were unable to adjust within-study associations for potential confounders. Instead, we did additional analyses using logistic regression models with a random effect at study level to estimate associations before and after adjustment for possible confounders in a common subset of participants. To build the adjusted model, we included each of our main exposures and HIV subtype. We also considered for inclusion individual-level information about age, sex, year of treatment initiation, and length of time on tenofovir, but rejected these covariates because of a lack of any univariate association with tenofovir resistance. We chose to only use these models for working out the likely extent of confounding, because estimated associations from these models are partly derived from between-study comparisons.</p><p>To clarify whether the association between baseline CD4 or baseline viral load and tenofovir resistance was linear (ie, followed a dose-response pattern), we categorised participants into four categories based on baseline CD4 cell count (<100, 100–200, 201–300, >300 cells per μL reference category) or baseline viral load (<25 000 [reference]; 25 001–100 000; 100 001–300 000; >300 000 copies HIV-1 RNA per mL). We assessed associations by plotting the estimated OR against the mean level of baseline CD4 (or baseline viral load), in a random-effects logistic regression model adjusted for region, co-administered drugs, and baseline viral load (or baseline CD4).</p><p>To assess the potential transmissibility of mutant viruses, we graphically compared the distribution of plasma HIV-1 RNA concentrations of patients from the same study with and without tenofovir resistance.</p><p>We did not use multiple imputation to adjust for missing data because most missing data were the result of a lack of availability at the study level. Instead, we restricted analyses to the subset of participants with information available about all relevant covariates for each specific analysis. The <xref rid="sec1" ref-type="sec">appendix</xref> presents the amount of missing data and which studies contributed towards specific analyses. We used Stata (version 11.2) for all analyses.</p></sec><sec id="cesec50"><title>Role of the funding source</title><p>The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. RKG and JG had full access to all the data in the study and had final responsibility for the decision to submit for publication.</p></sec></sec><sec id="cesec60"><title>Results</title><p>The TenoRes collaboration included 1926 individuals from 36 countries (<xref rid="fig1" ref-type="fig">figure 1</xref> and <xref rid="sec1" ref-type="sec">appendix</xref>). <xref rid="tbl1" ref-type="table">Table 1</xref> summarises the median size and year of ART initiation for the cohorts comprising the collaboration. Viral load monitoring was done in about 50% of the cohorts including nearly all of cohorts from upper-income regions and from a small proportion of the cohorts in low-income and middle-income countries (<xref rid="sec1" ref-type="sec">appendix</xref> shows income status for each cohort; <xref rid="tbl1" ref-type="table">table 1</xref>).</p><p>The region-level pre-ART median CD4 cell count ranged from 44 to 104 cells per μL in sub-Saharan Africa, Asia, and Latin America (<xref rid="tbl2" ref-type="table">table 2</xref>). As expected, in north America pre-ART median CD4 cell count was 144 cells per μL and 190 cells per μL in Europe. The proportion of individuals using emtricitabine (<italic>vs</italic> lamivudine) and efavirenz (<italic>vs</italic> nevirapine) varied significantly by region. Emtricitabine was used significantly more than lamivudine in Europe, North America, and west and central Africa, and efavirenz was used significantly more than nevirapine in all regions apart from east and west and central Africa. The median duration of ART ranged from 11 to 26 months. Pre-treatment viral load ranged between 4·80 and 5·58 log copies per mL and was significantly higher in eastern and western and central Africa and Latin America than the other regions (<xref rid="tbl2" ref-type="table">table 2</xref>).</p><p>Crude prevalence of tenofovir resistance in patients with treatment failure was highest in low-income and middle-income regions (<xref rid="fig1" ref-type="fig">figure 1</xref>). Prevalence of cytosine analogue resistance (M184V/I) was highest in sub-Saharan Africa and Latin America and lowest in western Europe. By contrast, resistance to NNRTI did not show this pattern (<xref rid="fig1" ref-type="fig">figure 1</xref>). Furthermore, the M184V/I mutation was less common than NNRTI resistance across all regions except in eastern Africa. Of the 700 patients with tenofovir resistance in the dataset, 457 (65%) had resistance to both remaining drugs. Participants with tenofovir resistant viruses were likely to be resistant to one or both accompanying drugs and therefore have profound compromise of their regimen, as compared with those without tenofovir resistance (<xref rid="fig1" ref-type="fig">figure 1</xref>).</p><p>Low baseline CD4 cell count was consistently associated with a higher prevalence of tenofovir resistance across regions. The pooled OR for tenofovir in individuals with a CD4 cell count of less than 100 cells per μL versus 100 cells per μL was 1·50 (95% CI 1·27–1·77; <xref rid="fig2" ref-type="fig">figure 2</xref>). By contrast, a high baseline viral load was only associated with a small, not significant increase in tenofovir resistance (OR for viral load ≥100 000 copies per mL <italic>vs</italic> <100 000 copies per mL was 1·17, 95% CI 0·94–1·44; <xref rid="sec1" ref-type="sec">appendix</xref>). We compared tenofovir resistance by use of co-administered antiretrovirals with tenofovir as first-line therapy. Use of lamivudine rather than emtricitabine (NRTIs) was associated with a higher prevalence of tenofovir resistance (OR 1·48, 95% CI 1·20–1·82), as was use of the NNRTI nevirapine rather than efavirenz (OR 1·46, 1·28–1·67; <xref rid="sec1" ref-type="sec">appendix</xref>). Subgroup analysis showed that as well as associations being consistent across regions, they were also generally similar across a range of study settings (<xref rid="sec1" ref-type="sec">appendix</xref>), although there was some evidence of a greater effect size of baseline CD4 when efavirenz was co-administered with tenofovir, as compared with nevirapine.</p><p>When considering the effect of baseline CD4, baseline viral load (<xref rid="fig3" ref-type="fig">figure 3</xref>), and co-administered antiretrovirals (<xref rid="sec1" ref-type="sec">appendix</xref>) on cytosine analogue and NNRTI resistance, we noted that the magnitude of associations were smaller than those recorded for tenofovir resistance.</p><p>We also assessed the relation between viral subtype C on acquisition of tenofovir resistance. We restricted this analysis to western European studies in view of the consistent standard of care available in this region and relatively lower level of subtype diversity in other regions (<xref rid="fig1" ref-type="fig">figure 1A</xref>). We also limited the comparison to subtypes found in immigrant populations to minimise bias due to socioeconomic factors (thereby excluding subtype B infections mainly recorded in participants born in western Europe). Tenofovir resistance was higher in subtype C compared with non-C, non-B infections with a pooled OR of 2·44 (1·66–3·59).</p><p>As a sensitivity analysis we studied risk factors for tenofovir resistance using univariate (adjusted only for region) and multivariate logistic regression analyses (<xref rid="sec1" ref-type="sec">appendix</xref>). We noted a dose-response relationship for baseline CD4, which was not markedly altered by adjustment for baseline viral load, viral subtype, or type of co-administered drug used (<xref rid="sec1" ref-type="sec">appendix</xref>). Baseline viral load of 100 000 or more copies of HIV-1 RNA per mL was not significantly associated with tenofovir resistance (OR 1·31, 95% CI 0·91–1·91) and we noted no clear trend across increasing viral loads (<xref rid="sec1" ref-type="sec">appendix</xref>). Adjustment for several risk factors also had little effect on associations with tenofovir resistance of emtricitabine versus lamivudine and nevirapine versus efavirenz.</p><p>Finally, we compared the viral load at treatment failure in the presence and absence of tenofovir-associated mutations. The mean plasma viral load at treatment failure was not different in the presence or absence of tenofovir associated mutations (145 700 copies HIV RNA per mL [SE 12 480] <italic>vs</italic> 133 900 copies [SE 16 650]; p=0·626; <xref rid="fig4" ref-type="fig">figure 4</xref> shows the within-study viral load by region). These results did not change when analysis was restricted to individuals who had evidence of the K65R mutation, either with or without M184V/I (<xref rid="sec1" ref-type="sec">appendix</xref>). Mutations at aminoacids K65 and M184 in the RT gene have been associated with suboptimum replication.<xref rid="bib13" ref-type="bibr"><sup>13</sup></xref></p></sec><sec id="cesec70"><title>Discussion</title><p>Our study has three main findings relating to the prevalence, risk factors for, and transmissibility of tenofovir resistance. First, we noted that levels of tenofovir resistance in individuals with viral failure ranged from 20% in Europe to more than 50% in sub-Saharan Africa. Second, a CD4 cell count of less than 100 cells per μL, treatment with nevirapine rather than efavirenz, and treatment with lamivudine rather than emtricitabine, were consistently associated with a 50% higher odds of tenofovir resistance in those with viral failure. Third, we noted that in patients with viral failure, viral loads were similar in the presence or absence of tenofovir resistance.</p><p>Our findings are important in view of the fact that following WHO recommendations,<xref rid="bib2" ref-type="bibr"><sup>2</sup></xref> tenofovir is replacing thymidine analogues (zidovudine and stavudine) as part of the NRTI backbone in first-line regimens in resource-limited settings. Every drug in these regimens can be compromised by one aminoacid mutation, and the combination therapy is therefore potentially fragile. In view of the crucial role of tenofovir-containing ART in both treatment and prevention of new infections, restriction of drug resistance in high-burden settings is of paramount importance. Understanding how common tenofovir resistance is, and how and why it varies, is key to its prevention. Although our risk factors are only associated with a modest 50% increase in odds, this translates to a roughly 10% increase in resistance in those who fail when the overall tenofovir resistance prevalence is about 50% (as recorded in sub-Saharan Africa).</p><p>We hypothesise that the regional differences in tenofovir resistance are due to the frequency of viral load monitoring with close patient follow-up and feedback of results. For example, although viral load monitoring is not routinely done in most low-income and middle-income countries, in high-income countries viral load is tested three to four times per year with close patient follow-up and adherence support. Such an approach is likely to lead to earlier detection of viral failure, before selection of drug resistance mutations against tenofovir has occurred.<xref rid="bib14" ref-type="bibr"><sup>14</sup></xref> This view is supported by the uncommon detection of drug resistance mutations in specimens with low viral load (400–1000 copies per mL) from patients given tenofovir in both high-income settings (<xref rid="fig1" ref-type="fig">figure 1</xref>; see higher prevalence of tenofovir resistance where viral load >1000 copies per mL is used as threshold in western Europe)<xref rid="bib15" ref-type="bibr"><sup>15</sup></xref> and sub-Saharan Africa (Chunfu Yang, Centres for Disease Control, Atlanta, GA, USA, personal communication). Tenofovir resistance could be limited by viral load monitoring,<xref rid="bib16" ref-type="bibr"><sup>16</sup></xref> with rapid feedback to clinicians followed by adherence counselling to preserve first line, or switch to second line when this approach fails. Furthermore, pre-ART (baseline) resistance testing for key NNRTI mutations could potentially protect against tenofovir resistance by avoiding use of partly active treatment regimens. In our report, transmitted NNRTI resistance was low in the regions studied (<10%),<xref rid="bib17" ref-type="bibr"><sup>17</sup></xref> and therefore not likely to be a major driver of wide variation in drug resistance across income settings.</p><p>Other factors that vary geographically could also affect success of ART and should be noted. Treatment failure is associated not only with drug resistance, but also side-effects. Efavirenz is associated with CNS side-effects such as sleep disturbance and is associated with treatment discontinuation.<xref rid="bib18" ref-type="bibr"><sup>18</sup></xref> Furthermore, drug stock-outs and other indicators of quality of HIV services that have shown geographic variation would also predispose to treatment failure.<xref rid="bib19" ref-type="bibr"><sup>19</sup></xref> The issue of regional variation in adherence levels has received considerable attention, with data from several studies suggesting that adherence is not worse in sub-Saharan Africa compared with North America.<xref rid="bib20" ref-type="bibr">20</xref>, <xref rid="bib21" ref-type="bibr">21</xref></p><p>With regards to increased tenofovir resistance in individuals with low baseline CD4 counts, this finding is consistent with results from the ACTG 5202 trial<xref rid="bib22" ref-type="bibr"><sup>22</sup></xref> suggesting higher frequency of RT mutations in patients given ART with low CD4 cell counts, and offer a benefit of CD4 cell count measurement after diagnosis of HIV infection beyond establishing prophylaxis against opportunistic infections.<xref rid="bib23" ref-type="bibr"><sup>23</sup></xref> Lamivudine warrants further study in first-line regimens in view of data presented in our study and the conflicting reports regarding virological efficacy of lamivudine versus emtricitabine.<xref rid="bib24" ref-type="bibr">24</xref>, <xref rid="bib25" ref-type="bibr">25</xref>, <xref rid="bib26" ref-type="bibr">26</xref> Of note, the differences between lamivudine and emtricitabine might become less important in high-income regions where implementation of the second generation integrase inhibitor dolutegravir occurs, in view of the fact that this agent has not been associated with any cytosine analogue resistance at virological failure.<xref rid="bib27" ref-type="bibr"><sup>27</sup></xref></p><p>Viral load has been associated with transmission risk.<xref rid="bib28" ref-type="bibr"><sup>28</sup></xref> Despite evidence for diminished replication of tenofovir resistant viruses (containing the K65R mutation in the RT gene) in vitro, we noted similar viral loads in participants with and without tenofovir resistance. Therefore, there might be substantial potential for onward transmission to uninfected individuals,<xref rid="bib29" ref-type="bibr"><sup>29</sup></xref> despite little evidence of K65R transmission up to now.<xref rid="bib30" ref-type="bibr"><sup>30</sup></xref> This finding reinforces the need for drug resistance surveillance activities in both untreated and treated HIV-positive individuals.</p><p>There are several important limitations of our study. First, because we only included patients with virological failure related to existing study cohorts,<xref rid="bib1" ref-type="bibr"><sup>1</sup></xref> our estimates of the prevalence of tenofovir resistance might not be representative in certain high-burden regions. Although this situation might have biased our findings on absolute prevalences of tenofovir resistance, it is unlikely to have affected associations with baseline CD4 or co-administered drugs. Second, we only included patients at failure so were unable to assess overall rates of tenofovir resistance in all patients starting first-line treatment. We used this method because many of the contributing studies had no clear denominator, especially those done in resource-limited settings. However, extensive WHO-led analysis reported that 15–35% (on treatment <italic>vs</italic> intention to treat) of patients in sub-Saharan Africa have virological failure by 12 months.<xref rid="bib31" ref-type="bibr"><sup>31</sup></xref> Therefore, using a conservative 50% prevalence of tenofovir resistance at failure from our analysis, we suggest that it is likely that 7·5–17·5% of individuals given tenofovir plus cytosine analogue plus efavirenz will develop tenofovir resistance within 1 year of treatment initiation under present practices in sub-Saharan Africa.</p><p>Third, our findings on risk factors for tenofovir resistance were derived from an unadjusted meta-analysis involving very different study populations. Although this enhances the generalisability of results, it has the potential to lead to biased comparisons. However, we took measures to minimise biases. We exclusively used within-study and within-country comparisons for our primary analyses, thereby ensuring that comparisons were for participants undergoing similar treatment monitoring practices. We tested associations between risk factors and found that they were generally weak. For example, baseline CD4 cell count and viral load were only weakly associated with one another and neither was strongly associated with type of co-administered drug. Additionally, we undertook sensitivity analyses, which suggested that adjustment for other covariates had minimum effect on estimated associations. Lastly, our data tended to be consistent with previous studies—eg, our findings of higher resistance in subtype C patients are consistent with in-vitro data suggesting subtype C viruses are more susceptible to developing the K65R mutation.<xref rid="bib32" ref-type="bibr"><sup>32</sup></xref></p><p>Fourth, despite our analysis being the largest drug resistance study ever undertaken after failure of first-line tenofovir-containing cART, patient numbers were somewhat limited by the slow uptake of tenofovir-based regimens in west and central Africa, eastern Europe, and Asia (in particular China and Russia), and information about baseline viral load in these settings was uncommon. As a result, European countries, Thailand, and South Africa contributed substantially to the analysis.</p><p>In summary, extensive drug resistance emerges in a high proportion of patients after virological failure on a tenofovir-containing first-line regimen across low-income and middle-income regions. Optimisation of treatment programmes and effective surveillance for transmission of drug resistance is therefore crucial.</p><p><boxed-text id="cetextbox20"><p>Correspondence to: Dr Ravindra K Gupta, UCL, Department of Infection, London WC1E 6BT, UK <ext-link ext-link-type="uri" xlink:href="mailto:ravindra.gupta@ucl.ac.uk" id="interrefs20"><bold>ravindra.gupta@ucl.ac.uk</bold></ext-link></p><p>or</p><p>Prof Robert W Shafer, Department of Medicine, Stanford University, Stanford, CA 94305, USA <ext-link ext-link-type="uri" xlink:href="mailto:rshafer@stanford.edur" id="interrefs30"><bold>rshafer@stanford.edur</bold></ext-link></p></boxed-text></p></sec></body><back><ref-list><title>References</title><ref id="bib1"><label>1</label><element-citation publication-type="other" id="sbref10"><person-group person-group-type="author"><collab>UNAIDS</collab></person-group><article-title>World AIDS Day 2014 Report - fact sheet</article-title><ext-link ext-link-type="uri" 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id="ecomp10"><caption><title>Supplementary appendix</title></caption><media xlink:href="mmc1.pdf"></media></supplementary-material></p></sec><ack id="ceack10"><sec><title>Acknowledgments</title><p>We thank the following groups: ACTG 5208 study team; the Lazio and Emilia Romagna Cohorts, Italy; Uganda Virus Research Institute/Ministry of Health (UVRI/MoH) Uganda surveillance study team; the Uganda HIV Drug Resistance Working group; participants and study teams from HIV treatment centres at Masaka and Mbale regional referral hospitals and Nsambya Home-Care; The ClinSurv Study Group; EuResist Network; Swiss HIV Cohort Study; the Athena cohort, Netherlands; CoRIS, Spain; Honduras and Nicaragua cohorts; RFVF, South Africa; Sinikithemba Clinic at McCord Hospital in Durban, South Africa; Tanzanian, Kenyan, and Ugandan Ministries of Health; Harvard/AIDS Prevention Initiative in Nigeria (APIN) prevention, treatment, and care programme; Stichting HIV Monitoring; Tanzanian, Nigeria, and Kenyan Ministries of Health. Infectious Disease Institute, Uganda and Tropical Disease Research Centre, Zambia; PEPFAR; The Cross Sectional Survey of Acquired Drug Resistance Study at Sentinel Sites Study Team; Kenya National HIVDR working group; CDC-Kenya; CDC-Tanzania; CDC-Atlanta; and Andrew Hill for helpful discussions.</p></sec></ack><ack><title>Contributors</title><p>RKG and RWS conceived the study; JG, RKG, and RWS designed the study; MT, SYR, RLH, VCM, LD, IM, KB, NN, KT, TFRdeW, MA, FG, SM, JNT, HFG, CH, PK, NK, BK, OM, CC, ET, CR, LG, EKH, HS, DDC, AA, AM, AL, CM, NG, CVV, AB, AA, AS, UN, WJF, CFP, SA, MMS, CY, JLB, JJM, GH, LM, DS, CW, JA, WK, AT, TEH, NC, RC, TdeO, DP, CS, DD, PK, ER, RK, RKG, RWS, JG, SAR, GRT, AMO, SS, KR, and SM generated and analysed data; and JG, RWS, and RKG wrote the first draft.</p></ack><ack><title>TenoRes Study Group members</title><p>John Gregson, Michele Tang*, Nicaise Ndembi*, Raph L Hamers*, Soo-Yon Rhee, Vincent C Marconi, Lameck Diero, Katherine Brooks, Kristof Theys, Tobias F Rinke de Wit, Monica Arruda, Frederico Garcia, Susana Monge, Huldrych F Günthard, Christopher J Hoffmann, Phyllis J Kanki, Nagalingeshwaran Kumarasamy, Bernard Kerschberger, Orna Mor, Charlotte Charpentier, Eva Todesco, Casper Rokx, Luuk Gras, Elias K Halvas, Henry Sunpath, Domenico Di Carlo, Antonio Antinori, Massimo Andreoni, Alessandra Latini, Cristina Mussini, Avelin Aghokeng, Anders Sonnerborg, Ujjwal Neogi, William J Fessel, Simon Agolory, Chunfu Yang, Jose L Blanco, James M Juma, Erasmus Smit, Daniel Schmidt, Christine Watera, Juliet Asio, Wilford Kirungi, Anna Tostevin, Tal El-Hay, Nathan Clumeck, Dominique Goedhals, Cloete van Vuuren, Philip Armand Bester, Caroline Sabin, Irene Mukui, Maria M Santoro, Carlo F Perno, Gillian Hunt, Lynn Morris, Ricardo Camacho, Tulio de Oliveira, Deenan Pillay, Eugene Schulter, Akio Murakami-Ogasawara, Gustavo Reyes-Terán, Karla Romero, Santiago Avila-Rios, Sunee Sirivichayakul, Kiat Ruxrungtham, Suwanna Mekprasan, David Dunn, Pontiano Kaleebu, Elliot Raizes, Rami Kantor, Robert W Shafer**, Ravindra K Gupta**, Department of Statistics, London School of Hygiene & Tropical Medicine (J Gregson PhD); Department of Medicine, Stanford University, Stanford, CA, USA (M Tang MD, S-Y Rhee PhD, R W Shafer MD); Institute of Human Virology Nigeria, Abuja, Federal Capital Territory, Nigeria (N Ndembi PhD); Amsterdam Institute for Global Health and Development, Department of Global Health and Department of Internal Medicine, Academic Medical Center of the University of Amsterdam, The Netherlands (R L Hamers MD, T F Rinke de Wit MD); Department of Global Health, Emory University Rollins School of Public Health, Atlanta, GA, USA (V C Marconi MD); Division of Infectious Diseases, Emory University School of Medicine, Atlanta, GA, USA (V C Marconi); Moi University and the Academic Model Providing Access to Healthcare, Eldoret, Kenya (L Diero MD); Division of Infectious Diseases Brown University Alpert Medical School, USA (K Brooks BA); KU Leuven–University of Leuven, Department Microbiology and Immunology, Rega Institute for Medical Research, B-3000 Leuven, Belgium (K Theys PhD, R Camacho, R Kantor MD); Laboratório de Virologia Molecular-LVM Instituto de Biologia - Universidade Federal do Rio de Janeiro (M Arruda PhD); Complejo Hospitalario Universitario de Granada, Granada, Spain (F Garcia); Universidad de Alcalá, Spain; CIBERESP, Spain (S Monge); Division of Infectious Diseases and Hospital Epidemiology, University of Zurich, Zurich, Switzerland (H F Günthard MD); Institute of Medical Virology, University of Zurich, Zurich Switzerland (H F Günthard); Johns Hopkins University, Baltimore, USA (C J Hoffmann MD); Aurum Institute, Johannesburg, South Africa (C J Hoffmann MD); Department of Immunology and Infectious Disease, Harvard T H Chan School of Public Health, Boston, MA, USA (P J Kanki MD); YRGCARE Medical Centre, VHS, Chennai, India (N Kumarasamy MD); Medecins Sans Frontieres (Operational Centre Geneva), Mbabane, Swaziland (B Kerschberger); Central Virology Laboratory, Public Health Services, Israel Ministry of Health (O Mor PhD); IAME, UMR 1137, Univ Paris Diderot, Sorbonne Paris Cité, Paris, France (C Charpentier PhD); IAME, UMR 1137, INSERM, Paris, France (C Charpentier); AP-HP, Hôpital Bichat-Claude Bernard, Laboratoire de Virologie, F-75018 Paris, France (C Charpentier PhD); Hôpital Pitié-Salpêtrière, Laboratoire de Virologie, Paris (E Todesco PhD); Department of Internal Medicine—Infectious Diseases, Erasmus University Medical Center, Rotterdam, Netherlands (C Rokx MD); Stichting HIV monitoring, Amsterdam, Netherlands (L Gras MSc); University of Pittsburgh, Pittsburgh, PA, USA (E K Halvas); Ethekwini District Health Office, KwaZulu-Natal, South Africa (H Sunpath MD); University of Rome Tor Vergata, Department of Experimental Medicine and Surgery, Rome, Italy (D Di Carlo MRes, M M Santoro PhD); INMI L. Spallanzani, Infectious Disease Unit, Rome, Italy (A Antinori); University Hospital Tor Vergata, Clinical Infectious Diseases, Rome, Italy (M Andreoni); San Gallicano Dermatological Institute, HIV/AIDS Unit, Rome, Italy (A Latini); Azienda Ospedaliero-Universitaria Policlinico, Clinic of Infectious Disease, Modena, Italy (C Mussini MD); Virology Laboratory CREMER-IMPM, Yaoundé, Cameroon (A Aghokeng PhD); Division of Clinical Microbiology and Unit of Infectious Diseases, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden (A Sonnerborg MD, U Neogi PhD); Kaiser Permanente Medical Care Program - Northern California, San Francisco, CA, USA (W J Fessel); Division of Global HIV/AIDS, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, GA, USA (S Agolory MD, E Raizes MD); International Laboratory Branch, Division of Global HIV/AIDS, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, GA, USA (C Yang PhD); Clinic Universitari–Institut d'Investigacions Biomèdiques August Pi i Sunyer, University of Barcelona, Barcelona, Spain (J L Blanco); Ministry of Health and Social Welfare, Tanzania (J M Juma); Public Health Laboratory, Birmingham, Public Health England (E Smit MD); Department of Infectious Disease Epidemiology, HIV/AIDS, STI and Blood Born Infections, Robert Koch-Institute, Berlin, Germany (D Schmidt PhD); Uganda Research Unit on AIDS, Entebbe, Uganda (C Watera MSc, J Asio MSc, P Kaleebu PhD); Ministry of Health, Uganda (W Kirungi MD); MRC Clinical Trials Unit at UCL, London, UK (A Tostevin PhD, D Dunn PhD); IBM Haifa Research Lab, Israel (T El-Hay PhD); Saint-Pierre University Hospital, Université Libre de Bruxelles, Belgium (N Clumeck MD); Department of Medical Microbiology and Virology, National Health Laboratory Service/University of the Free State, Bloemfontein, South Africa (D Goedhals PhD, C van Vuuren MD); Infection and Population Health, UCL, London, UK (C Sabin PhD); National AIDS & STI Control Programme, Ministry of Health, Nairobi, Kenya (I Mukui); INMI L Spallanzani, Antiretroviral Drugs Monitoring Unit, Rome, Italy (C F Perno MD); National Institute for Communicable Diseases, Sandringham, South Africa (G Hunt PhD, L Morris PhD); Wellcome Trust Africa Centre for Health and Population Studies, South Africa (T de Oliveira PhD, D Pillay FRCP); College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa (T de Oliveira); Department of Infection, UCL, London, UK (D Pillay, R K Gupta MRCP); Institute of Virology, University of Cologne, Cologne, Germany (E Schulter DIP); Centre for Research in Infectious Diseases, National Institute of Respiratory Diseases, Mexico City, Mexico (A Murakami-Ogasawara MD); Department of Medicine, Chulalongkorn University, Bangkok, Thailand (S Sirivichayakul PhD, K Ruxrungtham PhD, S Mekprasan BSc); and MRC/UVRI Uganda Research Unit on AIDS, Entebbe, Uganda (P Kaleebu)</p><p>*These authors contributed equally.</p><p>**Equal second author contributions.</p></ack><ack><title>Declaration of interests</title><p>CR has received personal fees from ViiV Healthcare, personal fees from MSD/Gilead outside of the submitted work. RG has received personal fees from BMS and Janssen-Cilag outside of the submitted work. HG reports personal fees from BMS, Gilead Sciences, Janssen-Cilag, ViiV Healthcare, Abbvie, and Merck outside the submitted work. AA reports grants and personal fees from BMS, Gilead Sciences, Janssen-Cilag, ViiV Healthcare, Abbvie, and Merck outside the submitted work. CS has received personal fees from BMS, Gilead, ViiV outside of the submitted work. RC reports personal fees from ViiV Healthcare and personal fees and grants from Abbvie outside the submitted work. CC reports personal fees from outside the submitted work. RWS reports grants from Gilead Sciences, Merck, Celera, Siemens Health care and Roche molecular diagnostics outside the submitted work. FG reports personal fees from MSD, Gilead Sciences, Janssen-Cilag, ViiV Healthcare, and Abbvie outside the submitted work. CvV reports personal fees from Pfizer and Mylan. AS reports fees from MSD, Gilead Sciences, Janssen-Cilag, ViiV Healthcare, and Abbvie outside the submitted work.</p></ack></back><floats-group><fig id="fig1"><label>Figure 1</label><caption><p>(A) Countries contributing data to resistance analysis and HIV-1 subtype distribution, (B) prevalence of drug resistance by mutation and by region</p><p>NNRTI=non-nucleotide reverse-transcriptase inhibitor. TDF=tenofovir disoproxil fumarate. *24% (n=462) of participants had tenofovir resistance when genotypes from viral load >1000 copies HIV-1 RNA per mL were considered.</p></caption><graphic xlink:href="gr1"></graphic></fig><fig id="fig2"><label>Figure 2</label><caption><p>Pooled odds ratios for tenofovir resistance after viral failure for baseline CD4 cell count <100 <italic>vs</italic> ≥100 × 10<sup>6</sup> cells per μL</p><p>TDF+ denotes presence of tenofovir resistance. TDF=tenofovir disoproxil fumarate.</p></caption><graphic xlink:href="gr2"></graphic></fig><fig id="fig3"><label>Figure 3</label><caption><p>Odds ratios for NNRTI resistance for (A) baseline CD4 cell count <100 <italic>vs</italic> ≥100 cells per μL, (B) viral load ≥100 000 <italic>vs</italic> <100 000 copies HIV-1 RNA per mL</p><p>NNRTI=non-nucleotide reverse-transcriptase inhibitor.</p></caption><graphic xlink:href="gr3"></graphic></fig><fig id="fig4"><label>Figure 4</label><caption><p>Boxplot of log viral load by presence (TDF-positive) or absence (TDF-negative) of tenofovir resistance at viral failure in studies with at least ten patients with TDF resistance and a viral load measurement at treatment failure</p><p>We restricted to studies with at least ten TDF-resistant mutations to help with graphical clarity, although the pattern of similar distributions of failure viral load in the presence or absence of TDF resistance was true for all studies. TDF=tenofovir disoproxil fumarate. Blue dots represent outliers.</p></caption><graphic xlink:href="gr4"></graphic></fig><table-wrap id="tbl1" position="float"><label>Table 1</label><caption><p>Characteristics of resistance studies included in analysis</p></caption><table frame="hsides" rules="groups"><thead><tr><th></th><th align="left"><bold>Countries</bold></th><th align="left"><bold>Studies</bold><xref rid="tbl1fn1" ref-type="table-fn">*</xref></th><th align="left"><bold>Mean study size</bold></th><th align="left"><bold>Median year of initiation of cART (range)</bold></th><th align="left"><bold>Studies in which frequent viral load monitoring was done (>2 viral loads per year)</bold></th><th align="left"><bold>Studies in which genotypic resistance testing done at viral load <1000 copies per mL</bold></th><th align="left"><bold>Studies in which baseline resistance testing was done</bold></th><th align="left"><bold>Rural clinics</bold></th></tr></thead><tbody><tr><td align="left">Eastern Africa (n=143)</td><td align="left">3</td><td align="left">7</td><td align="left">24</td><td align="left">2011 (2005–12)</td><td align="left">0</td><td align="left">1 (14%)</td><td align="left">1 (14%)</td><td align="left">2 (29%)</td></tr><tr><td align="left">Asia (n=356)</td><td align="left">4</td><td align="left">5</td><td align="left">71</td><td align="left">2010 (2005–13)</td><td align="left">2 (40%)</td><td align="left">2 (40%)</td><td align="left">2 (40%)</td><td align="left">1 (20%)</td></tr><tr><td align="left">Eastern Africa (n=143)</td><td align="left">3</td><td align="left">7</td><td align="left">24</td><td align="left">2011 (2005–12)</td><td align="left">0</td><td align="left">1 (14%)</td><td align="left">1 (14%)</td><td align="left">2 (29%)</td></tr><tr><td align="left">Latin America (n=68)</td><td align="left">5</td><td align="left">6</td><td align="left">11</td><td align="left">2008 (2000–15)</td><td align="left">4 (67%)</td><td align="left">2 (67%)</td><td align="left">2 (67%)</td><td align="left">0 (100%)</td></tr><tr><td align="left">North America (n=94)</td><td align="left">2</td><td align="left">3</td><td align="left">47</td><td align="left">2008 (2000–14)</td><td align="left">3 (100%)</td><td align="left">3 (100%)</td><td align="left">3 (100%)</td><td align="left">3 (100%)</td></tr><tr><td align="left">Southern Africa (n=404)</td><td align="left">6</td><td align="left">15</td><td align="left">45</td><td align="left">2010 (2005–12)</td><td align="left">4 (27%)</td><td align="left">4 (27%)</td><td align="left">4 (27%)</td><td align="left">5 (33%)</td></tr><tr><td align="left">West and central Africa (n=107)</td><td align="left">5</td><td align="left">10</td><td align="left">12</td><td align="left">2008 (2005–13)</td><td align="left">1 (10%)</td><td align="left">0</td><td align="left">0</td><td align="left">0</td></tr><tr><td align="left">Western Europe (n=754)</td><td align="left">11</td><td align="left">20</td><td align="left">69</td><td align="left">2008 (1998–2013)</td><td align="left">20 (100%)</td><td align="left">20 (100%)</td><td align="left">20 (100%)</td><td align="left">0</td></tr><tr><td align="left">All (n=1926)</td><td align="left">36</td><td align="left">66</td><td align="left">29</td><td align="left">2008 (1998–2015)</td><td align="left">34 (52%)</td><td align="left">32 (49%)</td><td align="left">32 (49%)</td><td align="left">11 (17%)</td></tr></tbody></table><table-wrap-foot><fn><p>Data are n, range, or n (%). cART=combination antiretroviral therapy.</p></fn></table-wrap-foot><table-wrap-foot><fn id="tbl1fn1"><label>*</label><p id="cenpara10">Multinational studies were treated as separate studies within each country.</p></fn></table-wrap-foot></table-wrap><table-wrap id="tbl2" position="float"><label>Table 2</label><caption><p>Participant characteristics and details of antiretroviral therapy</p></caption><table frame="hsides" rules="groups"><thead><tr><th></th><th align="left"><bold>Men</bold></th><th align="left"><bold>Age (years)</bold></th><th align="left"><bold>Efavirenz</bold></th><th align="left"><bold>Emtricitabine</bold></th><th align="left"><bold>Baseline CD4 cell count (× 10</bold><sup>6</sup><bold>cells per μL)</bold></th><th align="left"><bold>Pre-treatment log</bold><sub>10</sub><bold>baseline viral load</bold></th><th align="left"><bold>Number of months on TDF</bold></th></tr></thead><tbody><tr><td align="left">Asia (n=356)</td><td align="left">229 (67%)</td><td align="left">35 (30–39)</td><td align="left">300 (84%)</td><td align="left">73 (21%)</td><td align="left">100 (45–229)</td><td align="left">5·00 (4·55–5·68)</td><td align="left">14 (9–21)</td></tr><tr><td align="left">Eastern Africa (n=143)</td><td align="left">57 (40%)</td><td align="left">36 (29–44)</td><td align="left">56 (39%)</td><td align="left">53 (37%)</td><td align="left">104 (42–210)</td><td align="left">5·58 (5·30–5·83)</td><td align="left">14 (12–26)</td></tr><tr><td align="left">Latin America (n=68)</td><td align="left">19 (70%)</td><td align="left">34 (26–44)</td><td align="left">65 (96%)</td><td align="left">44 (65%)</td><td align="left">44 (14–86)</td><td align="left">5·47 (5·00–5·93)</td><td align="left">26 (11–57)</td></tr><tr><td align="left">North America (n=94)</td><td align="left">78 (84%)</td><td align="left">41 (35–48)</td><td align="left">81 (87%)</td><td align="left">61 (66%)</td><td align="left">144 (25–303)</td><td align="left">5·00 (4·59–5·53)</td><td align="left">11 (6–24)</td></tr><tr><td align="left">Southern Africa (n=404)</td><td align="left">147 (36%)</td><td align="left">34 (28–40)</td><td align="left">290 (72%)</td><td align="left">89 (22%)</td><td align="left">98 (40–169)</td><td align="left">4·80 (3·81–5·47)</td><td align="left">18 (12–28)</td></tr><tr><td align="left">West and central Africa (n=107)</td><td align="left">45 (42%)</td><td align="left">36 (30–42)</td><td align="left">39 (36%)</td><td align="left">79 (74%)</td><td align="left">89 (37–166)</td><td align="left">5·32 (4·92–5·81)</td><td align="left">13 (11–18)</td></tr><tr><td align="left">Western Europe (n=754)</td><td align="left">571 (76%)</td><td align="left">38 (32–44)</td><td align="left">653 (87%)</td><td align="left">633 (84%)</td><td align="left">199 (91–300)</td><td align="left">5·00 (4·28–5·46)</td><td align="left">12 (7–26)</td></tr><tr><td align="left">All (n=1926)</td><td align="left">1146 (62%)</td><td align="left">37 (30–44)</td><td align="left">1485 (77%)</td><td align="left">1032 (54%)</td><td align="left">139 (53–250)</td><td align="left">5·06 (4·45–5·56)</td><td align="left">14 (9–27)</td></tr></tbody></table><table-wrap-foot><fn><p>Data are n (%) or median (IQR). 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