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Temporal trends of transmitted HIV drug resistance in a multinational seroconversion cohort

Olson, Ashleya; Bannert, Norbertb; Sönnerborg, Andersc; de Mendoza, Carmend; Price, Matthewe,f; Zangerle, Robertg; Chaix, Marie-Laureh; Prins, Mariai; Kran, Anne-Marte, Bakkenj,k; Gill, Johnl; Paraskevis, Dimitriosm; Porter, Kholoudafor CASCADE Collaboration in EuroCoord

doi: 10.1097/QAD.0000000000001689

Background: The rate of transmitted drug resistance (TDR) may increase with wider use of antiretroviral therapy and can contribute to therapeutic failure. We analysed time trends in TDR among HIV seroconverters.

Methods: Using CASCADE data of individuals with well estimated dates of HIV seroconversion, we examined HIV nucleotide sequences collected prior to antiretroviral therapy use from 1996–2012. All samples were taken within 12 months of testing HIV positive. Using logistic regression, we examined the association between TDR and year of seroconversion, adjusting for confounders.

Results: Of 4717 individuals seroconverting between 1996 and 2012, median (IQR) age at seroconversion was 33 (27, 39) years. The majority (3839; 92%) were male, mainly exposed through MSM (3767; 80%), and infected with subtype B (3464; 73%). Overall, 515 (11%) individuals had at least one drug resistance-related mutation; 280 individuals with nucleoside reverse transcriptase, 185 with nonnucleoside reverse transcriptase, and 144 with protease inhibitor mutations. Estimated TDR prevalence was 19.4% (8.2, 36.0) in 1996, significantly decreasing to 8.5% (5.9, 11.9) in 2012 [odds ratio (OR; 95% confidence interval (CI)) = 0.92 (0.90, 0.95) per year increase]. Individuals exposed through sex between men and women were significantly less likely to have been infected with a drug-resistant strain [OR (95% CI) = 0.59 (0.41, 0.87) compared with MSM], and there was marginal evidence that sampling during acute infection was associated with higher odds of resistance [OR (95% CI) = 1.20 (0.97, 1.7), P = 0.093] compared with later sampling.

Conclusion: TDR has decreased over calendar time although a significant proportion of new infections still carry resistance-related mutations.

aUniversity College London, London, UK

bDivision of HIV and Other Retroviruses, Robert Koch Institute, Berlin, Germany

cUnit of Infectious Diseases, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden

dDepartment of Internal Medicine, Puerta de Hierro Research Institute and University Hospital, Majadahonda, Madrid, Spain

eInternational AIDS Vaccine Initiative, New York, New York

fDepartment of Epidemiology and Biostatistics, University of California San Francisco, California, USA

gDepartment of Dermatology and Venerology, Innsbruck Medical University, Innsbruck, Austria

hHôpital Necker-Enfants Malades, Université Paris Descartes, Paris, France

iPublic Health Service of Amsterdam, Cluster of Infectious Diseases, Amsterdam, the Netherlands

jDepartment of Microbiology, Oslo University Hospital

kInstitute of Clinical Medicine, University of Oslo, Oslo, Norway

lUniversity of Calgary, Calgary, Alberta, Canada

mDepartment of Hygiene, Epidemiology and Medical Statistics, University of Athens, Athens, Greece.

Correspondence to Professor Kholoud Porter, University College London, Gower St, Bloomsbury, London WC1E 6BT, UK. E-mail:

Received 22 February, 2017

Revised 26 September, 2017

Accepted 9 October, 2017

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Website (

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Combination antiretroviral therapy (cART) is effective at suppressing plasma HIV RNA to undetectable levels [1] thereby improving patient prognosis [2,3] and reducing the risk of onward transmission of HIV when viral suppression is achieved [4]. However, poor adherence [5–9] can lead to the development of mutations [10] which are associated with HIV drug resistance and subsequent cART failure. Individuals failing treatment have worse health outcomes [11–13], are less likely to benefit from newer drugs, and can pass drug resistant strains of HIV to others [14]. Given this concern, international guidelines recommend that newly diagnosed individuals are tested for evidence of resistance to optimize the selection of first-line cART regimes [15,16].

Recent data from cART-naive seroprevalent cohorts suggest the prevalence of TDR has either stabilized [17,18] or decreased from 2002 to 2009 [19–21]. Given that timing of HIV infection is not known for individuals in seroprevalent cohorts; however, estimated TDR rates may reflect historical trends but not necessarily trends among those recently infected. Furthermore, because of the reversion of a number of mutations to wild-type over time in the absence of cART [22], analysis of TDR rates among seroprevalent cohorts may under-estimate actual TDR prevalence. Trends of TDR among HIV seroconverters are unclear with some studies showing increased TDR between 1987 and 2003 [23] or stability between 1996 and 2007 [24].

Temporal trends of transmitted drug resistance (TDR) among individuals recently infected need to be monitored as new drugs and classes are introduced to inform clinical decision making. We aim to describe the temporal trends of TDR among recently infected individuals using CASCADE data of HIV seroconverters, and to identify predictors of TDR.

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Study population

We used pooled data from the Concerted Action on SeroConversion to AIDS and Death in Europe (CASCADE) 2014 data release on HIV-1 seroconverters in EuroCoord (, which has been described in detail elsewhere [25]. Briefly, CASCADE is a cohort collaboration of 31 772 HIV-1 seroconverters from 16 countries across Europe (95%), Australia (1%), Canada (1%), and Sub-Saharan Africa (3%). Date of HIV seroconversion was estimated most commonly (87%) as the midpoint between the last documented negative and the first documented positive HIV antibody test dates with an interval of less than 3 years between the two dates. The remaining individuals had seroconversion dates estimated through laboratory evidence of seroconversion (PCR positivity in the absence of HIV antibodies or antigen positivity with fewer than four bands on western blot – 10%), or as the date of seroconversion illness with both an earlier documented negative and a later positive HIV test not more than 3 years apart (2%).

We restricted our analysis to those with documented seroconversion in the cART era (>1995) with at least one viral genetic sequence within the first year of testing positive for HIV while still being ART naive. Additionally, we restricted the analysis to those seroconverting before 1 January 2013 as to allow at least 1 year of follow-up.

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Resistance and subtype analysis

Genotypic resistance data were derived from sequencing of the protease and reverse transcriptase genes performed by laboratories in the country of care using a variety of in-house and commercial resistance assays. The Stanford HIVdb algorithm 7.0 was used centrally to analyse all nucleotide sequences (; updated on 27 February 2014) [26]. Subtype was analysed and assigned centrally using the REGA algorithm [27].

An individual was categorized as having a transmitted HIV-1 drug resistance-associated mutation if their virus contained one or more mutations from the Surveillance Drug Resistance Mutations list defined by the WHO [28]. We further derived susceptibility to antiretroviral drugs using the Stanford HIV database algorithm. Individuals were considered to have high level of resistance if the Stanford score was higher than 3. Using this algorithm, we further identified mutations associated with drugs of current first-line recommendations according to the European AIDS Clinical Society guidelines (categories A and B) [29].

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Statistical methods

Proportions and their associated 95% confidence intervals (CI) were calculated using exact CIs for binomially distributed data. Linear logistic regression was used to assess the time trends of TDR as there was no statistical evidence for departures from linearity using natural cubic splines [30]. Time trend models were adjusted for sex, HIV transmission risk group, seroconversion age, and HIV diagnosis during acute HIV infection, defined as laboratory evidence of HIV seroconversion or having an HIV test interval of less than 30 days. Age at HIV seroconversion was modelled linearly as there was no evidence for departures from linearity using natural cubic splines. Owing to small numbers, we were not able to evaluate the time trends of individual mutations. Instead, we list the most common mutations over the calendar period.

In a sensitivity analysis, we restricted our analysis to include only individuals infected with subtype B as our cohort consists predominantly of subtype B (>70%), and HIV genetic diversity may influence the emergence and type of resistance mutations.

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Baseline characteristics

We analysed data from 4717 seroconverters in CASCADE with at least one ART-naive nucleotide sequence available during the first year following HIV seroconversion. Median age at HIV seroconversion was 33 (IQR = 27, 39) years, and the most common HIV transmission risk group was MSM (80%) followed by sex between men and women (MSW, 15%), people who inject drugs (PWID, 3%) and unknown (n = 101, 2%). HIV subtype was mainly B (n = 3464, 73%), followed by C (n = 288, 8%), A (n = 240, 6%), and a recombinant form (n = 176, 4%), Table 1. Median (IQR) time from HIV seroconversion to sample collection was 124 (44, 256) days, and did not differ between those with and without mutations associated with HIV drug resistance (P = 0.31, data not shown). Of the 4717 seroconverters, 1222 (26%) were diagnosed with HIV during acute HIV infection, a proportion which did not differ between those with and without mutations associated with HIV drug resistance (P = 0.26, data not shown). The majority of individuals were receiving care in Germany (34%), the UK (21%), or Sweden (12%).

Table 1

Table 1

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Transmitted drug resistance

Overall, 203 (4.3%; 95% CI = 3.7–4.9) individuals had one mutation and 515 (10.9%; 95% CI = 10.0–11.8) had one or more mutations associated with TDR. Among these 515 individuals, 93 (2.0%; 1.6–2.4), 98 (2.1%; 1.7–2.5), and 67 (1.4%; 1.1–1.8) had one mutation associated with nucleoside reverse transcriptase inhibitors (NRTI), non-NRTIs (NNRTI), or protease inhibitors, respectively, and 280 (5.9%; 5.2–6.6), 185 (3.9%; 3.4–4.5), and 144 (3.1%; 2.6–3.6), had one or more mutations associated with NRTI, NNRTI, or protease inhibitors, respectively.

The most frequent mutations (>5% of individuals with mutations) related to NRTIs were 41L (n = 91; 18%), 215S (n = 61; 12%), 184V (n = 34; 7%), 67N (n = 30; 6%), 210W (n = 28; 5%) 219Q (n = 27; 5%). For NNRTIs, the most common mutation was 103N (n = 119; 23%) and, for protease inhibitors these were 90M (n = 39; 8%), 46I (n = 31; 6%), and 46L (n = 26; 5%) (Supplementary Table 1; In total, 436 (9%) individuals had mutations associated with a single class, 79 (2%) had mutations associated with two or more classes, and 15 (<1%%) had mutations associated with three classes (NRTI, NNRTI, and protease inhibitor).

We observed a significant decline in the prevalence of TDR to any class during 1996–2012, the calendar year of seroconversion; odds ratio (OR) = 0.92 (95% CI; 0.90, 0.95) per year, starting at 19.4% (8.2, 36.0) in 1996 and falling to 8.5% (5.9, 11.9) in 2012. The same decreasing trend over time was observed for transmitted NRTI resistance, OR = 0.89 (0.86, 0.91) per year, NNRTI resistance, OR = 0.96 (0.93, 1.00) per year, and protease inhibitor resistance, OR = 0.93 (0.89, 0.97) per year (Table 2, Fig. 1).

Table 2

Table 2

Fig. 1

Fig. 1

In more recent years (2007–2012), data were available on 2546 individuals, 216 [8.5% (7.4, 9.6)] of whom had a mutation associated with TDR. Among these individuals, 98 (3.8%; 3.1–4.6), 89 (3.5%; 2.8–4.2), and 62 (2.4%; 1.8–3.1), had one or more mutations associated with NRTI, NNRTI, or protease inhibitor, respectively. The most common mutations in this time period include NTRI mutations 41L (n = 34; 16%), 215S (n = 26; 12%), and 215D (n = 15; 7%); NNRTI mutation 103N (n = 56; 26%); and protease inhibitor mutations 90M (n = 19; 9%) and 46L (n = 12; 6%).

In a sensitivity analysis, restricting to those infected with subtype B, we observed the same trends of TDR decreasing over the calendar period (data not shown). Findings were also consistent across all CASCADE participating cohorts.

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Drug susceptibility

Of 4717 individuals, 296 (6.3%; 5.5–7.0) had a transmitted mutation associated with high-level resistance to a drug according to the Stanford HIV database algorithm, 190 (4.0%; 3.5–4.6) of these were associated with an agent in a recommended first-line treatment regimen with efavirenz having the highest proportion of high-level resistance, Fig. 2. In total, 102 (2.2%; 1.8–2.6), 163 (3.5%; 2.9–4.0), and 83 (1.8%; 1.4–2.2), individuals had at least one transmitted mutation associated with high level of resistance to NRTIs, NNRTIs, and protease inhibitor, respectively. Among the 2546 individuals seroconverting more recently (2007–2012), 154 [6.0% (5.2, 7.0)] had a transmitted mutation associated with high-level resistance; 93 (3.7%; 3.0–4.5), 42 [1.6% (1.2, 2.2)], 91 [3.6% (2.9, 4.4)], 46 [1.8% (1.3, 2.4)] with high-level resistance associated with a first-line regimen, NRTIs, NNRTIs, and protease inhibitors, respectively.

Fig. 2

Fig. 2

During the calendar period of observation, the rate of transmitted high-level drug resistance declined; OR = 0.97 (95% CI; 0.94, 1.0005) per year, P = 0.054. A significant decreasing trend over time was observed for high-level resistance to first-line regimens, OR = 0.92 (0.87, 0.97), P less than 0.001 per year and high-level NRTI resistance, OR = 0.89 (0.85, 0.93), P less than 0.001 per year. The same trend was observed in high-level protease inhibitor resistance, OR = 0.96 (0.91, 1.01), P = 0.18 per year. There was no evidence of a decrease in high-level NNRTI resistance over calendar time, although levels have remained relatively low throughout the period of observation of our study at 3.4%.

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Predictors of transmitted drug resistance

There was significant heterogeneity between HIV transmission risk group and any TDR and NRTI TDR with those exposed through MSW having a lower probability of being infected with a drug-resistant strain compared to MSM. Older individuals were more likely to have been infected with a protease inhibitor resistant strain (P = 0.003) as were females, although the evidence for females was modest [OR = 2.03 (0.92, 4.47, P = 0.08)]. Individuals diagnosed during acute HIV infection were slightly more likely to be infected with a resistant strain, OR = 1.20 (0.97, 1.47; Table 2). Of the 1222 individuals in our study diagnosed during acute HIV infection, 144 (11.8%) had at least one mutation associated with TDR compared with 10.9% of individuals with TDR diagnosed later in infection.

When we restricted to those seroconverting in more recent years (2007–2012), older age was the only significant predictor for transmitted HIV drug resistance; OR = 1.58 (1.01, 2.45; P = 0.043), 1.50 (0.94, 2.41; P = 0.092), and 1.93 (1.13, 3.29; P = 0.016) for ages 25–34, 35–44, and 45 and above, respectively, compared with those aged 15–25 years at seroconversion.

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The prevalence of TDR and high-level resistance among individuals with recent HIV infection decreased between 1996 and 2012. Our estimates provide a realistic estimation of actual TDR in those years as our study was restricted to analysing viral sequences from individuals sampled close to the time of HIV seroconversion. Our results confirm and expand findings from studies of ART-naive individuals with unknown duration of HIV infection [19,20], and consistent with European reports of TDR with unknown duration of HIV infection [31,32]. Of note, although we show clear evidence for a decline in TDR rates over time, the 8.5% TDR prevalence in the most recent years highlights a moderate but ongoing risk of being infected with drug resistant virus remains.

We detected moderate evidence of an association between TDR and sampling during acute HIV infection. This suggests that TDR may be associated with seroconversion symptoms, possibly leading to presentation to care and HIV diagnosis during acute infection. It may also simply reflect that TDR rates are underestimated if genotypic resistance testing is not performed close to seroconversion because of reversion of mutations to wild type in the absence of drug selective pressure [11]. Of note, we found a similar proportion of TDR, 11.8%, among those diagnosed during acute infection throughout our period of study. There was also a similar association between TDR and acute HIV infection [OR = 1.16 (0.84, 1.58)], although this did not reach statistical significance as fewer individuals contributed to these analyses.

We also found evidence that MSM were more likely to have been infected with resistant strains compared with PWID and MSW. This has been reported by a number of studies in high-income countries [33–36] and may be because of historical access to HIV care, where MSM have been typically more exposed to ART than other risk groups [37], particularly the use of thymidine analogues such as stavudine and zidovudine, the mutations associated with which are known to be persistent [38]. This is supported by the differentially higher rates of NRTI mutation among MSM compared with other risk groups; 6.5, 4.5, and 3.2% among MSM, PWID, and MSW, respectively. The high prevalence of TDR among the MSM especially the last years, could also be because of the high incidence of HIV in this group in Western Europe, where in some cases transmissions may have occurred in transmission clusters of resistant strains in this population.

Our study has a number of limitations. Although we analysed data only from HIV seroconverters to assess actual TDR trends by year of infection, it is known that risk behaviour differs between seroconverters and nonseroconverter HIV-positive individuals [39,40], and that such behaviour may put them at greater risk of becoming infected with drug-resistant HIV. The prevalence of TDR, however, in our cohort was similar to that reported among other (seroprevalent) cohorts in Europe [19,20,24,41] suggesting that our time trends for TDR are generalizable to the HIV-positive population in Europe. However, our numbers outside Europe are small, so although our estimates were consistent across all CASCADE cohorts, our estimates might not be as robust and generalizable in lower income countries. It is also feasible that there were treatment misclassifications and patients with prior ART experience were included in our analysis. Research by the UK HIV Drug Resistance Database suggests that if there is more than a 4% misclassification, time trends could be distorted [42]. Being that integrase inhibitors are a new drug class, we were not able to provide temporal trend estimates for mutations associated with integrase inhibitors, as data on such mutations were limited, where only two individuals had a resistance mutation associated with integrase inhibitor raltegravir. In addition, those with genotypic tests tended to be different than those without genotypic tests, where individuals with genotype tests tended to seroconvert in later years, were more likely to be MSM, present with acute HIV infection, and have shorter HIV test intervals. Also, certain countries tended to test more for genotypic resistance (e.g. Germany and the UK) compared with other countries (e.g. France). We may, therefore, have underestimated the overall prevalence of TDR, given that the risk was higher in earlier years. It is unlikely, however, that the preferential inclusion of MSM among sequenced individuals will have affected our main finding of a decreasing TDR trend given that the proportion of MSM sequined has remained stable at about 60% over the calendar period.

In conclusion, we found a steady decline in TDR among individuals newly infected with HIV between 1996 (19.4% TDR) and 2012 (8.5% TDR). Although the rate of transmitted drug-resistant HIV has decreased, a not insubstantial proportion of newly infected individuals are being diagnosed with drug-resistant strains. Given that resistance testing among such individuals remains cost-effective for baseline resistance above 1% [43], testing for evidence of TDR remains justifiable.

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Role of authors: All authors made significant contributions to this manuscript by providing data and extensive comments on the manuscript drafts prepared by A.O. and K.P.

The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under EuroCoord grant agreement n° 260694.

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CASCADE Collaboration in EuroCoord

CASCADE Steering Committee: Julia Del Amo (Chair), Laurence Meyer (Vice Chair), Heiner C. Bucher, Geneviève Chêne, Osamah Hamouda, Deenan Pillay, Maria Prins, Magda Rosinska, Caroline Sabin, Giota Touloumi.

CASCADE Co-ordinating Centre: Kholoud Porter (Project Leader), Annabelle Gourlay, Andrea Cartier, Lorraine Fradette, Sarah Walker, Abdel Babiker.

CASCADE Clinical Advisory Board: Heiner C. Bucher, Andrea De Luca, Martin Fisher, Roberto Muga

CASCADE Collaborators: Australia PHAEDRA cohort (Tony Kelleher, David Cooper, Robert Finlayson, Mark Bloch) Sydney AIDS Prospective Study and Sydney Primary HIV Infection cohort (Tony Kelleher, Tim Ramacciotti, Linda Gelgor, David Cooper, Don Smith); Austria Austrian HIV Cohort Study (Robert Zangerle); Canada South Alberta clinic (John Gill); Estonia Tartu Ülikool (Irja Lutsar); France ANRS CO3 Aquitaine cohort (Linda Wittkop, Francois Dabis, Rodolphe Thiebaut), ANRS CO4 French Hospital Database (Dominique Costagliola, Marguerite Guiguet), Lyon Primary Infection cohort (Philippe Vanhems), French ANRS CO6 PRIMO cohort (Marie-Laure Chaix, Jade Ghosn), ANRS CO2 SEROCO cohort (Laurence Meyer, Faroudy Boufassa); Germany German HIV-1 seroconverter cohort (Osamah Hamouda, Claudia Kücherer, Barbara Bartmeyer); Greece AMACS (Helen Sambatakou, Nikolaos V Sipsas, Charalambos A Gogos); Greek Haemophilia cohort (Giota Touloumi, Nikos Pantazis, Olga Katsarou); Italy Italian Seroconversion Study (Giovanni Rezza, Maria Dorrucci), ICONA cohort (Antonella d’Arminio Monforte, Andrea De Luca.) Netherlands Amsterdam Cohort Studies among homosexual men and drug users (Maria Prins, Ronald Geskus, Jannie van der Helm, Hanneke Schuitemaker); Norway Oslo and Ulleval Hospital cohorts (Mette Sannes, Oddbjorn Brubakk, Anne-Marte Bakken Kran, Anne Margarita Dyrhol Riise); Poland National Institute of Hygiene (Magdalena Rosinska); Spain Badalona IDU hospital cohort (Roberto Muga, Jordi Tor), Barcelona IDU Cohort (Patricia Garcia de Olalla, Joan Cayla), CoRIS-scv (Julia del Amo, Santiago Moreno, Susana Monge); Madrid cohort (Julia Del Amo, Jorge del Romero), Valencia IDU cohort (Santiago Pérez-Hoyos); Sweden Swedish InfCare HIV Cohort, Sweden (Anders Sönnerborg); Switzerland Swiss HIV Cohort Study (Heiner C. Bucher, Huldrych Günthard, Alexandra Scherrer); Ukraine Perinatal Prevention of AIDS Initiative (Ruslan Malyuta); United Kingdom Public Health England (Gary Murphy), UK Register of HIV Seroconverters (Kholoud Porter, Anne Johnson, Andrew Phillips, Abdel Babiker), University College London (Deenan Pillay); African cohorts: Genital Shedding Study (US: Charles Morrison; Family Health International, Robert Salata, Case Western Reserve University, Uganda: Roy Mugerwa, Makerere University, Zimbabwe: Tsungai Chipato, University of Zimbabwe); International AIDS Vaccine Initiative (IAVI) Early Infections Cohort (Kenya, Rwanda, South Africa, Uganda, Zambia: Pauli N. Amornkul, IAVI, USA; Jill Gilmour, IAVI, UK; Anatoli Kamali, Uganda Virus Research Institute/Medical Research Council Uganda; Etienne Karita, Projet San Francisco, Rwanda).

EuroCoord Executive Board: Fiona Burns, University College London, UK; Geneviève Chêne (Chair), University of Bordeaux, France; Dominique Costagliola (Scientific Coordinator), Institut National de la Santé et de la Recherche Médicale, France; Carlo Giaquinto, Fondazione PENTA, Italy; Jesper Grarup, Region Hovedstaden, Denmark; Ole Kirk, Region Hovedstaden, Denmark; Laurence Meyer, Institut National de la Santé et de la Recherche Médicale, France; Heather Bailey, University College London, UK; Alain Volny Anne, European AIDS Treatment Group, France; Alex Panteleev, St. Petersburg City AIDS Centre, Russian Federation; Andrew Phillips, University College London, UK, Kholoud Porter, University College London, UK; Claire Thorne, University College London, UK.

EuroCoord Council of Partners: Jean-Pierre Aboulker, Institut National de la Santé et de la Recherche Médicale, France; Jan Albert, Karolinska Institute, Sweden; Silvia Asandi, Romanian Angel Appeal Foundation, Romania; Geneviève Chêne, University of Bordeaux, France; Dominique Costagliola, INSERM, France; Antonella d’Arminio Monforte, ICoNA Foundation, Italy; Stéphane De Wit, St. Pierre University Hospital, Belgium; Peter Reiss, Stichting HIV Monitoring, Netherlands; Julia Del Amo, Instituto de Salud Carlos III, Spain; José Gatell, Fundació Privada Clínic per a la Recerca Bíomèdica, Spain; Carlo Giaquinto, Fondazione PENTA, Italy; Osamah Hamouda, Robert Koch Institut, Germany; Igor Karpov, University of Minsk, Belarus; Bruno Ledergerber, University of Zurich, Switzerland; Jens Lundgren, Region Hovedstaden, Denmark; Ruslan Malyuta (Chair), Perinatal Prevention of AIDS Initiative, Ukraine; Claus Møller, Cadpeople A/S, Denmark; Kholoud Porter, University College London, United Kingdom; Maria Prins, Academic Medical Centre, Netherlands; Aza Rakhmanova, St. Petersburg City AIDS Centre, Russian Federation; Jürgen Rockstroh, University of Bonn, Germany; Magda Rosinska, National Institute of Public Health, National Institute of Hygiene, Poland; Manjinder Sandhu, Genome Research Limited; Claire Thorne, University College London, UK; Giota Touloumi, National and Kapodistrian University of Athens, Greece; Alain Volny Anne, European AIDS Treatment Group, France.

EuroCoord External Advisory Board: David Cooper, University of New South Wales, Australia; Nikos Dedes, Positive Voice, Greece; Kevin Fenton, Public Health England, USA; David Pizzuti, Gilead Sciences, USA; Marco Vitoria, World Health Organisation, Switzerland.

EuroCoord Secretariat: Silvia Faggion, Fondazione PENTA, Italy; Lorraine Fradette, University College London, UK; Richard Frost, University College London, UK; Andrea Cartier, University College London, UK; Dorthe Raben, Region Hovedstaden, Denmark; Christine Schwimmer, University of Bordeaux, France; Martin Scott, UCL European Research & Innovation Office, UK.

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Conflicts of interest

There are no conflicts of interest.

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1. Gulick RM, Mellors JW, Havlir D, Eron JJ, Gonzalez C, McMahon D, et al. Treatment with indinavir, zidovudine, and lamivudine in adults with human immunodeficiency virus infection and prior antiretroviral therapy. N Engl J Med 1997; 337:734–739.
2. Palella FJ Jr, Delaney KM, Moorman AC, Loveless MO, Fuhrer J, Satten GA, et al. Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection. HIV Outpatient Study Investigators. N Engl J Med 1998; 338:853–860.
3. Dieffenbach CW, Fauci AS. Thirty years of HIV and AIDS: future challenges and opportunities. Ann Intern Med 2011; 154:766–771.
4. Cohen MS, Chen YQ, McCauley M, Gamble T, Hosseinipour MC, Kumarasamy N, et al. HPTN 052 Study Team. Prevention of HIV-1 infection with early antiretroviral therapy. N Engl J Med 2011; 365:493–505.
5. Martin M, Del Cacho E, Codina C, Tuset M, De Lazzari E, Mallolas J, et al. Relationship between adherence level, type of the antiretroviral regimen, and plasma HIV type 1 RNA viral load: a prospective cohort study. AIDS Res Hum Retroviruses 2008; 24:1263–1268.
6. Nachega JB, Hislop M, Dowdy DW, Chaisson RE, Regensberg L, Maartens G. Adherence to nonnucleoside reverse transcriptase inhibitor-based HIV therapy and virologic outcomes. Ann Intern Med 2007; 146:564–573.
7. Bangsberg DR. Less than 95% adherence to nonnucleoside reverse-transcriptase inhibitor therapy can lead to viral suppression. Clin Infect Dis 2006; 43:939–941.
8. Paterson DL, Swindells S, Mohr J, Brester M, Vergis EN, Squier C, et al. Adherence to protease inhibitor therapy and outcomes in patients with HIV infection. Ann Intern Med 2000; 133:21–30.
9. Maggiolo F, Ravasio L, Ripamonti D, Gregis G, Quinzan G, Arici C, et al. Similar adherence rates favor different virologic outcomes for patients treated with nonnucleoside analogues or protease inhibitors. Clin Infect Dis 2005; 40:158–163.
10. Wittkop L, Gunthard HF, de Wolf F, Dunn D, Cozzi-Lepri A, de Luca A, et al. EuroCoord-CHAIN study group. Effect of transmitted drug resistance on virological and immunological response to initial combination antiretroviral therapy for HIV (EuroCoord-CHAIN joint project): a European multicohort study. Lancet Infect Dis 2011; 11:363–371.
11. Zaccarelli M, Tozzi V, Lorenzini P, Trotta MP, Forbici F, Visco-Comandini U, et al. Multiple drug class-wide resistance associated with poorer survival after treatment failure in a cohort of HIV-infected patients. AIDS 2005; 19:1081–1089.
12. Lucas GM, Gallant JE, Moore RD. Relationship between drug resistance and HIV-1 disease progression or death in patients undergoing resistance testing. AIDS 2004; 18:1539–1548.
13. Hogg RS, Bangsberg DR, Lima VD, Alexander C, Bonner S, Yip B, et al. Emergence of drug resistance is associated with an increased risk of death among patients first starting HAART. PLoS Med 2006; 3:e356.
14. Yanik EL, Napravnik S, Hurt CB, Dennis A, Quinlivan EB, Sebastian J, et al. Prevalence of transmitted antiretroviral drug resistance differs between acutely and chronically HIV-infected patients. J Acquir Immune Defic Syndr 2012; 61:258–262.
15. Gazzard BG, Anderson J, Babiker A, Boffito M, Brook G, Brough G, et al. BHIVA Treatment Guidelines Writing Group. British HIV association guidelines for the treatment of HIV-1-infected adults with antiretroviral therapy 2008. HIV Med 2008; 9:563–608.
16. Hicks CB. Guideline watch. Antiretroviral drug resistance testing: updated guidelines from the IAS-USA. AIDS Clin Care 2008; 20:64.
17. Vercauteren J, Wensing AM, van de Vijver DA, Albert J, Balotta C, Hamouda O, et al. Transmission of drug-resistant HIV-1 is stabilizing in Europe. J Infect Dis 2009; 200:1503–1508.
18. Yerly S, von Wyl V, Ledergerber B, Böni J, Schüpbach J, Bürgisser P, et al. Swiss HIV Cohort Study. Transmission of HIV-1 drug resistance in Switzerland: a 10-year molecular epidemiology survey. AIDS 2007; 21:2223–2229.
19. Dolling D, Sabin C, Delpech V, Smit E, Pozniak A, Asboe D, et al. UK Collaborative Group on HIV Drug Resistance. Time trends in drug resistant HIV-1 infections in the United Kingdom up to 2009: multicentre observational study. BMJ 2012; 345:e5253.
20. UK Collaborative Group on HIV Drug Resistance; UK Collaborative HIV Cohort Study; UK Register of HIV Seroconverters. Evidence of a decline in transmitted HIV-1 drug resistance in the United Kingdom. AIDS 2007; 21:1035–1039.
21. Scherrer AU, von Wyl V, Yang WL, Kouyos RD, Böni J, Yerly S, et al. Emergence of acquired HIV-1 drug resistance almost stopped in Switzerland: a 15-year prospective cohort analysis. Clin Infect Dis 2016; 62:1310–1317.
22. Gandhi RT, Wurcel A, Rosenberg ES, Johnston MN, Hellmann N, Bates M, et al. Progressive reversion of human immunodeficiency virus type 1 resistance mutations in vivo after transmission of a multiply drug-resistant virus. Clin Infect Dis 2003; 37:1693–1698.
23. Masquelier B, Bhaskaran K, Pillay D, Gifford R, Balestre E, Jørgensen LB, et al. CASCADE Collaboration. Prevalence of transmitted HIV-1 drug resistance and the role of resistance algorithms: data from seroconverters in the CASCADE collaboration from 1987 to 2003. J Acquir Immune Defic Syndr 2005; 40:505–511.
24. Bartmeyer B, Kuecherer C, Houareau C, Werning J, Keeren K, Somogyi S, et al. German HIV-1 Seroconverter Study Group. Prevalence of transmitted drug resistance and impact of transmitted resistance on treatment success in the German HIV-1 Seroconverter Cohort. PloS One 2010; 5:e12718.
25. de Wolf F, Sabin C, Kirk O, Thorne C, Chene G, Porter K. Developing a multidisciplinary network for clinical research on HIV infection: the EuroCoord experience. Clin Invest 2012; 2:255–264.
26. Liu TF, Shafer RW. Web resources for HIV type 1 genotypic-resistance test interpretation. Clin Infect Dis 2006; 42:1608–1618.
27. de Oliveira T, Deforche K, Cassol S, Salminen M, Paraskevis D, Seebregts C, et al. An automated genotyping system for analysis of HIV-1 and other microbial sequences. Bioinformatics 2005; 21:3797–3800.
28. Bennett DE, Camacho RJ, Otelea D, Kuritzkes DR, Fleury H, Kiuchi M, et al. Drug resistance mutations for surveillance of transmitted HIV-1 drug-resistance: 2009 update. PloS One 2009; 4:e4724.
29. European AIDS Clinical Society (EACS). Guidelines. Version 8.0. 2015; [Accessed 9 August 2016]
30. Durrleman S, Simon R. Flexible regression models with cubic splines. Stat Med 1989; 8:551–561.
31. Rahim S, Fredrick LM, da Silva BA, Bernstein B, King MS. Geographic and temporal trends of transmitted HIV-1 drug resistance among antiretroviral-naive subjects screening for two clinical trials in North America and Western Europe. HIV Clin Trials 2009; 10:94–103.
32. Frentz D, Boucher CA, van de Vijver DA. Temporal changes in the epidemiology of transmission of drug-resistant HIV-1 across the world. AIDS Rev 2012; 14:17–27.
33. Frange P, Assoumou L, Descamps D, Chéret A, Goujard C, Tran L, et al. 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 Chemother 2015; 70:2084–2089.
34. Vega Y, Delgado E, Fernandez-Garcia A, Cuevas MT, Thomson MM, Montero V, et al. Spanish Group for the Study of New HIV-1 Diagnoses in Galicia and Basque Country. Epidemiological surveillance of HIV-1 transmitted drug resistance in Spain in 2004–2012: relevance of transmission clusters in the propagation of resistance mutations. PloS One 2015; 10:e0125699.
35. Pineda-Pena AC, Schrooten Y, Vinken L, Ferreira F, Li G, Trovão NS, et al. Trends and predictors of transmitted drug resistance (TDR) and clusters with TDR in a local Belgian HIV-1 epidemic. PloS One 2014; 9:e101738.
36. Chilton DN, Castro H, Lattimore S, Harrison LJ, Fearnhill E, Delpech V, et al. UK Collaborative Group on HIV Drug Resistance. HIV type-1 drug resistance in antiretroviral treatment-naive adults infected with non-B subtype virus in the United Kingdom. Antivir Ther 2010; 15:985–991.
37. CASCADE (Concerted Action on SeroConversion to AIDS and Death in Europe) Collaboration. Changes in the uptake of antiretroviral therapy and survival in people with known duration of HIV infection in Europe: results from CASCADE. HIV Med 2000; 1:224–231.
38. Castro H, Pillay D, Cane P, Asboe D, Cambiano V, Phillips A, Dunn DT. UK Collaborative Group on HIV Drug Resistance. Persistence of HIV-1 transmitted drug resistance mutations. J Infect Dis 2013; 208:1459–1463.
39. Leaity S, Sherr L, Wells H, Evans A, Miller R, Johnson M, Elford J. Repeat HIV testing: high-risk behaviour or risk reduction strategy?. AIDS 2000; 14:547–552.
40. Elford J, Leaity S, Lampe F, Wells H, Evans A, Miller R, et al. Incidence of HIV infection among gay men in a London HIV testing clinic, 1997–1998. AIDS 2001; 15:650–653.
41. Booth CL, Geretti AM. Prevalence and determinants of transmitted antiretroviral drug resistance in HIV-1 infection. J Antimicrob Chemother 2007; 59:1047–1056.
42. Castro H, Pillay D, Sabin C, Dunn DT. UK Collaborative Group on HIV Drug Resistance. Effect of misclassification of antiretroviral treatment status on the prevalence of transmitted HIV-1 drug resistance. BMC Med Res Methodol 2012; 12:30.
43. Sax PE, Islam R, Walensky RP, Losina E, Weinstein MC, Goldie SJ, et al. Should resistance testing be performed for treatment-naive HIV-infected patients? A cost-effectiveness analysis. Clin Infect Dis 2005; 41:1316–1323.

* EuroCoord members are listed in the Acknowledgements section.


HIV drug resistance; HIV seroconverters; temporal trends; time trends

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