In Japanese HIV patients, long-term treatment with raltegravir is well-tolerated and effective at viral suppression as measured by HIV-1 RNA levels and subsequent change in CD4+ cell counts. Such benefits can be expected for not only treatment-naïve but also treatment-experienced patients.Antiretroviral agents are approved in Japan based on non-clinical and clinical data reported from overseas. Neither the long-term tolerability nor the effectiveness of raltegravir or other integrase strand transfer inhibitors in Japan is known. This study reports on the long-term tolerability and effectiveness of raltegravir in Japanese clinical practice using data collected through approximately 9 years of post-marketing surveillance. This observational survey used data on human immunodeficiency virus (HIV) infected patients initiated treatment with raltegravir between 2008 and 2017 in the HIV-related drug (HRD) cooperative survey to assess the safety and effectiveness of raltegravir in real world clinical practice. There were totally 1,303 patients prescribed raltegravir across 30 institutions; 1,293 patients and 1,178 patients were included for the safety and effectiveness analyses, respectively. The overall risk of adverse drug reaction was 17.25%, with abnormal hepatic function and hyperlipidaemia (<1.5%) having the highest proportion. Median HIV-1 RNA viral loads rapidly decreased below 40 copies/mL after 3 months of raltegravir use in treatment-naïve patients, and consistently sustained below 40 copies/mL after the start of raltegravir use in treatment-experienced patients. Among the patients who were treated for 7 years, 92.00% (95% CI: 73.97–99.02) maintained HIV-1 RNA viral load below 50 copies/mL. Additionally, CD4 Antiretroviral therapy (ART) has dramatically improved the overall survival of people living with human immunodeficiency virus (HIV), but the life-long tolerability of ART has yet to be revealed. Raltegravir  is the world’s first in class of HIV integrase strand transfer inhibitor (INSTI) for the treatment of HIV-1 infection. The safety and efficacy of raltegravir administration in clinical trials for up to 5 years among HIV-infected patients in North American, South American, Australian, and South Asian countries have been previously reported . After iIn Japan, around 1,500 HIV/Acquired immunodeficiency syndrome (AIDS) cases have been reported annually since 2007 and 1,448 HIV/AIDS  cases were reported in 2016. Men who have sex with men (MSM), including bisexual contacts, made up 73%  of all HIV cases and the majority was in their 20’s to 40’s. The cumulative number of reported HIV/AIDS cases (excluding coagulating agent-related cases) was 27,443 as of the end of 2016 .A rapid drug approval process is applied for antiretroviral agents in Japan, and this approval is based on non-clinical and clinical data reported from overseas as an orphan drug. As such, raltegravir was approved for clinical use under the condition of conducting a post-marketing surveillance to collect domestic data on the safety and effectiveness of this agent in clinical practice. Because antiretroviral agents are usually used concomitantly with other anti-HIV drugs, all pharmaceutical companies with an approved anti-HIV drug work together to conduct a HIV-related drug (HRD) cooperative survey .The surveillance of raltegravir through the HRD cooperative survey started at the time of its marketing, in July 2008. To date, no data on the long-term tolerability and effectiveness in Japan of either raltegravir or other INSTI agents are available. Furthermore, only a few studies on the long-term effectiveness of key drug have been conducted in other countries; they include the 12-year experience of nevirapine use in France , a 10-yeThis observational survey used post-marketing surveillance data collected for the HRD cooperative survey and was conducted in accordance with the requirements of the pharmaceutical affairs law and the ministerial ordinance of ‘Good Post-Marketing Study Practice (GPSP)’. At their discretion, investigators of the contracted institutions registered patients who were newly prescribed with particular antiretroviral agents and provided data on the safety and effectiveness of the antiretroviral agents for each treated patient. Patient background information, such as age, sex, comorbidity on administration , presence of allergy, status of anti-HIV drug use, and concomitant drug use , was collected at registration. Data were collected by filling out a case report form upon registration and annually thereafter. If a patient experienced an adverse event (AE), the corresponding data were reported immediately using the AE report form. The management of the HRD cooperative survey was delegated to CMIC PMS Co., Ltd. . All data were fully anonymized before the authors of this study accessed them.Data on patients registered as newly treated with raltegravir between July 2008  and March 2017 were drawn from the HRD cooperative survey for this study. Of the 33 institutions in which patients were prescribed raltegravir, three institutions did not agree to the disclosure of information, so they were excluded from these analyses.This post-marketing surveillance (PMS) conducted in accordance with Good Post-marketing Study Practice for drugs . The survey protocol was reviewed and approved in advance by the Pharmaceuticals and Medical Devices Agency (PMDA). The requirements of ethical approval by an institutional review board and informed consent from individual patients for this survey were waived. However, all 30 facilities obtained approval in advance by their institutional review board according to each institutional rule. Names of the 30 facilities were anonymized for publication due to the contract of HRD cooperative survey. Of these 30 facilities, 29 are HIV specialized hospitals, 22 are national or public hospitals, and mean number of beds are 758 .To assess the safety of raltegravir, AEs and abnormal variations in laboratory test parameters  were collected during the treatment period. All events with a relationship between the AE and drug were defined as adverse drug reactions (ADRs). AEs and ADRs were classified according to the Medical Dictionary for Regulatory Activities/Japanese version (MedDRA/J Ver.20.0).+ cell counts, HIV-1 RNA levels, and HIV infection clinical stages  before + cell counts were calculated over time at 0, 3, 6, 12, 24, 36, 48, 60, 72, 84, and 96 months after the start of raltegravir treatment for treatment-naïve patients and treatment-experienced patients. The proportion of patients with <50 copies/mL of HIV-1 RNA, including blip cases , was also calculated for the virologic assessment, and its 95% confidential intervals was estimated using Clopper-Pearson method. All statistical tests were two-sided at a significance level of 0.05 and were conducted using SAS Release 9.4 .Patient demographics, clinical characteristics, AEs, and ADRs were summarized descriptively from the collected data. The long-term safety of raltegravir was assessed by summarizing the risk of ADRs by the time of occurrence from the start of raltegravir treatment: <90 days, between 90 and <180 days, between 180 and <270 days, between 270 days and <1 year, between 1 year and <2 years, between 2 and <3 years, between 3 and <4 years, between 4 and <5 years, between 5 and <6 years, and ≥6 years. To assess potential risk factors for ADRs, the ADR occurrence was further analysed according to baseline characteristics using a Fisher’s exact test or Cochran-Armitage test. Changes in the median HIV-1 RNA levels and median CD4+ cell counts, number of HIV-1 RNA copies, or CDC categories either before or after raltegravir administration were excluded. Finally, data from the remaining 1,178 patients were included for the effectiveness analysis . The most common ADRs were abnormal hepatic function , hyperlipidaemia , renal impairment , hyperuricaemia , liver disorder , dyslipidaemia , hypertension , hypertriglyceridaemia , immune reconstitution inflammatory syndrome , insomnia , and increased blood creatinine levels  .For predefined events of interest on monitoring the safety of raltegravir, the most frequently reported ADRs that were related to musculoskeletal and connective tissue disorders were back pain , followed by rhabdomyolysis  and osteoporosis  . As for p < 0.001).The ADR risk by the time period from raltegravir treatment initiation was 10.20% (20/196 cases), 16.16% (37/229 cases), 16.13% (40/248 cases), 22.11% (44/199 cases), 18.44% (26/141 cases), and 23.68% (18/76 cases) for treatment durations of between 1 and <2 years, 2 and <3 years, 3 and <4 years, 4 and <5 years, 5 and <6 years, and ≥6 years, respectively . In partp = 0.039), CDC category of B (p = 0.019), the presence of any comorbidities , the presence of hepatic disease , the presence of allergic disease , or an increasing number of concomitant medications (p < 0.001) (ADR rates were significantly higher in patients with an older age (< 0.001) .At the start of the treatment, the median HIV-1 RNA viral loads among the treatment-naïve patients were considerably higher compared with those of treatment-experienced patients , but this level rapidly decreased to 78.5 copies/mL after one month of raltegravir treatment. Median HIV-1 RNA viral loads in treatment-naïve and treatment-experienced groups each maintained below 40 copies/mL after three months of raltegravir treatment . Regardi+ cell counts in treatment-naïve patients were lower compared with those in treatment-experienced patients (216 vs. 408 cells/μL), but the CD4+ cell counts in the treatment-naïve group reached 346 cells/μL after 3 months and 522 cells/μL after 36 months of raltegravir treatment  and category B  maintained their pre-treatment CDC category even after raltegravir administration. Only nine cases had disease progression.This study was conducted using the results of a nine-year post-marketing surveillance on raltegravir in Japan. Data from 1,303 patients were initially extracted from the HRD cooperative survey, and, after excluding 10 ineligible patients, a total of 1,293 patients were included in the safety analysis. The overall ADR risk 17.25%) in this survey was fairly low, compared with previous international clinical trials reporting the ADR incidence for raltegravir, which ranged from approximately 44%‒61% with study periods spanning 1‒5 years . Hyperli.25% in tThe effectiveness analysis was conducted on data from a total of 1,178 patients. The median HIV-1 RNA viral loads in treatment-naïve patients decreased rapidly after one month of raltegravir treatment and were identical in both treatment-naïve and treatment-experienced patients after 3 months of raltegravir treatment. Although decreasing numbers on raltegravir treatment as time goes on, using this as denominator, the proportion of patients with <50 copies/mL of HIV-1 RNA remained at 92.00%  in patients treated for 7 years, which is higher than or at a similar level as the corresponding proportions reported by previous clinical trials conducted overseas for a maximum of 5 years [+ cell counts in treatment-naïve patients were initially lower than those in treatment-experienced patients, but they rapidly increased to 346 cells/μL after 3 months of raltegravir treatment and were maintained at >500 cells/μL after 3 years of raltegravir in treatment-naïve patients and after 4 years in treatment-experienced patients. Previous studies reported that the changes in CD4+ cell counts from baseline were 189 cells/μL, 240 cells/μL, and 374 cells/μL in treatment-naïve patients (STARTMRK study) and 109 cells/μL, 123 cells/μL, and 293 cells/μL in patients with triple-class drug resistance in whom previous ART had failed (BENCHMRK-1 and -2 study) after approximately 1 year, 2 years, and 5 years of raltegravir administration, respectively [+ cell counts resulted from virological suppression in raltegravir-treated Japanese patients. The observed improvement in the immunologic response even for treatment-experienced patients implies that an improvement for patients is likely after changing their ART regimen to include raltegravir.Similarly, the median CD4There are several limitations to the present study. First, our results may be specific to particular groups of patients with HIV infection. The included patients in this study were registered at designated institutions, and, although in principle all patients receiving raltegravir were registered, each enrolment decision was made by contractor investigators. Therefore, a selection bias is inevitable. Second, the effectiveness results in this study cannot be purely attributed to raltegravir because antiretrovirals are commonly used in combinations. The present results support the effectiveness of raltegravir, but they must be interpreted with care. Third, as this data was drawn from HRD cooperative survey conducted by all companies having an HIV drug approved in Japan, we can only extract data of patients still on treatment with raltegravir at the time of the annual report. If patients collected as raltegravir data and switched for viral loads ≥50 copies/mL judged from collected effectiveness data, these patients were counted as failure. However, after they have switched to another ART regimen, we might not have been able to follow them any longer in this study. Therefore, a selection bias for over estimating effectiveness is inevitable. Fourth, as we had no control group for comparison, the safety and effectiveness results for raltegravir cannot be compared with those in HIV-infected patients who received no or other antiretroviral treatments. Last, data on patients who were treated with raltegravir for longer than 7 years were scarce, which may have limited the precision of those results.+ cell counts, in Japanese HIV patients. Such benefits can be expected not only for patients who are about to start antiretroviral therapy but also for patients who switch antiretroviral regimens to one including raltegravir.In conclusion, long-term treatment with raltegravir is well-tolerated and effective regarding viral suppression, as measured by HIV-1 RNA levels and CD4S1 Appendix(DOCX)Click here for additional data file.S2 AppendixDetection threshold of HIV-1 RNA viral loads were treated as 39 until 2011, and 19 since 2012.(DOCX)Click here for additional data file.S3 AppendixaCase counts include blip cases (<50 copies/mL with transient increases up to 1000 copies/mL).(DOCX)Click here for additional data file.S4 Appendix(DOCX)Click here for additional data file.


In a Policy Forum, Peter Ehrenkranz and colleagues discuss the contribution of CD4 and viral load testing to outcomes for people with HIV in low- and middle-income countries. The combination of CD4 and viral load (VL) testing has long been recognized as integral to the management of HIV disease. However, recent shifts in the global HIV response have driven rapid changes in the prioritization and use of these tests.CD4 remains the gold standard for assessing disease progression and the need for the World Health Organization’s advanced disease package of screening, prophylaxis, or treatment for major opportunistic infections, which decreases mortality among eligible individuals. Yet, support for site-level provision of CD4 testing capacity is declining.Access to routine VL testing, which is the focus of most laboratory resources in low- or middle-income countries (LMICs), is required to assess an individual’s response to treatment. Results should lead to VL-informed differentiated service delivery and better clinical decision-making, including referral to intensified or less frequent clinical care.However, available evidence suggests that the majority of CD4 and VL tests currently performed in LMICs do not lead to changes in clinical management, drawing urgent attention to the need to rethink the approach to testing and use of results along with continued efforts to improve access to the tests.Frontline access to CD4 and VL remain essential. Yet, a laboratory system is only as good as its ability to return a result to patients and their providers. HIV programs and funders could improve clinical outcomes by measuring the success of their laboratory investments not just by the numbers of tests performed but by the ability of those test results to lead to better outcomes among people living with HIV.CD4 and viral load (VL) testing have long been recognized as integral to the management of HIV disease ,2. HowevWhile CD4 testing continues to serve the critical role of identifying individuals with advanced HIV disease and elevated mortality risk , the scaCD4 was initially recommended by WHO for use in three settings: 1) as a major criterion for treatment initiation, 2) monitoring for treatment failure, and 3) risk stratification. With each successive set of HIV guidelines, the immunological threshold for treatment initiation rose: from 200 cells/μL in 2002, to 350 cells/ μL in 2009, to 500 cells/ μL in 2013, and ultimately to treatment for all regardless of CD4 cell count in 2016 .WHO’s remaining recommended use for CD4 is risk stratification, both at treatment initiation and for patients re-presenting for care with virological failure and/or clinically advanced disease . This isBaseline risk stratification for patients initiating therapyAd hoc testing of patients with clinical signs of advanced disease One-time risk stratification of individuals re-presenting to care after a substantial period of absence Despite continuing gains in treatment coverage, CD4-based risk stratification remains essential. Of the approximately 2 million people starting or restarting ART every year , as manyIn addition, increasing proportions of individuals on ART incur treatment interruptions, which often lead to decreased CD4 cell counts and unsuppressed VLs ,18. The Some declines in CD4 usage are expected as its use becomes more focused on risk stratification, and between 2017 and 2018, the numbers of CD4 tests conducted in LMICs decreased from 19.2 million to 15.7 million . TogetheIn this environment, some resource-constrained settings may choose to centralize their CD4 testing capacity in referral centers that manage advanced disease, providing access to peripheral centers via sample transport. Alternatively, since the test’s main function is to rapidly identify those at highest risk of morbidity , other sFollowing WHO’s 2013 recommendation to implement routine VL testing, many LMICs used both domestic and donor resources to accelerate scale-up of VL. In 2017, over 14 million VL tests were conducted in LMICs, and testing volumes in these settings may reach as high as 29 million tests by 2022 [Ideally, improved access to routine VL results should lead to better clinical decision-making, including VL-informed differentiated service delivery (DSD). DSD is the concept that HIV care should be adapted to people’s needs in ways that may reduce unnecessary burdens on individuals and the health system and improve outcomes ,26. A viSuch promise has led to rapid improvements in access to VL testing in recent years. However, challenges with the use of results for individual management are only starting to garner the attention they require ,10,30. FThe costs of underutilized laboratory tests—CD4, VL, or any other—are substantial. In addition to the direct costs of the instruments and commodities, infrastructure, human resources, and sample transport, there are the anticipated poorer outcomes among patients whose medications were not appropriately managed and the opportunity costs of not spending these resources on another priority. While there are clear programmatic benefits to assessing the proportion of individuals on ART who are virally suppressed (the “third 90”) on a national level, such aggregate data could be more efficiently and perhaps more accurately assessed with routine surveillance at a representative sample of sites or through cross-sectional national studies .Successful scale-up or maintenance of routine individual-level testing requires a systems approach that goes beyond procurement of commodities, expansion of laboratory testing capacity, choice of centralized versus POC testing, or decision about which specimen to collect . First, the placement of platforms within networks and staffing patterns could be managed such that there is high coverage of testing needs and each machine’s capacity is optimized. Second, scale-up requires finding efficiencies, such as service delivery contracts with the machine manufacturers that include training, use of text messages for automated results return to patients, and other novel contractual features in addition to machine rental and commodities. Third, successful scale-up planning could emphasize that laboratory systems be patient-centered, giving as much attention to the preanalytic and postanalytic activities as to the lab testing itself. Furthermore, laboratory testing recommendations are dynamic and require responsive systems. For instance, both the increase in numbers of people living with HIV (PLHIV) leaving and re-entering care as well as the emergence of drugs with higher resistance thresholds such as dolutegravir within both first- and second-line regimens may affect the optimal frequency of, and response to, VL testing .Indeed, a laboratory system is only as good as its ability to return a result to a patient and lead to a change in clinical management. PLHIV and their providers should be armed with the information needed to demand access to testing and insist on the policy and programming changes to ensure that their results are used. Basic requirements are described in Both CD4 and VL are essential tools for management of HIV, but their full impact remains unrealized in most LMICs. The importance of CD4 for identifying and treating people at risk of advanced disease has been displaced by attention to scale-up of VL testing, the results of which remain grossly underutilized. Lifesaving benefits for PLHIV can be achieved by ensuring that CD4 testing remains widely available to frontline providers and is linked directly to an effective advanced disease package proven to decrease HIV-related mortality. Likewise, every VL test performed should lead to improved use of interventions such as less intense models of care or rapid access to second-line treatment.To maximize the value of and efforts to scale up clinical monitoring tests, HIV programs and donors are encouraged to commit to measuring success not by the numbers of tests performed but by the improved clinical outcomes achieved through the use of test results. People with HIV deserve to know their results, be engaged in their care decisions, and benefit from the use of test results. The United States President’s Emergency Plan for AIDS Relief (PEPFAR) should be lauded for including support for these concepts in its 2019 Country Operational Guidance and its encouragement to countries to monitor change in clinical outcomes through routine data or targeted QI programs . Yet, co


Resistance to antiretroviral drugs is a major challenge among Human Immunodeficiency Virus (HIV) positive patients receiving antiretroviral therapy (ART). Mutations that arise as a result of this are diverse across the various drugs, drug classes, drug regimens and subtypes. In Uganda, there is a paucity of information on how these mutations differ among the different drug regimens and the predominant HIV-1 subtypes. The purpose of this study was to determine mutation profile differences between first-line drug regimens: TDF/3TC/EFV and AZT/3TC/EFV and HIV-1 subtypes: A and D in Uganda. The study also investigated the potential usage of rilpivirine, doravirine and etravirine in patients who failed treatment on efavirenz.A retrospective study was conducted on 182 archived plasma samples obtained from patients who were experiencing virological failure between 2006 and 2017 at five Joint Clinical Research Center (JCRC) sites in Uganda. Sanger sequencing of the Reverse Transcriptase (RT) gene from codons 1–300 was done. Mutation scores were generated using the Stanford University HIV Drug Resistance Database. A Chi-square test was used to determine the association between drug resistance mutations (DRMs) and drug regimens or HIV-1 subtypes.The prevalence of DRMs was 84.6% among patients failing a first-line efavirenz (EFV)-based regimen. The most prevalent Nucleoside Reverse Transcriptase Inhibitor (NRTI) mutations were M184V/I (67.3%), K219/Q/E (22.6%) and K65R (21.1%). While K103N (50.8%) and G190A/S/E/G (29.1%) were the most prevalent Non-Nucleoside Reverse Transcriptase Inhibitor (NNTRI) mutations. As expected, discriminatory DRMs such as K65R, L74I, and Y115F were noted in Tenofovir (TDF) containing regimens while the Thymidine Analogue Mutations (TAMs) L210W and T215 mutations were in Zidovudine (AZT)-based regimens. No significant difference (p = 0.336) was found for overall DRMs between HIV-1 subtypes A and D. Among the patients who had resistance to EFV, 37 (23.6%) were susceptible to newer NNRTIs such as Rilpivirine and Etravirine.Accumulation of DRMs between AZT/3TC/EFV and TDF/3TC/EFV is comparable but individual mutations that confer resistance to particular drugs should be considered at virological failure. Having either HIV-1 subtype A or D is not associated with the acquisition of DRMs, therefore HIV diversity should not determine the choice of treatment. Rilpivirine, etravirine and doravirine had minimal benefits for patients who failed on efavirenz. Globally, a total of 38.9 million (31.1–43.9 million) people are living with HIV while in Sub-Saharan Africa, a total of 19.6 million (17.5–22.0 million) are living with the virus  while taking either TDF/3TC/EFV or AZT/3TC/EFV at the Joint Clinical Research Centre, Kampala, Uganda. All samples that met the inclusion criteria of no prior exposure to ART and a viral load above 1000 copies/ml over 10 years (between 2006 and 2017) were included in the analysis. These samples were collected for routine (once in a year) monitoring of patients’ response to treatment after ART initiation. Patients’ duration on ART, immunological and adherence data were not available. Laboratory assigned sample IDs were used as unique identifiers to maintain confidentiality. The study was carried out under IRB approval  at Center for AIDS Research laboratory, Joint Clinical Research Center, Kampala Uganda.Viral RNA was extracted from plasma using the Qiagen QIAamp Viral RNA Mini Extraction Kit  according to the manufacturer’s instructions . Reversehttps://hivdb.stanford.edu/) [Sequences generated were edited using an online DNA editing software Recall , the edird.edu/)  to generrd.edu/) . Statistrd.edu/) , in whicA total of 182 samples were successfully analyzed. The average age of patients was 29.1 ± 13.4 years. Among the participants, 89 (48.9%) were female and 78 (42.9%) were male, the rest of the patients had sex data missing. The patients were in two groups based on the treatment regimen, 101 (55.5%) were on TDF/3TC/EFV and 81 (44.5%) were on AZT/3TC/EFV. The average viral load was 203,072.29 (1287-3910237) copies/ml, Table The study had two classes of drugs: the NRTI and the NNRTI class. Overall resistance to at least one class of drugs occurred in 154 (84.6%) of the participants. Resistance to NNRTI class only occurred in 16 (8.8%), NRTI class only occurred in 4 (2.2%) and resistance to both classes occurred in 134 (73.6%) of the participants. When we compared individual mutations within the NRTI class, M184V/I mutation had the highest prevalence of 120 (65.9%) among patients. This was followed by K70R, K65R and K219 mutations occurring at 56 (24.3%), 42 (23.1%) and 40 (22%) respectively. On the other hand, the least frequent NRTI mutations were F77L that occurred in 2 (1.1%) of the patients followed by Q151M and T69D at 3 (1.6%). Comparisons of individual mutations within the NNRTI class showed the most frequent mutation to be K103N; this occurred in 98 (53.8%) of the patients. This was followed by G190A/S/E/G that occurred in 55 (30.2%) of the patients, P236L mutation occurred in 2 (1.1%) and L234I that occurred in only 4 (2.2%) of the participants , Y115F  and L74I  mutations appeared more in the TDF/3TC/EFV group as compared to AZT/3TC/EFV group. As expected, L210W  and T215 mutations  were significantly noted more in AZT/3TC/EFV as compared to TDF/3TC/EFV group. Within the NNRTI class, G190 mutations , Y181C , L100I  were significantly more in the TDF/3TC/EFV group whereas mutation K238T  was significantly more in the AZT/3TC/EFV group , Y188L (p = 0.008) and TAMs (p = 0.011) were significantly more common in Subtype A as compared to Subtype D and others Fig. .Fig. 3DrNNRTI drugs are often compromised by cross-resistance within the class, but with the introduction of newer NNRTIs such as rilpivirine, doravirine and etravirine which offer protection even in the presence of resistant variants, there may still be hope for use of some of these drugs in this class. In this study, we compared the predicted drug susceptibility scores of efavirenz together with those of newer NNRTIs. Results showed that out of the 182 patients, 143 (78.5%) had high-level resistance to efavirenz. These patients who had high-level resistance to efavirenz were selected for assessment of drug susceptibility to rilpivirine, doravirine and etravirine to compare percentage reduction in resistance. Of these 36 (25.2%) were susceptible to etravirine and rilpivirine, 22 (15.4%) were susceptible to doravirine, Table Findings from this study have shown that 84.6% of the patients had drug resistance mutations (DRMs) conferring resistance to at least one class of drugs and 73.6% had resistance to both NRTI and NNRTI classes of drugs. Similar studies in sub-Saharan countries had a prevalence of DRMs at 70%  and in STAMs and K65R had a prevalence of 35.7% and 23.1% respectively, similar to a study done in Uganda  where K6The current study showed that there is no significant difference (p < 0.367) between AZT/3TC/EFV and TDF/3TC/EFV regimens in attaining DRMs for NRTIs, NNRTIs. The choice of regimen should therefore, be based on other factors other than resistance mutation profiles. These findings are in line with the consolidated guidelines for prevention and treatment of HIV in Uganda which recommends both TDF/3TC and AZT/3TC containing regimens as first-line but TDF/3TC-containing regimens being the preferred first-line . Within Overall, drug resistance mutation profiles had no significant association (p = 0.336) with HIV-1 subtypes as previously reported by Hamers et al. and Venner et al. , 54. TheThe study explored the reliability of newer NNRTIs, rilpivirine, etravirine and doravirine as possible alternatives for future use in patients with high-level resistance to efavirenz. The results revealed that of the 143 patients who had high-level resistance to efavirenz, 107 (74.8%) patients retained high-level resistance to rilpivirine or etravirine and 121 (84.6%) retained resistance to doravirine. The study revealed that only 35 (25.2%) of patients would benefit from rilpivirine or etravirine and 22 (15.4%) from doravirine as options in salvage regimens. These results are in range with findings from a study done in Thailand  which shThis study found no association between AZT/3TC/EFV and TDF/3TC/EFV in attaining resistance mutations NRTIs, NNRTIs suggesting that the choice of regimen should be based on other factors other than resistance mutation profiles. However, there were associations for individual mutations in the TDF-containing regimen and AZT-containing regimen; these, therefore must be put into consideration when choosing a regimen for patients either at baseline or at virological failure. In addition, the study showed that the newer NNRTI; rilpivirine or etravirine or doravirine benefit only a small percentage of people with high-level resistance to efavirenz, therefore are less likely to be considered as options in the national guidelines at second-line for patients who had efavirenz in the first-line regimen. For use in salvage regimen, drug resistance profiles should guide the choice of drugs.In this study, probable confounders were noted such as patients’ adherence to treatment, time spent on treatment, time to report back for viral load and drug resistance monitoring and the sample size which might have affected the statistical power of the study given the level of occurrence for the individual mutations.


Evaluate long-term rates of virological failure and treatment interruption for people living with HIV (PLWHIV) with viral suppression on first-line efavirenz + tenofovir disoproxil fumarate + emtricitabine/lamivudine (EFV + TDF + FTC/3TC), and compare these according to patient characteristics.PLWHIV enrolled in the Collaboration of Observational HIV Epidemiological Research Europe cohort collaboration, who started first-line EFV + TDF + FTC/3TC at age at least 16 years and had viral suppression (<200 copies/ml) within 9 months were included. Rates of virological failure (≥200 copies/ml) and (complete) treatment interruption were estimated according to years since initial suppression. We used Poisson regression to examine associations of baseline characteristics with rates of virological failure or treatment interruption.Among 19 527 eligible PLWHIV with median (interquartile range) follow-up 3.7 (2.0–5.6) years after initial viral suppression, the estimated rate of the combined incidence of virological failure or treatment interruption fell from 9.0/100 person-years in the first year to less than 4/100 person-years beyond 3 years from suppression; considering only those remaining on EFV + TDF + FTC/3TC, the combined rate dropped from 8.2/100 person-years in the first year to less than 3.5/100 person-years beyond 3 years. PLWHIV with injecting drug-related or heterosexual transmission were at higher risk of virological failure or treatment interruption, as were those of Black ethnicity. PLWHIV aged less than 35 years were at higher risk of virological failure and treatment interruption.PLWHIV starting first-line EFV + TDF + FTC/3TC had low rates of virological failure and treatment interruption up to 10 years from initial suppression. Demographic characteristics can be used to identify subpopulations with higher risks of these outcomes. The combination of efavirenz (EFV), tenofovir disoproxil fumarate (TDF) and emtricitabine (FTC) or lamivudine 3TC) was established as preferred first-line antiretroviral therapy (ART) for HIV in 2013 WHO guidelines TC was es and so tAn analysis from the UK Collaborative HIV Cohort (UK CHIC) Study showed that PLWHIV on ART regimens with initial viral suppression have annual rates of virological rebound (200 copies/ml threshold) that decrease from around 9/100 person-years in the first year to less than 3/100 person-years after some years on treatment ; the autWe estimated rates of virological failure, treatment interruption and treatment switches for PLWHIV with initial viral suppression on first-line EFV + TDF + FTC/3TC within a multinational collaboration of European HIV cohort studies. We evaluated demographic and clinical risk factors for these events.We analysed data, merged in June 2015, from 20 cohorts in the Collaboration of Observational HIV Epidemiological Research Europe (COHERE) . AdditioPLWHIV were included if they were ART-naïve at cohort enrolment and started first-line EFV + TDF + FTC/3TC at age at least 16 years with viral suppression (defined as one measurement undetectable or <200 copies/ml) within 9 months. Initial regimen was ignored if it changed within 1 week of first treatment. PLWHIV were excluded if their last viral load measurement was less than 9 months after starting ART, if treatment was interrupted before viral suppression or if at least one pre-ART viral load measurement was either undetectable or ≤50 copies/ml within 1 year prior to starting ART (to remove those who may have started ART before the date recorded). COHERE cohorts with fewer than 20 PLWHIV meeting the inclusion criteria were dropped.Follow-up started at the date of viral suppression. Virological failure was defined as one measurement ≥ 200 copies/ml to allow consistency of analysis across cohorts and over the timespan considered. Treatment interruption was defined as cessation of all ART, but interruptions of up to 1 week were ignored. We also estimated rates of virological failure whilst on EFV + TDF + FTC/3TC, of complete interruption of ART directly from treatment with EFV + TDF + FTC/3TC and of switching from EFV + TDF + FTC/3TC to any other regimen.or interruption event was counted): these were used to estimate the rates and cumulative incidence of each event, accounting for the competing risk of the other [Piecewise exponential time-to-event models were used to estimate event rates, which were estimated for yearly intervals from initial viral suppression, with a single rate estimated for follow-up more than 9 years. Rates were first estimated without adjustment for patient characteristics. For virological failure and treatment interruption, cause-specific piecewise exponential models were fitted with censoring for the other event  and viral load , time-updated age , year of starting ART  and cohort. For five cohorts, ethnicity was not recorded so this variable was set to reference (i.e. ‘white’) for the purpose of multivariable analysis. For categorical variables, the group with highest frequency was chosen as reference. Baseline CD4+ cell counts and viral load were defined as the last measurement obtained within the 6-month period before ART start. Follow-up was censored at 6 months after last recorded viral load or at death. The adjusted analyses were conducted without censoring at switch to other ART regimen.We estimated adjusted associations of the virological failure and treatment interruption outcomes with patient sex, mode of acquisition , ethnicity , prior AIDS diagnosis, baseline CD4+, viral load and age. Imputation models used square root CD4+ cell counts and log10 viral load. MSM status, sex and IDU status were imputed separately; these factors were then combined for analysis models with IDU status considered the primary mode of acquisition in PLWHIV who were also MSM. PLWHIV with transfusion-related or ‘other’ acquisition were excluded due to low numbers.For analyses adjusted for patient characteristics, full covariate data were available in 83.0% of cases (ignoring ethnicity for cohorts without this information recorded). Multiple imputation using chained equations was implemented using the Stata ‘ice’ package . ImputatThe study population included 19 527 PLWHIV . The majority mode of acquisition was MSM (59.6%). Where known, white ethnicity was most common (70.2%) with 20.6% Black and 4.2% Asian ethnicities (further details in Tables S1 and S2).Unadjusted incidence rates of virological failure and ART interruption according to years since initial viral suppression are shown in Fig. + cell count more than 200 cells/μl was associated with lower rate of virological failure, but those with baseline CD4+ above 500 cells/μl had higher rates of treatment interruption. Rates of virological failure increased with increasing baseline viral load, but there was little evidence that baseline viral load was associated with treatment interruption. Rates of both virological failure and treatment interruption declined in later compared with earlier calendar years of starting ART. Age below 35 years was associated with a higher rate of virological failure and of treatment interruption.Fifty-five PLWHIV with transfusion-acquired HIV and 262 with ‘other’ acquisition were excluded from multivariable analyses. Adjusted associations of patient characteristics with virological failure and treatment interruption are shown in Table Amongst PLWHIV enrolled in a large collaboration of European cohort studies starting first-line EFV + TDF + FTC/3TC, rates of virological failure and treatment interruption declined over 3 years following initial virological suppression before stabilizing at low levels: the subsequent combined incidence rate of virological failure or treatment interruption was below 4/100 person-years for PLWHIV remaining on ART, and was below 3.5/100 person-years considering only those on the EFV + TDF + FTC/3TC regimen.The regimen included in this analysis, EFV + TDF + FTC/3TC, is no longer preferred first-line ART in most patients: WHO now recommends dolutegravir-based ART  followinc. 9.0/100 person-years) dropping to less than 6/100 person-years beyond 3 years (c. <4/100 person-years). Long-term studies have not yet been published regarding the durability of viral suppression on first-line dolutegravir-based ART, but as there is evidence from trials of superior viral suppression on dolutegravir vs. EFV at 48, 96 and 144 weeks [We found lower rates of both virological failure and treatment interruption for PLWHIV on first-line EFV + TDF + FTC/3TC in comparison to UK patients starting any 3 + drug ART , for who44 weeks  it is liet al.[Black ethnicity was associated with virological failure and treatment interruption, which is consistent with the findings of O’Connor et al. for the et al.. Rates oet al. and undeet al.,14 and Let al. settingset al..+ cell count more than 200 cells/μl was associated with a lower rate of virological failure on treatment [+ cell counts (>500 cells/μl) had highest rate of treatment interruption, consistent with previous studies [+ cell count.Consistent with previous literature ,18 viralreatment . PLWHIV  studies ,20, whicRates of virological failure and treatment interruption for PLWHIV declined in later compared with earlier calendar years of ART initiation. This may be linked to a reduction in pill count as combination tablets became available , but a lWe have quantified long-term virological suppression achieved using first-line EFV + TDF + FTC/3TC across a large multinational cohort collaboration. This regimen remains in use worldwide, so the low failure rate with sustained virological suppression for up to a decade on treatment is encouraging. The substantial differences in rates of virological failure and treatment interruption according to demographic and clinical characteristics may be useful for targeted monitoring and adherence interventions.Contribution of working group members: A.P., D.D. and J.S. developed the research question and study design. D.B. coordinated collaboration between cohorts for the project. O.S. performed the statistical analyses and drafted the initial text of the article. All other working group members contributed data to the analysis, and all working group members were involved in the interpretation of results and final text of the article.The Long-Term Virological Suppression Working Group: Oliver T. Stirrup1, Jonathan Sterne2, David T. Dunn1, Katharina Grabmeier-Pfistershammer3, Vasileios Papastamopoulos4, Marie-Anne Vandenhende5,6, Ferdinand Wit7, Kholoud Porter1, Barbara Gunsenheimer-Bartmeyer8, Inma Jarrin9, Federico Garcia10, Gerd Fätkenheuer11, Niels Obel12, Anna Schultze13, Andrea Antinori14, Francesca Ceccherini-Silberstein15, Cristina Mussini16, Geneviève Chêne5,17, Bastian Neesgaard18, Antonella Castagna19, Roger Kouyos20, Stéphane De Wit21, Anders Sönnerborg22, Caroline Sabin1, Dolores Merino23, Diana Barger5,17, Andrew Phillips1.1Institute for Global Health, University College London, London; 2Population Health Sciences, Bristol Medical School, Bristol, UK; 3Medical University of Vienna, Vienna, Austria; 4Evaggelismos General Hospital, Athens, Greece; 5University Bordeaux, Inserm, Bordeaux Population Health Research Center, U1219; 6Bordeaux University Hospital, Hôpital Saint-André, Bordeaux, France; 7Academic Medical Center, Amsterdam, The Netherlands; 8Robert Koch Institute, Berlin, Germany; 9Instituto de Salud Carlos III, Madrid; 10Clinical Microbiology & Infectious Diseases Unit, Hospital Universitario San Cecilio, Instituto de Investigación Ibs. Granada, Granada, Spain; 11University Hospital Cologne, Cologne, Germany; 12Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark; 13University College London, London, UK; 14INMI, Lazzaro Spallanzani; 15Department of Experimental Medicine and Surgery, University of Rome Tor Vergata, Rome; 16Clinic of Infectious Diseases, University Hospital, University of Modena and Reggio Emilia, Modena, Italy; 17ISPED, CHU Bordeaux, Bordeaux, France; 18CHIP, University of Copenhagen, Copenhagen, Denmark; 19Clinic of Infectious Diseases, Vita-Salute San Raffaele University, Milan, Italy; 20Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zürich, Switzerland; 21Department of Infectious Diseases, St Pierre University Hospital, Brussels, Belgium; 22Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden; 23Unidad de Gestión Clínica de Enfermedades Infecciosas, Complejo Hospitalario de Huelva, Huelva, Spain.Steering Committee – Contributing Cohorts: Ali Judd (AALPHI), Robert Zangerle (AHIVCOS), Giota Touloumi (AMACS), Josiane Warszawski (ANRS CO1 EPF/ANRS CO11 OBSERVATOIRE EPF), Laurence Meyer (ANRS CO2 SEROCO), François Dabis (ANRS CO3 AQUITAINE), Murielle Mary Krause (ANRS CO4 FHDH), Jade Ghosn (ANRS CO6 PRIMO), Catherine Leport (ANRS CO8 COPILOTE), Linda Wittkop (ANRS CO13 HEPAVIH), Peter Reiss (ATHENA), F.W. (ATHENA), Maria Prins (CASCADE), Heiner Bucher (CASCADE), Diana Gibb (CHIPS), G.F. (Cologne-Bonn), Julia Del Amo (CoRIS), N.O. (Danish HIV Cohort), Claire Thorne , Amanda Mocroft (EuroSIDA), Ole Kirk (EuroSIDA), Christoph Stephan (Frankfurt), Santiago Pérez-Hoyos (GEMES-Haemo), Osamah Hamouda (German ClinSurv), B.G.-B. (German ClinSurv), Nikoloz Chkhartishvili , Antoni Noguera-Julian (CORISPE-cat), A.A. (ICC), Antonella d’Arminio Monforte (ICONA), Norbert Brockmeyer (KOMPNET), Luis Prieto (Madrid PMTCT Cohort), Pablo Rojo Conejo (CORISPES-Madrid), Antoni Soriano-Arandes (NENEXP), Manuel Battegay (SHCS), R.K. (SHCS), C.M. (Modena Cohort), Jordi Casabona (PISCIS), Jose M. Miró (PISCIS), A.C. (San Raffaele), Deborah Konopnick (St. Pierre Cohort), Tessa Goetghebuer (St Pierre Paediatric Cohort), A.S. (Swedish InfCare), Carlo Torti , C.S. (UK CHIC), Ramon Teira (VACH), Myriam Garrido (VACH), David Haerry (European AIDS Treatment Group).Executive Committee: S.D.W. , Jose Mª Miró (PISCIS), Dominique Costagliola (FHDH), Antonella d’Arminio-Monforte (ICONA), A.C. (San Raffaele), Julia del Amo (CoRIS), Amanda Mocroft (EuroSida), Dorthe Raben , G.C. . Paediatric Cohort Representatives: Ali Judd, Pablo Rojo Conejo.Regional Coordinating Centres: Bordeaux RCC: D.B., Christine Schwimmer, Monique Termote, Linda Wittkop; Copenhagen RCC: Casper M. Frederiksen, Dorthe Raben, Rikke Salbøl Brandt.Project Leads and Statisticians: Juan Berenguer, Julia Bohlius, Vincent Bouteloup, Heiner Bucher, Alessandro Cozzi-Lepri, François Dabis, Antonella d’Arminio Monforte, Mary-Anne Davies, Julia del Amo, Maria Dorrucci, D.T.D., Matthias Egger, Hansjakob Furrer, Marguerite Guiguet, Sophie Grabar, Ali Judd, Ole Kirk, Olivier Lambotte, Valériane Leroy, Sara Lodi, Sophie Matheron, Laurence Meyer, Jose Mª Miró, Amanda Mocroft, Susana Monge, Fumiyo Nakagawa, Roger Paredes, A.P., Massimo Puoti, Eliane Rohner, Michael Schomaker, Colette Smit, J.S., Rodolphe Thiebaut, Claire Thorne, Carlo Torti, Marc van der Valk, Linda Wittkop.www.COHERE.org.The COHERE study group has received unrestricted funding from Agence Nationale de Recherches sur le SIDA et les Hépatites Virales (ANRS), France; HIV Monitoring Foundation, The Netherlands; and the Augustinus Foundation, Denmark. The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under EuroCoord grant agreement no 260694. The group has also received project-specific funding from UK Medical Research Council (Award Number 164587). A list of the funders of the participating cohorts can be found at There are no conflicts of interest.


The gag-vpu region of 87 plasma samples from HIV-infected individuals from three cohorts was amplified and sequenced by Illumina HiSeq2500. The sequence reads were adapter-trimmed, followed by analysis using in-house scripts. Samples from Swedish and Ethiopian cohorts were also sequenced by Sanger sequencing. The pipeline was validated against the online tool PASeq . Based on an error rate of <1%, a value of >1% was set as reliable to consider a minor variant. Both pipelines detected the mutations in the dominant viral populations, while discrepancies were observed in minor viral populations. In five HIV-1 subtype C samples, minor mutations were detected at the <5% level by MiDRMpol but not by PASeq. MiDRMpol is a computationally as well as labor efficient bioinformatics pipeline for the detection of DRM from HTS data. It identifies minor viral populations (<20%) of DRMs. Our method can be incorporated into large-scale surveillance of HIV-1 DRM. The detection of drug resistance mutations (DRMs) in minor viral populations is of potential clinical importance. However, sophisticated computational infrastructure and competence for analysis of high-throughput sequencing (HTS) data lack at most diagnostic laboratories. Thus, we have proposed a new pipeline, MiDRM Genotypic resistance testing (GRT) to monitor antiretroviral therapy (ART) of human immunodeficiency virus type 1 (HIV-1) infection is challenging due to drug resistance mutations (DRMs) in minor viral populations not detected by Sanger sequencing, although the impact of such DRMs on clinical outcome is still under debate . On the pol, for analysis of HTS data which is cost, labor, and computationally efficient. The Fastq files generated by HTS can be used as input to get easily inferable diagnostic reports and can be applied in large-scale surveillance. It can be used without prior knowledge of HTS or bioinformatics. Here, we restricted the analysis of DRMs to the pol region of the HIV-1 genome, including the targets of the vast majority of presently approved HIV-1 drugs: the reverse transcriptase, protease, and integrase.In this study, we evaluated a simplified bioinformatics pipeline, named MiDRMn = 60), India (n = 10), and Ethiopia (n = 17). All patients were treatment naïve except 10 Swedish subjects, of whom only 2 were given ART at the time of plasma sampling. The majority  of the Swedish treatment-naïve subjects had been infected outside the country. Eight of the 10 Indian samples were from children who were infected through mother-to-child transmission (MTCT). Besides, to deduce the reliability of the method, a standard molecular clone (pMJ4) [Plasma samples were obtained from three cohorts originating from Sweden   was amplified and gel-purified using the QIAamp gel extraction kit . Briefly, the purified amplicon was fragmented on the Covaris S200 at 300 bp for 75 s with peak power-50 and cycle/burst-200, and the library was prepared using NEBNext® Ultra™ DNA Library Prep Kit for Illumina®  with multiplexed NEB next adaptors. The samples were then pooled together in sets of 48 samples along with other unrelated nonviral indexed libraries. Paired-end sequences of read length 250 bp were carried out on the Illumina HiSeq2500. The cDNA was prepared using gene-specific primers and the HTS was carried out as described by us . The F1 https://github.com/neogilab/MiDRMPol.The raw reads were adapter-trimmed using the Cutadapt v1.8 program using the default setting (error rate of <0.1) , followeViroSeq HIV-1 genotyping system had been used for the Swedish patients as a part of routine clinical practice. HIV-1 GRT by population sequencing (GRT-PS) was also performed for the Ethiopian patients using an in-house method [The e method  but not pol sequences were generated from the base count data with the occurrence of a particular nucleotide of >50% in a given position and subtyped by REGAv3 [Consensus y REGAv3  and COMEy REGAv3 , followeFor treatment-naïve individuals, DRMs was described using definitions for surveillance of transmitted HIV-1 drug resistance, 2009 Update (sDRM2009) . MutatioThe GenBank IDs for the sequences are available with the following accession numbers: for the Indian cohort: KX069219-228; for the Swedish cohort: MF373124-206; and for the Ethiopian cohort: KP411823-826, 828 and KP411830-845. Fastq files: Submission ID: SUB5359871, BioProject ID: PRJNA529776.Ethical permissions were obtained from the respective sites. Swedish samples: Regional Ethics Committee Stockholm (Dnr: 2006/1367-31/4); Ethiopian samples: the Ethiopian Science and Technology Agency (Ref. No. RPHE/126-83/08), and the Drug Administration and Control Authority of Ethiopia (Ref. No. 02/6/22/17); Indian samples: National Institute for Research in Tuberculosis Institutional Ethics Committee (NIRT IEC No. 2009009). The patients’ information was anonymized and delinked before analysis. The amino acid coverage at each postion of the HIV-pol region was calculated in terms of quartiles. The range of first quartile was 3836x–12,725x whereas for third quartile, it was 15,403×–36,451x. All the DRM positions had median coverage >5000x a. To estn = 78, 90%) were subtype C, of which 10 isolates were from treatment-experienced individuals. Seven (8%) isolates were subtype B. In addition, we identified one HIV-1A1 and one 01_AE. No cross contamination was found  ; major--integrase strand transfer inhibitors (INSTI) mutation Q148H or E138K: n = 2)). Among Indian patients, 5/10 (50%) had reverse transcriptase inhibitors (RTI) DRM, and all 5 were MTCT patients. No DRMs were detected in horizontally infected patients. Among Ethiopian patients, 6/17 (35%) had DRMs, of whom 5 had a single-class DRM and one had both nucleoside reverse transcriptase inhibitors (NRTI) (M184I) and INSTI (Q148H) DRM.DRMs were identified and quantified in 23/87 patients . In the Among the 10 treatment-experienced patients from the Swedish cohort, only two patients were on ART at the time of plasma sampling, although they had high viral RNA levels, indicating that they did not take the drugs and no DRMs were found. In three patients, DRMs were found. One patient  who had terminated nevirapine, tenofovir, and raltegravir therapy one month earlier had D67G and L74I. This patient had earlier been given abacavir-containing therapy. Patients SE70 and SE73 (HIV-1C) had stopped cART ABC + DDI + EFV and d4T + 3TC + NVP, respectively, a few months before plasma sampling. These subjects were epidemiologically linked and were identified with the same set of RTI mutations: D67N, L210W, T215Y, K103N, and G190A.n = 77), GRT-HTS detected DRMs in 26% (20/77) of the samples , T125S (n = 1), and M230L (n = 1)), whereas GRT-PS detected them in only one naïve patient (M230L). While comparing GRT-PS and GRT-HTS among the Swedish and Ethiopian patients, additional DRMs were detected by GRT-HTS . Among tn = 10), DRMs were detected in two and three samples by GRT-PS and GRT-HTS, respectively. In one sample (SE73), Y188YC was detected by GRT-PS and not by GRT-HTS. One of the Indian MTCT samples (IN07) had several major NRTI and NNRTI DRMs at frequencies of <20%. GRT-HTS also identified major INSTI mutations at low frequencies , which were undetectable by GRT-PS. In two samples (SE73 and SE31), GRT-PS did not detect DRMs which were >20%. In treatment-experienced patients . In four samples, PASeq did not deliver results due to the large file size (the file upload limit of PASeq is 1 GB). When comparing MiDRMequences . In six pol but not in PASeq, in three samples . In sample SE03, D67G and L74I ; in samples SE07 and ET171, Q148H ; and in sample ET122, M230L (4.8%) were reported by MiDRMpol but not by PASeq. This is possibly because of the FastUniq tool used in MiDRMpol, which removes duplicate reads, due to which the minor populations of mutations are enriched. In detail, the discrepancy was due to M184I (1.0%–1.5%), which is considered to be a DRM in MiDRMIn sample 24C, T215A (99.7%) and T69N (41.7%) were not detected in our pipeline because we do not consider T215A and T69N as resistance mutations against any of the RTIs. One of the mutations (D67E) was detected at 77.1% in PASeq but not detected in our pipeline.pol, was evaluated for the identification of DRMs in sequences obtained by HTS. Patients from Swedish, Indian, and Ethiopian cohorts, representing diverse subtypes, were included. The MiDRMpol pipeline was successful in detecting all major and minor DRMs. Identification of mutations such as M184I, which appears at the very early stage of the evolution of M184V, and T215S, a revertant mutation, by GRT-HTS shows that it can detect the early evolution of DRM and earlier exposure of cART, which can provide further information about, for example, pretreatment drug resistance (PDR) in global surveillances of the spread of resistant HIV-1. Although GRT-HTS detects HIV DRMs more sensitively than GRT-PS, the generalized application of such methods for clinical DR monitoring is not currently feasible due to the high cost per sample. However, the cost per megabase of raw data of DNA sequences has decreased 370-fold, from US$5.200 in 2001, to US$0.014 in 2015 [pol would cut the costs down by excluding the necessity of bioinformaticians to analyze HTS data. In this study, our in-house pipeline, MiDRM in 2015 . EquipmeDRMs were identified 8 times more often by GRT-HTS than by GRT-PS, which is in agreement with another study, which observed that 30%–50% of transmitted drug resistance (TDR) mutations were not identified by GRT-PS ,20. An ipol was designed to identify >1% of minor DRM populations, independent of the subtype. Although 10 of the patients from Sweden were treatment experienced, only 2 of them claimed to be undergoing treatment but had most likely not taken the drugs. Only 3 of the 10 patients had detectable DRMs despite earlier treatment failures. It should, however, be noted that ART had been terminated just a few months before sampling, suggesting that the DRMs had not yet had time to disappear. In other patients, the treatment had been terminated several months or years before. Thus, although no precise analysis can be done due to lack of samples during earlier treatment failure, our data indicate that even the use of a very sensitive HTS may fail to detect DRMs which had developed at earlier treatment failures. However, the pipeline MiDRMIn the Indian cohort, we identified minor DRMs in 2 out of 10 treatment-naïve individuals who were vertically infected. Eight minor RTI DRMs, including K65R (3.0%), M184V (7.5%), and V106M (3.9%), were detected in one infant (IN07), as a result of the transmission of the resistant virus from the mother. Thus, our data show that GRT-HTS improves detection of vertically transmitted DRMs in infants . Similar algorithms for determining the frequency of DRM variants are available, for example, PASeq , a web spol, which does not require onsite bioinformatics expertise. This pipeline can detect minor DRMs in viral populations at a >1% cutoff and was successfully evaluated in three cohorts consisting of various subtypes. The reliability was analyzed by comparing the sequences generated through both GRT-HTS and GRT-PS. In all of our cohorts, MiDRMpol identified DRMs against the three drug classes in minor viral quasi-species at analysis of sequences obtained through HTS. The complete script is available at GitHub at https://github.com/neogilab/MiDRMPol. Our simplified online pipeline for HTS data of the HIV-1 pol gene would be a valuable tool in the use of diagnostics of drug resistance variants before initiation of ART and after ART failure in optimizing subsequent regimens. In this study, we developed an efficient and simplified high-throughput amplicon sequence analysis pipeline named MiDRM


The study aimed to survey maraviroc use and assess effectiveness and durability of maraviroc-containing antiretroviral treatment (ART) in routine practice across Europe.. Treatment failure (TF) was defined as either virological failure  or maraviroc discontinuation for any reason over 48 weeks. Predictors of TF were explored by logistic regression analysis. Time to maraviroc discontinuation was estimated by Kaplan-Meier survival analysis.Data were retrieved from 26 cohorts in 8 countries comprising adults who started maraviroc in 2005–2016 and had ≥1 follow-up visit. Available V3 sequences were re-analysed centrally for tropism determination by geno2pheno[coreceptor]At maraviroc initiation (baseline), among 1,381 patients, 67.1% had experienced ≥3 ART classes and 45.6% had a viral load <50 copies/mL. Maraviroc was occasionally added to the existing regimen as a single agent (7.3%) but it was more commonly introduced alongside other new agents, and was often (70.4%) used with protease inhibitors. Accompanying drugs comprised 1 (40.2%), 2 (48.6%) or ≥3 (11.2%) ART classes. Among 1,273 patients with available tropism data, 17.6% showed non-R5 virus. Non-standard maraviroc use also comprised reported once daily dosing (20.0%) and a total daily dose of 150mg (12.1%). Over 48 weeks, 41.4% of patients met the definition of TF, although the 1-year estimated retention on maraviroc was 82.1% . Among 1,010 subjects on maraviroc at week 48, the viral load was >50 copies/mL in 19.9% and >200 copies/mL in 10.7%. Independent predictors of TF comprised a low nadir CD4 count, a detectable baseline viral load, previous PI experience, non-R5 tropism, having ≥3 active drugs in the accompanying regimen, and a more recent calendar year of maraviroc initiation.This study reports on the largest observation cohort of patients who started maraviroc across 8 European countries. In this overall highly treatment-experienced population, with a small but appreciable subset that received maraviroc outside of standard treatment guidelines, maraviroc was safe and reasonably effective, with relatively low rates of discontinuation over 48 weeks and only 2 cases of serum transaminase elevations reported as reasons for discontinuation. Among antiretrovirals approved for the treatment of HIV-1 infection, maraviroc and the recently approved ibalizumab are unique in targeting a host protein rather than a viral enzyme. By engaging the transmembrane helices of the CC chemokine receptor 5 (CCR5), maraviroc disrupts the geometry of the multi-point interaction between the second extracellular loop of CCR5 and the V3 loop of HIV-1 glycoprotein (gp) 120, allosterically preventing R5 virus from binding. As a result of the targeted mode of action, a tropism test demonstrating the presence of CCR5-tropic (R5) virus is a prerequisite for maraviroc use. During clinical development, tropism was determined with the Trofile phenotypic test provided by Monogram Biosciences . Subsequently, largely retrospective validation studies established genotypic tropism testing as an alternative, based on the analysis of the gp120 V3 sequence through an automated predictive algorithm, most commonly the geno2pheno[coreceptor] system . ImportaThe efficacy and safety of maraviroc have been demonstrated in phase 3 clinical trials of both antiretroviral treatment (ART)-naïve and ART-experienced subjects with R5 virus –12. WhilWith the aim of gaining a comprehensive understanding of maraviroc use, this multicentre observational cohort study surveyed reasons for starting maraviroc and measured the efficacy and durability of maraviroc-containing regimens across Europe. A secondary objective was to determine the performance of genotypic tropism testing in relation to virological outcomes.Subjects eligible for inclusion were HIV-1 positive adults who started their first maraviroc-containing ART regimen between January 2005 and December 2013 within routine clinical practice, and had ≥1 follow-up visit after receiving ≥1 dose of maraviroc. Fully anonymised data available from individual electronic databases and clinical cohorts were collected as part of a formal European audit of clinical service; no ethics permission was required, and the audit was registered with the Royal Liverpool University Hospital in the United Kingdom. A total of 26 clinical cohorts in 8 European countries participated. Each centre adhered to local research governance regulations concerning the collection and analysis of routinely collected, anonymised clinical data for audit purposes. Data submission to the central audit repository occurred through a structured case record form that collected simple demographic data , current and nadir CD4 cell count, CD4 cell count and plasma HIV-1 RNA load at the start of maraviroc  and during follow-up, ART history , results of drug resistance and tropism testing performed at any time before and after starting maraviroc, and HIV-1 subtype if known. We used objective measures from the database in order to classify the context of maraviroc use. ART-naïve patients were classified on the objectively verified absence of previous ART use. In ART-experienced individuals, treatment was classified as “ART switch” when one or more components of the existing regimen were changed alongside the introduction of maraviroc, and as “ART intensification” when maraviroc was added as a single agent to the existing regimen. These treatment categories were subdivided based on suppressed or detectable viral load  prior to maraviroc initiation.www.hivdb.stanford.edu), whereby each drug in the regimen was assigned a susceptibility score based on the estimated levels of drug resistance: susceptible and potential low-level resistance = 1; low-level and intermediate resistance = 0.5; and high-level resistance = 0. For enfuvirtide, gp41 sequences were interpreted using HIV GRADE . In the absence of an integrase or gp41 sequence, integrase inhibitors and enfuvirtide were assumed to be fully active in case of first use or previous use without failure (score = 1) and not active (score = 0) in case of previous use with documented failure. HIV-1 subtypes were assigned based on all pol sequences using the Rega subtyping tool 3.0 (http://dbpartners.stanford.edu:8080/RegaSubtyping/stanford-hiv/typingtool) and the Comet algorithm (https://www.ncbi.nlm.nih.gov/pubmed/25120265). In case of discordant results between the two algorithms, the subtype was set as undetermined.Results of genotypic tropism testing were verified by a centralised re-analysis of gp120 V3 sequences using geno2pheno[coreceptor] version 2.5 . CentresThe date of maraviroc initiation was considered the baseline for the study. Treatment outcomes were measured over 48 weeks . Treatment failure (TF) was defined by either virological failure  or maraviroc discontinuation prior to week 48 for any cause. The VF analysis comprised patients who remained on maraviroc at week 48. Time to maraviroc discontinuation was estimated by survival analysis using the Kaplan-Meier method; where data were available past week 48, these were retained in the analysis. Predictors of TF and VF were analysed by univariate and multivariable logistic regression. All p-values were calculated by a univariate mixed logistic model taking into account the clustering effect of the clinical centre. In the multivariable models, a backward stepwise selection method was employed starting from a model with all variables showing an association with the outcome of interest with a p-value ≤ 0.2 according to the univariate analysis. These models employed a stepwise exclusion criterion of variables with p-values >0.2, except for viral tropism that was manually included in all models. In the final multivariable models, all variables retained by the selection method were simultaneously adjusted. Statistical analysis was performed using the STATA version 13.0 software package.3, and 782/1,381 (56.6%) with a current CD4 cell count ≥350 cells/mm3. Almost half  had a suppressed viral load (<50 copies/mL). The overall cohort was heavily ART-experienced, with 718/1,381 (52.0%) having received ≥7 antiretroviral drugs and about two-thirds  having experienced ≥3 drug classes including protease inhibitors (PIs) in 1213/1,381 (87.8%) and integrase inhibitors in 651/1,381 (47.1%).Data were retrieved from 26 clinical centres in 8 countries totalling 1,381 patients, and comprising 538 from the United Kingdom and Ireland, 291 from Italy, 259 from Germany, 206 from Spain, 43 from France, 30 from Belgium, and 14 from Luxemburg. The characteristics of the study population at the time of starting maraviroc (baseline) are summarized in Tropism assay results were available for 1,273 (92.3%) participants: 1,075 through genotypic testing and 189 through a phenotypic assay . In 9 cases the type of assay was not specified and no V3 sequences were available for re-analysis. Both phenotypic and genotypic tropism assay results were available in 14 cases, with only one discordant case where the phenotypic result was considered. Tropism testing was performed using plasma HIV-1 RNA in 696 cases and HIV-1 DNA (from whole blood or PBMC) in 561; in 16 cases the source was not specified. The tropism result was R5 in 1,049/1,273 (82.4%) and non-R5 in 224/1,273 (17.6%). The FPR results were available for 1,036/1,075 genotypic tropism assays and comprised: <10% in 104 cases, 10% to 20% in 133 cases, 20% to 40% in 249 and ≥40% in 550 cases. The median FPR value (IQR) was 50.5 (33.9–78.1) for results assigned as R5 and 10.4 (4.6–15.5) for those assigned as non-R5.The GSS of the regimen accompanying maraviroc was available for 661/1,381 (47.9%) subjects, including 393/709 (55.4%) subjects that started maraviroc with HIV-1 RNA ≥50 copies/mL. The GSS was <1 in 83/661 (12.6%), 1 in 254/661 (38.4%), 2 in 228/661 (34.5%), and ≥3 in 96/661 (14.5%). The viral subtype was available in 794/1,381 patients (57.5%): most carried subtype B , followed by C , A , CRF02_AG , G , others , and unassigned subtype .Clinician-reported reasons for maraviroc initiation were available in 1,297/1,381 (93.9%) patients. Most patients that started maraviroc were described as treatment experienced. Among the reported reasons, VF accounted for 547/1,297 (39.6%) initiations, whereas a change of a virologically suppressive regimen was reported in 465/1,297 (35.9%) as a result of toxicity  or other reasons . Intensification of suppressive ART was described in 104/1,297 (8.0%) subjects and the reasons comprised low CD4 cell counts  and miscellaneous other reasons including aiming to improve ART activity in the central nervous system (CNS). Maraviroc was started in ART-naïve subjects in 49/1,297 (3.5%) cases. For the remaining 132/1,297 (9.6%) subjects, the reason for maraviroc initiation was not reported. For analytic purposes, the context of maraviroc initiation was classified using objective measures . Among tThe most frequently employed total daily dose of maraviroc was reported as 300mg , followed by 600mg , 150mg  and 1,200mg ; the dose was not reported in 222/1,381 (16.1%) of cases. The dosing schedule was reported as twice daily in 661/1,381 (47.9%) subjects, once daily in 276/1,381 (20.0%), and was not reported in 444/1,381 (32.2%). The accompanying drugs belonged to 1, 2, and 3 or more classes in 518/1,381 (40.2%), 626/1,381 (45.3%) and 144/1,381 (10.4%) regimens, respectively ; 906  subjects experienced TF over 48 weeks of follow-up. The logistic regression analysis of factors associated with TF is shown in Of the 1,010 patients still on maraviroc at week 48, 201 (19.9%) had a viral load >50 copies/mL, including 93 (9.2%) with levels between 50 and 200 copies/mL and 108 (10.7%) with levels >200 copies/mL. The logistic regression analysis of factors associated with VF is shown in Tables This study reports the largest data set of maraviroc-containing treatment cases ever collected from routine clinical practice. We asked clinical sites to include all their patients initiating maraviroc outside clinical trials to assess the use and effectiveness of maraviroc across Europe, in a time frame spanning from 2005 to 2016. Based on this survey enrolling cases through 26 different clinical sites in 8 European countries, we observed that maraviroc was used in multiple clinical scenarios. Its most frequent use was as a switch therapy in highly ART-experienced patients with either detectable or undetectable viral load. In this population, maraviroc use was safe and reasonably effective. Maraviroc discontinuation was mostly due to VF, desire to simplify the treatment regimen, or issues of incomplete adherence with the regimen. Toxicity accounted for 18% of the reported reasons of maraviroc discontinuation. Clearly, neither toxicity nor VF could be specifically attributed to maraviroc, due to concomitant antiretrovirals. This being a retrospective study, it was not possible to investigate the details of the toxicity events and confirm their attribution to maraviroc or other drugs. Notably, only two cases of transaminase elevations were reported as reasons for maraviroc discontinuation. Major determinants of treatment failure–defined as discontinuation of maraviroc for any reason or virological failure–were the concomitant use of three or more predicted active drugs, and more recent calendar year of maraviroc initiation (after 2011). These findings are likely to reflect a higher propensity for maraviroc interruption in the presence of other active drugs, and the increased number of effective drugs that have become available in recent years.Interestingly, a significant proportion (17.6%) of patients in the cohort started maraviroc despite carrying a non-R5 virus. Given that the classification as R5 was largely based on the centralised re-analysis of V3 sequences, the observed off-label use of maraviroc may in part reflect technical aspects of tropism testing and the application of different interpretation thresholds. There also appeared to be interest in exploring maraviroc activity in patients with mixed tropism results and in those for whom selective tissue activity was postulated . Non-R5 tropism predicted higher odds of treatment failure, however it had a weaker effect on virological failure, with a higher proportion of patients with non-R5 virus experiencing virological failure in a univariable analysis but no clear association in the adjusted model. This suggests that some of the non-standard use might have been explorative and short-term. In this context, tropism would not be expected to be the key predictor of virological failure. In addition, in the highly treatment-experienced population we analysed, multiple determinants are expected to impact virologic responses. There is evidence from the MOTIVATE trials of maraviroc in treatment-experienced patients that the composition of the overall regimen  is a key predictor of virologic outcome, including in a small subset of patients with non-R5 virus .About one in five patients on maraviroc had a detectable viral load after 48 weeks of follow-up. It should be noted that the analysis of virological failure excluded patients who either previously discontinued or were lost to follow-up, and that these may have comprised cases of virological failure. Although this may be considered a high rate of virological failure , interpretation should consider the high stringency applied to the definition of failure. Indeed, applying a higher and clinically more relevant viral load threshold of 200 copies/mL halved the number of virological failures, indicating that a substantial number of cases of viraemia were at low level. Moreover, the cohort had a significant history of treatment exposure with about two thirds of participants having previously experienced 3 or more antiretroviral drug classes. Predictors of virological failure were a low nadir CD4 cell count, a detectable viral load at maraviroc initiation, and a history of PI exposure, with a marginal effect of younger age. In line with these findings, previous cohort studies showed that older age reduces the risk of virological failure, likely as a result of improved medication adherence . Higher The treatment collection included several cases of non-standard, off-label maraviroc use. Indeed, it included ART-naïve subjects (unlicensed indication in Europe), patient carrying non-R5 virus, and cases with once-daily maraviroc dosing and low daily doses of 150mg. While we cannot exclude prescription errors, it is also realistic to assume that the drug was deliberately used in off-label indications. Off-label use may result from lack of alternative treatment options because of toxicity or drug resistance, hypothesised residual drug activity , or the This study has several limitations. First, no measure of medication adherence was available, therefore this major determinant of treatment outcome could not be analysed. This is not different from the majority of other reported observational studies of ART outcomes, which did not collect medication adherence systematically and could not adjust for this factor. Second, some variables such as genotypic susceptibility of the concomitant regimen and viral subtype were not available for a large proportion of cases, therefore their predictive value could not be fully analysed. Third, the retrospective design of the study did not allow to confirm the reasons for maraviroc initiation or interruption. In order to partly overcome this limitation, we used objective data such as the pre-treatment viral load, the pre-maraviroc treatment regimen, and the drugs prescribed concomitantly with maraviroc to classify the different clinical scenarios of maraviroc prescription. Despite these limitations, this study is unique in depicting the clinical use of maraviroc in clinical practice throughout Western Europe during the last decade.In conclusion, in this large European survey we found that maraviroc was used in multiple clinical scenarios involving mostly ART-experienced patients, both virologically suppressed and with detectable viremia. In a population of highly experienced patients, maraviroc was overall safe and reasonably effective, also when considering that there was a considerable use of exploratory off label treatments, and a substantial number of virological failures occurred at viral load <200 copies/mL. High discontinuation rates in recent years presumably reflected the availability of alternative active agents. In current guidelines, maraviroc continues to represent a valid antiretroviral option in selected patients, particularly those with limited drug options or intolerance to agents from other classes. The virological rationale for using CCR5 antagonists early in therapy is still strong, as reflected by the significant impact of a low nadir CD4 count on treatment outcomes . Whether


N = 11689). For pharmacy data (N = 7156), we examined associations of percentage adherence during the 1st year of ART with VF (>500 copies/mL) at 1 year. For self-report data (N = 4533), we examined 28-day adherence with VF based on closest viral load measure within 6 months after questionnaire date. Since adherence differed markedly by measurement type, we defined different cut-off points for pharmacy  and self-report  data. Adjusted odds ratios (ORs) for VF in lower and medium, compared to higher adherence groups, were 23.04 (95% CI: 18.44–28.78) and 3.84 (3.36–4.39) for pharmacy data. For self-report data, they were 3.19 (2.31–4.40) and 1.08 (0.80–1.46). Both types of measure were strongly associated with VF. Although adherence measurements over longer time-frames are preferable for prediction, they are less useful for intervention.Adherence to antiretroviral therapy (ART) is critical for successful treatment of Human Immunodeficiency Virus (HIV), but comparisons across settings are difficult because adherence is measured in different ways. We examined utility of different adherence measures for identification of patients at risk of viral failure (VF). Eight cohorts in the ART Cohort Collaboration contributed data from pharmacy refills or self-report questionnaires collected between 1996 and 2013 ( Adherence to antiretroviral therapy (ART) sufficient to suppress viral replication is critical for successful treatment of HIV ,2,3,4,5.Methods to assess medication adherence include self-report questionnaires, pharmacy-refill data, pill counts, electronic drug monitoring, and monitoring drug levels in the blood ,8. HowevWe examined whether different adherence measures can be calibrated for use in pooled analyses by using different cut-off points. In an era of large international HIV cohort collaborations, the appropriate use of data combined from different settings is ever more important. Identifying those at risk of viral failure is crucial for successful treatment, and so we also investigated the utility of different adherence measures for identifying those at risk of viral failure, among cohorts participating in the ART Cohort Collaboration (ART-CC).www.bris.ac.uk/art-cc). Prospective cohort studies were eligible if they enrolled at least 100 HIV-1-positive ART-naïve patients aged ≥16 years who started ART on at least three drugs, including nucleoside reverse-transcriptase inhibitors (NRTIs), protease inhibitors (PIs), or non-nucleoside reverse-transcriptase inhibitors (NNRTIs), with a median follow-up of at least 1 year. All cohorts use quality control procedures and provided a predefined and anonymised set of demographic, laboratory, and clinical variables. ART-CC is a collaboration of cohort studies from Europe and North America established with the aim of describing the prognosis of antiretroviral-naïve patients starting ART  (www.briwww.cohere.org and www.EuroCoord.net). The NHS Health Research Authority South West—Cornwall and Plymouth Research Ethics Committee, UK, has approved the ART-CC study (REC reference 12/SW/0253). Eight cohorts, whose patients were enrolled in differing healthcare systems see , contribFour cohorts provided adherence data from pharmacy refills  and four from self-report questionnaires . Only the VACS cohort provided data from both pharmacy refills and self-report questionnaires. Adherence data were available for only a subset of the patients in ICONA, SHCS, UAB, UW, and HAVACS as either, not all patients consented, or they spoke a different language or answered a different version of the adherence question, which was not comparable as there was too little discrimination . However, the choice of these subsets should not have introduced bias as patient characteristics in the analysis sample were similar to those of included patients from the same cohort. Adherence data were available for all patients in Alberta, HOMER, and VACS.Self-report questionnaires asked about behaviour in the last 28 days, and were administered when patients attended clinical visits. For ICONA, UAB, and UW, patients were asked how often they took their antiretrovirals in the last 28 days (month for ICONA), and asked to mark it on a visual analogue scale ranging from 0 (never) to 100 . We used this as the percentage adherent. For SHCS, the percentage adherence over the last 4 weeks was calculated based on patient-reported number of missed doses. Questionnaires were administered multiple times, but at infrequent intervals. In SHCS, the median time between questionnaires was 5 months, UW 7.5 months, ICONA 6.5 months, UAB 6 months. Viral suppression (≤500 copies/mL) was based on the closest viral load measure within 6 months after the questionnaire date .Pharmacy refill data record the date that a prescription was filled and how many days’ worth of drug was supplied. From this, we know when a patient should return for another refill. For pharmacy data, we derived 1-year percentage adherence and corresponding viral suppression (≤500 copies/mL) based on the viral load closest to (and within ± 3 months of) the 1-year time point . PercentPatients were only included in the analysis if they had data on both adherence and viral load. Median levels of adherence were compared between patients who were and were not suppressed. We fitted receiver operating characteristic (ROC) curves (plots of (1-specificity) against sensitivity) to assess the relationship between percentage adherence and viral suppression, separately in each cohort. The area under the ROC curve (AUROC) was used to measure the discrimination of the adherence measure for viral suppression: an AUROC of 0.5 corresponds to discrimination no better than expected by chance, and 1 to perfect discrimination.TM version 13.0 [Logistic regression was used to examine associations of percentage adherence with viral suppression. As a first step, adherence was categorised as <95% and ≥95%, because this is a widely used classification. However, for self-report data, this categorisation had little meaning as most patients rated their adherence to be very high. After examining the distribution of adherence among cohorts with self-report and pharmacy data, we categorised adherence differently for cohorts with pharmacy data (as <45% (low adherence), 45–99% (medium), and 100% (high)) and for cohorts with self-report data (as ≤95% (low adherence), 96–99% (medium), and 100% (high)). These cut-offs were chosen to make proportions as similar as possible across the pharmacy and self-report data. We fitted crude and adjusted  logistic regression models to assess the association of adherence with viral suppression. Stataion 13.0  was usedWe considered whether the effect of adherence on suppression was modified by age, and conducted sensitivity analyses (1) using a viral load cut-off of 50 copies/mL to define viral suppression; (2) restricted to the most recent 5 years of data (2009–2013) in order to report on regimens which are currently prescribed; and (3) restricted to patients who were still on their baseline ART regimen at the time of the outcome measure. The different time frames used for pharmacy and self-report adherence measures led us to consider using different time frames (3 and 6 months) for pharmacy data, which could be more easily compared with self-report.There has been discussion in the field of adherence to diabetes medication that patients who are “over-adherent” (those who stockpile their medications and so appear to have >100% adherence) may be different from the rest of the population ,19. We wThe VACS cohort had both pharmacy and self-report measures available for direct comparison between the two methods. As the pharmacy measure is based on a 12-month period, we used the question “In the past 12 months, when you take your HIV medications, how often do you take all the medications you’re supposed to?” from self-report questionnaires for comparison . In their self-report data, VACS did not ask a question using the visual analogue scale, so we were unable to calculate percentage adherence.3 and 4.9 log10 copies/mL, respectively. VACS and HAVACS are cohorts of military veterans, most of whom are men and were older, on average. The distribution of risk groups for HIV acquisition also differs between cohorts: VACS has poorly recorded transmission risk in their cohort and HOMER has a high proportion of injection drug users (IDU) and patients with unknown transmission risk. Three out of eight cohorts supplied refill drugs automatically without the patient requesting it.Adherence data were available on 11,689 patients: 7156 from the four cohorts with pharmacy data, and 4533 from the four cohorts with self-report data. Among cohorts with pharmacy data, estimated adherence was much lower in patients with subsequent viral failure than in those who were suppressed. This pattern was not seen to the same extent among cohorts with self-report data. Associations of adherence with viral failure were similar for Alberta and HOMER, but weaker for VACS. For HAVACS, there was little evidence that adherence was associated with viral failure, although associations were imprecisely estimated because the sample size was small. Using adherence data pooled over all cohorts with pharmacy data, the odds ratios (ORs) (95% CI) for viral failure in lower and medium, compared to higher adherence groups, were 26.1 (21.1–32.4) and 4.4 (3.9–5.0), respectively. After adjusting for baseline covariates, the ORs were 23.0 (18.4–28.8) and 3.8 (3.4–4.4), respectively. We also compared lower with medium levels of adherence. Across all cohorts, there was strong evidence that lower adherence led to higher rates of viral failure compared to medium adherence.Among cohorts with self-report data, there was little evidence that medium level adherence was associated with higher odds of viral failure. However, self-reported low adherence was associated with higher odds of viral failure. Using adherence data pooled over all cohorts with self-report data, the ORs (95% CI) for viral failure in lower and medium, compared to higher adherence groups, were 3.1 (2.4–4.2) and 1.2 (0.9–1.5), respectively. After adjusting for baseline covariates, the ORs were 3.2 (2.3–4.4) and 1.1 (0.8–1.5), respectively. As with pharmacy data, we also compared lower with medium levels of adherence and, again, found that lower levels of adherence led to higher rates of viral failure compared to medium adherence.For cohorts with pharmacy data, there was weak evidence that age modified the effect of adherence on failure . Among pWhen restricting to the most recent 5 years of data (2009–2013), data were only available from the Alberta, ICONA, SHCS, UAB, and Washington cohorts. Most were cohorts with self-report data and odds ratios were similar to those for cohorts with self-report data in the main analyses . Resultsp < 0.001). We compared the associations of pharmacy/self-report adherence measures with viral failure in 331 patients. To compare self-report and pharmacy measures directly, we used data from 348 VACS patients. Due to the way the self-report question was asked (see Methods section), we could not calculate adherence percentage, and so had to use the raw data. As self-reported adherence increased, so did the pharmacy adherence measure (We combined data from eight HIV cohort studies: four with adherence measured using patient self-report and four using pharmacy refill data. There was heterogeneity between cohorts in both levels of adherence and viral failure. Both self-report and pharmacy refill adherence data can be used to predict viral failure and show evidence that increasing adherence decreases the risk of viral failure. Pharmacy measures were much more strongly associated with viral failure than self-reported measures, although this may be due, in part, to the longer time-frame used in the pharmacy data and the higher % with viral failure in the pharmacy cohorts. When considering data from the VACS cohort, which provided pharmacy and self-report measures, the strength of associations of the different measures with viral failure were similar. To make full use of adherence data, there needs to be an awareness of cohort-specific factors affecting adherence. For example, in the Alberta cohort, patients with very poor adherence may have drugs stopped pending correction of underlying issues compromising adherence.Pharmacy refill and self-report are different tools for measuring adherence that have different characteristics and uses . Short-tAdvantages of pharmacy refill data include being inexpensive and immune to social desirability/recall bias or tampering ,11. SuchSelf-reported adherence, in context of viral load monitoring, is commonly used in both clinical care and research settings, because of its low respondent and staff burden, ease and speed of administration, and low cost ,24. The Several studies have compared self-report to pharmacy refill, both among HIV-infected individuals and other disease conditions, such as chronic obstructive pulmonary disease medications . Self-reWe investigated how adherence to ART is measured across cohorts from two continents providing routine clinical care in high-income settings. These data are representative of patients in usual clinical care and, so, it is likely that our results are generalisable to other high-income settings. Our analyses may be subject to a number of biases. We assumed that viral load measures should be done every 6 months: if a viral load measurement was not available within this time period, then we had to exclude the patient from analyses. Thus, patients included in analyses may have been more adherent to care than excluded patients. On the other hand, less adherent patients may have been monitored more closely and, therefore, be more likely to be included. Questionnaires were not routinely administered at regular time intervals and, therefore, it was not feasible to derive a 1-year self-report adherence measure without heavily reducing the sample size or making strong assumptions about adherence in the time between questionnaires. Association of adherence levels with viral failure may be different for newer ART regimens which have longer half-lives. Cohorts should consider carefully how best to collect and make use of adherence data for patient care within their healthcare setting. Pharmacy refill data require time and effort for their management, but provided a better tool, than self-report data, for predicting viral failure in our study. Harmonisation of pharmacy refill data management should be attempted in order to ensure that we are using the same tools. Without this, we need to recognise that differences in dispensing will influence refill data. Refill data are not as useful as self-report data in facilitating immediate interventions to change behaviour, which may prevent patients from experiencing subsequent viral failure.