Uptake of antiretroviral treatment (ART) is expanding rapidly in low- and middle-income countries (LMIC). Monitoring of virological suppression is recommended at 6 months of treatment and annually thereafter. In case of confirmed virological failure, a switch to second-line ART is indicated. There is a paucity of data on virological suppression and clinical management of patients experiencing viremia in clinical practice in LMIC. We report a large-scale multicenter assessment of virological suppression over time and management of viremia under programmatic conditions.Linked medical record and laboratory source data from adult patients on first-line ART at 52 South African centers between 1 January 2007 and 1 May 2018 were studied. Virological suppression, switch to second-line ART, death, and loss to follow-up were analyzed. Multistate models and Cox proportional hazard models were used to assess suppression over time and predictors of treatment outcomes. A total of 104,719 patients were included. Patients were predominantly female (67.6%). Median age was 35.7 years (interquartile range [IQR]: 29.9–43.0). In on-treatment analysis, suppression below 1,000 copies/mL was 89.0% at month 12 and 90.4% at month 72. Suppression below 50 copies/mL was 73.1% at month 12 and 77.5% at month 72. Intention-to-treat suppression was 75.0% and 64.3% below 1,000 and 50 copies/mL at month 72, respectively. Viremia occurred in 19.8%  of patients during a median follow-up of 152 (IQR: 61–265) weeks. Being male and below 35 years of age and having a CD4 count below 200 cells/μL prior to start of ART were risk factors for viremia. After detection of viremia, confirmatory testing took 29 weeks (IQR: 16–54). Viral resuppression to below 1,000 copies/mL without switch of ART occurred frequently  but was associated with renewed viral rebound and switch. Of patients with confirmed failure who remained in care, only 41.5%  were switched. The median time to switch was 68 weeks (IQR: 35–127), resulting in 12,325 person-years spent with a viral load above 1,000 copies/mL. Limitations of this study include potential missing data, which is in part addressed by the use of cross-matched laboratory source data, and the possibility of unmeasured confounding.In this study, 90% virological suppression below the threshold of 1,000 copies/mL was observed in on-treatment analysis. However, this target was not met at the 50-copies/mL threshold or in intention-to-treat analysis. Clinical management in response to viremia was profoundly delayed, prolonging the duration of viremia and potential for transmission. Diagnostic tools to establish the cause of viremia are urgently needed to accelerate clinical decision-making. Lucas Hermans and co-authors study virological suppression in people with HIV receiving antiretroviral therapy during 2007-2018, in South Africa. The global community has set ambitious targets for virological suppression during antiretroviral treatment (ART) for HIV infection, with the ultimate goal of halting the HIV epidemic.Data from clinical trials and cohorts show that these suppression rates are attainable. However, there is a paucity of data on actual suppression rates from large-scale treatment programs in low- and middle-income countries (LMIC), where the majority of HIV-infected patients reside.We studied virological suppression in a large multicenter observational cohort in LMIC reflecting clinical care under programmatic conditions of over 100,000 HIV-infected patients at 52 South African treatment sites.In this cohort, a virological suppression rate of 90% was attained below the 1,000-copies/mL HIV-DNA threshold. However, in intention-to-treat analysis, the virological suppression rate was substantially lower.The clinical management in response to viremia was delayed, resulting in a substantially prolonged duration of viremia at levels allowing for transmission.Our findings indicate that although ART is highly successful, viremia still occurs frequently in clinical practice.The delay in response to viremia contributes to a stable and large pool of potentially infectious patients. The global community has adopted ambitious targets for rollout and success rates of antiretroviral treatment (ART) with the ultimate goal of halting the HIV epidemic. These 90-90-90 targets, set by the Joint United Nations Program on HIV/AIDS (UNAIDS), stipulate that suppression of the HIV-RNA load  should be achieved in 90% of HIV-infected patients on ART by 2020 . RecentlSeveral cohorts in high-income countries (HICs) as well as recent clinical trials have reported virological suppression rates exceeding this ambitious target –5. HowevIn addition, the frequency of VL monitoring during treatment varies globally. WHO guidelines, which are generally applied in LMIC, advise annual VL monitoring after attaining virological suppression , whereasLarge-scale assessment of VL data from programmatic clinical care in LMIC is urgently needed in order to assess virological suppression and clinical management of viremia. We report a longitudinal assessment of virological suppression and clinical management of viremia in a large South African multicenter cohort of patients receiving programmatic HIV treatment and monitoring.We performed an analysis of routinely collected clinical and laboratory data in an open multicenter observational cohort of HIV-infected patients receiving ART at South African healthcare facilities. Data from this cohort have been reported previously . Data anAdult HIV-infected patients on ART attending 52 urban and rural public healthcare facilities across four South African provinces were included in the analysis. ART was provided in the framework of the South African national ART program, which provides treatment free of charge using WHO-aligned ART regimens and laboratory monitoring including VL assessment. First-line ART consisted of two nucleoside reverse transcriptase inhibitors (NRTIs) and a non-NRTI (NNRTI), and second-line ART consisted of two NRTIs and a ritonavir-boosted protease inhibitor (PI/r). Virological monitoring consisted of VL measurements at 6 and 12 months after initiation of ART and annual measurements thereafter in case of virological suppression. Virological failure is defined by guidelines as a VL of ≥1,000 copies/mL confirmed by a second measurement within 12 weeks. VL testing was performed on plasma samples using the Roche COBAS AmpliPrep/COBAS TaqMan HIV-1 Test, version 2.0, or Roche COBAS 8800 system  and by other assays in a minority of cases.Cohort patients were included in this analysis if they met inclusion criteria consisting of prescription of NNRTI-based first-line ART and availability of at least one VL result performed at least 20 weeks after initiation of ART. In patients treated with insufficiently potent ART , the episode during which this was prescribed was censored from the analysis. Patients with unknown age and/or sex were excluded from the analysis.Medical record data were extracted from the standardized Three Integrated Electronic Registers (Tier.NET) electronic medical databases . Anonymized database records were subjected to quality control, which included removal of duplicated or ambiguous data points. After quality control, all records from HIV-infected patients registered on ART at the participating facilities between start of large-scale rollout of ART in South Africa (1 January 2007) and date of data extraction (1 May 2018) were screened for inclusion as described above. To verify accuracy of electronic medical records, records of patients that received laboratory testing from the National Health Laboratory Services (NHLS) were matched to primary NHLS source data using a probabilistic matching algorithm. Additional information regarding sourcing and curation of data is available in the supplementary materials .The primary endpoint was viremia during ART, defined as any VL measurement ≥ 1,000 copies/mL during first-line ART, and performed at least 20 weeks after initiation of first-line ART. Secondary endpoints were confirmed virological failure , switch to second-line ART (defined as switch from NNRTI-containing to PI-containing ART after viremia), resuppression after viremia without switch to second-line ART, death, and loss to follow-up (LTFU). Patients were considered LTFU in case of a premature end of follow-up of at least 12 weeks before 1 May 2018 without confirmed death or transfer out.Virological suppression during follow-up was evaluated using a multistate model into which all available VL results performed at least 20 weeks after initiation of first-line ART until end of follow-up or switch to second-line ART were entered as a repeated measure. The model allowed for transition between discrete virological states based on the most recent VL result. Virological states were defined as virological suppression (most recent VL below 50 copies/mL), low-level viremia (most recent VL between 51 and 999 copies/mL), and viremia . In on-treatment analysis, patients were right-censored after the last available VL result on first-line ART. In intention-to-treat analysis, patients were right-censored after the last available VL if they were still in care, had transferred out, or had deceased but not if they had become lost to follow-up. In this case, patients were regarded as lost to follow-up from 12 weeks after their last recorded clinic visit until date of data extraction. On-treatment and intention-to-treat results were reported as proportions and visualized using Aalen-Johansen curves in order to evaluate whether the UNAIDS-defined 90% virological suppression target was attained.Mixed-effects Cox proportional hazards models were performed in order to assess baseline risk factors for the primary and secondary study outcomes. In a separate analysis of the risk of renewed rebound after a first episode of rebound followed by resuppression, patients were classified according to virological state, which was entered as a time-dependent covariate in which the patient is dynamically allocated to an exposure group based on the most recent VL result. Virological states were virological suppression below 50 copies/mL, low-level viremia (at least one VL result 51–999 copies/mL), viremia with subsequent resuppression below 50 copies/mL without switch of ART, or viremia with subsequent resuppression to low-level viremia (51–999 copies/mL) without switch of ART. All Cox proportional hazards models were adjusted for factors at start of ART that are known to affect treatment outcomes, i.e., sex, age, CD4-positive T-lymphocyte count (CD4 count), and ART regimen. Province of origin was entered as a random effect. Age and CD4 count variables were dichotomized at the approximate median value in all multivariable analyses. Patient records with missing data on one or more of the covariates were censored from the multivariable analysis. Patients who did not reach any of the study outcomes were right-censored after their last available VL result. Results were reported as hazard ratios (HRs) and adjusted HRs (aHRs) and 95% confidence intervals (95% CIs) and displayed as Kaplan-Meier curves. Validity of the proportional hazards assumption was evaluated using Schoenfeld residuals.Sensitivity analysis was performed in order to assess the robustness of the medical record data. A comparative analysis of the primary study endpoint of viremia and virological suppression during follow-up was performed using results from medical record data and results from matched laboratory source data. In addition, stratified analyses of suppression by sex, CD4 count category, age category, and clinical setting were performed. A sensitivity analysis of Cox proportional hazards models was performed in which only patients with at least two VL results during treatment were entered.Data from 190,465 HIV-infected patients with recorded start of ART were screened for inclusion. Of screened patients, 8,743 were below 18 years of age at start of ART, and 2,252 patients exclusively received second-line ART during study follow-up. For 64,118 patients, no VL results were available during study follow-up, and in a further 10,633 patients, VL results were available but obtained prior to week 20 of ART. This resulted in the inclusion of 104,719 patients in the analysis . Median p < 0.001). The proportion of patients with no VL data after 6 years of follow-up was 3.8%.The overall on-treatment virological suppression rate below 1,000 copies/mL was 89.0% at week 52 (1 year) and 90.4% at week 312 (6 years) of ART, whereas suppression below 50 copies/mL was 73.1% at 1 year and 77.5% at 6 years of ART . In inteDuring follow-up, 20,766 (19.8%) patients experienced viremia on first-line ART. In 6,018 (29.0%) of these patients, this occurred at the first VL measurement and during the first year of ART, suggesting an insufficient viral response rather than viral rebound. Overall, viremia occurred after a median duration of 92 weeks of first-line ART (IQR: 46–183). Death during follow-up occurred in 2.0%  of patients after a median 176 weeks (IQR: 108–277) of first-line ART. LTFU occurred in 17.6%  of patients after a median of 160 weeks (IQR: 95–255), and 12.6%  of patients transferred out.p < 0.001) for male patients, 0.91  per 5-year age increment, and 0.95  per 50-cells/μL CD4 count increment. Increased hazards of switch to second-line ART were also observed for these risk groups (p < 0.001) and death . Higher age was associated with a decreased risk of LTFU  and an increased risk of death , whereas higher CD4 count was associated with an increased risk of LTFU  and a decreased risk of death   .Virological suppression below 1,000 copies/mL varied between geographical settings, from 94.6% in urban settings to 88.0% in rural and urban-rural mixed settings at 72 months in on-treatment analysis . Sensitip < 0.001). In patients who experienced viremia, risk factors for viremia  also increased the likelihood of confirmation of failure and decreased the likelihood of achieving resuppression , whereas virological failure was confirmed in 54.4% . After confirmation of virological failure, 19.9%  subsequently achieved resuppression without switch of ART. However, resuppression was less profound in these patients, and low-level viremia (51–999 copies/mL) remained present in 46.3% , compared to 25.9%  of patients who resuppressed directly after one viremic episode  after resuppression to below 50 copies/mL and 8.91  after resuppression to low-level viremia. The hazard of switch to second-line ART was also significantly increased for both groups  cases of resuppression to below 50 copies/mL and in 34.1%  of cases of resuppression to low-level viremia (51–999 copies/mL). Compared to sustained virological suppression below 50 copies/mL, the aHR for renewed rebound was 3.16  and varied between a minimum median of 17 weeks (IQR: 8–34) and a maximum median of 35 weeks (IQR: 21–61) between settings . Of patiIn this study, we demonstrate sustained high rates of virological suppression over time in South African patients on first-line ART in urban and rural settings. An on-treatment virological suppression rate of 90% was observed, with an intention-to-treat suppression rate of 75% after several years of follow-up. These results reflect the significant achievements of large-scale rollout of treatment, which has resulted in considerable health benefits and increased life expectancy ,15.The 90% target was only attained at the WHO-defined VL threshold of 1,000 copies/mL. There is a paucity of scientific evidence to support the use of this threshold. Previously, we and others have shown that viremia below this threshold during ART confers considerable risks of poor treatment outcomes and selection of drug resistance ,8,16,17.Intention-to-treat virological suppression below 1,000 copies/mL decreased to 75% after 6 years of follow-up. The observed differences between on-treatment and intention-to-treat suppression rates is mainly due to LTFU, which amounted to 17% after 6 years. Although this rate is much lower than in previous reports of LTFU across LMIC , it stilOver 20% of patients in this cohort experienced viremia during follow-up. Young adults and men, as well as patients with poor baseline immunological status, were at increased risk of viremia, as has been observed in several African countries ,22. We dAfter viremia, a substantial number of patients achieved resuppression in absence of switching to second-line ART. This is in line with previous data from South Africa and other LMIC ,26. The Confirmatory VL testing after detection of viremia was profoundly delayed. This delay may be due to a variety of provider-driven, patient-related, or health infrastructural factors such as patient nonattendance ,28. In cLack of access to diagnostic tools that give insight in the reasons of viremia leaves healthcare practitioners ill-equipped to improve the current situation. If viremia is solely due to nonadherence, adherence interventions are indicated to prevent unnecessary switches to second-line ART ,31. HoweThe planned introduction of the integrase strand-transfer inhibitor dolutegravir in LMIC, driven by the increasing presence of drug-resistant viral strains in the population, may increase overall virological suppression rates but does little to allay concerns regarding management of viremia. As no drug is impervious to resistance, the introduction of a new drug class should be accompanied by expansion of monitoring tools to understand viremia, especially in the context of high levels of drug resistance to the NRTI backbone ,33. UndeReported virological suppression rates in LMIC vary widely . The majLimitations of this study include potential missing clinical and laboratory data. Missing data may originate from lack of adequate capturing but also from patient movement between clinics. Despite these limitations, cross-referencing of medical record data to laboratory source data demonstrated the robustness of the study findings. Although care was taken to adjust associations for known confounders, residual confounding in the multivariable analyses due to unmeasured covariates that cannot be adjusted for is an inherent risk to observational studies and may have affected the results. A degree of survival bias can be expected in longitudinal analysis of virological suppression, as patients who reach adverse treatment outcomes such as switch to second-line ART or LTFU are commonly censored from these analyses. We have sought to overcome this important limitation by performing an intention-to-treat analysis in which patients were not censored after switching to second-line ART and contributed follow-up time in case of LTFU. However, lack of data on patient outcomes after LTFU renders us unable to account for any subsequent outcomes of treatment, such as reengagement into care elsewhere and death. Although of considerable scale, the findings from this study may not be translatable to other LMIC. Despite these limitations, this analysis, covering a large number of urban and rural South African treatment centers, allows for unique insights into treatment outcomes in current clinical practice under programmatic conditions in LMIC.In summary, high virological suppression rates were attained in the South African treatment program. However, one in five patients did not partake in this success. In these patients, clinical follow-up of VL results was delayed, potentially because of anticipation of resuppression and fear of unnecessary switches to second-line ART. The presence of a large subset of long-term infectious patients within the treated population poses a risk to the health of these individuals and impedes efforts to control the epidemic. Diagnostic tools to establish the cause of viremia are urgently required to perform targeted adherence interventions and informed timely switches to second-line ART.S1 Appendix(DOCX)Click here for additional data file.S2 Appendix(DOCX)Click here for additional data file.S3 Appendix(DOCX)Click here for additional data file.S4 Appendix(DOCX)Click here for additional data file.S5 Appendix(DOCX)Click here for additional data file.S6 Appendix(DOCX)Click here for additional data file.S7 Appendix(DOCX)Click here for additional data file.


Haiti initiated the scale-up of HIV viral load (VL) testing in 2015–2016, with plans to achieve 100% coverage for all patients on antiretroviral therapy (ART) for treatment of HIV/AIDS. In the absence of HIV drug susceptibility testing, VL testing is a key tool for monitoring response to ART and optimizing treatment results. This study describes trends in expanded use of VL testing, VL results, and use of second-line ART regimens, and explores the association between VL testing and second-line regimen switching in Haiti from 2010 to 2017.We conducted a retrospective cohort study with 66,042 patients drawn from 88 of Haiti’s 160 national ART clinics. Longitudinal data from the iSanté electronic data system was used to analyze the trends of interest. We described patients’ VL testing status in five categories based on up to two most recent VL test results: no test; suppressed; unsuppressed followed by no test; re-suppressed; and confirmed failure. Among those with confirmed failure, we described ART adherence level. Finally, we used Cox proportional hazards regression to estimate the risk of second-line regimen switching by VL testing status, after adjusting for other individual characteristics.p < 0.005) after adjustment for individual characteristics. Among patients with confirmed VL failure, 44.7% had strong adherence, and fewer than 20% of patients switched to a second-line regimen within 365 days of VL failure.The number of patients who had tests done increased annually from 11 in 2010 to 18,828 in the first 9 months of 2017, while the number of second-line regimen switches rose from 21 to 279 during this same period. Compared with patients with no VL test, the hazard ratio (HR) for switching to a second-line regimen was 22.2 for patients with confirmed VL failure (95% confidence interval [CI] for HR: 18.8–26.3; Haiti has significantly expanded access to VL testing since 2016. In order to promote optimal patient health outcomes, it is essential for Haiti to continue broadening access to confirmatory VL testing, to expand evidence-based initiatives to promote strong ART adherence, and to embrace timely switching for patients with confirmed ART failure despite strong ART adherence. HIV/AIDS is a life-threatening disease which, if untreated, destroys the immune system, leaving those infected susceptible to opportunistic infection and early death. Antiretroviral therapy (ART) for treatment of HIV, when used consistently, suppresses HIV replication and prevents progression of HIV disease , leadingThe initial treatment for most HIV patients is a first-line ART regimen, but either weak adherence or the presence of drug resistance can cause virologic failure. The number of patients who experience virologic failure and who need second-line therapy has increased –7. SeconTo maximize the duration of first-line treatment and to justify switching to a second-line regimen when drug resistance is suspected, ART monitoring is necessary. In the past, in resource-limited settings, clinician decisions about ART regimen switching tended to rely on the World Health Organization (WHO) clinical and immunological criteria (CD4 monitoring) for ART failure. However, these criteria suffer from poor sensitivity and specificity in detecting true cases of treatment failure, leading to delayed detection of failure and low rates of switching to second-line ART regimens. Routine viral load (VL) testing is the preferred modality for ART monitoring and has been demonstrated to improve health outcomes of HIV patients through timely detection of treatment failure –12. It hAfter sub-Saharan Africa, the Caribbean region has the second highest HIV prevalence globally , and HaiWith support by the US President’s Emergency Plan for AIDS Relief (PEPFAR) and other funding sources, Haiti and other resource-limited countries have taken steps to expand access to VL testing. In 2015–16, Haiti’s Ministry of Public Health and Population (MSPP) initiated the scale-up of VL testing for all ART patients after 6 months on treatment and annually thereafter. In July 2016, Haiti adopted the “Test and Start” approach to ART initiation, making all patients immediately eligible for ART and thereby broadening the population of patients requiring regular VL testing .Monitoring expanded access to VL testing and examining whether this has improved evidence-based clinical management, including timely switching to second-line regimens, are important goals of policy evaluation in Haiti. The objectives of the present research study are: 1) to describe time trends in VL tests and results; 2) to describe time trends in switching from first- to second-line regimens; and 3) to explore the association between VL testing and second-line regimen switching from 2010 to 2017 in Haiti. This time frame followed Haiti’s devastating 2010 earthquake, a period when HIV clinical guidelines and resources for virologic monitoring of ART evolved toward routine VL testing.This is a retrospective cohort study using longitudinal electronic medical record (EMR) data from the iSanté data system. iSanté is the largest of three EMRs in Haiti, which contains records for approximately 70% of ART patients in Haiti , 22. PatART sites were included in our study based on the timeliness of data uploaded to the central iSanté data repository. Health facilities with fewer than 80% of patient visit forms saved to the iSanté central server within 90 days of the patient’s visit were excluded from the analysis. The goal of excluding these sites was to ensure that the data reflected the reality of care processes taking place at the clinics, thereby limiting bias when analyzing the total number of VL tests, number and percentage of patients with at least one VL test, as well as outcome of the VL tests. Three prison clinics were also excluded from the analysis, based on restrictions to secondary data use from these sites. Eligible patients were adults aged 16 and above who initiated a standard first-line ART regimen between January 1, 2010 and September 30, 2017 and who completed at least 6 months on ART. The study excluded patients who initiated ART on a second-line regimen. In each calendar year, active patients were those who picked up ART medication at least once that year. Patients were divided into annual ART cohorts according to their year of ART initiation.Haiti national ART guidelines recommend VL testing after 6 months on ART and annually thereafter. Haiti uses the “Generic HIV Charge Virale” viral load assay  to measure plasma VL, with a lower limit of detection of 416 copies/ml when 250uL of plasma is used for testing; however, only values of ≥1000 copies/ml are considered to be unsuppressed per Haiti’s national guidelines . ART pat> 1000 copies/ml with no prior test or with a prior suppressed result); 4) re-suppressed (VL test result < 1000 copies/ml following an unsuppressed result); and 5) confirmed failure (VL result > 1000 copies/ml following a previous unsuppressed result).We classified VL status into five categories based upon the most recent VL test result for every patient and, if available, the test result immediately preceding it. The five categories were: 1) no test; 2) suppressed (VL test result < 1000 copies/ml with no prior test or with a prior suppressed result); 3) unsuppressed (VL result The preferred first-line ARV regimens in Haiti since 2008 have included two nucleoside reverse transcriptase inhibitors (NRTIs) and one non-nucleoside reverse transcriptase inhibitor (NNRTI). Prior to 2013, the preferred first-line regimens consisted of tenofovir plus emtricitabine plus efavirenz or nevirapine. After 2013, the preferred first-line regimens consisted of tenofovir plus lamivudine plus efavirenz. Several alternative first line regimens were recognized for pediatric patients of less than 10 years, patients with renal insufficiency, or patients with adverse drug reactions. Second-line regimens were defined as two NRTIs combined with a ritonavir-boosted protease inhibitor . Prior tFor this study, we defined ART regimens as first or second-line according to the national ART guidelines in place when the medication was picked up: the 2008 national ART guideline covered ART medications picked up from January 2010 to December 2012; the 2013 guideline covered medications picked up from January 2013 to December 2016; and the 2017 guideline covered medications picked up in 2017.Following an unsuppressed VL result, clinicians are expected to encourage improved adherence and to use standardized documentation of adherence in patients with confirmed ART failure to justify a regimen switch. In this study, we assessed adherence in the 180 days prior to confirmed cases of VL failure using the medication possession ratio (MPR), or the percentage of days that patients had medication in their possession. If the MPR was greater than 90%, the patients were considered as having strong adherence, and if the MPR was less than 90%, the patients were considered as having weak adherence –34.The total number of VL tests, the number and proportion of unsuppressed tests, the number of total patients in care, and the number and proportion of patients who had at least one VL test are described using frequency tables. We used these results to present the VL cascade by calendar year, to illuminate time trends in VL testing and results. We also analyzed VL testing and virologic outcomes by ART cohort for the 2010 to 2017 cohorts. In these ART cohort analyses, we first used the Kaplan-Meier method to assess time from ART initiation to first VL test by ART cohort, among all ART patients. Next, we considered the sub-set of patients with at least 18 months of possible follow-up time after ART initiation, since VL testing was not always consistently administered 6 months after ART initiation as directed by national guidelines. We characterized the VL status of the 7 ART cohorts (cohort 2010 to cohort 2016) using the results of up to two most recent tests available for each person.We described the rate of switching to second-line regimens by ART cohort, first among all patients and then among those observed to be on ART for at least 18 months, for the 2010 to 2016 ART cohorts. We explored the VL status among switching patients. Finally, we used the Kaplan-Meier method to estimate the proportion of patients switching to second-line regimens by two time-to-event outcomes: time from initial unsuppressed VL test to second-line switching, as well as time from confirmed failure to second-line switching.We used a Cox regression model to assess the relationship between VL status (using the five categories described above) and second-line regimen switching among the 2010 to 2017 ART cohorts. In this analysis, the VL status was a time-varying variable. We explored the association after adjusting for age, gender, WHO stage at ART initiation, and year of ART initiation. There were no missing values for year of ART initiation or age (since we excluded cases with missing age during the data exclusion process). We created a missing indicator category for cases with missing gender or WHO stage. For this analysis, we considered all available patients and all available VL tests prior to switching or administrative censoring (whichever came first), rather than limiting the analysis to patients with at least 18 months of follow up and limiting to the two most recent VL tests. Thus, patients had differing durations of follow up.When analyzing the outcomes of VL testing, time taken from ART start to initial VL test, and time from initial unsuppressed VL test to second-line regimen switching Tables , 3 and 4Out of 126 sites with data recorded in the iSanté system, there were 88 eligible sites with 66,042 patients from the 2010 to 2017 ART cohorts . A total of 14.1% of patients experienced an unsuppressed result in one or both of two most recent VL tests , and this decreased to 48.3% for 2016 ART cohort (913 out of 1890). The proportion of patients with no confirmatory testing following an initial unsuppressed result was higher among later ART cohorts. For the 2010 ART cohort, 50.6% of unsuppressed patients had no confirmatory test (278 out of 549), and this number increased to 70.1% for 2016 ART cohort (204 out of 291) . The rate of switching remained steady at approximately 1.0% of all active patients in each calendar year since 2013  of switching to a second-line regimen compared with those with no VL test done, after adjusting for age, gender, WHO stage at ART initiation, and year of ART initiation (Table p < 0.001) and those with a re-suppressed result had 2.3 times higher hazard  of switching compared with patients with no test. In contrast, patients who had suppressed VL result had a 0.4 times lower hazard  of switching compared to those with no test. Compared with patients at 16–24 age group when initiating ART, patients over age 55 had a 0.7 times lower hazard for switching to a second-line ART regimen , while comparisons with the 25–34, 35–44, 45–54 year age groups were not statistically significant. Males had a 1.4 times higher hazard for switching compared with females  in adjusted analyses. Patients with a more advanced WHO stage at ART initiation also had a higher hazard for switching to second-line ART in adjusted analyses. Compared with WHO stage I patients, those with stage II, III, and IV had 1.4 , 1.9 , and 3.2  times higher hazard for switching to a second-line ART regimen, respectively  conducted research assessing VL outcome among patients receiving ART at five hospitals around Port-au-Prince, Haiti from 2013-15 . Among 7In terms of virologic status as revealed by routine VL testing, our results were similar to those reported by Jean-Louis et al. (2017); both studies showed virologic suppression in around two-thirds of those tested in each ART cohort of patients. This low absolute level of suppression could indicate a preferential use of VL testing among those with clinical suspicion of treatment failure. Our finding that use of second-line regimens was limited to 1.4 switches per 100 person-years, is consistent or slightly lower than levels in other resource-limited settings . In a coBefore 2016, VL testing was not widely used as evidence for second-line switching in Haiti. But since 2016, VL testing has become a guide for clinicians to switch ART regimens. In terms of the association between VL testing status and second-line regimen switching, patients with confirmed VL failure were far more likely to be switched to second-line regimen compared with patients without a VL test. While this indicates that the VL test provides useful evidence to motivate health worker decisions to switch patients to second-line regimens, there remain gaps in timeliness of confirmatory testing and of regimen switching in Haiti. The delays in switching exceeded the timeframes described in the national ART guidelines for patient management. Fewer than half of patients who experienced confirmed VL failure switched to a second-line ART regimen within the 2 years following the confirmed failure. Such delays can increase the risk of developing high-level resistance to first-line ART, and of transmitting a resistant form of HIV to others.In theory, the broader use of VL testing should result in optimized HIV clinical management, with timely detection of unsuppressed VL, timely confirmation of VL failure, and timely switching to a second-line ART regimen in cases where ART adherence is strong and resistance is suspected. Our study found a mixed pattern where lack of confirmatory testing after unsuppressed VL results persisted through time, and timeliness of switching to second-line regimens also failed to improve markedly in recent ART cohorts. Confirmatory testing is necessary to determine effectiveness of enhanced adherence counseling and to inform clinical decisions about treatment options. Our findings suggest that use of confirmatory testing for VL failure and use of second-line regimens do not align with national guidelines. Even while expanding coverage of initial routine VL tests for ART monitoring, it is also important to prioritize repeat VL testing among those with unsuppressed results. Simply providing VL testing without being prepared to manage those with unsuppressed results is problematic. Indeed, Haiti has had underused stocks of second-line regimens available at the national level in the past . It is nThis study only included VL tests with results reported within the iSanté EMR system; some tests may have been done but without results returned to iSanté (reflecting a backlog of tests and results in Haiti’s reference laboratories). Our results cannot be taken as representative for all ART clinics in Haiti, since they exclude certain ART clinics from the GHESKIO and Partners in Health networks which did not use iSanté as well as 35 ART clinics using the iSanté data system but without current, reliable data saved to the central iSanté data repository. Exclusion of iSanté sites without reliable data may have biased our results. Weaknesses in routine clinical information systems may be associated with other health systems weaknesses , but we cannot know if bias extended to results related to HIV viral suppression.Other methods of monitoring effectiveness of ART using clinical or immunologic markers  were not considered in this study. Also, our study was not able to track patients who transferred care between health facilities or to detect cases where the same person may have been registered in the iSanté EMR using more than one patient identifier, meaning that our patient counts may have included duplicate records for the same person. Prior studies have estimated that the level of duplicate records within iSanté is approximately 8–10% , 39. OurThis study is the first to describe the routine uptake of VL test and its relationship to second-line ART regimen switching on a national scale in Haiti. The study included 66,042 patients from 88 sites from all regions of the country, accounting for around half of Haiti’s HIV patients over an almost 8 year period, meaning the results are meaningful in presenting a picture of national scale-up of VL testing and regimen switching. Based on these strengths, our study can inform policymakers and related stakeholders on key gaps, particularly the low rate of repeat VL testing after unsuppressed results and low rates of regimen switching, especially among women and among those who started ART at an early asympto-matic WHO stage. These gaps are important to address in order to reach the 95–95-95 goals for HIV epidemic control.Our study shows marked expansion of access to VL testing, especially since 2016, though still with half of patients not receiving an annual VL test. Clearly, VL monitoring will need to be increased to ensure achievement of 95–95-95 targets. Our study suggests use of second-line regimens changed little with time, and the lag in switching patients to second-line ART regimens remains a concern. Greater access to VL testing seems to have supported clinical decision-making about ART switching to some degree, but with progress still needed in order to achieve appropriate use of second-line regimens in Haiti. In the context of broadening access to VL testing overall, use of timely confirmatory VL testing is needed in order to guarantee that patients are placed on appropriate medication in cases of likely HIV drug resistance. To guarantee that HIV patients obtain effective treatment and avoid development of drug resistance, healthcare workers must be supported to ensure confirmatory testing and to take rapid action after confirmed VL failure, so that Haiti’s national ART monitoring guidelines move from theory to practice.


The accuracy calculated as the average Area Under the ROC (Receiver Operating Characteristic) Curve (AUC/ROC) for classifying exposure of the sequence to the HIV-1 protease inhibitors was 0.81 (±0.07), and for HIV-1 reverse transcriptase, it was 0.83 (±0.07). To predict cases of treatment effectiveness or failure, we used P1 and P0 values, obtained in PASS, along with the binary vector constructed based on short nucleotide descriptors and the applied random forest classifier. Average AUC/ROC prediction accuracy for the prediction of treatment effectiveness or failure for the combinations of HIV-1 protease inhibitors was 0.82 (±0.06) and of HIV-1 reverse transcriptase was 0.76 (±0.09).Human Immunodeficiency Virus Type 1 (HIV-1) infection is associated with high mortality if no therapy is provided. Currently, the treatment of an HIV-1 positive patient requires that several drugs should be taken simultaneously. The resistance of the virus to an antiretroviral drug may lead to treatment failure. Our approach focuses on predicting the exposure of a particular viral variant to an antiretroviral drug or drug combination. It also aims at the prediction of drug treatment success or failure. We utilized nucleotide sequences of HIV-1 encoding protease and reverse transcriptase to perform such types of prediction. The PASS (Prediction of Activity Spectra for Substances) algorithm based on the naive Bayesian classifier was used to make a prediction. We calculated the probability of whether a sequence belonged (P Human Immunodeficiency Virus Type 1 (HIV-1) causes acquired immunodeficiency syndrome (HIV/AIDS), a disease with severe complications, leading to death if no drugs are administered . A high We grouped HIV PR nucleotide sequences according to the following class types: (a) belonging to a viral variant exposed to certain drugs –“HIV PR treatment history dataset” and (b) the effectiveness of therapy by a combination of drugs–“The HIV PR combination dataset”.In our approach, we assumed that there was an association between the drugs that were prescribed and taken by the patient and changes in the nucleotide sequences of HIV-1 encoding viral proteins. In Classification Type (a), the set of the drugs taken by a patient was considered as a particular class regardless of whether they were taken sequentially or simultaneously. In Type (b), only combinations simultaneously taken by a patient were considered to be a class.The HIV PR treatment history dataset was used to predict associations between viral genotype and a set of drugs to which the virus was exposed. The prediction accuracy was identified through leave-one-out cross-validation (LOO CV) and fivefold CV. The corresponding AUC/ROC (Area Under ROC curve) values are given in We assumed that some mutations may occur in viral genes, resulting in higher viral fitness compared to wild-type HIV-1 when the virus is exposed to a particular drug . To check this hypothesis, we performed two computational experiments. First, we calculated the total number of isolates resistant to the drug in sets of sequences exposed to the same drug . Second, we calculated the Positive Predictive Value (PPV), the number of sequences exposed to the drug that displayed resistance to the same drug in the experiment testing (according to STDB) and were predicted to be exposed to the same drug by PASS in an LOO CV procedure. The results are provided in r = 0.735). Therefore, if exposure of a particular isolate was predicted by PASS to an antiretroviral drug, one could assume that this isolate could be resistant to that drug with a certain probability. Therefore, prediction of treatment history could be regarded as an additional method in the computational approach developed for the optimization of antiretroviral therapy, but it could not be the only method.There was an association between the prevalence of resistant samples among isolates (i) exposed to the drug according to STDB and (ii) exposed to the drug according to PASS prediction (Pearson correlation coefficient between Sets (i) and (ii), + cell number and viral RNA copies, nucleotide sequences encoding PR and RT, and the date when the sequence and clinical data were collected. Since nucleotide sequences in TCE are separately provided for PR inhibitors and RT inhibitors, we used information on PR sequences and PR inhibitors to build models for the viral effectiveness/treatment of PR inhibitors and performed the same for RT inhibitors. However, each TCE included PR inhibitors in combination with RT inhibitors; therefore, each patient took PR inhibitors along with RT inhibitors.The prediction of the effectiveness or failure of any treatment is based on the set of antiretroviral drug combinations taken by a patient and data on the sequencing of isolates collected from the patient’s blood plasma. The HIV PR combination dataset was used for prediction. For a prediction of treatment effectiveness/failure, we used the dataset of Treatment Change Episodes (TCE) from the STDB. Each file describing one TCE contained information about combinations of PR and RT inhibitors taken by a patient, clinical data on CD41 and P0 values reflecting the probability that a particular combination was associated with either therapeutic success or failure affecting the particular viral variant. P1 and P0 values, calculated by PASS in leave-one-out cross-validation, the number of CD4+ cells, and the number of copies of viral RNA were used as descriptors, as described in the Materials and Methods. Two types of antiretroviral therapy failure are considered in the literature [+ cells damaged by HIV-1 that do not exceed 250 cells per mm3 followed by clinical symptoms or below 100 cells in mm3 regardless of any changes in the clinical status of the HIV-1 patient. Virological failure of therapy occurs when the ART combination fails to suppress a patient’s viral load to fewer than 1000 copies of RNA per 1 mL. The prediction results of immunological treatment effectiveness/failure are provided in The PASS approach ,22,23,24terature . AccordiFor illustrative purposes, we investigated the frequency of mutations in the major drug resistance positions for PR inhibitors that were obtained from the STDB. We calculated the frequency of mutations for the subset of amino acid sequences of (i) resistant isolates and (ii) isolates selected as being associated with the treatment effectiveness/failure of a particular drug. The frequency distributions of a single amino acid substitution are given in 20 accuracy of the prediction of virological treatment effectiveness/failure for the combinations of HIV-1 PR inhibitors were 0.82 and 0.81, respectively. We provide detailed information about the combinations of drugs and corresponding accuracy in the The average AUC/ROC and AUC/ROC1 and P0 values and binary descriptors gave better average prediction performance compared to that of models built separately using either PASS or RF . Therefore, the combined application of RF models with probabilities calculated by PASS allowed for better recognition of the association between nucleotide sequence, clinical parameters, and immunological effectiveness/failure.Building models using an RF classifier based on the calculation of P20 values for the prediction of drug exposure were 0.828 and 0.80, respectively. The same values for the prediction of immunological effectiveness/failure of therapy were 0.71 (±0.01) and 0.70 (±0.01), respectively, and for virological effectiveness/failure of ART were 0.81 (±0.04) and 0.79 (±0.04), respectively. We provide detailed information about these accuracies in the We reproduced the experiments on the prediction of drug exposure and treatment effectiveness/failure for HIV-1 RT. Average AUC/ROC and AUC/ROCFrom the results of the prediction of drug exposure and effective/failed drug combinations, we could observe the association between nucleotide sequences encoding HIV-1 PR and a set of drugs taken by a patient with a prevalent isolate that was collected and subjected to sequencing. Although there was an association between drug exposure and drug resistance, average AUC/ROC values were about 0.81, while the standard AUC/ROC accuracy of classifying HIV variants into resistant and susceptible was above 0.90 . The folA. Pironti and coauthors  showed tSummarizing our observations, an approach that allows predicting drug treatment history can help physicians to decide at an early stage, which drugs should be taken by a patient who has a prevalent viral variant that might previously has been exposed to a particular drug or drug combinations.The average performance for predicting the effectiveness and failure of combinations for underrepresented combinations was lower than the predictive performance for viral resistance and sequence exposure to a single drug (AUC/ROC 0.79). We suggest several possible explanations for this observation. First, the dataset for the prediction of treatment history included over 10,000 samples, whereas the dataset for the prediction of treatment failure/effectiveness was much smaller (less than 1000 samples). Second, we assumed that each drug taken by a patient might affect viral fitness. Thus, changes in HIV-1 nucleotide sequences could be more considerable after a long duration of therapy, reflected in the dataset for the prediction of drug exposure (treatment history).+ cells was below 250 cells/mm3 during antiretroviral therapy . A drug combination was associated with virological failure of ART if the viral load was above 5000 copies/mL . There was some uncertainty in the determination of the thresholds of CD4+ cell counts in mm3 and the number of RNA copies in mL [1 and P0 values, nucleotide descriptors) led to decrease of prediction accuracy. Therefore, all types of descriptors used for prediction are essential for the prediction of both virological and immunological therapy failure/effectiveness of therapy.A combination of drugs was considered to be failed if the number of CD4es in mL ,27. HIV es in mL ,30,31,32Since for some schemes of ART AUC/ROC, the accuracy of prediction is lower than 0.80, we suggest a few strategies that might be helpful to improve the prediction accuracy of HIV/AIDS treatment effectiveness/failure. First, there is a need for a bigger collection of HIV/AIDS treatment schemes along with clinical data and a score reflecting patients’ adherence to treatment. Such collections can help researchers to perform their studies on HIV/AIDS treatment effectiveness/failure taking into account clinical data and adherence of a patient to the treatment. Second, probably the comorbidities of a patient should be taken into account when a prediction of HIV/AIDS treatment effectiveness/failure is performed.Contemporary research studies focus on the investigation of both HIV-1 and host factors to develop vaccines against HIV-1, which may represent the basis for the novel therapeutic approaches ,5,33. Wh+ count and viral load. Application of the computational models developed to predict HIV drug resistance, HIV treatment history, and virological and immunological therapy failure/effectiveness could be helpful in the optimization and personalization of antiretroviral therapy, which could be particularly important taking into account the toxicity and adverse effects [In summary, our computational experiments proved an association between viral genotype and treatment history of a particular viral isolate occurring in a patient or group of patients. It was possible to predict virological and immunological therapy failure/effectiveness based on the descriptors generated from a nucleotide sequence in combination with other descriptors, reflecting laboratory data and the clinical status of the patient, such as CD4 effects ,35,36 of+ cells as an indicator of therapy effectiveness. Each file with TCE usually contained some treatment episodes distinguished by the set of drugs. TCE data did not include information on the resistance to each drug and the complete list of drugs ever taken by a patient. We processed the data of the three types mentioned above  and virological and immunological treatment failure/effectiveness predicted for a particular HIV viral variant (based on the HIV PR combination dataset). We further summarized their description as types of association between sequence and clinical data.In our method, we used a modified naïve Bayesian classifier implemented in the PASS program ,21,24. B1 and P0 of the isolate to belong and not belong to class C, associated with clinical data. The details of the algorithm are given in the The prediction algorithm was described earlier in detail in the application to amino acid descriptors . In our 1 and P0 values calculated by PASS, the number of CD4+ cells, and the logarithmic value of viral RNA copies were added to the set of binary descriptors. The random forest classifier implemented in Weka 3.8.4 was used for building models.The random forest (RF) approach was applied in combination with the PASS approach, as described below. The binary descriptors for the random forest classifier were obtained based on nucleotide sequences, as described in . We geneWe presented an application of the PASS approach to the prediction of the treatment history of patients with HIV/AIDS based on nucleotide sequences of the HIV-1 isolate. The average AUC/ROC prediction accuracy was 0.81 (±0.07). We also demonstrated the combined application of PASS and random forest classifiers for the prediction of immunological and virological effectiveness/failure of antiretroviral therapy. The average AUC/ROC accuracy of this kind of prediction was 0.84 (±0.07). Prediction results of treatment history and effective/failed combinations based on computational methods could be helpful in HIV-1 therapy optimization.


To compare virologic and immunologic outcomes of integrase inhibitor (INSTI)-containing, contemporary boosted protease inhibitor (PI/b)-containing and non-nucleotide reverse transcriptase inhibitor (NNRTI)-containing regimens in a real-life setting.Using logistic regression, virologic and immunologic outcomes of INSTI use were compared to outcomes of PI/b or NNRTI treatment 12 months after treatment start or switch, for participants in the RESPOND cohort consortium. A composite treatment outcome (cTO) was used, defining success as viral load (VL) <200 copies/mL and failure as at least one of: VL ≥200 copies/mL, unknown VL in the time window, any changes of antiretroviral therapy (ART) regimen, AIDS, or death. In addition, on-treatment analysis including only individuals with known VL and no regimen changes was performed. Favorable immunologic response was defined as a 25% increase in CD4 count or as reaching ≥750 CD4 cells/μL.Between January 2012 and January 2019, 13,703 (33.0% ART-naïve) individuals were included, of whom 7,147 started/switched to a regimen with an INSTI, 3,102 to a PI/b and 3,454 to an NNRTI-containing regimen. The main reason for cTO failure in all treatment groups were changes in ART regimen. Compared to INSTIs, the adjusted odds ratio (aOR) of cTO success was significantly lower for PI/b , but similar for NNRTIs . On-treatment analysis and sensitivity analyses using a VL cut-off of 50 copies/mL were consistent. Compared to INSTIs, the aORs of a 25% increase in CD4 count were lower for NNRTIs  and PI/b .In this large analysis of a real-world population, cTO and on-treatment success were similar between INSTIs and NNRTIs, but lower for PI/b, though residual confounding cannot be fully excluded. Obtaining favorable immunologic outcomes were more likely for INSTIs than the other drug classes. Integrase inhibitors (INSTIs) have excelled in randomized clinical trials (RCTs) by showing potent and swift suppression of human immunodeficiency virus (HIV), good short-term drug safety and tolerability, and, for second generation INSTIs, high genetic barriers to resistance –7. In tuIn this study we analysed virologic and immunologic outcomes of INSTI-containing regimens compared to contemporary PI/b- and NNRTI-containing regimens within the large heterogenous RESPOND cohort consortium.https://chip.dk/Studies/RESPOND) was initiated in 2017 as an international collaboration between 17 pre-existing, prospective European and Australian based cohorts of HIV-1 positive participants  as defined in the European Union’s (EU) GCP Directive. All data supplied to RESPOND follows local or national guidelines as appropriate, and enrolled participants are pseudonymized by assignment of a unique identifier, by the participating cohort before data transfer. As data controller, the Coordinating Centre (CC) located within the Danish Capital Region of Copenhagen, Denmark, stores, shares and protects data in accordance with current legislation and under approval by The Danish Data Protection Agency , currently under the EU’s General Data Protection Regulation (EU) 2016/679.RESPOND is registered at Clinicaltrials.gov (Identifier: NCT04090151).For this specific analysis, we included ART-naïve and -experienced individuals, aged over 18 years who started or switched to an INSTI, PI/b or NNRTI-containing regimen with at least three antiretroviral drugs (ARVs). The eligible regimen was started between January 2012 and January 2019, and all included had a CD4 count and VL measured in the 12 months before or 3 months after treatment start/switch (baseline). Treatment-experienced individuals were naïve to the specific third agent they started when eligible for inclusion .All outcomes were assessed 12 months after baseline. The VL and CD4 count closest to this time were used, allowing a maximum time window of 3 months to either side (12±3 months).To estimate the durability of regimens, a composite treatment outcome (cTO) was used, defining treatment success as VL <200 copies(cp)/mL and failure as occurrence of at least one of either: VL ≥200 copies (cp)/mL, unknown VL in the time window, any ART regimen change, AIDS event, or death. Switching from a multi-tablet combination regimen to a single-tablet combination regimen including the same agents, or vice versa, was not considered as a regimen change. Conversely, switch to a two-drug regimen and/or any changes in individual regimen components were viewed as regimen changes .Sensitivity analyses tested the robustness of the cTO by excluding either individuals with unknown VL values within the time widow or those with any regimen change. Furthermore, an analysis which did not define changes in the NRTI backbone as a regimen change was performed.Additionally, the efficacy of the regimens to control HIV (VL <200 cp/mL) was estimated using on-treatment analysis, including only individuals with a known VL at 12±3 months and no regimen changes within the period.The use of a VL <200 cp/mL threshold for the cTO and on-treatment analysis followed a consensus agreement within the RESPOND virologic outcomes working group, reflecting differences in the sensitivity of VL assays available in different cohorts. Sensitivity analyses using a VL <50 cp/mL threshold were also performed.A favorable immunologic response was defined as a 25% increase in CD4 count from baseline. As individuals with high CD4 counts at baseline would presumably have lower odds of reaching such an increase, we also defined a favorable immunologic response as reaching CD4 count ≥750 cells/μL (excluding those with CD4 count ≥750 cells/μL at baseline), following the rationale described in earlier work by Mocroft et al. .To ascertain if there were any variations in outcomes depending on treatment status at baseline, outcomes were determined for three pre-specified sub-groups: ART-naïve individuals, ART-experienced individuals switching to a new ART-regimen with ongoing viremia (≥200 cp/mL), and ART-experienced individuals switching to a new ART-regimen with virologic control (<200 cp/mL). Given the heterogeneity of the populations, tests for interactions between ART-experience and treatment status at baseline for each outcome were planned a priori.2 P-values for categorical variables. For continuous variables, data were presented as medians and interquartile ranges (IQR), with P-values from the Wilcoxon-Mann-Whitney test.Descriptive statistics were summarized as frequencies and proportions with χVirologic and immunologic outcomes for individuals starting/switching to an INSTI -containing regimen were compared to participants starting/switching to a PI/b (ritonavir- or cobicistat-boosted darunavir or atazanavir)-containing or NNRTI (rilpivirine or efavirenz)-containing regimen, using separate logistic regression models.Factors considered for multivariable analyses included demographics  and region of origin, categorized as West Central Europe , South Europe and Argentina , North Europe and Australia , East Central Europe  and East Europe . Other variables included HIV-related factors , hepatitis B and C coinfection, cardiovascular risk factors  and other non-AIDS events . All factors included in the models were decided a priori. Full lists of variables included in the specific multivariate models are shown in the figure legends.As some cohorts did not have complete data on comorbidities, it was not possible to adjust for both cohort and comorbidities in the same analyses, due to the risk of collinearity. Therefore, our main analyses focused on adjusting for comorbidities as listed above, while acknowledging that there was some missing data. Sensitivity analyses adjusting for cohort rather than comorbidities were also performed.th January 2014 (the date dolutegravir was licensed in Europe) were performed.Finally, sensitivity analyses restricted to ART-naïve individuals starting treatment after 16All analyses were performed using SAS  version 9.4., all tests of significance were 2-sided with p<0.05 used for statistical significance and all confidence intervals (CI) were 95%.In total, 13,703 participants were included . Of thes2, and comorbidities such as hypertension, diabetes, chronic kidney disease and prior cardiovascular disease, was found in the INSTI group compared the other two treatment groups. All p-values for all comparison of baseline characteristics between treatment groups were < 0.001.Overall, 75.3% of those included were of male sex, with men who have sex with men (MSM) being the most common route of HIV acquisition 46.1%; . The mosThe crude proportion of cTO success was lowest in the PI/b group, while being fairly similar between the INSTI and NNRTI groups  were included in the on-treatment analyses . The crude proportion of individuals achieving success was higher in the INSTI and NNRTI groups than in the PI/b group  individuals had CD4 measurements available after 12±3 months . The crude proportion of individuals achieving a 25% increase in CD4 count from baseline was lowest for individuals on INSTIs compared to individuals on PI/b or NNRTIs  had a CD4 count <750 cells/μL at baseline and could be assessed for achieving a CD4 count ≥750 cells/μL. The crude proportion reaching this level was higher in the INSTI group than in both the PI/b and NNRTI groups  –22, shorBoth cTO and on-treatment analysis revealed a lower likelihood of virologic control for individuals treated with a PI/b compared to an INSTI, as has previously been described , 23, 24.The proportions of individuals with unknown VL within the 12±3 months time window were relatively high for all three drug classes and without inter-class difference, as also reflected by the consistent results when excluding unknown VL from the cTO. While current recommendations suggest that VL should be measured at least every twelve months for individuals on stable ART, and more frequently following regimen switches –11, it iAs this is an observational study, we cannot with certainty determine whether the lack of VL measurements was a consequence of data not being reported to RESPOND, or of tests not being performed locally within the time period. However, quality assessments are performed as RESPOND data is electronically transferred from all participating sites , 25, andWe saw only a very small difference in the likelihood of a 25% increase in CD4 count between INSTIs and PI/b, and no difference in the likelihood of achieving ≥750 CD4 cells/μL between the two ARV classes, consistent with prior reports , 7. SimiAlthough the differences found between drug classes were minor, the potential effect on ongoing inflammation and longer-term disease progression is to date not known. Therefore, it will be imperative to observe if these differences will be associated with more frequent adverse outcomes over longer periods of time.Although there was some evidence suggesting that reaching a CD4 count ≥750 cells/μL differed slightly according to ART status and level of viremia at baseline, we saw no evidence of a subgroup effect on any of the other outcomes, and the results should be interpreted accordingly with multiple testing in mind. Specifically, for the assessment of outcomes for ART-experienced individuals with VL ≥200 cp/mL at baseline, it should be noted, that due to the comparatively lower resistances barrier of NNRTIs, clinicians may be reluctant to prescribe this drug class to ART-experienced individuals with ongoing viremia, likely reflected in the low number of individuals on NNRTIs in this stratum.Overall, these findings suggest that INSTIs can safely be used regardless of treatment status and history at treatment initiation, though more studies with comprehensive data on resistance testing is still needed.Interactions between high VL, low CD4 counts and age with virologic and immunologic outcomes have been investigated in another RESPOND analysis, where no differences were seen between these individuals treated with INSTIs, PI/b and NNRTIs .There are some study limitations to acknowledge. Firstly, our study is observational in nature, and although our analyses included adjustment for a wide range of potential confounders, and several sensitivity and subgroup analyses were performed, residual confounding can never be fully excluded, and our results should be interpreted accordingly. In particular, RESPOND does not systematically collect data on ARV-resistance nor HIV-subtypes, which can affect treatment choice, especially in the strata of ART-experienced individuals with VL ≥200 cp/mL at baseline.Secondly, as we wanted to ensure adequate power to reliably analyse outcomes and perform predefined subgroup analyses and test for potential interactions, we focused on class effects rather than on individual ARVs. Therefore, it is possible that there may be some intra-class differences not accounted for here. Finally, our analyses were restricted to a 12 months period, and we therefore cannot make any statements on longer-term outcomes. Longer follow-up on individual ARVs is required to allow for individual comparisons, as well as assessment of longer term clinical outcomes including serious non-AIDS clinical events.In conclusion, this large, real-world based analysis of a heterogeneous population of PLWH seen in routine clinical care, showed that treatment with INSTI and NNRTI-containing regimes was preferable to PI/b with regard to virologic outcomes, although the potential for residual confounding cannot be fully excluded. Favorable immunologic responses were more likely with INSTI-containing regimens than with NNRTI-containing regimens, and to a lesser degree with PI/b-containing regimens. Crude numbers did not reveal any major differences in the occurrence of AIDS or death. These data supports the use of INSTI treatment and suggest that 12 months efficacy and durability of INSTIs are independent of prior treatment status and on-going viremia.S1 TableAll percentages are column percentages. The proportion of individuals with unknown/missing data were (%): Mode of transmission 6.8; ethnicity 11.8; hepatitis B 16.8; hepatitis C 13.8; BMI 29.5; smoking status 39.0; hypertension 28.9; diabetes 8.5; cardiovascular disease 26.3; chronic kidney disease 19.2. Regions: West Central Europe: Austria, Belgium, France, Germany, Luxembourg, Switzerland; South Europe and Argentina: Argentina, Greece, Israel, Italy, Portugal, Spain; North Europe and Australia: Australia, Denmark, Norway, Sweden, Finland, Iceland, Ireland, Netherlands, United Kingdom; East Central Europe: Bosnia-Herzegovina, Croatia, Czech Republic, Hungary, Poland, Romania, Serbia, Slovenia, Slovakia; Eastern Europe: Belarus, Estonia, Georgia, Latvia, Lithuania, Russia, Ukraine. Hypertension: Defined as use of antihypertensive drugs, systolic blood pressure >140 mmHg and/or diastolic blood pressure >90 mmHg. Diabetes: A clinical diagnosis of diabetes, use of antidiabetic drugs and/or blood glucose measurement ≥11.1 mmol/l or HbA1C ≥48 mmol/mol. HCV Positive: Positive if ever had a positive HCV antibody test, HCV RNA test, HCV genotype, or received HCV treatment prior to baseline. HBV positive: Hepatitis B surface antigen positive. Chronic kidney disease: Defined as confirmed (>3 months apart) eGFR ≤ 60 ml/min/1.73 m2, calculated by the CKD-EPI formula. Cardiovascular disease includes prior myocardial infarction, stroke or invasive cardiovascular procedure. *Among ART-experienced. Abbreviations: 3TC, lamivudine; ABC, abacavir; ART, anti-retroviral therapy; ARV, anti-retroviral drug; BMI, body-mass index; cp, copies of RNA; FTC, emtricitabine; IDU, intravenous drug user; MSM, men who have sex with men; NRTI, nucleos(t)ide reverse transcriptase inhibitor; TDF: tenofovir disoproxil fumarate; TAF: tenofovir alafenamide; VL, viral load. All p-values for comparisons were < 0.001.(PDF)Click here for additional data file.S2 Table*cTO success defined as a VL <200 cp/mL. in individuals without failure . **persons with known VL at 12±3 months without regimen changes . ***persons with known CD4 counts at 12±3 months . ****persons with known CD4 counts at 12±3 months excluding persons with ≥750 CD4 cells/μL at baseline .(PDF)Click here for additional data file.S3 Table*cTO failure was defined as at least one of: VL ≥200 cp/mL, unknown VL, any antiretroviral treatment (ART)-regimen change, AIDS, or death (note that it is possible to fail more than one parameter). ** number of specific reasons for cTO failure. ***persons with known VL at 12±3 months without regimen changes.(PDF)Click here for additional data file.S1 Fig*persons with known VL at 12±3 months, without regimen changes. Numbers above each column indicate the total number of the specific reasons for cTO failure overall, and for each of the treatment groups . Numbers in the bars indicate percent of total. The table below the bars shows the numbers individuals with each specific reason for cTO failure by treatment group, stratified by treatment status at baseline. Note that individuals could fail the cTO outcome for more than one reasons.(TIF)Click here for additional data file.S2 Figth January 2014. 5: aOR of cTO success defined as in 1, model adjusted for cohort instead of comorbidities. 6: aOR of cTO success defined as a VL <200 cp/mL in individuals without failure . 7: aOR of cTO success defined as a VL <200 cp/mL in individuals without failure ; not defining changes in NRTI backbone as an ART regimen change. 8: aOR of cTO defined as a VL <200 cp/mL in individuals without failure .Multivariable models were adjusted for age (per ten years older), ethnicity, mode of transmission, baseline date (per year later), smoking status, hypertension, diabetes, prior AIDS event- cardiovascular disease, chronic kidney disease, end stage liver disease, non-AIDS-defining malignancies and fractures, HBV and HCV status, viral load , CD4 count , treatment regimen and number of drugs in regimen. 1: aOR of cTO success defined as a VL <200 cp/mL. in individuals without failure . 2: aOR of cTO success defined as in 1, at 6±3 months after baseline. 3 aOR of cTO success defined as in 1, restricted to individuals initiating or shifting to one of the study regimens after 16th January 2014. 4 aOR of cTO success defined as in 1, restricted to ART-naïve individuals initiating one of the study regimens after 16(TIF)Click here for additional data file.S1 Appendix(PDF)Click here for additional data file.


Combination antiretroviral therapy (cART) has markedly increased survival and quality of life in people living with HIV. With the advent of new treatment options, including single-tablet regimens, durability and efficacy of first-line cART regimens are evolving.We analyzed data from the prospective multicenter German Clinical Surveillance of HIV Disease (ClinSurv) cohort of the Robert-Koch Institute. Kaplan–Meier and Cox proportional hazards models were run to examine the factors associated with treatment modification. Recovery after treatment initiation was analyzed comparing pre-cART viral load and CD4+ T-cell counts with follow-up data.n = 7040; 80.1%), of whom 4470 (63.5%) were reporting sex with men as the transmission risk factor. Overall, 4210 (47.9%) patients modified their first-line cART after a median time of 63 months (IQR 59–66). Regimens containing integrase strand transfer inhibitors (INSTI) were associated with significantly lower rates of treatment modification  compared to protease inhibitor (PI)-based regimens. We found a decreased durability of first-line cART significantly associated with being female, a low CD4+ T-cell count, cART initiation in the later period (2011–2017), being on a multi-tablet regimen (MTR).We included 8788 patients who initiated cART between 2005 and 2017. The sample population was predominantly male (Drug class and MTRs are significantly associated with treatment modification. INSTI-based regimens showed to be superior compared to PI-based regimens in terms of durability.The online version of this article (10.1007/s15010-020-01469-6) contains supplementary material, which is available to authorized users. Combination antiretroviral therapy (cART) has improved markedly over the past decades. Today, people living with HIV (PLWH) can mostly be treated with safe and well-tolerated cART leading to a long-term suppression of viremia , which rWhile several of these factors are conclusive and have been proven by different cohort studies, most of these studies have been done before the introduction of integrase strand transfer inhibitors (INSTI). The first INSTI, raltegravir (RAL), was approved by the Food and Drug Administration (FDA) in 2007 . It was Therefore, we examined the durability of different first-line cART regimens and characteristics of those who modified first-line cART in a real-world setting. We also aimed to describe the characteristics of those who achieved viral suppression after cART initiation, as found in the national German Clinical Surveillance of HIV Disease Cohort (ClinSurv) in Germany between 2005 and 2017.This study was planned and conducted by the academic and public sector researchers of the University Hospital of Cologne and German Center for Infection Research. We conducted a retrospective analysis of PLWH enrolled in the German national ClinSurv HIV cohort of the Robert Koch Institute (RKI), an ongoing, long-term observational multicenter cohort initiated in 1999. Details of the ClinSurv HIV cohort have been published previously . In briePLWH enrolled in ClinSurv from January 2005 through June 2017 were eligible for our analysis if they initiated their first-line therapy during this time period, were older than 18 years, and had both, an available pre-cART CD4+ T-cell count and viral load, yielding 8788 participants. Patients who received their first-line treatment in the setting of a clinical study were excluded from this analysis.The first endpoint was defined as the date when the first-line drug class was changed to another class during follow-up. Modification was not counted if individuals alternated the dosage or used other drugs within the same drug class or if they interrupted the first-line drug class. The second outcome was defined as immunological recovery after 12 months of first-line treatment. Patients were censored if they died during the study period, failed to follow-up, or reached the end of the observation period before experiencing the endpoint. The epidemiological trends were evaluated between 2005 and 2017 (date of starting the respective cART). Moreover, we compared an early period (2005–2010) and late period (2011–2017), with the latter representing the period in which current INSTI regimens and STRs become available.Baseline characteristics of included patients were reported as absolute numbers with percentage and median with interquartile range (IQR), as appropriate. Patients were compared during the period 2005–2010 (early period) and 2011–2017 (late period), using the Chi-square test.p > 0.2 to reach the simplest model that explained the data. Our final multivariable model was adjusted for sex, transmission risk group, pre-cART CD4+ T-cell count and viral load, first-line drug class, antiretroviral drugs that were included in the first-line regimen , the tablet regimen (single versus multi tablet regimen), and the period of cART initiation (2005–2010 and 2011–2017). Hazard ratio (HR) and adjusted hazard ratio (aHR) with 95% confidence intervals (CI) were reported to measure the strength and association between variables.We analyzed two different outcomes. First, we examined the durability of the first-line regimen, defined as switching the first-line cART drug class. Second, we analyzed viral suppression after cART initiation, defined as achieving low or undetectable plasma HIV RNA (< 200 copies/mL) after 12 months (± 6 months). The Kaplan–Meier (KM) method was used to examine factors independently associated with the durability of first-line cART. Differences between subgroups were compared by the log-rank test. The presence of multicollinearity problems was assessed among the explanatory variables using the Tolerance and Variance Inflating Factor . A multiP values of < 0.05 were considered statistically significant. All analyses were compiled using STATA .We further analyzed immunological recovery after first-line initiation. Pre-cART viral load and CD4+ T-cell count were compared to the closest measurement of month 12 (± 6 months). The RKI is the national public health institute and is responsible for disease prevention and control in Germany. The Federal Commissioner for Data Protection is the responsible entity for studies conducted by the RKI. All HIV infections are reported to the RKI as a statutory duty for anonymous notification, implemented by the national Protection against Infection Act. The data collected in the ClinSurv cohort are generated during routine care. In this scenario, no informed consent or permission for secondary analysis of the anonymized data was required. This study was performed in accordance with the Declaration of Helsinki.n = 7040; 80.1%). Among male patients, 4470 (63.5%) reported sex with men (MSM) as the main transmission risk factor. In the total study population, the median pretreatment CD4+ T-cell count was 241 cells/µL (IQR 111–369 cells/µL), and 39.6% of patients had a CD4+ T-cell count below 200 cells/µL. The median pretreatment HIV RNA was 65,000 copies/mL , and 38.9% of patients had a pretreatment viral load greater than 100,000 copies/mL. A total of 338 (3.8%) patients died over the observation period, of whom 177 (52.4%) were on a PI-based regimen, 105 (31.1%) on a nucleotide reverse-transcriptase inhibitor (NRTI)/non-nucleotide reverse-transcriptase inhibitor (NNRTI) regimen, and 22 (10.1%) on an INSTI-based regimen.Between January 2005 and June 2017, a total of 8788 PLWH met the inclusion criteria and were eligible for our analyses . Baseline characteristics are presented in Table n = 1734/8788; 19.7%) and TDF/FTC/DRV/r . Within the early period of 2005–2010, TDF/FTC/EFV accounted for almost one third  of all prescribed cARTs, while TDF/FTC/DRV/r  was the most frequent cART during the late period of 2011–2017. Most of the common first-line drug class combinations were NRTI/PI/boosted , NRTI/NNRTI , and NRTI/INSTI , shown in Table The most common prescribed first-line cART regimens were TDF/FTC/EFV (p = 0.002) (Table S1).During 44,439 patient-years of follow-up and a median follow-up time of 3.83 years (IQR 1.30–7.81) per patient, the overall rate of first-line cART modification was 25 per 100 person-years. In total, 4210 (47.9%) patients modified their first-line therapy during follow-up. The median durability was 63 months (IQR 59–66), and was significantly longer in the early period compared to the late period  patients. The most commonly reported causes in men and women were side effects of drugs 792/3597 (22.0%), simplification of therapy 394/3597 (11.0%), patients’ choice 267/3597 (7.4%), decision of the responsible physician 259/3597 (7.2%), non-adherence 212/3597 (5.9%), comorbidities 136/3597 (3.8%), and virological failure 133/3597 (3.7%). Among women, side effects of drugs 152/588 (25.9%), patients’ choice 75/588 (12.8%), simplification of therapy 70/588 (11.9%), and pregnancy 51/588 (8.7%) were the most common causes to modify first-line therapy.Physicians’ choice to modify first-line therapy was reported in 4.9% (128/1609) of patients during the early period and increased to 8.1% (131/2601) during the late period. The percentage of patients who modified first-line cART due to the simplification of therapy was lower in the early period than in the late period .p < 0.001). A total of 31.3% (1084/3464) switched from a non-INSTI towards an INSTI-based regimen, the proportion increased from 24.6% (564/2297) to 44.6%  comparing the early to the late period.Of the 4210 patients who modified their first-line cART, 21.5% (701/3259) switched from a MTR to a STR. The proportion increased from 19.4% (384/1981) in the early period to 24.8% (317/1278) during the late period (p < 0.001), different drug classes (p < 0.001), and the year of cART initiation (p = 0.002). The median durability of the first-line regimen was significantly shorter in patients on MTR than in patients on STR  (Table S1). KM analyses also revealed an increasing trend of first-line cART modification with a lower pre-cART CD4+ T-cell count (< 350 µL) (p < 0.001). These differences remained significant in the adjusted multivariable Cox regression model.Time-to-event analyses revealed prognostic factors to modify the first-line regimen, illustrated in the KM plots in Fig. Women were more likely to modify the first-line regimen than men . Patients on a STR were significantly less likely to modify the first-line regimen compared to patients on an MTR . In addition, the frequency of tablet intake twice daily compared to once daily was significantly associated with treatment modification . We found that being on a NRTI/NNRTI  or a NRTI/INSTI  first-line regimen was associated with lower rates of modification, compared to being on a NRTI/PI/boosted first-line regimen. Modification of first-line regimen increased in the late period (2011–2017) compared to the early period (2005–2010)  . However, the transmission risk group did not remain significant in the adjusted multivariable Cox regression model, and INSTI regimens were excluded due to multicollinearity. Uni-and multivariable analyses were also performed separately for the early and late period. Details are displayed in supplementary table S2–S4.Among patients with an available HIV-1 RNA assessment at month 12 (± 6 months), 5745/6089 (95.4%) achieved viral suppression (< 200 copies/mL).p = 0.013). In the whole group, the median decrease in viral load after 12 months on cART was 3.4 log copies/mL (IQR 2.8–4.0 log copies/mL) and was greater in those who remained on their first-line cART than in patients who modified the initial treatment . The overall pre-cART CD4+ T-cell count increased with a median gain of 205 cells/µL (IQR 180–374 cells/µL) at month 12 (± 6 months), a relative increase of 84%. No differences were observed between individuals who remained on their first-line regimen compared to those who modified their first-line regimen (p = 0.843).Pre-cART viral load was significantly higher in patients who modified their first-line cART regimen within 12 months (± 6 months)  than in patients who remained on their first-line regimen , and tablet intake more than once a day.The significant difference in sex, as well as in people presenting with low pre-cART CD4+ T-cell count, may be related to non-adherence that is more frequently seen in female PLWH and individuals originating from sub-Saharan Africa, as well as in late presenters . In our Interestingly, in our study, there was no tendency towards a better durability of first-line therapy in recent years as it was found by other studies , 8. The Most subjects, especially in the early period, received PI-based cART regimens, which showed a higher risk for first-line modification compared to NNRTI- or INSTI-based regimens. These results are in line with previous studies, showing an inferiority of PI-based regimens compared to NNRTI- or INSTI-based regimens in terms of treatment , 23. ThiOnce-daily regimens, especially those with an STR, showed a better durability of the first-line treatment, as also shown in other studies , 24, 25.From 2014 onwards, INSTI-based regimens already accounted for the majority of initial treatments resulting in a maximum of 86% in the year 2017. We found a higher risk for modification on RAL compared to EVG and DTG, mainly due to therapy simplification, which is comparable to previous studies , 28. FurOur study had a couple of limitations. First, these are retrospective, “real-life” data predominantly clinical HIV centers, which occupy a key position in outpatient care in the German health care system. In our analysis, patients had a median age of 38 years and were predominantly men (80.1%), of which about one third (63.5%) reported to be MSM. These baseline characteristics did not change notably over time comparing the early period of 2005–2010 with the late period of 2011–2017. Thus, while our study was limited to PLWH in Germany, the characteristics of patients starting their first-line antiretroviral treatment compare very well with those reported in other cohorts in the USA, France, and Australia and, therefore, seem to be representative for PLWH seen in outpatient clinics in industrialized countries . Second,In conclusion, overall efficacy of first-line treatment was good, with 95.4% achieving viral suppression 1 year after starting cART. Amongst the different classes, INSTI-based regimens showed superiority in terms of durability. Thus, our data confirm the rationale of the current guidelines that recommend INSTI-based regimens as first-line treatment in HIV-infected patients. However, future studies are required to assess the efficacy and durability of these treatments over a longer period. Recent studies observed high modification rates of INSTIs, in particular for DTG, due to adverse events and weight gain , 30.We elucidated several factors that were significantly associated with the modification of first-line regimens. The modification rates were higher during the late period, particularly among women, and in patients on an MTR. Patients at higher risk for treatment modification might require more frequent follow-up visits and better monitoring during their first-line cART regimen.Supplementary material 1 (DOCX 179 kb)Supplementary material 2 (DOCX 36 kb)Below is the link to the electronic supplementary material.