Switch strategies based on rilpivirine/tenofovir/emtricitabine or on an integrase inhibitor (InSTI) plus tenofovir/emtricitabine have never been compared in randomized clinical trials. The main aim of the study was to investigate the durability of these two switch regimens in virologically suppressed, HIV-infected patients.Retrospective analysis of patients who started rilpivirine or an InSTI (both with tenofovir and emtricitabine) with <50 HIV-RNA copies/mL and had at least one HIV-RNA assessed while receiving the study regimen. Virological failure (VF) was defined as two consecutive measurements of HIV-RNA >50 copies/mL. Treatment failure (TF) was define as either VF or discontinuation of any drug of the regimen. Durability was assessed by the Kaplan-Meier method and compared by Log-rank test. Residual viremia was defined as any detectable HIV-RNA below 50 copies/mL, as assed by a real-time PCR assay.Six hundred seventy-five patients . The proportion of time spent with residual viremia was comparable in the two groups .The median  follow-up in the rilpivirine and in the InSTI group was 16.7 (8.8–22.2) and 10.4 (5.4–19.6) months. The 1-year cumulative probabilities (95%CI) of VF and TF were 0.97% (0.36%–2.62%) and 9.73% (7.21%–13.06%) in the rilpivirine group and 1.83% (0.57%–5.77%) and 8.75% (5.25%–14.4%) in the InSTI group, with no difference between groups (p = 0.018), baseline total/HDL-cholesterol ratio , baseline estimated glomerular filtration rate  and baseline hemoglobin , but not with treatment group (rilpivirine vs. InSTI).By the multivariable Cox regression model, TF was independently associated with being on therapy with a protease inhibitor vs. a non-nucleoside reverse transcriptase inhibitor at switch  contains supplementary material, which is available to authorized users. Randomized clinical trials support the switch both to the fixed dose combination (FDC) of rilpivirine/tenofovir disoproxil fumarate/emtricitabine from a ritonavir-boosted protease inhibitor (PI/r) and to regimens based on integrase strand transfer inhibitors (InSTI) from any kind of antiretroviral therapy. In the SPIRIT Study switching from a regimen based on a PI/r to the FDC of rilpivirine/tenofovir/emtricitabine was not inferior to continuing the PI/r, with virological success in 93,7% and 89,9% of patients at 48 weeks . Non-infHowever, these switch strategies have never been compared in randomized clinical trials and it is very unlikely that such a trial will be performed.The aim of this study was two-fold: first, we aimed at identifying factors associated with the choice of a FDC of rilpivirine/tenofovir/emtricitabine vs. an InSTI-based switch regimen; secondly, we aimed at investigating the durability of rilpivirine/tenofovir/emtricitabine and of InSTI-based switch regimens  in virologically suppressed HIV-infected patients in clinical practice.Retrospective cohort study on patients followed at the Infectious Diseases Department of the San Raffaele Scientific Hospital in Milan . Data recorded in the database of the Infectious Diseases Department of the San Raffaele Hospital (IDD-HSR) were used for the analyses. At their first visit in our clinic, subjects provide written informed consent to include their clinical and laboratory data in the IDD-HSR for scientific purposes. The study was approved by the ethics committee of the San Raffaele Scientific Institute.Eligible patients were those who started rilpivirine or an InSTI  with <50 HIV-RNA copies/mL and had at least one HIV-RNA assessed while receiving the study regimen. Patients who switched to one of the study regimens since 2008  were included in the analyses. Patients were followed up to virological failure (VF) or discontinuation of any drug or data freezing (8th September 2015), whichever occurred first.Estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration Equation (CKD-EPI)  and the HIV-RNA was quantified by using the kinetic PCR molecular system  up to March 2014 and by using the Abbot Real-Time PCR  thereafter. The kPCR assay gives three possible outputs: (i) a quantitative result for HIV-RNA values of ≥37 copies/mL; (ii) a semiquantitative result (detectable below 37 copies/mL) when HIV RNA is detectable but not precisely quantifiable; (iii) a qualitative result (‘undetectable’) when no signal can be detected. The Abbot Real-Time PCR assay gives also three possible outputs: (i) a quantitative result for HIV RNA values of ≥40 copies/mL; (ii) a semiquantitative result (detectable below 40 copies/mL) when HIV RNA is detectable but not precisely quantifiable; (iii) a qualitative result (‘undetectable’) when no signal can be detected.VF was defined as two consecutive measurements of HIV-RNA >50 copies/mL or a single HIV-RNA >50 copies/mL followed by ART modification; an unconfirmed HIV-RNA >50 copies/mL (i.e. one measurement >50 copies/mL preceded and followed by a measurement <50 copies/mL), not followed by ART modification, was defined as viral blip. Residual viremia was defined as any detectable HIV-RNA below 50 copies/mL, as assed by Siemens kPCR or by Abbot Real-Time PCR.t is the time length of interval i, j is the last observation and ttot is the patient’s cumulative follow-up. If, during the ith interval, viremia changed from undetectable to residual or vice-versa, then a = 2, else a = 1.Time spent with residual viremia was calculated as a proportion of time with residual viremia on observed follow-up. If between 2 observation the viremia changed from undetectable to residual or vice-versa, the time spent considered in this interval was the half. The mathematical formula was:Treatment failure (TF) was define as either VF or discontinuation (for any length) of any drug of the regimen, for any reason. Causes of change in the regimen were reviewed independently by two clinicians; discordances were discussed and reconciled.Descriptive data are expressed as median (interquatile range) of frequency (%), as appropriate.Chi-square and Mann-Whitney tests were used to evaluate differences between the two groups for categorical and continuous variables respectively. Durability was assessed by the Kaplan-Meier curve and compared by Log-rank test. Multivariable logistic regression was used to identify predictors of opting for an InSTI- rather than a rilpivirine-based regimen and a multivariable Cox regression model was used to identify factors independently associated with TF.All of the statistical tests were two-sided at 5% level, and were performed using SAS Software .Six hundred seventy-five patients , on antiretroviral therapy since 6.6 [3.3–14.1] years and with HIV-RNA <50 copies/mL since 3.1 [1.1–5.6] years, were included in the analysis; their baseline characteristics are illustrated in Table p = 0.015), with longer exposure to antiretroviral therapy  and shorter time with undetectable viremia , treated with protease inhibitors (PIs) vs NNRTIs , and treated with regimens not based on a PI/r and not based on a NNRTI vs those treated with NNRTIs .After adjusting for age, gender, HIV risk factor, higher HIV-RNA value before starting ART, nadir and baseline CD4+ count, baseline triglycerides and cholesterol, history of failure to nucleoside reverse transcriptase inhibitors (NRTIs) or to non-NRTIs (NNRTIs), opting for an InSTI- rather than a rilpivirine-based regimen was more likely in subjects co-infected with HCV  follow-up in the rilpivirine and in the InSTI group was 16.7 8.8–22.2) and 10.4 (5.4–19.6) months. Four (0.9%) and three (1.4%) patients showed VF at 1 year in the rilpivirine and in the InSTI group; cumulatively, 12 patients (8 [1.7%] in the rilpivirine and 4 [1.9%] in the InSTI group) showed VF during follow-up: their characteristics at VF are detailed in Table 2.2 and 1p = 0.988).The incidence rate (IR) (95%CI) of viral blips was 4.46 (3.07–6.27) and 4.48 (2.51–7.40) per 1000 person months of follow-up in the rilpivirine and in the InSTI group (p = 0.087).The proportion of time spent with residual viremia was comparable in the two groups  and 41/209 (19.6%) patients in the rilpivirine and in the InSTI group discontinued at least one drug of the regimen for any reason. Discontinuations were due to toxicity in 34 (7%) and in 17 (8%) patients in the rilpivirine and in the InSTI group. Of the 51 discontinuations occurred because of toxicity, 28 (55%) were deemed tenofovir toxicity (15 [3.2%] and 13 [6.2%] in the rilpivirine and in the InSTI group); other leading causes of discontinuation were non-tenofovir related toxicity or untoward drug interactions (19 [4.1%] and 4 [1.9%] in the rilpivirine and in the InSTI group) and treatment simplification (none and 12 [5.7%] in the rilpivirine and in the InSTI group).Non-tenofovir related toxicities leading to discontinuation were: liver toxicity in 9 (2%), gastrointestinal toxicity in 5 (1%), central nervous system toxicity in 4 (1%) and undefined toxicity in one further patient in the rilpivirine group, liver toxicity in 1 (<1%) and central nervous system toxicity in 1 (<1%) in the InSTI group. Three (1.5%) patients in the InSTI group discontinued for untoward drug interactions.Of note, discontinuations occurred in 37/82 (45%) patients who started raltegravir; 27 of these 37 patients (73%) discontinued only raltegravir; the main reason for raltegravir discontinuation was treatment simplification (12/27 [44%]).p = 0.018), baseline total/HDL-cholesterol ratio , baseline eGFR  and baseline hemoglobin , whereas treatment group (rilpivirine vs. InSTI), HCV-coinfection, nadir and baseline CD4+ cell count, time with HIV-RNA <50 copies/mL, time spent with residual viremia, years of antiretroviral therapy, failure to NRTIs, failure to NNRTIs, failure to PIs, triglycerides and FIB-4 were not. No violation of the proportional hazard assumption was detected using graphical representation (Log-log plot).By the multivariable Cox regression model, TF was independently associated with being on therapy with a PI vs. a NNRTI at switch  –13, to tMajor limitations of this study are the lack of randomization and the fact that the patients switched to rilpivirine/tenofovir disoproxil fumarate/emtricitabine were different from those switched to an InSTI in many baseline clinical features; however, after adjustment for these differences, the multivariable analysis confirmed that switching to a regimen rather than the other was not independently associated to TF.In our clinical practice, the durability of switch regimens based on rilpivirine and on InSTI  was comparable and both showed a very low probability of VF.


The three most commonly used nNRTIs are nevirapine (NVP), efavirenz (EFV) and rilpivirine (RPV). This study aimed to determine the incidences of hepatotoxicity and skin rashes within 4 weeks of initiation of cART containing 1 nNRTI plus 2 NRTIs.Two nucleos 2014 was used for reporting clinical and laboratory adverse events.During the 3.5-year study period, 2,341 patients initiated nNRTI-containing cART: NVP in 629 patients, EFV 1,363 patients, and RPV 349 patients. Rash of any grade occurred in 14.1% (n = 331) of the patients. In multiple logistic regression analysis, baseline CD4 cell counts  and use of NVP  (compared with efavirenz) were independently associated with the development of skin rashes. Among the 1,455 patients (62.2%) with aminotransferase data both at baseline and week 4, 72 (4.9%) developed grade 2 or greater hepatotoxicity. In multiple logistic regression analysis, presence of antibody for hepatitis C virus (HCV)  or hepatitis B surface antigen , and development of skin rashes  were independently associated with the development of hepatotoxicity.The baseline CD4 cell counts and use of NVP were associated with increased risk of skin rashes, while hepatotoxicity was independently associated with HCV or hepatitis B virus coinfection, and development of skin rashes in antiretroviral-naïve HIV-positive Taiwanese patients within 4 weeks of initiation of nNRTI-containing regimens. Other ttor (PI)  and virator (PI) .The antiretroviral regimens containing the first-generation nNRTIs, EFV and NVP, have been shown to be efficacious and safety in different populations , 8. In pThe frequency of elevation of liver enzymes in patients on EFV-containing regimens ranges from 1 to 8% –20, wherThe second-generation nNRTIs, RPV, has demonstrated antiviral efficacy similar to that of EFV in antiretroviral-naïve adults with baseline plasma HIV RNA load (PVL) ≦100,000 copies/ml over 96 weeks in phase 3 clinical trials (ECHO and THRIVE) –29. CompIn Taiwan, the three most commonly used nNRTIs among antiretroviral-naive patients are NVP, EFV, and RPV. A higher prevalence of chronic viral hepatitis B or C among HIV-positive patients in Taiwan , 31 and This retrospective observational study was conducted at 8 designated hospitals for HIV care around Taiwan . We included all HIV-positive patients aged 20 years or greater who were antiretroviral-naive and initiated nNRTI-containing cART between 1 June, 2012 and 31 November 2015. All patients were followed until 31 January, 2016, death or loss to follow-up, whichever occurred first. The study was approved by the research ethics committee of each participating hospital and informed consent was waived.HIV care, including cART and monitoring of CD4 cell count and PVL, has been provided free-of-charge since cART became available in Taiwan in April 1997. Due to financial constraints on the provision of free-of-charge access to cART, the Centers of Disease Controls (CDC) in Taiwan implemented regulations on the prescription of cART to antiretroviral-naive HIV-positive patients who received their first-line cART on 1 June 2012. Four categories of cART were defined: the first category consisted of NVP, RPV or EFV plus zidovudine/lamivudine (coformulated); the second category, NVP or EFV plus abacavir/lamivudine (coformulated); or TDF/emtricitabine (coformulated) or TDF and lamivudine; the third category, zidovudine/lamivudine plus protease inhibitors (PIs) or raltegravir; and the fourth category, TDF/emtricitabine, TDF and lamivudine, or abacavir/lamivudine plus PIs or raltegravir. Patients could start antiretroviral regimens in the first three categories, but initiation of regimens in the fourth category required approval before prescription. Raltegravir was not available in clinical use for antiretroviral-experienced patients until 2009; and in 2012, it was available for antiretroviral-naïve patients to be combined with 2 NRTIs. RPV was not available until January 2014. In patients with chronic HBV infection, TDF-containing regimens were recommended and RPV was recommended only for patients with baseline PVL <100,000 copies/ml.Before initiation of cART, baseline assessment included hemogram, CD4 count, PVL, serologic markers of syphilis and hepatitis A, B, and C viruses, urinalysis, and serum biochemistry, including total bilirubin, alanine aminotransferase (ALT), aspartate aminotransferase (AST) and lipid profiles. Transmitted drug resistance mutations of HIV-1 to NRTIs, nNRTIs, PIs, and INSTIs were not routinely determined before cART was initiated; genotypic resistance testing was only performed retrospectively for the purposes of surveillance , 35.After initiation of cART, patients were mandatorily enrolled in case management program implemented by Taiwan CDC and patients were usually seen 2 weeks after initiation of cART to assess the adverse effects and tolerability of the regimens prescribed. Aminotransferases and hemogram were determined. Patients returned for reassessment of virological and immunological responses and adverse effects at week 4 of cART, and subsequently every 8 to 12 weeks. At these visits, physical examination was performed and PVL, CD4 cell count, serum chemistries, including total bilirubin, AST, ALT, and lipid profiles, were determined to assess the clinical and laboratory adverse events. A standardized case record form was used to collect information on demographic and clinical characteristics and immunological and virological responses.We assessed the incidence of skin rashes within 4 weeks of cART initiation. Hepatotoxicity grading was based on ALT and AST levels, which was defined in accordance with the Division of AIDS Table for Grading the Severity of Adult and Pediatric Adverse Events (DAIDS AE Grading Table) , in the HCV infection was defined as presence of antibodies for HCV, while hepatitis B virus (HBV) infection was defined as presence of HBV surface antigen (HBsAg).2 test and continuous variables were compared using Student’s t test. A P-value of <0.05 was considered statistically significant. All P values were two-tailed. Variables with P<0.10 or those of biological significance in the univariate analyses were entered into a multivariate logistic analyses. Association between hepatotoxicity and skin rash and clinical characteristics were assessed in logistic regression analysis. Variables included in these analyses were age, gender, HIV risk group, baseline CD4 cell count, baseline PVL, and baseline AST and ALT. Statistical analyses were performed using SAS software (Version 9.3).Categorical variables were analyzed by using X10 copies/mL, most of the patients initiated cART late with a mean CD4 count 279 cells/μl and only 29.8% initiated cART with a baseline CD4 count of 350 cells/μl or greater (data not shown). HBsAg was determined in 2,291 patients (97.9%) with 275 (12.0%) testing positive, while anti-HCV antibody was determined in 2,286 patients (97.7%) with 437 (19.1%) testing positive.A total of 2,341 antiretroviral-naïve patients started cART between June 2012 and November 2015; 629 patients received NVP plus 2 NRTIs, 1,363 patients EFV plus 2 NRTIs, and 349 patients RPV plus 2 NRTIs. Their baseline demographic and clinical characteristics are shown in 10 copies/ml) and higher CD4 count .Not unexpectedly, clinical characteristics differed significantly among the patients initiating cART with 3 different regimens consisting of nNRTIs plus 2 NRTIs because of the regulations on prescription of the first-line antiretroviral therapy in antiretroviral-naïve patients, a higher prevalence of chronic HBV infection that required cART containing TDF, and injection drug users who often had low PVL and higher CD4 counts at baseline than other risk groups owing to infections with defective HIV-1 subtype CRF 07_BC in Taiwan . TherefoWithin the first 4 weeks of cART, the percentage of patients who discontinued nNRTIs due to any adverse events was 55.4%. Of the patients discontinuing nNRTIs, 67.1% were due to skin rash, 23.2% due to neuropsychiatric symptoms, 5.6% due to gastrointestinal upset, 5.3% due to hepatitis, and 1.1% due to depression.P = 0002). Of the 149 patients who received NVP with skin rash, the proportions of HBV coinfection did not differ between those who discontinued and those who continued NVP , and neither did the proportions of HCV coinfection . Likewise, of the 180 patients who received EFV with rash, the proportions of HBV coinfection did not differ between those who discontinued and those who continued EFV , and neither did the proportions of HCV coinfection  (data not shown).Within 4 weeks of cART, rash of any grade occurred in 331 (14.1%) of the patients: 149 (23.7%) in NVP group, 180 (13.2%) in EFV group, and 2 (0.6%) in RPV group. The mean interval between initiation of cART and development of skin rashes was longer for the NVP group than EFV group , while those who initiated RPV plus 2 NRTIs had a lower risk. In multiple logistic regression analysis among patients who received NVP or EFV, we found a higher baseline CD4 cell counts  and use of NVP plus 2 NRTIs  were independently associated with the development of skin rashes (n rashes .P = 0.05) and age (P = 0.04) were associated with developing skin rashes in univariate analysis (data not shown), while in multiple logistic regression analysis, we were not able to identify any factor statistically significantly associated with developing skin rashes. In EFV group, developing skin rashes was associated with older age (P = 0.02) and baseline CD4 cell count≧350 cells/μl (P = 0.004) in univariate analysis (data not shown). In multiple logistic regression analysis, only baseline CD4 cell count ≧350 cells/μl  was independently associated with the development of skin rashes.For each of nNRTI-containing regimen, the results of multivariate analysis of associated factors with skin rashes are shown in Baseline aminotransferase levels available for patients initiating EFV-, NVP-, and RPV-containing regimens are shown in Of the 24 patients who received NVP with hepatotoxicity, the proportions of HBV coinfection did not differ between those who discontinued and those who continued NVP , and neither did the proportions of HCV coinfection . Of the 37 patients who received EFV with hepatotoxicity, the proportions of HBV coinfection did not differ between those who discontinued and those who continued EFV , and neither did the proportions of HCV coinfection  (data not shown).P = 0.0038), anti-HCV positivity (P<0.0001), HBsAg positivity (P = 0.0007), and development of skin rashes within 4 weeks of cART (P = 0.0008) were associated with hepatotoxicity of grade 2 or greater. In multiple logistic regression analysis, anti-HCV positivity , the development of skin rash  and HBsAg positivity  were independently associated with the development of hepatotoxicity , HBsAg positivity (P = 0.04) and development of skin rash within 4 weeks of cART (P<0.001) were associated with hepatotoxicity of grade 2 or greater. In multiple logistic regression analysis, a higher baseline CD4 cell count  and development of skin rashes  were independently associated with the development of hepatotoxicity.The results of multivariate analysis for each nNRTI-containing regimen are shown in P = 0.02), anti-HCV-positivity (P = 0.02), and HBsAg positivity (P = 0.02) were associated with hepatotoxicity of grade 2 or greater. In multiple logistic regression analysis , we found that that older age  or agents that might cause hepatotoxicity or skin rashes  . Third, In conclusion, our study among a large treatment-naive HIV-positive population receving nNRTI- containing regimens in Taiwan reveals that the overall rate of hepatotoxicity within 4 weeks of cART initiation was low (4.9%). HCV or HBV coinfection and development of skin rash were independently associated with the development of hepatotoxicity, whereas higher baseline CD4 counts and use of NVP were independently associated with skin rashes within 4 weeks of cART initiation.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S1 Data(XLSX)Click here for additional data file.


In 2010 South Africa revised its HIV treatment guidelines to allow the initiation and management of patients on antiretroviral therapy (ART) by nurses, rather than solely doctors, under a program called NIMART . We compared the outcomes and costs of NIMART between the two major public sector HIV treatment delivery models in use in South Africa today, primary health clinics and hospital-based HIV clinics.The study was conducted at one hospital-based outpatient HIV clinic and one primary health clinic (PHC) in Gauteng Province. A retrospective cohort of adult patients initiated on ART at the PHC was propensity-score matched to patients initiated at the hospital outpatient clinic. Each patient was assigned a 12-month outcome of alive and in care or died/lost to follow up. Costs were estimated from the provider perspective for the 12 months after ART initiation. The proportion of patients alive and in care at 12 months did not differ between the PHC (76.5%) and the hospital-based site (74.2%). The average annual cost per patient alive and in care at 12 months after ART initiation was significantly lower at the PHC (US$238) than at the hospital outpatient clinic (US$428).Initiating and managing ART patients at PHCs under NIMART is producing equally good outcomes as hospital-based HIV clinic care at much lower cost. Evolution of hospital-based clinics into referral facilities that serve complicated patients, while investing most program expansion resources into PHCs, may be a preferred strategy for achieving treatment coverage targets. With over 2.6 million people on HIV treatment, South Africa has had unprecedented success in rolling out its public sector antiretroviral therapy (ART) program. DespiteWhen the South African national antiretroviral therapy (ART) program began in 2004, it relied primarily on hospital-based HIV clinics with services delivered by doctors , 6 underNIMART shifted the focus of the South African treatment program from doctors to nurses and from hospitals to PHCs, increasing the number of accredited ART delivery facilities sites from 496 to 4333 . With thWhile several studies have examined outcomes of task shifting and decentralization in South Africa –24, few The study was conducted at one hospital-based outpatient HIV treatment clinic and one primary health clinic. Both sites are situated in the same municipality  in West Rand District of Gauteng Province, South Africa. The district was one of the early adopters of NIMART across all its facilities. The two sites are seven kilometers apart and serve similar populations.The hospital-based HIV clinic is a large regional hospital hereafter referred to as the ‘HIV outpatient clinic’. As of March 2014 it had 4,396 patients actively on ART and saw an average of 1,956 ART patients per month. It originally provided ART initiation and management by doctors, with nurse support for screening and monitoring. With the introduction of NIMART, responsibility for these services was progressively shifted to nurses. During the study period, the HIV outpatient clinic had one dedicated, full time doctor and sixteen nurses (including enrolled nurse assistants and managers).The primary health clinic (PHC), hereafter referred to as “the PHC”, had as of March 2014 1,958 patients actively on ART and saw approximately of 884 HIV patients for ART pickup in March 2014, which was roughly 11% of the patient load. As of January 2012, HIV was fully integrated into general chronic disease care at the site. During the study period (2012) it had fifteen clinical staff (nurses and a doctor) serving all patients seeking care at the clinic for all conditions.3). Viral load is not routinely performed at initiation and could therefore not be included as a matching variable. We used propensity score matching without replacement [We constructed a retrospective cohort of adult (≥18 years) patients initiated on ART at the PHC and matched them to patients initiated at the HIV outpatient clinic. To be included in the cohort, patients had to have at least 15 months of potential follow up as of the date of data collection, not have transferred to another site during their first year after initiation, having initiated after 1 January 2011 (NIMART policy in place) and have a complete patient record available for review. Data collection commenced on 15 January 2014 at the PHC and 1 March 2014 at the HIV outpatient clinic, resulting in the cohorts including patients initiated prior to 15 October 2013 and 1 December 2013 at the PHC and HIV outpatient clinic respectively. At the PHC we enrolled the first 260 patients based on date of initiation who met these inclusion criteria. These patients were then matched to hospital outpatient clinic patients 1:3 on gender, age at initiation , baseline ART regimen, and baseline CD4 count  at the HIV outpatient clinic. Study data collectors extracted data from the paper files at the primary health clinic and site staff routinely captured the data found in Tier.net and the Therapy Edge datasets. All three of these sources contained only routinely collected data. Fields collected for the first 12 months following ART initiation for each patient included baseline CD4 count, date of ART initiation, resource usage , and outcome at 12 months. CD4 count and viral load results up to 15 months were also collected to assign 12-month outcomes. All patient level data were collected using a study specific database designed and managed in CS Pro .Clinical data were collected from paper files and the national electronic HIV register (Tier.net) at the primary health clinic and from a separate electronic patient record .Each patient was assigned a single primary, 12-month outcome of either “alive and in care” or “died / lost to follow-up (LTFU)”. If a patient died before 12 months or was >3 months late for their last scheduled visit within the 12-month follow up period (lost to follow-up) then the patient was assigned to the outcome “died / LTFU”. All other patients were considered “alive and in care”. Secondary outcomes based on virologic and immunologic status were also assigned. Patients with a viral load ≥ 1,000 copies/mmThrough sensitivity analysis, we investigated the effect of missing paper files excluded at the PHC (no patients were excluded at the HIV outpatient clinic because of missing files). Data on age, gender, baseline CD4 count, and 12-month primary outcome were collected from Tier.net for patients with missing files, where possible. In the sensitivity analysis, all primary health clinic patients were then matched on age, gender and baseline CD4 count to the hospital outpatient clinic and outcomes were compared. The data available on Tier.net were not sufficient to extract resource utilization and calculate costs. The analytic cohort therefore only included patients who had a paper patient file at the primary health clinic.Costs were estimated from the provider perspective for the 12 months after ART initiation using standard costing methods, as outlined in The study protocol was reviewed by the Institutional Review Boards of the University of Witwatersrand and Boston University, who approved the collection of the data without informed consent and the use of an anonymous analytic dataset.3 (122–269 cells/mm3)) than those included (162 cells/mm3 (87–257 cells/mm3)).Sample selection is outlined in 3 (IQR: 69.5–239.5 cells/mm3); two thirds were female. Most patients were initiated on a baseline regimen of lamivudine and tenofovir with either efavirenz (83%) or nevirapine (8%). There were no important differences in sample characteristics between the two sites.Characteristics of the sample are described in The primary and secondary outcomes are presented in Costs by site, outcome, and cost category are presented in The average cost per patient initiated on ART over the 12 months following initiation was significantly lower at the PHC ($213) than at the HIV outpatient clinic ($342). This finding of lower costs at the PHC held for all outcomes and remained valid even when the longer duration of care for those ultimately not in care was taken into account: $20 v. $36 per month at the PHC and HIV outpatient clinic, respectively, for patients in care and $13 v. $33 per month for patients not in care. The cost per month in care was calculated by dividing the total average cost per patient  by the aIn this analysis of outcomes and costs of providing antiretroviral therapy under South Africa’s two major models of service delivery, we found that both models achieved similar proportions of patients alive and in care 12 months after initiation, but the primary health clinic model cost substantially less per patient treated, despite providing more months of patient care overall. This cost difference is due largely to the higher staff and infrastructure costs incurred in a hospital-based clinic, and reflect the fact that ART patients rarely require the more specialized services and equipment available at a hospital.Other studies in South Africa have consistently found that decentralization to PHCs from centralized clinics and task shifting to nurses produce favorable or equivalent results for patients , 21, 24.Shifting ART responsibilities from doctors to nurses has occurred to varying degrees across all treatment facilities in South Africa. At PHCs, nurses provide nearly all HIV services, with only occasional referral, and HIV care is largely integrated with other primary health care. HIV outpatient clinics at hospitals remain stand-alone services with relatively significant doctor involvement, with NIMART trained nurses working alongside but not always replacing doctors. We found that this staffing mix, which also affects patient volume and the efficiency of staff time use, is one of the two main causes of the high cost of HIV outpatient clinics . The importance of the staff complement suggests that a re-allocation of responsibilities, with complicated patients  referred to hospital-based HIV clinics and the vast majority of uncomplicated patients initiated and managed at PHCs. Supporting this recommendation, a study of the NIMART rollout in the City of Johannesburg found that NIMART increased ART initiations at PHCs and reduced them at hospital-based HIV clinics, allowing the hospital clinics to focus on more difficult cases .Although we estimated both costs and effectiveness of the two models of ART delivery, our study was not designed as a cost-effectiveness analysis (CEA), as we do not believe that a choice can be made between the two models. In view of the vast demand for HIV treatment in South Africa, both models will continue to be required for years to come. The information we report will help support efficient allocation of patients between facilities, decisions about future expansion of treatment capacity, and planning and budgeting.This study had a number of limitations, most of which are common to retrospective, observational cohort studies. Most important, the study was limited to a single pair of sites in one province, which limits geographic generalizability. The study sites are, however, public sector treatment facilities following the national treatment guidelines, and are thus likely to be typical of the public sector in other provinces in South Africa, if not of other countries. Although we matched our samples carefully using a rigorous matching algorithm, moreover, unobserved differences between the samples may bias our estimates. With small samples and limited covariates its possible that although individual patients were matched on their p-score some residual confounding may remain. Our results are dependent on the accuracy and completeness of routinely collected patient records, which may also have varied by site. Finally, despite our access to relatively recent data, the rapid pace of change of national and global treatment guidelines makes it nearly impossible for research to “keep up” with the current treatment landscape.In spite of these limitations, we conclude that initiating and managing ART patients at primary health clinics under South Africa’s NIMART policy is producing equally good outcomes as hospital-based HIV outpatient clinic care at much lower cost. Evolution of the country’s hospital-based clinics into well-resourced, centralized, expert referral facilities that focus on complicated patients, while investing program expansion resources into PHCs, may thus be the country’s preferred strategy. There are currently no widely-utilized guidelines for how to triage patients between routine PHC care and specialized HIV clinic care. Developing guidance in this area may thus be a priority for policy makers.While our findings should support the continued expansion of NIMART, we conclude by noting that the impact of the program on non-HIV care must also be considered. So far, nurses appear to have incorporated HIV care into their workloads smoothly, but there is no evidence to suggest how much additional capacity remains on the system or that the addition of HIV care has not been to the detriment of other patients. While we have looked specifically at the provider costs of ART, a full evaluation of the NIMART program—and of similar decentralizing and task-shifting initiatives in other countries—should take into account both the impact of the program on non-HIV care and its benefits and costs to patients themselves.S1 Fig(PDF)Click here for additional data file.


Criteria for the 2007 WHO algorithm for diagnosing tuberculosis among HIV-infected seriously ill patients are the presence of one or more danger signs  and cough ≥ 14 days. Determining predictors of poor outcomes among HIV-infected inpatients presenting with WHO danger signs could result in improved treatment and diagnostic algorithms.We conducted a prospective cohort study of inpatients presenting with any duration of cough and WHO danger signs to two regional hospitals in Cape Town, South Africa. The primary outcome was all-cause mortality up to 56 days post-discharge, and the secondary outcome a composite of any one of: hospital admission for > 7 days, died in hospital, transfer to a tertiary level or tuberculosis hospital. We first assessed the WHO danger signs as predictors of poor outcomes, then assessed the added value of other variables selected a priori for their ability to predict mortality in common respiratory opportunistic infections , being on antiretroviral therapy (ART), hypotension, and confusion) by comparing the receiver operating characteristic (ROC) area under the curve (AUC) of the two multivariate models.484 participants were enrolled, median age 36, 66% women, 53% had tuberculosis confirmed on culture. The 56-day mortality was 13.2%. Inability to walk unaided, low BMI, low CD4 count, and being on ART were independently associated with poor outcomes. The multivariate model of the WHO danger signs showed a ROC AUC of 0.649 (95% CI 0.582–0.717) for predicting 56-day mortality, which improved to ROC AUC of 0.740  with the multivariate model including the a priori selected variables. Findings were similar in sub-analyses of participants with culture-positive tuberculosis and with cough duration ≥ 14 days.The study design prevented a rigorous evaluation of the prognostic value of the WHO danger signs. Our prognostic model could result in improved algorithms, but needs to be validated.The online version of this article (10.1186/s12981-018-0192-0) contains supplementary material, which is available to authorized users. Undiagnosed tuberculosis is a major cause of death among hospitalised HIV-infected patients in Africa , 2. The Pneumocystis jirovecii pneumonia (PJP), bacterial pneumonia, and tuberculosis. Most reports of prognostic indicators for PJP include laboratory tests, pulmonary function tests, and/or sophisticated imaging that are not widely available in resource-limited settings. Simple predictors of mortality in PJP include wasting, hypoxia, hypotension, and lymphopenia [We were unable to find any studies that evaluated predictors of poor outcomes in the WHO algorithm for seriously ill patients. Many studies have evaluated predictors of mortality of the three commonest respiratory opportunistic infections in HIV-infected patients: phopenia , 6. The phopenia –9. CRB-6phopenia . Most ofphopenia .We assessed the WHO danger signs together with other prognostic variables selected for their ability to predict mortality in HIV-associated respiratory illness  as predictors of mortality and poor outcomes in participants fulfilling entry criteria for the WHO algorithm for seriously ill HIV-infected patients with a cough enrolled into a prospective cohort study in Cape Town, South Africa. We enrolled participants with cough of any duration, rather than the WHO recommendation of 2 weeks or more, because studies in high burden countries have shown that acute presentations of pulmonary tuberculosis occur commonly in HIV-infected patients , 13. We We conducted a prospective cohort study. The study sites were two regional hospitals serving communities with a high burden of HIV and tuberculosis in Cape Town, South Africa: GF Jooste Hospital from November 2011 to February 2013, when the hospital closed; and Khayelitsha District Hospital from March 2013 until October 2014. Inclusion criteria were: known or newly diagnosed HIV infection, within 24 h of hospital admission, ≥ 18 years of age, cough of any duration, and at least one of the WHO danger signs. Exclusion criteria were: being on anti-tuberculosis therapy, having completed anti-tuberculosis therapy in the previous month, defaulting anti-tuberculosis therapy within the past 6 months, exacerbations of congestive cardiac failure or chronic obstructive pulmonary disease, and inability to produce a spontaneous or induced sputum sample. After discharge from hospital, participants were followed up at 28 and 56 days. Follow up was either a physical visit to hospital or a telephonic consult to assess their clinical response and outcome. During the study period the CD4 criterion for ART initiation was < 350 cells/uL.® specimen bottle).Participants enrolled into the study received a standardized work-up to assess the aetiology of their respiratory illness. A standard case record form was used for capturing demographic data, medical history, symptoms, and signs on clinical examination. All participants had a chest radiograph on admission. CD4 counts were done on admission unless a result was available within 6 months prior to admission. Sputum samples were taken from all participants: 1 sample for Gram stain, culture and sensitivity; and 2 samples for smear examination with auramine staining for acid-fast bacilli (AFB) and mycobacterial culture. On 1 sample sent for mycobacterial culture the Cepheid Xpert MTB/RIF assay was performed. If participants were unable to produce sputum spontaneously, sputum induction was performed using an ultrasonic nebulizer and hypertonic saline. Participants had blood taken for a mycobacterial blood culture ; and/or radiological criteria ; and/or or pleural effusions/ascites showing a lymphocytic exudate. Anti-tuberculosis therapy was also commenced if participants showed no clinical improvement after 3–5 days of antibiotic therapy.The diagnosis of bacterial pneumonia was made clinically with consistent symptoms and evidence of pulmonary consolidation on a chest x-ray. Participants clinically diagnosed with bacterial pneumonia were started on empirical antibiotic therapy with a ß-lactam antibiotic . A macrolide was added if participants fulfilled the criteria for severe pneumonia (CRB-65 score > 2) .PJP was diagnosed if the following were present: cough duration ≤ 12 weeks, bilateral interstitial infiltrates on chest radiograph, and hypoxia at rest or on exertion (> 5% drop in oxygen saturation). Weight based high dose trimethoprim-sulfamethoxazole and corticosteroid therapy were initiated in these participants.The primary outcome was all-cause mortality from admission to 56 days post-discharge. The secondary outcome was a composite of any one of: hospital admission for > 7 days, died in hospital, transfer to a tertiary level hospital, or transfer to a tuberculosis hospital. In Cape Town patients with tuberculosis are only admitted to tuberculosis hospitals if they are too ill for ambulatory care (unless they have extensively drug-resistant tuberculosis), therefore admission to a tuberculosis hospital reflects need for prolonged hospitalisation.Analyses were performed using STATA 12.1 . Missing data were imputed using chained equations and five iterations. We checked the results of the imputation by comparing a complete case analysis with the imputation set.Multivariate logistic regression analysis was performed including variables in the multivariate models selected a priori for their ability to predict mortality in common respiratory opportunistic infections and their implementability in resource-limited settings. We first investigated the primary outcome of all-cause mortality within the 56 days of follow-up post-discharge. We tested two multivariate models for this outcome: the WHO multivariate model (variables were the WHO danger signs); and the augmented multivariate model , being on ART, hypotension (systolic blood pressure < 90 mmHg or diastolic blood pressure ≤ 60 mmHg), and confusion). We compared the area under the curve (AUC) for the receiver-operating characteristic (ROC) of the two models. We then investigated the composite secondary outcome in a similar manner. A sub-analysis on all participants with culture positive tuberculosis was performed using the same approach for each of the specified outcomes.Two thousand and fifty-four patients were screened for inclusion into the study; 484of whom met the inclusion criteria and were enrolled Fig. . The basThe WHO multivariate model showed that being unable to walk unaided was the only WHO danger sign that was independently associated with death at 56 days post-discharge Table . A sub-aMycobacterium tuberculosis culture-positive patients, showed that none of the WHO danger signs independently predicted death at 56 days post-discharge , and 4 were failing ART with a viral load (VL) of > 1000 RNA copies/mL. In this sub-analysis of culture confirmed tuberculosis the WHO model showed a ROC AUC of 0.604 (95% CI 0.503–0.705) for predicting death at 56 days post-discharge. The augmented model showed an improved ROC AUC of 0.748   Fig. b. Study The WHO multivariate model showed that being unable to walk unaided was the only danger sign that was independently associated with the secondary outcome  Table . The augA sub-analysis of the WHO multivariate model among culture-positive tuberculosis participants, showed that being unable to walk unaided was the only WHO danger sign that independently predicted the secondary outcome  improved the ability to predict poor outcomes. The high prevalence of tuberculosis in our cohort enabled us to also assess prognostic predictors in participants with culture-positive tuberculosis, with similar findings. To our knowledge ours is the first study to have evaluated the prognostic ability of the WHO danger signs, as well as other potential predictors, in the population of interest and in the sub-group with a final diagnosis of tuberculosis. In 2016 WHO updated the seriously ill algorithm to include the Xpert MTB/RIF assay and cough of any duration, [The strong associations we found between being unable to walk unaided and the primary and secondary outcomes in our cohort indicate that this WHO danger sign is a simple, objective prognostic marker. The association between poor outcomes and both low CD4 counts and BMI was expected, as these are well-established prognostic markers in HIV infection , 17–20. Among the culture-positive tuberculosis participants, being unable to walk unaided, low BMI, low CD4 count, and being on ART remained strong prognostic indicators of poor outcomes. Most studies that assessed predictors of mortality among HIV-infected tuberculosis participants have been retrospective observational cohorts and evaluated outcomes at 6 months. We could not find any studies of inpatients that assessed predictors of 56-day mortality or poor outcome. Some of the independent predictors of poor outcomes in patients with HIV-associated tuberculosis from other studies include: age, , 23 sex,Being on ART independently predicted death at 56 days post-discharge in the whole cohort, as well as among culture positive tuberculosis participants, which was an unexpected finding. Two studies reported a similar result to our findings, with increased mortality among patients who started ART within 3 months  and 6 moOur study has several limitations. First, we were unable to determine the cause of death in our participants. Second, all our participants had one or more WHO danger signs, and the lack of a control group without danger signs limited our ability to determine the prognostic value of the danger signs. Third, we did not have definitive reference standards to diagnose bacterial pneumonia and PJP. Finally, our cohort was from a setting with high prevalence of both HIV and tuberculosis. Our findings may not be generalizable to areas with lower incidence of tuberculosis or to children.In conclusion, we assessed prognostic indicators of respiratory illness in our prospective cohort of HIV-infected participants presenting with a cough of any duration and WHO danger signs. We established that being unable to walk unaided, low BMI, and low CD4 count were strong predictors of morbidity and mortality. These findings were similar among culture-positive tuberculosis patients. The increased mortality we observed in participants on ART is an important determinant to keep in mind when assessing acute respiratory illness in HIV-infected patients. Future research should focus on filling these gaps and validating our results in different study populations.Additional file 1. Additional figures and tables.


P < .001). However, the increased risk was greatly attenuated in analyses adjusting for demographic and clinical factors . There were no differences between subtypes C and subtypes non-B and non-C in either univariate or multivariate analysis. These observations imply there is no intrinsic effect of viral subtype on the efficacy of tenofovir-containing regimens.Concern has been expressed that tenofovir-containing regimens may have reduced effectiveness in the treatment of human immunodeficiency virus type 1 (HIV-1) subtype C infections because of a propensity for these viruses to develop a key tenofovir-associated resistance mutation. We evaluated whether subtype influenced rates of virological failure in a cohort of 8746 patients from the United Kingdom who received a standard tenofovir-containing first-line regimen and were followed for a median of 3.3 years. In unadjusted analyses, the rate of failure was approximately 2-fold higher among patients infected with subtype C virus as compared to those with subtype B virus (hazard ratio [HR], 1.86; 95% confidence interval [CI], 1.50–2.31;  Human immunodeficiency virus type 1 (HIV-1) subtype C viruses have a predisposition to develop the K65R mutation in reverse transcriptase, an observation first reported in cell culture experiments . The likData on the relationship between viral subtype and response to antiretroviral therapy are surprisingly limited, although 2 recent studies reported a higher rate of virological failure associated with subtype C infection , 10. Herhttp://www.ukchic.org.uk) collates routinely collected data on HIV-infected patients who have attended ≥1 of the collaborating clinics since 1 January 1996. Patients were eligible for the present analysis if they initiated a first-line regimen that contained tenofovir, plus lamivudine or emtricitabine, and either a nonnucleoside reverse transcriptase inhibitor (efavirenz or nevirapine) or a ritonavir-boosted protease inhibitor . In addition, they were required to have sufficient follow-up to potentially meet the criteria for virological failure—this was defined as the first of 2 consecutive viral loads (<6 months apart) of >200 copies/mL after 6 months of antiretroviral therapy. Follow-up was censored at the earlier of the last viral load measurement or the discontinuation of tenofovir, ignoring changes in the prescription of other antiretroviral drugs. Viral subtype was generated from linked pol gene sequences collated by the UK HIV Drug Resistance Database (available at: http://www.hivrdb.org.uk), using the Rega subtyping tool (version 3) [The UK Collaborative HIV Cohort Study (available at: rsion 3) , and grorsion 3) , we comp+ T-cell count, and date of initiation of antiretroviral therapy), year of diagnosis, and region of birth . The imputation models included all covariates included in the analysis model  had a determined subtype: 4123 had subtype B, 823 had subtype C, and 1203 had non-B/C subtypes. The most common non-B/C subtypes were A (n = 272), CRF02_AG (n = 267), G (n = 118), CRF01_AE (n = 114), other CRFs (n = 90), and D (n = 80). Baseline characteristics are shown in Table The 2597 patients without a resistance test were assigned, averaging over imputations, to subtype B (n = 1342), subtype C (n = 632), and non-B/C subtypes (n = 623). This resulted in total (average) sample sizes of 5465, 1455, and 1826, respectively. The proportionate increase in sample size, relative to those with known subtype, was greatest for subtype C (77%), lowest for subtype B (33%), and intermediate for subtype non-B/C (52%), reflecting variation in the availability of resistance tests by demographic and clinical characteristics associated with viral subtype.A and Table P < .001), whereas there was no difference compared with subtype non-B/C . The estimated cumulative risk of virological failure at 5 years was 7.5%  for subtype B, 13.1%  for subtype C, and 12.8%  for subtype non-B/C . Adjustment for demographic and clinical factors had a marked effect on the comparison of subtypes B and C . The comparison between subtype non-B/C and subtype C remained relatively unchanged . Adjusted Kaplan–Meier curves of the time to virological failure confirmed the lack of association with viral subtype, after accounting for potential confounders . Similar relationships between subtypes were observed in a sensitivity analysis of the complete case data (Supplementary Table 1).Patients were followed up for a median of 3.3 years . On average, 309 (5.7%) of subtype B–infected patients, 142 (9.8%) of subtype C–infected patients, and 173 (9.5%) of non-B/C subtype–infected patients experienced virological failure .We explored the reasons for the change in the estimated effect of subtype between unadjusted and adjusted analyses by fitting a series of models containing various combinations of the various factors. The most influential factors were exposure group  and ethnicity . Antiretroviral regimens that included an NNRTI (particularly efavirenz) were significantly more durable than regimens that included a boosted PI, although this may due to channeling bias, rather than an intrinsic pharmacological effect . NonlineP = .003).Genotypic resistance tests were available for 260 of 624 patients (41.7%) who experienced virological failure Table . TenofovIn the present study patients infected with HIV-1 subtype C viruses who were receiving a first-line tenofovir-containing regimen experienced a higher rate of virological failure than patients infected with subtype B viruses. However, this effect was almost entirely explained by differences between the groups in demographic and clinical characteristics, particularly exposure group and ethnicity, possibly related to differential nonadherence . Also, tAlthough several studies have previously examined the association between viral subtype and response to therapy, all included a spectrum of different NRTI backbones, which could have masked a specific effect of tenofovir. A further general limitation has been the combined analysis of subtype C infections with other subtype non-B infections because of limited numbers. A meta-analysis of European cohort studies reported almost identical virological outcomes among approximately 7000 patients infected with subtype B virus and 700 patients infected with subtype C virus, but patients were followed for a maximum of only 16 months, and all 3-drug regimens were considered . A FrencOur study has several strengths. First, it is the only study that has exclusively examined tenofovir-containing first-line regimens, which makes it highly relevant to current practice. Second, the data were derived from a single national health system that offers near uniform care and thus avoids confounding biases inherent in multinational studies. Third, our estimates of effect are relatively precise because of the large absolute number of virological failure end points and the presence of all major viral subtypes in the United Kingdom. Finally, the diversification of the epidemic, particularly the spread of non-B viruses in the MSM population , has allFurther research is required to reconcile the paradox of the absence of a subtype effect on virological response with the observation that subtype C viruses are more likely to express the K65R mutation in viremic patients , which wSupplementary Material. The UK HIV Drug Resistance Database steering committee comprises the following individuals: Celia Aitken ; David Asboe, Anton Pozniak ; Patricia Cane ; David Chadwick ; Duncan Churchill ; Duncan Clark (St Bartholomew's and The London NHS Trust); Simon Collins ; Valerie Delpech ; Samuel Douthwaite ; David Dunn, Esther Fearnhill, Kholoud Porter, Anna Tostevin, Ellen White ; Christophe Fraser ; Anna Maria Geretti ; Antony Hale ; Stéphane Hué ; Steve Kaye ; Paul Kellam ; Linda Lazarus ; Andrew Leigh-Brown (University of Edinburgh); Tamyo Mbisa ; Nicola Mackie ; Samuel Moses ; Chloe Orkin ; Eleni Nastouli, Deenan Pillay, Andrew Phillips, Caroline Sabin ; Erasmus Smit ; Kate Templeton ; Peter Tilston ; Ian Williams ; Hongyi Zhang .Collaborators in the UK CHIC study are listed in the The coordinating center  is the MRC Clinical Trials Unit at UCL .The following centers  contribute data: Clinical Microbiology and Public Health Laboratory, Addenbrooke's Hospital, Cambridge (Jane Greatorex); Guy's and St. Thomas' NHS Foundation Trust, London ; PHE – Public Health Laboratory, Birmingham Heartlands Hospital, Birmingham (Erasmus Smit); PHE – Virus Reference Department, London (Tamyo Mbisa); Imperial College Health NHS Trust, London (Alison Cox); King's College Hospital, London (Richard Tandy); Medical Microbiology Laboratory, Leeds Teaching Hospitals NHS Trust (Tracy Fawcett); Specialist Virology Centre, Liverpool ; Department of Clinical Virology, Manchester Royal Infirmary, Manchester (Peter Tilston); Department of Virology, Royal Free Hospital, London ; Edinburgh Specialist Virology Centre, Royal Infirmary of Edinburgh (Jill Shepherd); Department of Infection and Tropical Medicine, Royal Victoria Infirmary, Newcastle ; South Tees Hospitals NHS Trust, Middlesbrough (David Chadwick); Department of Virology, St Bartholomew's and The London NHS Trust ; Molecular Diagnostic Unit, Imperial College, London (Steve Kaye); University College London Hospitals (Stuart Kirk); West of Scotland Specialist Virology Laboratory, Gartnavel, Glasgow .Supplementary materials are available at http://jid.oxfordjournals.org. Consisting of data provided by the author to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the author, so questions or comments should be addressed to the author.


Thymidine analogs, namely AZT (Zidovudine or Retrovir™) and d4T (Stavudine or Zerit™) are antiretroviral drugs still employed in over 75% of first line combination antiretroviral therapy (cART) in Kampala, Uganda despite aversion to prescribing these drugs for cART in high income countries due in part to adverse events. For this study, we explored how the continued use of these thymidine analogs in cART could impact emergence of drug resistance and impact on future treatment success in Uganda, a low-income country.We examined the drug resistance genotypes by Sanger sequencing of 262 HIV-infected patients failing a first line combined antiretroviral treatment containing either AZT or d4T, which represents approximately 5% of the patients at the Joint Clinical Research Center receiving a AZT or d4T containing treatment. Next generation sequencing (DEEPGEN™HIV) and multiplex oligonucleotide ligation assays (AfriPOLA) were then performed on a subset of patient samples to detect low frequency drug resistant mutations. CD4 cell counts, viral RNA loads, and treatment changes were analyzed in a cohort of treatment success and failures.Over 80% of patients failing first line AZT/d4T-containing cART had predicted drug resistance to 3TC (Lamivudine) and non-nucleoside RT inhibitors (NNRTIs) in the treatment regimen but only 45% had resistance AZT/d4T associated resistance mutations (TAMs). TAMs were however detected at low frequency within the patients HIV quasispecies (1–20%) in 21 of 34 individuals who were failing first-line AZT-containing cART and lacked TAMs by Sanger. Due to lack of TAMs by Sanger, AZT was typically maintained in second-line therapies and these patients had a low frequency of subsequent virologic success.Our findings suggest that continued use of AZT and d4T in first-line treatment in low-to-middle income countries may lead to misdiagnosis of HIV-1 drug resistance and possibly enhance a succession of second- and third-line treatment failures.The online version of this article (doi: 10.1186/s40249-017-0377-0) contains supplementary material, which is available to authorized users. Please see Additional file Uganda has an estimated 1.6 million people living with human immunodeficiency virus type 1 (HIV-1) with 140 000 new diagnoses and 63 000 AIDS-related deaths per year, which has significant socioeconomic consequences on the nation’s population , 3, assoThe HIV drug resistance surveillance program conducted by the World Health Organization (WHO) in 2012 concluded that 72% of virologic failures during antiretroviral therapy (ART) in LIMCs were directly associated with HIV-1 drug resistance . In high+ T-cell counts and plasma HIV RNA loads were examined prior to and following the initial Sanger sequencing drug resistance test.In this study, we identified 50 HIV-infected individuals receiving first-line cART with or without AZT or d4T and experiencing virologic failure while harboring viruses with dominant FTC/3TC resistance mutations  or NNRTI resistance mutations, but lacking any TAMs based on Sanger sequencing. As expected for Uganda, the majority of these patients were retained on AZT or d4T and received a treatment boost by adding a protease inhibitor while removing or retaining the NNRTI. We used both a deep sequencing-based HIV-1 genotyping assay (DEEPGEN™HIV)  and an on = 50) were selected to be analyzed using the AfriPOLA , (ii) Triomune (d4T + 3TC + NVP) (one pill combination QD) [n = 53], or (iii) AZT + 3TC administered as Combivir or Duovir BID + NNRTI (NVP or EFV QD) [n = 69].With d4T- and AZT-containing cART, drug resistance was observed in over 80% of virologic and/or immunologic treatment failures, defined as having 1+ primary DRMs conferring resistance to any of the three drugs in the first-line treatment regimen . As controls, we evaluated 15 patients failing cART for which AZT or d4T were not prescribed (control group). The distribution of HIV-1 subtypes among these patients was consistent with the region: subtype A , D , B , C  or CRF01_AE  (Table pol gene of patients failing an AZT/d4T (with or without dominant TAMs detected by Sanger sequencing)  in the HIV-1 ng) Fig. . Resistang) Fig.  with theng) Fig. . Using Ang) Fig. .Fig. 2DeIn 94% (47/50) of patients, AfriPOLA identified at least one additional drug resistance-associated mutation that was not reported by Sanger sequencing. Percentage of patients infected with viruses carrying the K65R, L74 V, and Y115F mutations at any frequency (>1%) increased from 0 to 18%, 6 to 44%, and 6 to 40%, respectively Fig. . AfriPOLTo confirm the AfriPOLA results, we selected 15 samples of the 50 clinical specimens analyzed by Sanger sequencing and AfriPOLA to be tested by the deep sequencing-based DEEPGEN™HIV assay. Using DEEPGEN™HIV we confirmed the presence of dominant mutations (>20% frequency) identified by Sanger sequencing and AfriPOLA, including the highly prevalent M184 V mutation Fig. . To direr = 0.88, P < 0.0001, Pearson coefficient correlation) while no correlation was observed between any of the high sensitive assays and Sanger sequencing  would typically start a new second line treatment regimen, which likely explains for the significant reduction in plasma HIV-1 RNA loads and increase in CD4+ T cells 3 months post drug resistance testing  led to no statistically significant difference in the high viral load or low CD4 cell counts before and after Sanger-based drug resistance testing  where we tested for and found low frequency TAMs. Viral loads and CD4 T cell counts remained unchanged over the 90 days prior to and 90 days post drug resistance testing  was the first FDA approved drug for treatment of HIV infections . Within At the JCRC in Kampala, Uganda, we treat approximately 10 000 patients and over 70% have received a first line AZT- or d4T-containing cART. Virologic failures are slightly more common in this LIMC population (~10%/year) of first line treatment failure) than observed in cART treated patients in HICs –57. In 2Drug resistance to at least one drug in the regimen was observed in 82% of JCRC patients failing first line cART involving AZT or d4T. However, majority of this drug resistance was related to the M184 V mutation conferring 3TC/FTC resistance or various NNRTI mutations whereas only 45% of these same patients had TAMs conferring resistance to AZT or d4T. Second line treatment was provided but AZT or d4T was commonly retained in the regimen if resistance was not detected by Sanger. In this study, majority of these patients lacking TAMs (but harboring 3TC and NNRTI resistant virus) had low frequency TAMs as determined by AfriPOLA and/or DEEPGEN™HIV analyses. In addition, our assays also detected minority mutations associated with resistance to TDF, ABC, ddI, NVP, and EFV  that were not identified by Sanger sequencing. These findings suggest that low frequency TAMs (>1%) in the HIV-1 quasispecies could impact treatment outcomes in continued first line or salvage treatments involving AZT or d4T. Moreover, AfriPOLA-based drug resistance testing in Uganda or in other LMICs may be an affordable and easily implemented alternative to Sanger sequencing, which would also provide valuable information on low frequency drug resistance mutations.As we discussed in a previous study , antiretIn summary, dominant AZT and d4T resistance was only observed in 45% of patients failing an AZT- or d4T-containing treatment regimen in Uganda. Slower emergence of TAMs as compared to 3TC and NNRTI drug resistance mutations during virologic failure has been described in terms of historic treatments involving AZT in HICs , 61; how


We study non-linear correlations in the HIV dynamics over time using information theory. This approach requires a large dataset of CD4+ T lymphocytes and viral load concentrations over time. Since it is unfeasible to collect the required amount of data in clinical trials we use C-ImmSim, a clinically validated in silico model of the HIV infection, to simulate the HIV infection and temporary cART in 500 virtual patients for a period of 6 years post infection in time steps of 8 hours. We validate the results of our model with two published clinical trials of temporary cART in acute infection and analyse the impact of cART on the immune response. Our quantitative analysis predicts a “window of opportunity” of about ten months after the acute phase during which a temporary cART has significantly longer-lasting beneficial effects on the immune system as compared to treatment during the chronic phase. This window may help to explain the controversial outcomes of clinical trials that differ by the starting time and duration of the short-term course cART and provides a critical insight to develop appropriate protocols for future clinical trials.It is still unclear under which conditions temporary combined antiretroviral therapy (cART) results in a prolonged remission after interruption. Clinical trials have contradicting reposts about the effect of cART during primary HIV infection on the disease progression. Here we propose that the apparent contradiction is due the presence of a window of opportunity for cART treatment observed in the  Treatment interruptions are still a controversial topic –7 despitA recent study assessing long term outcomes for patients on cART reported that treatment interruptions longer than 3 months have significant negative effects on immune recovery . Other sIn silico studies provide a feasible and ethical alternative to investigate different treatment scenarios . In this case the Pearson correlation between the two functions yields a value of 0 while the mutual information is non-zero.Where  maximal , 36. An SX→Y(t), as the characteristic time at which I(X(t),Y(t+Δ)) decays to a  constant as function of the time step Δ. Calculating SRS involves several steps because we observe that I(X(t),Y(t+Δ)) typically first grows to a maximum correlation value and then decays roughly exponentially (not necessarily converging to zero) as function of Δ (τ) from the peak onward also known as information dissipation time [μ + τ) already characterizes the total time it takes for the (non-equilibrium) correlations to disappear. However, it ignores the absolute value of the correlations. Since large correlation values are a necessary prerequisite to large perturbation impacts, we account for this by multiplying μ + τ with the height of the peak λ.We define the Sustained Response Score (SRS), also denoted as ion of Δ . Therefoion time , 38. TheWritten mathematically:t necessarily has only a short-lived effect, as there cannot be causation without correlation [X on Y potentially lasts for a long period of time. The only way in which a high SRS value between X and Y could be a ‘false positive’, i.e. the effect turns out to be actually short-lived, is by a confounding third variable Z which induces these non-causal correlations through interactions X ← Z → Y. However, assuming the network of interactions in In summary, a low SRS means that a (temporary) treatment administered at time relation . On the 10 viral RNA copies/ml). The key elements to evaluate the progression of HIV-associated disease in a patient are its CD4++ cell count and the amount of viral genome copies in the infected cells (provirus), since their role in the survivability of HIV-1 infected virtual patients is well characterized [We focus our analysis on the three most important indicators of the HIV infection: CD4+ cells (T helper lymphocytes), provirus (the amount of HIV-1 DNA included in infected cells) and viral load  might help to define guidelines for treatment interruptions in clinical studies and might improve the predictive power of models for the HIV pandemics since the effects of treating patients during the period of 10 months post infection are not currently taken into account. Finally, the identified "window of opportunity" may be relevant for future research aimed at preserving immune function and containing the viral reservoir as a support to innovative future approaches to a cure for HIV.


The 2016 WHO consolidated guidelines on the use of antiretroviral drugs defines HIV virologic failure for low and middle income countries (LMIC) as plasma HIV-RNA ≥ 1000 copies/mL. We evaluated virologic failure and predictors in four African countries.We included HIV-infected participants on a WHO recommended antiretroviral therapy (ART) regimen and enrolled in the African Cohort Study between January 2013 and October 2017. Studied outcomes were virologic failure (plasma HIV-RNA ≥ 1000 copies/mL at the most recent visit), viraemia (plasma HIV-RNA ≥ 50 copies/mL at the most recent visit); and persistent viraemia (plasma HIV-RNA ≥ 50 copies/mL at two consecutive visits). Generalized linear models were used to estimate relative risks with their 95% confidence intervals.nd line ART ; other ART combinations not first line and not second line , a history of fever in the past week , low CD4 count  and missing any day of ART  increased the risk of virologic failure. Being on 2nd line therapy, the site where one receives care and CD4 count < 500 predicted viraemia, persistent viraemia and virologic failure.2054 participants were included in this analysis. Viraemia, persistent viraemia and virologic failure were observed in 396 (19.3%), 160 (7.8%) and 184 (9%) participants respectively. Of the participants with persistent viraemia, only 57.5% (92/160) had confirmed virologic failure. In the multivariate analysis, attending clinical care site other than the Uganda sitebeing on 2In conclusion, these findings demonstrate that HIV-infected patients established on ART for more than six months in the African setting frequently experienced viraemia while continuing to be on ART. The findings also show that being on second line, low CD4 count, missing any day of ART and history of fever in the past week remain important predictors of virologic failure that should trigger intensified adherence counselling especially in the absence of reliable or readily available viral load monitoring. Finally, clinical care sites are different calling for further analyses to elucidate on the unique features of these sites. The goal of antiretroviral therapy (ART) for HIV infection is to achieve and maintain virologic suppression, thereby preventing disease progression and transmission. In 2014, the Joint United Nations Programme on HIV/AIDS (UNAIDS) set the 90-90-90 global targets for elimination of HIV, whereby the third 90 represents a target to achieve viral suppression in at least 90% of patients initiating ART by 2020 . By the Progress towards the 90-90-90 targets in Sub-Saharan Africa is hampered by reports from the region that viraemia and virologic failure are common 11% to 24%), with 71% to 90% of the latter having HIV drug resistance mutations [% to 24%,Previously published research findings highlight a number of factors that may be associated with viraemia, including WHO stage, clinician skill level, age, CD4 count, treatment history, and suboptimal adherence –15. Howehttps://www.hivresearch.org/sites/default/files/RV%20329%20Protocol%20v2.6%2021NOV2016%20%28clean%29.pdf) and has previously been described [The African Cohort Study (AFRICOS) is a prospective, multicenter cohort study following HIV-infected participants aged 18 years and older attending outpatient clinical care facilities supported by the U.S. Military HIV Research Program (MHRP) through the U.S. President’s Emergency Fund for AIDS Relief (PEPFAR) in East Africa and Nigeria . A detaiLaboratory assessment at each visit included CD4 T-cell count, plasma HIV viral load, full heamogram, serum chemistry, serum cryptococcal antigen, and QuantiFERON for TB exposure. HIV RNA viral load was assessed every 6 months using several different platforms; Roche Cobas Ampliprep/Cobas TaqMan HIV-1 Test, v2.0 , Roche High Pure/COBAS TaqMan HIV-1 Test v2·0 , Roche COBAS AmpliPrep/COBAS TaqMan 48 HIV-1 Test  or Abbott Real Time HIV-1 Viral Load assay . Adherence was assessed by self-report.2), normal (18·5 kg/m2–24·9 kg/m2) or high (≥25 kg/m2). Current CD4 count was categorized as <500 vs ≥500 cells/mm3. Other exploratory variables considered included duration on ART , history of fever in the past week (Yes vs No), adherence (zero days of ART missed vs at least one day of ART missed in the past month), ART regimen type (1st line as efavirenz/nevirapine based regimens vs 2nd line as lopinavir-ritonavir/atazanavir-ritonavir based regimens), drug or alcohol use (no drugs or <3 drinks per day vs. drug use or ≥3 drinks per day).Data were entered and verified into the ClinPlus Data Management system . Participants’ data were eligible for inclusion in the analysis if they had been continuously taking ART for at least six months and had viral load data at the most recent visit. The 6 months cut off was informed by evidence that the majority of patients achieve viral suppression within 3–6 months of initiating ART –23 and tParticipants were dichotomized as those with and without virologic failure at their most recent visit. Characteristics were compared across the two groups using chi-squared testing for categorical variables and Kruskall-Wallis test for continuous variables. Generalized linear models with a robust standard error and Poisson distribution were used to estimate unadjusted, site-adjusted, and fully adjusted relative risks (RRs) and 95% confidence intervals (CIs) for associations between factors of interest and virologic failure. Backwards selection with 0.05 significance level was used to select variables for inclusion in the final multivariable models. We repeated the analyses examining our two secondary outcomes, viraemia and persistent viraemia. All analyses were performed using Stata 14·0 .The study was approved by institutional review boards of the Walter Reed Army Institute of Research, Makerere University School of Public Health, Kenya Medical Research Institute, Tanzania National Institute of Medical Research, and Nigerian Ministry of Defence. Each participant provided informed consent that was documented with a signature or fingerprint if illiterate.This work was primarily funded by PEPFAR. The funding source had no role in the study design, data collection, data analysis, data interpretation, or writing of the report. The authors had full access to all the data related to this analysis and independently made the decision to submit the findings for publication.Between January 2013 and October 2017, 2678 HIV-infected participants enrolled in AFRICOS. Of these, 2577 (96·2%) had viral load data for the most recent visit. After excluding 523 participants on ART for less than six months, 2054 HIV-infected participants were included in the final analysis .st line therapy; and 73% had been on ART for at least 2 years , Kisumu-Kenya , Uganda , Tanzania  and Nigeria . Most participants were female (57·4%), aged 40 years or older (60·5%), married or cohabiting (59·4%), and had some form of employment (59·2%). Overall, 4·1% of all participants reported a history of illicit drug use or consumption of ≥ 3 drinks of alcohol per day. The majority of participants (89·2%) were on 1 2 years .Of the 2054 eligible participants, 184 (9%) had virologic failure at the most recent visit, varying by study site with a low of 3.4% (12/352) at the Uganda site to a high of 16.6% (51/307) at the Tanzania site . Viraemind line ART ; a history of fever in the past week , and missing any day of ART dosing/adherence . The factors that were associated with decreased risk for virologic failure included having a current CD4 count ≥ 500 cells/mm3 ; older age ; and high BMI .Results of the unadjusted and site adjusted analyses are shown in Tables nd line ART, being a participant at a site other than the Ugandan site, and current CD4 count < 500 cells/mm3  as used in the high-income countries , 25 whilsettings , 28. Prosettings , might esettings . Whereassettings , 32, othsettings , 34. In settings , althougsettings .We also found that younger age was significantly associated with virologic failure but not viraemia. Whereas some published studies have found that socio-demographic factors like age are associated with virologic suppression –39, othend line therapy and virologic failure in this study appears to be independent of adherence or other measured factors like the current CD4 count, BMI or clinical site.Last, being on a second-line ART regimen was significantly associated with risk of virologic failure, independent of adherence. This is in line with findings reported by previous studies that have shown being on second line therapy is associated with viraemia and virologic failure . Patientrd of the UNAIDS 90-90-90 targets. We are aware of randomised trials like the SESOTHO clinical trial [The authors recognize four major limitations of the analysis. First, the cross sectional nature of the analysis does not allow for causal inference or calculations of rates of failure. Second, these analyses do not include underlying HIV drug resistance that could be a driver of virologic failure. There is variability in the rates of baseline/pre-treatment HIVDR resistance in the literature. For example, while some reports indicate low rates of transmitted HIVDR , the WHOal trial  that areIn conclusion, this multi-center analysis demonstrates that HIV-infected patients established on ART for more than six months in the African setting frequently experienced viraemia while continuing to be on ART. We have shown that clinical care sites home to AFRICOS are different and that further analyses will be required to elucidate on the unique features of these sites. We have also demonstrated that low BMI, low CD4 count, and history of fever in the past week remain important predictors of virologic failure that should be used as a marker for intensified adherence counselling especially in the absence of reliable or readily available viral load monitoring. Finally, younger age and single marital status are associated with virologic failure, which has implications for programmatic treatment monitoring practices.S1 PDF(PDF)Click here for additional data file.S2 PDF(PDF)Click here for additional data file.


The World Health Organisation approved boosted atazanavir as a preferred second line protease inhibitor in 2010. This is as an alternative to the current boosted lopinavir. Atazanavir has a lower genetic barrier than lopinavir. We compared the virological outcomes of patients during the roll out of routine viral load monitoring, who had switched to boosted second- line regimens of either atazanavir or lopinavir.This was a cross-sectional study involving adult patients at the Infectious Diseases Institute Kampala, Uganda started on a standard WHO recommended second-line regimen containing either boosted atazanavir or boosted lopinavir between 1 Dec 2014 and 31 July 2015.. Mantel -Haenszel chi square was used to test for the statistical significance of the odds of being suppressed (VL < 400 copies/ml) when on boosted atazanavir compared to boosted lopinavir after stratifying by duration on antiretroviral therapy (ART). Multivariate logistic regression analysis used to determine if the type of boosted protease inhibitor (bPI) was associated with virological outcome.p = 0.09). In a multivariate analysis the type of bPI used was not a predictor of virological outcome (p = 0.60).Ninety (90) % on ATV/r and 83% on LPV/r had a VL less than 1000 copies/ml. The odds of being suppressed using the same viral load cut-off while on boosted atazanavir compared to boosted lopinavir was not statistically significant after stratifying for duration on ART (Patients using the WHO recommended second-line of boosted atazanavir have comparable virological suppression to those on boosted lopinavir. The Joint United Nations Programme on HIV and AIDS (UNAIDS) 2016 report estimates that 17 million people living with HIV are accessing antiretroviral therapy (ART), 60.6% (10.3 million) of these are living in sub-Saharan Africa [Prior to 2013, treatment failure was determined using clinical criteria  or immunological criteria (dropping CD4 count or persistent < 100 cells/ml) or a detectable viral load (VL) greater than 5000 copies/ml. Since 2013, routine viral load monitoring has been recommended for monitoring response to ART. While the exact number of patients on second-line therapy in resource limited settings is not known, the World Health Organisation (WHO) estimates that 6% of all individuals receiving first-line therapy in sub-Saharan Africa need to switch to second-line regimens in any given year [The recommended first-line regimen by WHO for a public health approach consists of two nucleos(t)ides reverse transcriptase inhibitors  and a non-nucleoside reverse transcriptase inhibitor . The second-line regimen comprises of two nucleosides reverse transcriptase inhibitors (NRTIs) plus a boosted protease inhibitor (bPI) (preferred is boosted lopinavir or boosted atazanavir) –7. Due tGuidelines initially recommended boosted lopinavir as the preferred protease inhibitor, but in 2010 the WHO revision of guidelines for ART for HIV in adults and adolescents added boosted atazanavir alongside boosted lopinavir as preferred bPIs for second-line therapy –16. WhilIn 2011, Uganda adopted the WHO recommendation to use boosted atazanavir as a preferred alternative to boosted lopinavir [The Infectious Diseases Institute (IDI) in Kampala, Uganda is a center for specialist management of HIV with over 8000 patients in care, and 1200 of these were on second-line therapy. Patient medical records are maintained via an electronic system and use of all routinely collected clinic data is approved for analysis and reporting by the Makerere University Faculty of Medicine, Research and Ethics committee  and Uganda National Council for Science and Technology  hence the need for consent was waived by an IRB. All abstracted data was de-identified and stored on a password protected computer to protect maintain patients’ anonymity. We identified patients who were initiated on a second-line therapy of boosted atazanavir and boosted lopinavir between 01/Jan/2010 and 01/Dec/2014. We included patients aged ≥18 years, who were active (attended clinic at least once in the previous 3 months), had undergone VL testing and who had been on a standard first-line therapy comprising of two NRTIS and either nevirapine (NVP) or efavirenz (EFV) and switched to a standard second-line of two NRTIs (one new and the other recycled) and either boosted atazanavir or boosted lopinavir. These drugs are generic preparations, from WHO accredited manufacturers. All reviewed patients must have attended clinic at least once in the previous 3 months (not lost to follow up) and must have been on second-line therapy for at least 6 months. Patients who missed their routine visits in the study period were excluded as well as those who were enrolled in an ongoing observational cohort and were being followed up using non-routine VLs.From December 2014, routine VLs were carried out at the Ministry of Health Central Public Health Laboratory (CPHL) using (Roche CAP-CTM and Abbott M2000sp/M2000rt with cut-offs of 20 copies/μL and 75 copies/ μL respectively). Results were returned back to the facility within 2 weeks.Baseline demographic and clinical characteristics at the time of switch to second-line were compared between patients on boosted atazanavir and boosted lopinavir Categorical variables were compared using the chi-square test. The Wilcoxon rank-sum test was used to compare non-normally distributed continuous variables. Virological suppression was defined as having a VL less than 400 copies/ml.P value less than 0.2.. Variables were considered significant at the 95% level.Mantel -Haenszel chi square was used to test for the statistical significance of the odds of being suppressed when on boosted atazanavir compared to boosted lopinavir after stratifying by duration on ART. Propensity scores were generated to account for the probability of being switched to either boosted atazanavir or boosted lopinavir and the variables used to predict this were type of type of bPI, gender, age, body mass index (BMI) and CD4 at switch to second-line. At the multivariable level analysis, a logistic regression was used to determine the factors associated with suppression (VL < 400 copies/ml)., Only variables with an unadjusted p = 0.315)  and 271 on boosted lopinavir (LPV/r) in the study period, of which 252 (88.4%) and 225 (83.0%) were still active in the clinic and 224 in the ATV/r, and 205 in the LPV/r had a VL available. The rates of loss to follow up, death and transfer outs of patients started on ATV/r and on LPV/r were similar;(33/285) 12% on ATV/r and (46/271) 17% on LPV/r (3 and had been on nevirapine with no difference between the groups (Table p = 0.025). The median duration (IQR) on second-line by time of VL was also shorter for patients on (ATV/r)19 months (21–25) versus 40 months on LPV/r (32–52) (p < 0.001)). TDF/3TC was the NRTI combination used in the majority, mostly in the group on ATV/r (85.3%) compared to 154 (75.1%) on LPV/r (P < 0.05) .The majority in either group were female (ATV/r: 148 (66.1%), LPV/r: 128 (62.4%), the median age (IQR) was 37 (30–42) and 36 years (31–42) respectively for ATV/r and LPV/r. Most patients at time of switch had a normal BMI, low CD4 below 200 cells/mmp = 0.09). Further sensitivity analyses using a cut-off of VL < 1000 copes/ ml resulted in 92% on ATV/r and 85% on LP/r suppressed and after stratifying by time on second-line therapy this was also not statistically significant. (p = 0.26). However, a cut-off of < 75 copies/ml showed that the odds of being suppressed were more favorable for ATV/r (85%) compared to LPV/r (76%) on stratifying by time on therapy (p = 0.03)  Table .Table 2Mp = 003). However previous studies have shown that a VL < 75 copies/ml is not predictive of virological failure and therefore while patients on ATV/r are more likely to achieve a VL < 75 copies/ml this might not confer an advantage in terms of clinical outcomes [In this snapshot of African patients on second-line ART, we report a high proportion of patients with viral suppression on both boosted atazanavir and boosted lopinavir containing regimens. Using different VL cut-offs that is, < 1000 and < 400 copies/ml, the proportions suppressed did not differ significantly between the two groups. However, further sensitivity tests showed that the odds of being suppressed were significantly different when a cutoff of < 75 copies/ml was used  are used. This evidence supports the WHO recommendation of boosted atazanavir as a component of second-line regimens in developing countries.


Tenofovir alafenamide (TAF)-containing combinations were introduced in Switzerland after October 2016 and are recommended over tenofovir disoproxil fumarate (TDF) in patients with osteoporosis or impaired renal function.We included all participants of the Swiss HIV Cohort Study on TDF-containing antiretroviral therapy with follow-up visits after January 2016. We determined the proportion of switches from TDF to TAF overall, and among patients with risk factors for TDF toxicity, including osteoporosis, impaired renal function or marked proteinuria. We used multivariable logistic regression to explore predictors of switching from TDF to TAF.We included 5′012 patients, of whom 652 (13.0%) had risk factors for TDF toxicity. A switch from TDF to TAF was undertaken in 2′796 (55.8%) individuals overall, and in 465 (71.3%) with risk factors. Predictors of switching to TAF were male sex , age > 50 years  and the presence of risk factors for TDF toxicity . In contrast, patients with a non-nucleoside reverse transcriptase inhibitor (NNRTI)-based single-pill regimen , those treated in non-tertiary care centers , as well as those with CD4 cell counts below 500/μL  and with chronic hepatitis C infection  were most likely to stay on TDF.Over 50% of patients on TDF-containing therapy, including the majority of patients at risk for TDF toxicity, were switched to TAF within two years of its introduction in Switzerland. Individuals on NNRTI-based single-pill regimens were most likely to remain on TDF. As AIDS-related mortality is decreasing worldwide, improving the quality of life and preventing long-term side effects of antiretroviral agents have become priorities in the management of HIV infection. When treated with antiretroviral therapy (ART), the average life expectancy of HIV-infected individuals is similar to that of uninfected individuals , 2. HoweTenofovir disoproxil fumarate (TDF) is a highly potent drug included in many first-line ART regimens recommended in the past decade . HoweverIn Switzerland, TAF became available in combination with emtricitabine/elvitegravir/cobicistat  in October 2016, with emtricitabine alone  in May 2017, and with emtricitabine/rilpivirine  in July 2018. These drugs were introduced at a slightly lower price than their TDF-containing counterparts, and no generic version of TDF-containing compounds other than TDF as a single substance are available to date in Switzerland. We used data from the nationwide Swiss HIV Cohort Study (SHCS) to determine the proportion of patients with and without risk factors for TDF-related toxicity who had been switched from TDF to TAF and explored individual predictors for being switched.www.shcs.ch) is a prospective cohort that enrolls close to 80% of all HIV-infected adults living in Switzerland  41–56). Measurements of creatinine and proteinuria at baseline were available for 4′813 (96.0%) and 3′102 (61.9%) patients respectively, and a bone densitometry measurement was available in 1′624 (32.4%) individuals. In total, 652 patients (13.0%) had one or more risk factors for TDF-associated toxicity: 243 had an eGFR < 60 mL/min (4.8%), 154 (3.1%) had marked proteinuria, and osteoporosis was diagnosed in 325 (6.5%) patients. Table Of 10′246 HIV-infected individuals in active follow-up after January 1st 2016, 8′245 (80.5%) ever received TDF for more than 30 days. After excluding patients who switched to abacavir or initiated TAF more than 90 days after stopping TDF (p < 0.001). Overall, most individuals received F/TAF and a third drug , followed by F/TAF/EVG/c  and F/TAF/RPV . In those who received F/TAF, the most common third drug was dolutegravir , followed by boosted darunavir , nevirapine  and raltegravir . In 1475 (52.8%) instances, the switch from TDF to TAF was the only modification in the ART regimen with all other components remaining unchanged.Nearly two years after the introduction of TAF in Switzerland, 2′796 (55.8%) individuals had TDF replaced by TAF, with large differences across cohort centers, ranging from 32.6 to 65.3% (p = 0.15). Thirty-four patients had access to TAF prior to its official licensing, either through an early access program or within a study protocol, and remained in our study population.Of the 652 patients with at least one risk factor for TDF-associated toxicity, 465 (71.3%) were switched to TAF. Patients switched at a median of 9.7 months (IQR 7.1–12.2 months) after the introduction of TAF into the Swiss market, without a significant difference between those with or without TDF-toxicity risk factors , rifabutin (n = 14) and carbamazepine (n = 3) were more common. No patient in the study population received phenytoin.The main reasons for replacing TDF by TAF, as reported by SHCS physicians, were “prevention of expected side-effects” (24.9%), followed by “simplification of current treatment” (9.2%), and “presence of established kidney toxicity” (8.2%) Table . Less spTwo years after the introduction of TAF in Switzerland, 56% of all patients on TDF-containing ART overall, and 72% of those with risk factors for TDF-associated toxicity had TDF replaced by TAF. The highest proportions of patients switched to TAF were found in men, those older than 50 years, as well as in individuals with renal impairment, whereas the use of a NNRTI-based single-pill regimen was predictive of staying on TDF. The main reason for switching to TAF, as reported by treating physicians, was the prevention of potential side effects due to TDF. Our study underlines the importance of monitoring treatment changes and related predictors in order to evaluate a program’s potential to react to changes in guidelines and new drug availability, as well as to foster patient-centered management.Although the majority of individuals on TDF-containing ART were switched to TAF, we found large differences in the use of TAF across treatment sites and between tertiary and non-tertiary sites. Similar diversity in patterns of treatment changes were observed across other studies: in a cohort of 444 patients on TDF-containing ART in Germany, only 34% of all patients switched to TAF-containing ART within 2 years of its introduction . In contOur study highlights the multitude of factors which potentially play a role in shaping physicians’ choices and patient preferences in terms of ART modalities. Although only 8.2% of all switches in our study could be attributed to the presence of established kidney dysfunction, as reported by treating physicians, a low eGFR  was a predictor for receiving TAF. This finding is in line with previous reports –18 and sIn general, the potential for DDI of TDF and TAF is similar. However, drugs such as carbamazepine, phenytoin, rifampicin or rifabutin seem to be more problematic when combined with TAF than with TDF . For insThe large number of patients analyzed during the months following the registration of TAF in Switzerland allowed us to explore the main drivers of ART changes in response to the availability of drugs with an improved toxicity profile. Furthermore, the presence of detailed information on treatment changes and stopping reasons helped us improve our understanding of the determinants of switching from TDF- to TAF-containing ART. However, although this study is representative for current treatment strategies in Switzerland, extrapolations to other health care systems should be undertaken with caution. Additionally, given the large number of potentially nephrotoxic drugs with complex toxicity profiles taken by our patients, we could not include comprehensive information on their use in our analysis. As the prescription of such drugs may have motivated physicians to recommend switching to a TAF-containing regimen, we may have failed to grasp the reason for switching in some cases. Similarly, as the assessment of bone mineral density was available in only 32% of our study population, we may have underestimated the proportion of patients at risk of TDF-toxicity. The potential under-estimation of osteoporosis in our cohort was mitigated by our inclusion of data on fragility fractures systematically collected within the SHCS. Since TAF is not recommended during pregnancy, the desire to have children may have influenced treatment choices in some women and led to lower switching rates among this group of patients. Finally, information about physicians’ motivation to recommend a treatment change to their patients was limited to predefined stopping reasons and were inconclusive in almost 50% of cases. Such information would have been important to better understand the large differences in TAF prescriptions between tertiary centers and other health care facilities.The majority of patients at risk for TDF-toxicity were switched from TDF to TAF within two years after its introduction in Switzerland. Among 30% of patients at risk of TDF-toxicity who did not switch during this time-period, being on a NNRTI-based single-pill regimen seemed to be an important reason for remaining on TDF. However, large differences across clinics were observed and related reasons should be further explored. Since current recommendations on switching to TAF are based on limited data from selected groups of patients in randomized controlled trials, further data on clinical outcomes after the introduction of TAF in cohorts such as ours remain essential to inform optimal patient management.