Antiretroviral treatment has played a pivotal role in the reduction of HIV/AIDS-related morbidity and mortality. However, treatment options can be impaired by the development of antiretroviral treatment failure. Regular monitoring of the Human Immunodeficiency Virus treatment outcome via viral load tests is the key approach. There is a scarcity of information about HIV treatment failure and risk factors in the study area. Therefore, the study was aimed to assess antiretroviral treatment failure and associated factors among patients on first-line antiretroviral treatment at Tefera Hailu Memorial Hospital, Sekota, northeast Ethiopia.P value < 0.05 was considered as statistically significant.A hospital-based cross-sectional study was conducted on 295 patients on first-line antiretroviral treatment from Nov. 2018 to Apr. 2019. Socio-demographic and clinical variables were collected using a pretested questionnaire, and blood specimen was collected for PCR viral load and CD4 + cell count estimation. Data were entered into Epi-Info and exported to SPSS for analysis. A binary logistic regression model was used to identify associated factors, and Of the 295 subjects on first-line ART, 49 (16.6%) and 18 (6.1%) experienced virological and immunological failures, respectively. The failure of the former was associated with poor adherence , CD4 + count < 500 cells/µL  and shorter (6–24 months) duration on ART , while poor treatment adherence  and drug interruption  were the independent risk factors for latter. Immunological tests to predict virological failures showed as sensitivity, specificity, PPV, and NPV were 20.4%, 96.7%, 55.5%, and 86.0%, respectively.The rate of ART failure was considerably high. Poor adherence, low CD4 + count, prolonged ART, and drug interruption were found to be the most predictor variables for virological and immunological failures. The discrimination power of the immunological parameter was low in comparison to virological measurements as standard methods. Therefore, the study highlighted the need for more attention and efforts to curb associated factors and maximize virological tests for monitoring treatment failures. Following the epidemic of HIV/AIDS, the global expansion of the combination antiretroviral treatment (ART) has been the primary contributor to the 51% decline AIDS-related deaths, from a peak of 1.9 million (1.4–2.7 million) in 2004 to 0.94 million (0.67–1.3 million) in 2017. The scaling up of ART was a critical turning point in the clinical management of the HIV/AIDS disease and the gradual evolution of HIV infection into a chronic non-fatal condition by restoring the immune function and suppressing the virus to an undetectable level. This resulted in preventing the transmission of the virus to other uninfected individuals.Globally, 21.7 million 59%) people living with HIV/AIDS (PLHA) accessed treatment in 2017 and Africa accounted for 15.3 million on ART . Despite9% peopleEthiopia has adopted the WHO plan “End the AIDS epidemic by 2020 to achieve the target of the three 90%’s ” ambitious plan. However, due to inaccessibility, costs and technical demands of the HIV RNA test, immunologic (CD4 + T cell test) is still widely recommended in Ethiopia for monitoring treatment failures. But immunologic parameters have a lower accuracy of identifying virologic failures, leading to premature changes or continuous uses of failed regimens. This leads to more complex HIV drug failures, and the health impact increases morbidity and mortality rates in settings where virologic tests are not available.There has been a marked paucity of information on ART failure and associated risk factors in Ethiopia, including in the study area. Besides, the lack of early detection of the virological failure is often coupled with delays in switching to efficacy drugs. Such conditions weakened the ability to prevent treatment failure and led to accumulation of further HIV-DR at individual and population level. Therefore, this study was conducted to assess the extent of antiretroviral treatment failure and its associated factors among HIV patients on first-line ART at Tefera Hailu Memorial Hospital, Sekota, northeast Ethiopia.The study was conducted at Tefera Hailu Memorial Hospital in Sekota town, the capital of Waghimra zone, east Amhara region, 720 km north of Addis Ababa and 320 km north of Dessie. The hospital provided ART and referral case services to nearly half amillion people. The hospital reported that about 1760 patients started ART until October 2018, and that 889 were on treatment at that moment. The hospital laboratory had a separate section for CD4 + count and an estimated 2000 blood specimens were delivered for the purpose annually from the hospital and the surrounding health centers. Blood specimens were collected for viral load determination, processed and made ready for transport to Dessie branch of the Amhara Public Health Institute.A hospital-based cross-sectional study was conducted on 295 adolescent and adult PLHA patients who were on first line ART follow ups at Tefera Hailu Memorial Hospital from Nov. 2018 to Apr. 2019. Systematic random sampling technique was used to enroll the participants Sample size was determined using the single population proportion formula, with the following assumption, n = sample size, d = 0.05; P = 0.222, which was reported in the previous study in Gondar  and Z α/All adolescent and adult patients who were on first-line ART and had at least a six-month follow up and volunteerd to participate were included in the study, while, patients who were on second-line ART and had incomplete data before the study were excluded.Antiretroviral treatment failure defined according to the WHO 2016 guideline was the outcome variable [Virological failure is defined as when antiretroviral therapy (ART) fails to suppress viral replication to lower than 1000 copies/mL, while immunological failure is a fall of CD4 + count below 250 cells/µL following clinical failure, or persistent CD4 + count below 100 cells/μL .Socio-demographic and clinical  data were collected by expert nurses from patient medical files and face to face interviews using a structured pre-tested questionnaire. The questionnaire was adapted from the WHO risk assessment tool for HIV treatment failure and was developed by using literature, on risk assessment for HIV treatment failure.Expert laboratory staff members collected 4 mL and 2 ml of whole blood into plasma preparation tube (PPT) and ethylenediaminetetraacetic acid (K3 EDTA) tube, for viral load test and CD4 counts, respectively, from each participants. After 30 min, PPT was centrifuged at 1500 rpm for 10 min to separate plasma (top), in between separator gel and the cell (bottom). Then, the plasma containing PPT was transported in a triple package sample transportation box at 2–8 ℃ to Amhara Hublic Health Institute Dessie center, by an orientated laboratory assistant.The CD4 + T cell count determination was carried out using 50 µl of EDTA whole blood added to the cartridge and run by the Becton–Dickinson Biosciences (BD) Fluorescent Activated Cell Sorter (FACS) Presto near patient machines. In the analysis, the software identifies the T-Lymphocyte populations and calculates the absolute counts of CD4 + cells and results printed out.6 copies/ml.RNA extraction from 0.2 mL of plasma and amplification reagent (master mix) preparation was done by using the Abbott m2000sp HIV-1 assay. Then both extracted RNA and master mix were dispensed into a 96 deep well plate (made ready for amplification). In the Abbott m2000rt analyzer extracted RNAs were changed to complementary deoxyribonucleic acid (DNA) by reverse transcriptase polymerase chain reaction (RT-PCR), and DNA was continued for amplification. Then, the DNA product was measured using the Abbott m2000rt quantitative Real-Time HIV-1 assay with HIV-1 RNA detection level depend on the amount of sample ranging 40 to 10 × 10The quality of the data was confirmed by pre-testing the questionnaire on 5% of respondents other than those involved in the actual study and by proper designing. Before beginning the actual data collection, training was given to data collectors, and the questionnaire was reviewed and checked. Data collectors were supervised during the process and given feedback by the principal investigator every morning. The whole process of work was assured and approved by advisors.The Abbott Real-time HIV-1 (m2000sp) assay internal control an RNA sequence unrelated to the HIV-1 target sequence was introduced into each specimen at the beginning of sample preparation. This unrelated RNA sequence was simultaneously amplified by RT-PCR and served as an internal control (IC) to demonstrate that the process proceeded correctly for each sample. Also, negative, low positive and high positive controls were used. For the CD4 test, the FACS Presto machine had internal performance control. Both viral load and CD4 tests were done by experts who used standard operating procedures.Data were cleaned and checked for completeness and entered into EPI-Info version 7 and exported to SPSS version 20 for analysis. Descriptive statistics  were used to describe results. The binary logistic regression analysis was used to determine univariable associations with ART treatment failures. All factors (P ≤  0.2) were finally tested by the multivariable logistic regression for adjusted odds ratios to decrease confounding errors of the independent variables for treatment failure. P-value < 0.05 was considered as statistically significant for treatment failure. Using a two-by-two contingency table, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were calculated to determine the validity of the immunological tests for predicting virological failures. Data were also prepared by using tables. The virological and immunological treatment failures were defined according to the WHO 2016 guideline for the use of ART drugs.A total of 295 HIV positive individuals, 169 (57%) of whom were female, on first-line ART regimens participated. The median age of the participants was 37 years (IQR: 30–43), and the majority, 115 (39%), were aged between 30 and 39; 129 (43.7%) were married; nearly three-fourths, 215 (72.9%), attended primary school and above; 143 (48.5%) were self-employed; distance from home to hospital was > 10 km; 79 (27%) of the participants were rural dwellers (Table The baseline and current median CD4 + counts were 198 (IQR: 135–314) and 414 cells/µL (IQR: 309–544), respectively. Participants were on first-line ART with a median follow up time of 83 months (IQR 53–116). At ART initiation, 183 62.37%) patients were ambulatory by their functional status, and 112 (38%) were baseline clinical stage III and IV. In contrast, during data collection, only 2.03% of the participants were in clinical stage III and IV. Presentations were not even observed among the respondents , tenofovir disoproxil fumarate (TDF), and stavudine (d4T) based regimens were 119 (40.3%), 110 (37.3%) and 66 22.4%), respectively. As illustrated in , of whom 28 (57.1%) were females. On the other hand, effective viral suppression, < 1000 copies/ml, was noted among 246 (83.4%) of the participants.The multivariable logistic regression showed that poor drug adherence (< 95%) was identified as one of the independent risk factors for virological treatment failure. Patients with poor adherence experienced just above six times higher odds to develop treatment failure at . participants with CD4 + counts < 500 cells/µL were almost five times more likely to develop virological treatment failure , P = 0.031) in comparison with those who had more CD4 + count. Furthermore, treatment duration was also another predictor variable; only patients who followed treatments for 6–24 months had the chance to minimize treatment failure by nearly 50%  compared to those on treatment for over 72 months  (95% CI 3.4–9.5) faced immunological failures, of these 11 (61.1%) were male. Among immunological failed participants, 10 (55.5%) of them had also viral failure and 8 (44.4%) encountered only CD4 + failure. Patients with poor drug adherence were intriguingly found to be 11.51 times more likely to experience immunological failure  compared to those who adhered (> 95%). Similarly, patients who interrupted drugs had 6.374 times higher odds of immunological failure  than those who did not.In the present study, immunologic failure showed low predictive values for detecting the virological failures. Using the two-by-two contingency table, screening immunologic failure was compared to the golden standard virological failure, and the sensitivity, specificity, PPV, and NPV were 20.4%, 96.7%, 55.5%, and 86%, respectively , and most of them had chances to decrease treatment failure, minimize transmission to others and the risks for clinical conditions, indicating that a combination of ART was highly effective for patients’ recover and the decline of opportunistic infection. Significant HIV associated morbidity and mortality had been reported in pre-ART era. Following the introduction of HAART, however, the quality of life and disease related outcomes have been improved especialty in high HIV burden countries like Ethiopia .On the other hand, we reported that the prevalence of virologic treatment failure was 16.6% 95% CI 12.5–20.9) among participants. The result was comparable to reports of previous studies in Gondar 14.7%)  and Addi.5–20.9 a%  and AdPatients with poor adherence had above six times higher odds to develop treatment failure  compared to those who adhere. Poor adherence leads to a low level of antiretroviral effect in the body, and this causes insufficient to suppress viral replication, finally resulting in treatment failure. In addition, individuals with CD4 + count < 500 cells/µL were also nearly five times more likely to develop virological treatment failure  as opposed to those who had greater CD4 + counts. It is evident that a high degree of viral replication is common among patients with a decreased level of CD4 count and subsequently leads to treatment failure.In the present study, patients with shorter (6–24 months) treatment duration were found to be 52% less likely to develop treatment failure  in comparison to those with > 72 months on treatment. Reasonably, if the duration of ART increases, the emergence of HIV-DR strain is expected as a result of HIV error-prone replication, mutation rate, and viral recombination . Over tiFurthermore, immunological failure was found to be 6.1% (95% CI 3.4–9.5). The finding was in line with those of studies conducted in Ethiopia and reported 3.8–6.8% , 21, 22.In the current study, immunologic failure had low predictive values for detecting the virologic failures. The reasons might be low prevalence of immunological failure and test inaccuracy. Compared to the golden standard virologic failure immunologic failure, sensitivity, specificity, PPV and NPV were 20.4%, 96.7%, 55.5%, and 86% respectively. Several studies also pointed out the low performance of immunological criteria for prediction of HIV/AID treatment failure –27. The The finding of the study is limited owing to the fact that specific drug resistance was not confirmed using genotypic method for resistance and susceptibility, for lack of resources. Being a institutional-based study, the result may not also be generalized to wider population. Despite its limitation, however, the work, we believe, provides important information which would be useful for the ART treatment programs in the country.In the present study, the burden of antiretroviral treatment failure according to WHO virological criteria was more than the 10% WHO target failure. The Immunological test had low predictive values for detecting treatment failure compared to viral load estimation as a standard method. Poor adherence, CD4 + count < 500 cells/μL and prolonged duration on ART were significant for virological failure. Therefore, our finding indicates the need for more focus and effort from the study area hospital and concerned bodies on significant risk factors to maximize the successes of patients’ health by preventing, enhance early detection and monitoring of antiretroviral treatment failure and control further complications.


Detectable serum or plasma cryptococcal antigen (CrAg) precedes symptomatic cryptococcal meningitis. The World Health Organization recommends CrAg screening for human immunodeficiency virus–positive persons with CD4 count <100 cells/μL initiating antiretroviral therapy (ART). However, an increasing proportion of patients with cryptococcosis are now ART experienced. Whether CrAg screening is cost-effective in those with virologic failure is unknown.We retrospectively performed nationwide plasma CrAg testing among ART-experienced Ugandan adults with virologic failure (≥1000 copies/mL) using leftover plasma after viral load testing during September 2017–January 2018. For those who were CrAg positive, we obtained ART history, meningitis occurrence, and 6-month survival via medical records review.P = .001). CrAg prevalence was 4.2% (32/768) among those with viral loads ≥5000 copies/mL and 0.7% (3/419) among those with viral loads <5000 copies/mL.Among 1186 subjects with virologic failure, 35 (3.0%) were CrAg positive with median ART duration of 41 months . Among 25 subjects with 6-month outcomes, 16 (64%) survived, 7 (28%) died, and 2 (8%) were lost. One survivor had suffered cryptococcal meningitis 2 years prior. Two others developed cryptococcal meningitis and survived. Five survivors were known to have received fluconazole. Thus, meningitis-free survival at 6 months was 61% (14/23). Overall, 91% (32/35) of CrAg-positive persons had viral load ≥5000 copies/mL compared with 64% (735/1151) of CrAg-negative persons (odds ratio, 6.0 ; In addition to the CD4 threshold of <100 cells/μL, reflexive CrAg screening should be considered in persons failing ART in Uganda with viral loads ≥5000 copies/mL. In addition to the CD4 threshold of <100 cells/μL, reflexive cryptococcal antigen screening should be considered in persons failing antiretroviral therapy with viral loads ≥5000 copies/mL. Cryptococcal meningitis is responsible for 15% of AIDS-related deaths and is the leading cause of adult meningitis in sub-Saharan Africa . Annual There is a substantial proportion of ART-experienced patients with virologic failure presenting with fulminant cryptococcosis . During Given the substantial proportion of ART-experienced patients presenting with cryptococcosis, new viral load (VL)–based CrAg screening strategies may be useful. Uganda has also adopted the “test and treat” strategy, which will enroll more people on ART irrespective of their CD4 cell counts. In addition, we are now encouraging more virologic monitoring compared to CD4 monitoring. This creates a challenge for CrAg screening, which is based on CD4 cell counts. We conducted this study to determine the CrAg prevalence and clinical outcomes of CrAg-positive persons among ART-experienced people with virologic failure. We evaluated the potential threshold of virologic failure where CrAg screening should be considered, and the cost of CrAg screening at this threshold.This cross-sectional study was conducted at the Uganda National Health Laboratory Services (UNHLS), which performs centralized VL monitoring in Uganda . The UNHLS processed a total of 843 020 VL tests for adults in 2017, of which 84 302 (10%) had unsuppressed viremia of ≥1000 copies/mL . Dried bUsing the UNHLS database, we identified all patients with virologic failure and leftover plasma samples from the months of September 2017 to January 2018. From these we selected a random sample of 1186 patients with leftover samples using an auto-generated command in Stata version 14 software . The sampling technique used draws observations without replacement from a dataset. Quantitative RNA VLs on plasma had been done by UNHLS using the COBAS AmpliPrep/COBAS TaqMan system. For this study, we performed CrAg testing on stored plasma samples at UNHLS; CrAg testing was performed using the CrAg LFA .Subjects’ demographics and clinical data were obtained from the VL testing laboratory request forms. Outcome data were obtained by records review and/or contacting health facility clinicians. Additionally, clinicians were duly informed of the positive CrAg results. Patients who had not had any interaction with their respective clinics in the prior 6 months (from the point of their VL result) were defined as lost to follow-up. Meningitis-free survival was defined as having not suffered from clinical cryptococcal meningitis during the 6-month period after the HIV VL testing.We obtained ethical review and approval from the Makerere University School of Medicine Research and Ethics Committee, the Uganda National Council of Science and Technology, and the University of Minnesota. A waiver for informed consent was obtained as CrAg testing was performed on leftover plasma samples, and the study posed no more than minimal risk to participants.2 test. We additionally used logistic regression to assess whether CrAg positivity was associated with quantitative HIV VL thresholds.Data analysis was primarily descriptive with variables summarized by mean with 95% CI, median with interquartile range (IQR), and number (percentage). We tested continuous variables via nonparametric Wilcoxon rank-sum test and categorical data via χ Once CrAg prevalence was determined, we used the inverse to calculate the number needed to test to detect 1 CrAg-positive person. The cost of CrAg screening using the LFA in Uganda is $3.50 . We multP < .001).Overall, 368 174 adults living with HIV had VL testing from September 2017 to January 2018; 5348 patients had virologic failure and leftover plasma samples. We found 73 patients without leftover samples for CrAg testing. Of the randomly selected 1186 selected patients, 588 were from the Central region, 191 from the East, 147 from the North, and 260 from the West. These samples were from 96 of the 127 districts in Uganda. P = .001). CrAg prevalence increased among higher VLs, with 4.2% (32/768) CrAg positivity among those with ≥5000 copies/mL vs 0.7% (3/419) CrAg positivity among those with <5000 copies/mL. Among the 1186 persons, 65% (767/1186) had VLs ≥5000 copies/mL. Overall, 91% (32/35) of CrAg-positive persons had VLs ≥5000 copies/mL compared with 64% (735/1151) of CrAg-negative persons  were known to be alive, 7 (28%) were confirmed dead, and 2 (8%) were lost to follow-up.Of the 25 CrAg-positive persons, only 1 person had a history of treatment for cryptococcal meningitis 2 years prior and was taking fluconazole for secondary prophylaxis. Of the 25 CrAg-positive persons, 17 were getting their first ever CrAg test. Five survivors were known to have been CrAg tested and received preemptive therapy with fluconazole around the time of their VL result. Another 2 patients who developed cryptococcal meningitis during these 6 months were treated and survived. Thus, meningitis-free survival at 6 months was 14 of 23 . Absent fluconazole receipt (n = 19), 6-month meningitis-free survival was 8 of 19 .We also did an analysis including those who were lost to follow-up. We used 6-month outcome findings from a CrAg-positive cohort in Uganda that found a 14% mortality rate, 77% meningitis-free survival, and 9% progression to meningitis . If we aP = .42). The Kruskal-Wallis test was used to compare the medians for age and VL across the 3 groups and the test was not significant for both age (P = .42) and VL (P = .10). Therefore, the likely outcome of the individuals lost to follow-up may be similar to those who were accounted.We determined the likely outcome of those lost to follow-up (including those without outcome data) by comparing their sex, median ages, and VLs with those who survived and died. We used the Fisher exact test for the sex comparison across the 3 groups and found no significant difference , Brazil (3.1%) , 19, andWe calculated that it would cost $87.50 to detect 1 CrAg-positive person if screening is performed among persons with VLs of ≥5000 copies/mL. In 2018, Uganda had 951 690 adult HIV VL samples tested; 858 426 were suppressed, 6661 tests were rejected, and 86 603 were virologic failures (VL ≥1000 copies/mL) . From ouAs HIV programs ramp up “test and treat” and scale up virologic monitoring, we have observed increasing proportions of persons with cryptococcal meningitis presenting as ART-experienced persons with undetected virologic failure , 21. WHOThe study had limited access to patient medical information, thus missed some clinically relevant data, such as CD4 cell count, which could have been useful in further characterizing the population of interest. This could also have introduced information bias in characterizing patients as meningitis free. The potential seasonal distribution of cryptococcal infections may have influenced prevalence results. While we only tested plasma specimens, whether dried blood spots would have a different CrAg prevalence is unclear as the CrAg LFA sensitivity is lower in dried blood spots than in plasma due to the extraction process (unpublished data). Viral load testing is being scaled up replacing CD4 monitoring, yet absolute CD4 cell counts provide the risk stratification to target evaluation for opportunistic infections, including CrAg screening. The cost of CD4 testing (~$6) is more than the cost of CrAg testing (≤$4), so from a program implementation perspective, using CD4 testing to then narrow the pool to select for CrAg testing is not efficient, unless a CD4 is already being performed , 23. We This study shows that ART-experienced people failing HIV therapy are at risk for disseminated cryptococcal antigenemia and eventually cryptococcal meningitis or death and demonstrates the feasibility of linking CrAg screening to VL monitoring. To further avert cryptococcosis among individuals with virologic failure, WHO should recommend CrAg screening in persons with virologic failure with VLs ≥5000/mL. Cost-effective studies are needed to establish whether CrAg screening based on VL thresholds  would be feasible. Studies to determine the association of virologic failure independent of CD4 and CrAg are needed. Prospective studies among ART-experienced populations to further evaluate the optimal VL threshold for CrAg testing, timing of ART switch, implementation of this strategy, and the potential benefit of CrAg screening are warranted.


In 2016, under its new National Adherence Guidelines (AGL), South Africa formalized an existing model of fast-track HIV treatment initiation counselling (FTIC). Rollout of the AGL included an evaluation study at 24 clinics, with staggered AGL implementation. Using routinely collected data extracted as part of the evaluation study, we estimated and compared the costs of HIV care and treatment from the provider’s perspective at the 12 clinics implementing the new, formalized model (AGL-FTIC) to costs at the 12 clinics continuing to implement some earlier, less formalized, model that likely varied across clinics (denoted here as early-FTIC).This was a cost-outcome analysis using standard methods and a composite outcome defined as initiated antiretroviral therapy (ART) within 30 days of treatment eligibility and retained in care at 9 months. Using patient-level, bottom-up resource-utilization data and local unit costs, we estimated patient-level costs of care and treatment in 2017 U.S. dollars over the 9-month evaluation follow-up period for the two models of care. Resource use and costs, disaggregated by antiretroviral medications, laboratory tests, and clinic visits, are reported by model of care and stratified by the composite outcome.A total of 350/343 patients in the early-FTIC/AGL-FTIC models of care are included in this analysis. Mean/median costs were similar for both models of care . For the subset achieving the composite outcome, resource use and therefore mean/median costs were similar but slightly higher, reflecting care consistent with treatment guidelines . Not surprisingly, costs for patients not achieving the composite outcome were substantially less, mainly because they only had two or fewer follow-up visits and, therefore, received substantially less ART than patients who achieved the composite outcome.The 2016 adherence guidelines clarified expectations for the content and timing of adherence counseling sessions in relation to ART initiation. Because clinics were already initiating patients on ART quickly by 2016, little room existed for the new model of fast-track initiation counseling to reduce the number of pre-ART clinic visits at the study sites and therefore to reduce costs of care and treatment.NCT02536768.Clinical Trial Number:  South Africa’s National Department of Health (NDOH) launched the National Adherence Guidelines for Chronic Diseases in 2015 [Prior to national roll out of the guidelines, the NDOH and its partners identified 24 clinics where guideline implementation would be staggered to facilitate a cluster-randomized study to evaluate impacts of the adherence interventions on various treatment outcomes. Patients were enrolled in this Adherence Guidelines Evaluation (AGL) study between January and December 2016, with follow up through 2017 , and, in response, some clinics initiated patients with minimal adherence counseling, while others continued to require multiple sessions before initiation . The 201With the newer, formalized FTIC model, the AGL provided explicit guidance on the timing and content of adherence counseling sessions relative to ART initiation. The guidelines called for patients to receive four adherence counseling sessions: one on the day of ART eligibility; one session seven days later ; and then two additional counseling sessions at subsequent clinic visits (at one- and two-months on ART). The overall goal of this new FTIC model was to standardize adherence counseling (timing and content) as part of the initiation process and reduce barriers to ART initiation, with the goal of increasing adherence and retention. A simple, written adherence plan is envisioned to be completed with the patient during these sessions, and a two-page sample plan is included in the AGL appendix.To complement the effectiveness results from the AGL evaluation study, the purpose of this analysis is to estimate the costs of HIV care and treatment from the provider’s perspective for patients enrolled in the AGL evaluation study from the day of treatment eligibility through a 9-month follow-up period  at the A basic cost-outcomes analysis, applying standard methods used in related studies of the cost of HIV care and treatment –9, is usFor patient costs over the specific follow-up period for the analysis, we calculated the quantities of specific resources used for each patient, and then based on a unit cost for each resource, we calculated costs over the time period for each patient (resource quantities times unit cost). We address each topic below in more detail.The full AGL evaluation study was approved by the Human Research Ethics Committee (HREC) of the University of the Witwatersrand and the Boston University Institutional Review Board (IRB). Both approved use of routine clinic data for the evaluation  and a waiver of patient consent. The trial is registered at clinicaltrials.gov (NCT02536768).For this analysis, the follow-up period is taken from the follow-up-start date as defined by the AGL evaluation, which for the FTIC portion of the overall study was from the day of treatment eligibility at the clinic through 270 days after the follow up start date, which coincides with the study primary endpoint of viral suppression within 9 months (see [TIER.Net) which provides information on visit date, ARV regimen, number of pills collected, and laboratory tests; (2) paper-based clinic records  which were used by AGL study staff to review patient enrolment in AGL-FTIC at the intervention sites and counselling sessions at the standard model sites; and (3) the National Health Laboratory Service (NHLS) database of all viral loads done in South Africa’s public sector.This analysis focuses on three categories of resources used for patient care during the study follow up period: ARV medications, laboratory tests, and clinic visits. Data for each patient came from three sources: (1) a national electronic patient database , study clinics typically did not record the timing and content of counselling sessions . Thus, dTIER.Net. While the AGL study team worked with facility staff on data enhancement and completion of missing data during a short period at the beginning of the study, the overall quality of the data collected at sites and entered into TIER.Net at the 24 study sites was largely beyond the control of the AGL study.As noted above, patient-level data were extracted from the national electronic patient database, S1 File provides all primary information used along with additional sources as needed to estimate all unit costs used in this analysis.All costs are reported in 2017 U.S. dollars (US$) using the 2017 average annual exchange rate (13.32 ZAR/US$) reported in the International Monetary Fund’s International Financial Statistics . S1 FileFor ARV medications, costs were obtained from official tender documents and converted to a daily equivalent . For labUnit costs for three types of visits are included in this analysis: pre-initiation visits, the initiation visit, and the post-initiation follow-up visits. All clinics included in the AGL study were Primary Health Care (PHC) clinics. The unit cost for a standard PHC clinic visit for HIV patients on treatment is from a recent paper by Larson et al , which iThe unit cost for a pre-ART visit is somewhat less clear. The AGL evaluation reported that patient records or systems were not adequate to identify if patients received counseling at clinic visits, and as a result the “extent and content of counselling provided remains unknown and likely varies by facility and healthcare provider” . In the reg command in STATA with the cluster by site option).The mean, median and interquartile range (IQR) for resource quantities  and costs are reported for each model of care. 95% confidence intervals for mean total costs are also reported (using the and was retained in care at 9 months (defined as completing a clinic visit during the 180–270 day period study follow up). If a patient satisfies both conditions, then they achieved this outcome. This composite outcome is consistent with the basic goals of FTIC, which is to initiate patients on ART promptly after known eligibility and retention after initiation. This composite outcome is also consistent with recent studies focused on both ART initiation and retention  ,8,15–19.ee, e.g. ), and SoThe composite outcome used here is not exactly comparable to the final 9-month endpoint in the AGL study. The 9-month outcome envisioned in the study protocol was viral suppression “within 9 months”, which was operationalized as viral suppression for any test completed during month 2 to 9 of study follow up. We did not consider a composite outcome using the viral suppression outcome as appropriate because it was based on any test during month 2–9 of follow up. For example, with any viral suppression between month 2–9, a patient could achieve this outcome but initiate ART on day 40 of follow up (so failing to achieve the short-term outcome), have a viral load test 3 months later that is suppressed (so achieving the 9-month primary outcome), but then be lost to follow up for the remaining study period. Costs for this person over 9-months are low because they only receive perhaps three months of ART, which is clearly not the intent of the South African AGL policy.S1 File, we also show in S1 Table that patient characteristics for the costing cohorts (transfers excluded) remain largely balanced and essentially the same as the full AGL evaluation cohorts.S1 File, S2 Table presents patient characteristics for both costing cohorts and stratified by composite outcome status. Patient characteristics for the subset achieving the composite outcome in each group (Early FTIC and AGL FTIC) remain largely balanced .The results provided in In S1 File . While multiple ARV regimens are available in South Africa, as reported in S1 File, almost all ARVs dispensed to patients in each model of care during the study period were the main national, once-a-day, fixed-dose, first-line regimen (TDF/FTC/EFV), with a daily cost of $0.32 ($116.8 per year). Similarly, although 29 different lab tests were utilized and included in the analysis, only three tests were somewhat common .S1 File). Assuming 18 working days per month , the daily salary equivalent is $105.61. With 8 hours of work expected daily and 7 hours directly spent with patients , the implied salary cost per one hour of patient time is $15.09. In other words, the follow-up clinic visit in We recognize that visit costs vary depending on the types of staff seen at a typical visit, patient/staff volume at clinics, and/or provider time spent with a patient. For perspective, public-sector professional nurse salaries in South African are based on Grade  and level within each grade. The median  annual salary in 2017 was $22,811  for the early-FTIC group and $167.50  for the AGL-FTIC group. Patients in both models who achieved this outcome had almost identical resource use and therefore costs. These patients received about 234 days of ARVs (median of 252 days), which is consistent with ART initiation within 30 days. Given that almost all ARV medications received were the standard fixed-dose combination, ARV medication costs were essentially identical for both models.Based on the estimated means and medians for visits, patients in both models of care typically had one pre-ART visit, one initiation visit (by definition), and 6 follow-up visits over the study follow up period (270 days). Given the number of visits were identical (including pre-ART visits), visit costs were also basically identical.Regarding laboratory tests, as part of treatment initiation, study subjects typically had one CD4 test and one creatinine clearance test. The median quantity of viral load tests was consistent with guidelines recommending viral load testing after 6 months on ART.As the quantities of resources  were almost the same for both models of care for the subset achieving the primary outcome, the cost for medications, laboratory tests, and visits were very similar as well. Results for those not achieving the composite outcome are provided in Not surprisingly, as shown in The AGL evaluation assessed the FTIC model of care during the early phase of rolling out the adherence guidelines, at a time when the comparison study clinics were attempting to balance competing guidance on adherence counseling but also faster ART initiation. During the study period in the non-intervention (early-FTIC) clinics, counselling as part of the standard care was guided by the National Consolidated Guidelines for PMTCT and the management of HIV in children, adolescents and adults but was not always standardized across sites . At the Average costs over the 9-month follow up period were very similar for both study groups , little reason exists to expect that costs for adults newly initiated on ART would vary with basic patient characteristics such as age or sex, given that patients in both study groups were adults, relatively healthy , not pregnant, and well balanced on baseline characteristics, as all such patients would be expected to receive the same services.TIER.Net to evaluate provider costs for patient care during the early roll out of the adherence guidelines. Other than a short period at the start of the study when the AGL evaluation study team worked with the facility staff on data enhancement and completion of missing data, the overall quality of the data collected and entered into TIER.Net at the 24 study sites was largely beyond the control of the AGL study.This analysis is subject to limitations and challenges. First, as noted in the methods section, we used routinely collected data extracted mainly from Second, this analysis assumes that the unit cost for a pre-ART visit is similar to the costs of a post-initiation follow up visit. However, in the study clinics during the study follow up period, most patients in each model of care received about one pre-ART visit . The basic unit cost for a follow up visit of $7.61 is equivalent to 30 minutes for a middle grade public health nurse.In addition, the unit cost for a clinic visit and ART initiation visit are based on studies completed in Gauteng Province, but both were completed in public health clinics where staff are paid based on governmental salary scales .By 2016, which was four years after the NDOH recommendation of fast-track ART initiation for some categories of patients, South African patients receiving standard of care typically only had one clinic visit before ART initiation. By the time that national adherence guidelines that included FTIC were rolled out, there existed little room to reduce the number of pre-ART clinic visits –24. The Despite the revision and clarification around the timing and content of the counselling sessions for fast-track initiation counselling, the ability to measure or monitor fidelity to implementation was limited for both models of care included in this analysis. Improved record systems that document the timing and content of counseling services provided to patients will facilitate future assessments of these national guidelines and help to determine more accurately the role these counselling sessions play in facilitating initiation and retention in care and adherence to treatment in the months after initiation.S1 File(XLSX)Click here for additional data file.S2 File(DOCX)Click here for additional data file.S3 File(PDF)Click here for additional data file.


HIV is a serious chronic medical condition. Significant improvements in antiretroviraltherapy have led to a transformation in its management. No curative treatment is availablefor HIV, and lifelong therapy is required with a combination of agents to control viralreplication and prevent complications. Some of the older agents are notorious for manyside effects, making patient compliance difficult, which is critical to preventing HIVresistance. Tenofovir is one of the newer, more tolerable, nucleotide reversetranscriptase inhibitors on the market; is a mainstay of many antiretroviral therapycombinations; and is now available in 2 different formulations, tenofovir disoproxilfumarate (TDF) and, the more recent, tenofovir alafenamide (TAF). These 2 formulationshave very different pharmacokinetics, which seem to affect their efficacy and safety. Thismanuscript provides insight into the history of TDF and TAF development, their uniquepharmacokinetics and pharmacology, clinically important adverse effects, monitoring,interactions, resistance, review of clinical studies, and guideline recommendations andclinical applications for tenofovir’s various indications. TDF and TAF are both recommended treatment options for HIV and hepatitis B.To our knowledge, this is the first review that summarizes and provides insight on theclinically relevant differences between TDF and TAF for all approved indications.The implications of our review focus on affecting practice and highlighting relevantclinical and research information regarding TDF and TAF to provide understanding whencaring for the HIV and hepatitis B population.Management of HIV and AIDS has evolved substantially over the past 3 decades. Asunderstanding of the retrovirus by the scientific community increased, advancements in itsmanagement and prevention soon followed. These advances shifted the diagnosis of HIV/AIDSfrom a terminal illness to a serious, but manageable, chronic medical condition.1 Following approval of zidovudine, several other antiretroviral (ARV) agents weredeveloped, including new classes of medications and various combinations of medications. Bythe mid- to late 1990s, it was realized that one active agent against HIV was insufficientto suppress viral replication and improve immune function, driving a change in management toutilization of combination therapy.2 Tenofovir disoproxil fumarate (TDF), an NRTI, received the Food and DrugAdministration (FDA) approval for HIV in 2001, further revolutionizing disease management,serving as a critical component of backbone therapy in many HIV-positive patients.3The early part of HIV/AIDS epidemic in the United States began in 1981, after numerouscases of individuals with severe immune deficiency were reported. Six years later,zidovudine, a nucleoside reverse transcriptase inhibitor (NRTI), was the first medicationapproved for AIDS.4 Tenofovir disoproxil fumarate received FDA approval for HBV in 2008 and is currentlyconsidered a preferred treatment option by the HBV guidelines.5The management of hepatitis B virus (HBV) has also evolved with the progression ofantiviral therapy. Significant improvements in controlling HBV and reduction of theincidence of cirrhosis and hepatocellular carcinoma due to HBV occurred over the past 2decades. Currently, 8 medications are approved for HBV treatment.6 Approval of TAF further transformed management of HIV and HBV, allowing for morepotent nucleotide transcriptase inhibitor with a different adverse effect profile to beutilized as a mainstay of therapy.7In 2015, a new formulation of tenofovir, tenofovir alafenamide (TAF), received FDA approval.This review provides insight into the clinical pharmacology, pharmacokinetics (PK), andtherapeutics of tenofovir, reviewing differences between the available formulations andconsiderations for selecting between TDF and TAF. A complete list of TDF- or TAF-containingregimens is provided in Ethics approval and informed consent was not required for this review of theliterature.22Tenofovir is a nucleotide analog (NA) of adenosine 5′-monophosphate. In its parent form,tenofovir is a dianion at physiologic pH and is associated with poor membrane permeabilityand low oral bioavailability. To improve oral bioavailability and membrane permeability,tenofovir is commercially available as prodrugs, TDF and TAF.24 Tenofovir is then activated to tenofovir–diphosphate intracellularly.21 This conversion of TDF and TAF into their active form, tenofovir–diphosphate, issimilar for HIV and HBV management. Tenofovir–diphosphate works to inhibit HIV replicationby competing with the natural substrate deoxyadenosine 5′-triphosphate for incorporationinto DNA during HIV transcription.21 Tenofovir–diphosphate inhibits replication of HBV by inhibiting HBV polymerase.25After oral administration, TDF is hydrolyzed by gut and plasma esterases to tenofovir, andTAF is metabolized mostly intracellularly by cathepsin A to tenofovir.27 In vitro, Robbins and colleagues demonstrated a greater than 100-fold increase inanti-HIV activity with TDF compared to tenofovir. They attribute this improvement to a rapidintracellular uptake of TDF, resulting in an increased intracellular accumulation of active tenofovir–diphosphate.26 In vivo, Gasselin and colleagues showed that single-dose oral TDF resulted in anearly 8 times higher peripheral blood mononuclear cell exposures to tenofovir–diphosphatecompared to subcutaneous tenofovir.27The prodrug TDF has demonstrated an improved PK profile and improved antiviral activitycompared to the parent tenofovir in vitro and in vivo.7 These toxicities, coupled with the need for long-term therapy with tenofovir,subsequently led to the FDA approval of TAF in 2015.Tenofovir disoproxil fumarate, administered as a 300-mg daily dose, has been used as apreferred backbone agent in the management of HIV for years; however, issues with bone andkidney toxicity have come to the forefront with widespread, chronic use of this medication.In phase 3 clinical trials, patients treated with TAF-containing regimens had significantlysmaller mean serum creatinine increases, significantly less proteinuria, and significantlysmaller decreases in bone mineral density (BMD) at the spine and hip compared to those givenTDF-containing regimens.22 In vitro, TAF is more stable in plasma and is selectively cleaved into its activemetabolite intracellularly. In whole blood, TAF concentrates mainly in mononuclear cells,such as the T lymphocytes that serve as the primary site of HIV replication.29Compared to TDF, TAF has been identified as an alternative tenofovir prodrug that moreefficiently loads HIV target cells, allowing for a 10-fold increased activity against HIV in vitro.29 Tenofovir alafenamide, in contrast, remains stable within the plasma and is onlyconverted intracellularly to tenofovir and then the active tenofovir diphosphate. Because ofthis, administration of TAF results in lower circulating plasma tenofovir levels than withTDF. These lower plasma levels of tenofovir are what lead to the differences in safetyprofile between TDF and TAF.30After oral absorption, the majority of TDF is rapidly converted to tenofovir while in theplasma, and then intracellularly to the active tenofovir diphosphate.31 Common adverse effects are similar, although TDF appears to be associated with morebone and renal toxicities and TAF with increases in low-density lipoprotein (LDL) and totalcholesterol.Both TDF and TAF are essential components of preferred initial HIV regimens because oftheir efficacy as well as improved tolerability in comparison to older agents.32 Nucleoside reverse transcriptase inhibitors, including TDF, have been associated withsevere lactic acidosis and severe hepatomegaly with steatosis.33 Risk factors include female sex, obesity, liver disease, and long-term therapy withan NRTI. Extra caution should be used when administering to patients with risk of liverdisease, but cases have occurred in patients with no known risk factors. Patients should bemonitored for any signs of an elevated lactate and hepatic function test elevations.33General adverse effects for TDF may include rash, diarrhea, headache, pain, depression,asthenia, and nausea.34 Tenofovir is renally eliminated via active tubular secretion as well as passiveglomerular filtration. Tenofovir accumulates and causes renal damage at the proximal tubulewhen there is an imbalance in the process of plasma uptake and renal clearance.22 This manifests as a high uptake of tenofovir into the plasma, with a less rapidefflux into the urine. More severe manifestations can include renal failure or Fanconi syndrome.33 Risk factors for new or worsening renal impairment may include advanced HIV disease,longer treatment duration, low body weight , and preexistingrenal impairment.31Tenofovir disoproxil fumarate can potentially be nephrotoxic and has been associated withnew or worsening renal impairment. The suspected mechanism for renal impairment with the useof TDF is damage to the proximal tubule by circulating plasma tenofovir.34 Per US Prescribing Information (USPI), it is recommended calculated creatinineclearance (CrCl) be determined upon initiation as well as throughout therapy as appropriate.Other measurements of renal function to monitor in situations of suspected renal impairmentinclude serum phosphate, urine glucose, urine protein, urine phosphate, and urine calcium.34 Concurrent use with high-dose nonsteroidal anti-inflammatory drugs (NSAIDs) is notrecommended because of specific reports of renal failure and hospitalizations in patientspreviously stable on TDF. Overall, concurrent use with other potentially nephrotoxic agentsshould be avoided if possible.Renal function should be monitored prior to initiation and throughout therapy as clinicallyappropriate, and caution should be taken with administering TDF in combination with otherpotentially nephrotoxic agents.29 Dosage adjustments to every 48 to 96 hours intervals are required if TDF is utilizedwith a CrCl < 50 mL/min. Tenofovir disoproxil fumarate has not been studied in patientswith a CrCl < 10 mL/min.Because of its potential nephrotoxicity, TDF is to be used with caution in patients withrenal impairment.34 The clinical importance of these changes is unclear, but BMD assessment isrecommended for both adult and pediatric patients with risk factors.22 Supplementation with calcium and vitamin D is likely prudent in patients receivingTDF. Patients who develop proximal tubule renal damage may be at risk of secondaryosteomalacia and hypophosphatemia. These conditions should be evaluated if a patientpresents with renal dysfunction and new or worsening bone symptoms. Generally, the initialdecrease in BMD with ART initiation is followed by a stabilization.31 In comparison to TAF, BMD loss is greater with TDF.Clinical studies of patients receiving TDF-containing regimens suggest a potential decreasein BMD from baseline.31 Frequently utilized PK boosters include cobicistat and ritonavir. The US Departmentof Health and Human Services (DHHS) Panel on ARV therapy recommends avoiding concomitant useof TDF with PK boosters if feasible.Both adverse renal and bone effects appear to be more apparent when TDF is administered aspart of a PK-boosted regimen.26 The most commonly reported adverse effects with TAF include abdominal and back pain,headache, fatigue, cough, and nausea.25 Newer data suggest that TAF may be associated with elevated lipids, fasting glucose,and increased risk of myocardial infarction, diabetes, and metabolic syndrome, compared with TDF.35As noted earlier, unique PK of TAF results in lower plasma and higher intracellulartenofovir concentrations, which allow for less bone- and kidney-related adverse effects.33 Tenofovir alafenamide carries a warning for hepatic effects as well as lacticacidosis and severe hepatomegaly similar to TDF.25 The same risk factors and monitoring recommendations apply, and treatment should besuspected if lactic acidosis or severe hepatotoxicity develops.25Unlike TDF, TAF does not require renal dose adjustment for CrCl greater than or equal to 15mL/min, allowing for use in some renal impairment populations more so than TDF.36 In one randomized study of TAF versus TDF, cardiovascular safety end points weremonitored for 96 weeks, including fasting lipids, proportion eligible for statin therapy,cardiovascular adverse events, and estimated 10-year atherosclerotic cardiovascular disease(ASCVD) risk.37 No significant differences between groups were noted, except for the mean estimated10-year ASCVD risk comparing TAF versus TDF .Despite lower risk of bone and renal toxicities, TAF has been associated with elevated LDL,high-density lipoprotein (HDL), and triglycerides in comparison to TDF.31 Both agents are substrates of BCRP/ABCG2, and P-glycoprotein/ABCB1, and inhibitors ofMRP2. Drugs that strongly affect P-glycoprotein and BCRP activity may affect TAF absorption.25Unlike many other components of ARV therapy, both TDF and TAF have minimal clinicallysignificant drug–drug interactions because of lack of CYP 450 enzymatic metabolism.38 P-glycoprotein transport is infrequently a major contributor to overall drugabsorption, unless the dissolution rate of the drug is very slow, or a small oral dose isgiven. The unique pharmacology of TAF involves a much smaller dose than is required withTDF, and it relies on metabolism intracellularly rather than primarily in the plasma, makingit much more susceptible to clinically important drug interactions with P-glycoproteinmanipulation. P-glycoprotein inducers will likely decrease the absorption of TAF, leading topotential treatment failure.25 P-glycoprotein inhibitors will lead to an increase in absorption of TAF and a higherthan normal plasma concentration of the drug. Strong P-glycoprotein inducers includeanticonvulsants , antimycobacterials, and the herbal product St. John’s wort, often used fordepression. The USPI recommends against the use of these agents together with TAF because ofrisk of treatment failure. The exception is carbamazepine, which has undergone a druginteraction study. When utilizing carbamazepine together with TAF, the recommendation is toincrease TAF to twice-daily administration instead of the standard once daily.P-glycoprotein is an efflux pump found in intestinal tissue and functions as a biologicalmechanism to transport toxins out of cells.33 This drug interaction warning applies to both TDF and TAF. Common examples ofmedications that may compete for active tubular secretion in the kidney include acyclovir,cidofovir, ganciclovir, valacyclovir, valganciclovir, aminoglycosides, and NSAIDs.Because tenofovir is eliminated by the kidney, coadministration with other drugs competingfor active tubular secretion may increase the plasma concentration of tenofovir and/or thecoadministered drug.33 Tenofovir disoproxil fumarate may be taken with or without food. Tenofoviralafenamide bioavailability is increased approximately 65% by a high-fat meal.33 It is recommended that TAF be administered with food.25The bioavailability of TDF is increased approximately 40% by a fatty meal, but this doesnot affect administration recommendations.HIV drug resistance is caused by mutations that develop during viral replication in thesetting of inadequate ARV drug exposure. When a single mutation causes resistance to otherdrugs in the same ARV class, this is referred to as cross-resistance. Mutations arerepresented by a codon number, preceded by a letter indicating the amino acid in thewild-type virus, followed by another letter indicating the amino acid substitution in themutant virus. For example, K65R indicates that there is a lysine (K) to arginine (R)substitution at amino acid codon 65 in the reverse transcriptase enzyme.39 The primary mutation that compromises the activity of TDF and TAF is K65R. The K65Rmutation is associated with cross-resistance to all other NRTIs, except zidovudine.3942 The Q151M mutation alone can cause low-level resistance to tenofovir, butintermediate resistance when found in combination with other mutations.43 The presence of multiple thymidine analog mutations (TAMs), such as M41L, D67N, K70R,L210W, T215Y/F, and K219Q/E, can mediate tenofovir resistance.45 Moreover, the presence of the T69 double serine insertion mutation can further reducethe susceptibility of tenofovir in the presence of TAMs.46 Resistance to tenofovir has also been described with less common mutations such asK70E and Y115F.48Resistance profiles are the same for both formulations of tenofovir. However, it has beensuggested that TAF may provide a higher level of protection against TDF-resistant mutantviruses due its ability to achieve higher intracellular concentrations.Numerous clinical studies have evaluated efficacy and safety of transitioning patients fromTDF-based regimens to TAF-based regimens for both HIV and HBV.49DeJesus and colleagues designed an actively controlled, open-label, noninferiority studyof virologically suppressed adult patients on 1 of 4 TDF-containing regimens. Patientswere followed for at least 96 weeks and randomized to switch to a TAF-containing regimenor continue their TDF-containing regimen. The TAF regimen contained elvitegravir boostedwith cobicistat and emtricitabine. Patients were randomized in a 2:1 ratio, and a total of959 TAF patients and 477 TDF-treated patients were included for analysis.P = .017).Regardless of previous treatment, the mean BMD of the hip and spine increased in the TAFgroup but remained stable or decreased in the TDF group (P < .001).Patients with spine or hip osteopenia or osteoporosis had a higher rate of recovery in theTAF group versus the TDF group. The TAF group had improved renal effects with significantimprovements in proteinuria or albumin to creatinine ratios (P <.001). Fasting values of total cholesterol, HDL, LDL, and triglycerides were higher in theTAF group versus the TDF group, which was statistically significant, but of unknownclinical significance.49At 96 weeks, TAF demonstrated superiority over TDF, with 93% versus 89% of patientshaving virologic suppression of HIV RNA to < 50 copies/mL (P < .0001), LDL-cholesterol, and total cholesterol toHDL-cholesterol ratio . Despite these increases,the clinically relevance of TAFs impact on lipids was not established. Effects on renaland bone outcomes were nonsignificant; however, patients treated with TAF had preservationof estimated glomerular filtration rate (eGFR), less tubular proteinuria, and improvementsin BMD scores compared to TDF-treated patients.35The EMERALD trial investigated the efficacy and safety of switching from boosted proteaseinhibitors plus emtricitabine and TDF regimens to single tablet darunavir, cobicistat,emtricitabine, and TAF at 48 weeks in virologically suppressed HIV-1-infected adults.Although the study found the single-tablet regimen containing TAF to be non-inferior toboosted protease inhibitors plus emtricitabine and TDF regimens in terms of efficacy, itdid find statistically significant differences in change in total fasting cholesterol,LDL-cholesterol, and total cholesterol to HDL-cholesterol ratio between the 2 study arms.Patients receiving the TAF containing regimen had significant increases in total fastingcholesterol , significantly less proteinuria, and smaller changes in BMDfor hip  and spine .50 At 96 weeks, 86.6% in the TAF arm and 85.2% in the TDF arm were virally suppressed]. Smaller declines in BMDand more favorable changes in proteinuria and albuminuria continued to be observed inTAF-treated patients.51 At 144 weeks, TAF was superior to TDF in virologic efficacy . Tenofovir alafenamide also continued to have less impact on BMD andrenal biomarkers compared to TDF.36Sax and colleagues evaluated the safety and efficacy of TAF as part ofelvitegravir/cobicistat/emtricitabine versus TDF as part ofelvitegravir/cobicistat/emtricitabine in a randomized, multicenter trial. Results at week48 demonstrated high rates of viral suppression among both groups (88.4% versus 87.9%)with similar improvements in CD4 count. Similar to previous studies, patients receivingTAF had smaller reductions in estimated CrCl . If baseline eGFR was <60 mL/min, difference in eGFR at 18 months was 9.6mL/min (95% CI: 5.1-14.0 mL/min) between patients receiving TAF compared to thosereceiving TDF. The authors concluded that there was an increase in eGFR over time in TAFcompared to TDF in patients with moderate-to-severe renal impairment.54 Of note, no direct studies of unboosted TAF versus unboosted TDF have beenconducted to date.In a recently published meta-analysis of 11 randomized clinical trials, Hill andcolleagues sought to investigate if the higher risk of renal and bone adverse effects seenwith TDF in comparison to TAF was associated with the concurrent use of the PK boostersritonavir or cobicistat, rather than TDF’s higher plasma concentration. They also soughtto investigate any differences in efficacy of viral suppression between TAF and TDF withand without PK boosting. Nine of the reviewed clinical trials included in theaforementioned meta-analysis were studied in an HIV-1 population and 2 in HBV. The 11trials consisted of over 4500 patients receiving boosted regimens and over 3500 patientsreceiving unboosted regimens. Participants across these trials were predominantly male(83%), white (59%), and had a mean age of 41 years.P = .05). No significant differences in HIV RNA suppression wereobserved in those taking unboosted regimens. Discontinuation secondary to renal adverseevents was 1% lower in patients receiving boosted TAF versus boosted TDF .54Results from the meta-analysis demonstrated that patients taking boosted TAF had 2%higher rates of HIV RNA suppression <50 copies/mL in comparison to boosted TDF . Patients taking boosted TAF were significantly less likelyto stop treatment secondary to bone adverse effects than those taking boosted TDF(P = .03). No differences in risk of fractures or bone-related adverseevents between unboosted TDF and TAF were detected.54The risk of bone fractures with boosted TAF compared to boosted TDF was 1% lower(P = .05), as well as larger decreases inBMD (P = <.001), more bone fractures (P = .04), andmore discontinuations for bone (P = .03) or renal (P =.002) adverse events. There were no significant differences in HIV RNA suppression rateswhen comparing unboosted TDF and unboosted TAF.54Patients with boosted TDF showed a statistically significant lower rate of HIV RNAsuppression of <50 copies/mL . Recentlyreleased data from the DISCOVER trial support the use of TAF in combination withemtricitabine as an effective and safe means of PrEP, leading to its FDA approval for HIVPrEP in certain patient populations. The DISCOVER trial is a phase III, randomized,parallel, double-blind study evaluating the safety and efficacy of fixed-doseemtricitabine (F) and TAF for PrEP in men and transgender women who have sex with men andare at risk of HIV-1 infection. The primary outcome of the study is the incidence of HIV-1infection per 100 person-years in patients who receive F/TAF versus F/TDF. Secondaryoutcomes include changes in BMD, renal function, and development of ARV resistance.P = .47) and inHBeAg-negative patients receiving TAF and TDF . The study concluded that TAF remained as effective as TDF insuppressing HBV replication over the 2-year treatment period, without development ofvirologic resistance.57Recently, 96-week data from 2 ongoing international, phase III, randomized, double-blindtrials evaluating the safety and efficacy of TAF versus TDF for the treatment of chronicHBV infection were released. The trials enrolled both treatment-naive andtreatment-experienced patients, with and without positive hepatitis B envelope antigen(HBeAg), randomizing patients in a 2:1 ratio to receive TAF 25-mg orally once daily or TDF300 mg orally once daily. In total, 866 patients received TAF and 432 received TDF. Atweek 96, rates of viral suppression were similar in HBeAg-positive patient receiving TAFand TDF  and lumbar spine (mean % change −0.75% versus −2.57%), and asignificantly smaller changes in eGFR (−1.2 mg/dL versus −4.8 mg/dL).31Nucleoside reverse transcriptase inhibitors are essential constituents that make up thebackbone of a complete ARV regimen. As per the Guidelines for the Use of AntiretroviralAgents in Adults and Adolescents Living with HIV, an ARV regimen for treatment-naivepatients should consist of 2 NRTIs in combination with a third active drug from one of thefollowing classes: integrase strand transfer inhibitor, non-NRTI, or protease inhibitorwith a PK enhancer. Of the 7 US FDA-approved NRTIs for HIV treatment, tenofovir is aprimary agent recommended by the DHHS.31 Safety, cost, and access are some factors to consider when choosing between the 2formulations of tenofovir. As discussed previously, TAF has fewer bone and renaltoxicities when compared to TDF, while TDF is associated with lower lipid levels.31 Both formulations of tenofovir are available in different combination tablets forease of administration. Tenofovir alafenamide or TDF in combination with emtricitabine or abacavir pluslamivudine are the preferred NRTI combinations in initial ARV regimens.58 Additionally, as seen in the ADVANCE trial, there is an increased risk ofdeveloping clinical obesity when TAF is used in combination with dolutegravir.52Of note, the World Health Organization currently does not recommend TAF-based regimensfor use in HIV treatment due to gaps in data. These gaps include safety of use in pregnantwomen and lack of experience in patients receiving concurrent treatment for tuberculosis.59 The 2017 CDC guidelines recommend PrEP for adults who meet the following criteria:sexually active adult men who have sex with men (MSM), adult heterosexually active men andwomen who do not regularly use condoms with partners of unknown HIV status who may be athigh risk of contracting HIV, and adult persons who inject drugs (PWID).59Pre-exposure prophylaxis encompasses the use of ARV agents in reducing the risk ofacquiring HIV infection in high-risk individuals. The Centers for Disease Control andPrevention (CDC) endorses the use of once-daily oral TDF or TAF and emtricitabine, inconjunction with patient counseling and monitoring, to prevent new HIV infections inadults who are at substantial risk.60 Tenofovir disoproxil fumarate alone may be considered an alternative regimen inheterosexually active adults and PWID, but not for MSM, since efficacy has not beenstudied in this population.62Truvada, a co-formulated tablet of TDF 300 mg and emtricitabine 200 mg, is FDA approvedfor the indication for PrEP in adults and adolescents weighing at least 35 kg.63 However, more recent data from the phase 3 DISCOVER study showed non-inferiority ofTAF to TDF when used in combination with emtricitabine for PrEP in cisgender MSM andtransgender women.56 Data from this trial led to the FDA approval of TAF in combination withemtricitabine for PrEP.35Results from a phase 1 PK study showed TAF exhibited lower mucosal tenofovirconcentrations compared with TDF, which led to concerns that TAF may be less effective for PrEP.64 Unlike PrEP, there are insufficient data to recommend a specific combination of ARVagents as the most effective regimen in PEP.Postexposure prophylaxis (PEP) with ARV agents is warranted in individuals after apotential exposure to HIV in order to prevent becoming HIV-infected. A 28-day course ofPEP should be initiated within 72 hours to HIV-negative persons after an exposure toblood, genital secretions, or other potentially infected body fluids of persons known tobe HIV-infected or of unknown HIV status.64 A 3-drug regimen consisting of TDF, emtricitabine, and raltegravir dosed based onbody weight is preferred for PEP in children 2 to 12 years old.Based on evidence demonstrating maximal viral suppression in the treatment of HIV when atleast 3 ARV drugs are used, the CDC recommends a 3-drug PEP regimen in order to preventbecoming HIV-infected after a potential exposure. In adults and adolescents at least 13years old with normal renal function (CrCl >60 mL/min), a 3-drug regimen consisting ofTDF 300 mg co-formulated with emtricitabine 200 mg (Truvada) once daily with raltegravir400 mg twice daily or dolutegravir 50 mg once daily is preferred.5 Compared to other available HBV therapies, TDF and TAF demonstrate increasedHBV-DNA suppression, regardless of the HBeAg status of the patient and maintain a higherbarrier to resistance.5 In the management of antiviral resistance, TDF has been shown to remain effectivein HBV resistant to other NAs such as lamivudine, adefovir, and entecavir.6567 Tenofovir disoproxil fumarate is the preferred salvage therapy, particularly inpatients in whom the history of past NAs is unclear.5 In patients with HBV coinfected with HIV, tenofovir (TDF or TAF) plus lamivudine oremtricitabine is recommended.31 Although there is more experience with TDF compared with TAF in HBV, TAF appears tobe equally effective and is associated with less renal and bone toxicity.68Both TDF and TAF are FDA-approved and preferred therapies in treatment of chronic HBV inboth treatment-naive and treatment-experienced patients.Both TDF and TAF serve as vital components in preferred treatment regimens for HIV and HBV.The agents have similar efficacy and unique adverse effect profiles. The main pharmacologicdifferences between the 2 formulations of tenofovir are decreases in renal and bone adverseeffects, and increases in total cholesterol and LDL observed with TAF. The increased rate ofbone and kidney adverse effects associated with TDF was attributed to its use in combinationwith a PK booster. When utilized without a PK booster, TDF’s renal and bone effects may besimilar to TAF, although no clinical studies comparing TAF and TDF in this setting have beenconducted. Due to the nature of HIV and HBV management requiring chronic lifelong treatment,the choice between TAF or TDF should be based on patient specific factors, concomitant useof other ARV agents, and cost.


Predicting long-term care trajectories at the time of HIV diagnosis may allow targeted interventions. Our objective was to uncover distinct CD4-based trajectories and determine baseline demographic, clinical, and contextual factors associated with trajectory membership.We used data from the Sizanani trial (NCT01188941), in which adults were enrolled prior to HIV testing in Durban, South Africa from August 2010–January 2013. We ascertained CD4 counts from the National Health Laboratory Service over 5y follow-up. We used group-based statistical modeling to identify groups with similar CD4 count trajectories and Bayesian information criteria to determine distinct CD4 trajectories. We evaluated baseline factors that predict membership in specific trajectories using multinomial logistic regression. We examined calendar year of participant enrollment, age, gender, cohabitation, TB positivity, self-identified barriers to care, and ART initiation within 3 months of diagnosis.688 participants had longitudinal data available. Group-based trajectory modeling identified four distinct trajectories: one with consistently low CD4 counts (21%), one with low CD4 counts that increased over time (22%), one with moderate CD4 counts that remained stable (41%), and one with high CD4 counts that increased over time (16%). Those with higher CD4 counts at diagnosis were younger, less likely to have TB, and less likely to identify barriers to care. Those in the least favorable trajectory (consistently low CD4 count) were least likely to start ART within 3 months.One-fifth of people newly-diagnosed with HIV presented with low CD4 counts that failed to rise over time. Less than 40% were in a trajectory characterized by increasing CD4 counts. Patients in more favorable trajectories were younger, less likely to have TB, and less likely to report barriers to healthcare. Better understanding barriers to early care engagement and ART initiation will be necessary to improve long-term clinical outcomes. The use of antiretroviral therapy (ART) can drastically improve outcomes for people living with HIV in low-and middle income countries , 2. HoweCurrent measurements of HIV care engagement tend to occur at the population level or through point-in-time assessments . Such meIn this study, we used group based statistical modeling to characterize CD4 trajectories for patients newly diagnosed with HIV in South Africa. CD4 count was chosen as an outcome to describe HIV care, as those engaged in care and adherent to ART (when indicated) would be expected to display a steady CD4 count increase early in treatment, followed by maintained high levels. Patients displaying different patterns of CD4 counts  are likely to be experiencing lapses in care or ART adherence. We additionally sought to understand how demographic, clinical, and contextual factors correlate with longitudinal CD4 trajectories. Ultimately, these findings may be used to identify which patients may benefit from enhanced efforts for improving retention in care, and to inform what types of interventions could be most impactful.Data for this study were collected through the Sizanani Trial (NCT01188941), a randomized controlled trial evaluating the use of health systems navigators to improve linkage to HIV and TB care in South Africa. This trial is described in detail elsewhere , 13. PatThis study was approved by McCord Hospital Medical Research Ethics Committee, St. Mary’s Hospital Research Ethics Committee, University of KwaZulu-Natal Biomedical Research Ethics committee and Partners Institutional Review Board . Participants provided written informed consent for participation. The study was monitored by an independent Data Safety Monitoring Board.Upon enrollment, patients completed a baseline questionnaire that included items about demographics, emotional health, social support, and self-identified barriers to care. Demographics included patient age and gender. We measured emotional health using an adapted version of the five-item Mental Health Inventory screening test . We measTo provide additional long-term data, we cross-matched patients with two national registries using name, gender, date of birth, and South African ID number. Cohort data was linked with data from the National Health Laboratory Services (NHLS) to obtain additional CD4 count measurements. The NHLS provides services to over 80% of the population of adults living with HIV in South Africa through a network of 265 laboratories . We alsoj) to the proportion classified in that group based on the highest posterior probability, (2) examined the tightness of the confidence intervals around πj, (3) compared the average posterior probability (AvePP) of group membership for individuals assigned to each group with 0.7 threshold, and (4) assessed whether the odds of correct classification (OCC) exceeded the minimum threshold of 5 [Longitudinal CD4 count was our primary parameter of interest for trajectory definition. CD4 counts were available for up to seven years after study enrollment; however, since few study participants had CD4 counts measured beyond 5 years (5%), we focused modeling on the 5 years following enrollment. Some participants had serial CD4 measurements within a short time period. To create more balanced data, we averaged serial CD4 counts such that each person had at most one CD4 measurement per year entered into the model. Given the wide range of CD4 values, we used square root transformation for model building strategies which reduced variability in the data. With mortality, patients stopped contributing CD4 measurements. We built a series of group-based trajectory models with specifications of 2 to 5 trajectory groups. We used Bayesian information criteria (BIC) to identify the model with optimal number of trajectories by calculating approximation of Bayes factor between models I and J as exp(BIC_i-BIC_j) , 20. To old of 5 . We usedAfter trajectories were unmasked, we used multinomial logistic regression to assess which baseline demographic, clinical, and contextual factors predicted membership in CD4 trajectories. To assess predictors, we used backward selection and maintained variables that showed statistically significant associations with trajectory type in the most parsimonious model. Factors considered included age, gender, the number of cohabitants in a patient’s house, a summative estimate of self-identified barriers to care, TB positivity, and ART initiation within three months of diagnosis. Barriers were counted as the number of domains  reported by a participant. Coefficients for risk factors indicate the increase in relative odds of being in a specific trajectory relative the reference trajectory per unit change in the risk factor.Among the 1,899 HIV positive patients enrolled in the Sizanani trial, 688 (36%) had multiple CD4 measurements spanning greater than one year allowing inclusion in this analysis. The mean age of study participants was 33 years. There was an equal gender split; 337 (49%) of study participants were male. The median CD4 count at study enrollment was 218 cells/μL, with an interquartile range of 94–368. Coinfection with TB was found in 191 (28%) of participants at the time of HIV diagnosis. Among all study participants, only 108 (16%) were started on ART within three months of study enrollment. Approximately half (52%) of study participants reported no barriers to care, while a minority of participants (9%) reported barriers to care in all five domains. A total of 57 (8%) study participants died during the study period.Compared to the patients included in this analysis, the 64% of Sizanani trial participants without multiple CD4 counts who were excluded from analysis were somewhat older (36 years-old versus 33 years-old), less likely to be married (77% versus 87%), and more likely to be employed (53% versus 45%). They had similar mean baseline CD4 counts at diagnosis (234 versus 260) and had similar rates of TB infection (27% versus 28%).Using the principle of maximization of Bayesian information criteria (BIC), we determined that the model with four groups had the best fit. We named the four identified groups based upon CD4 trajectories observed: ‘1. Low Stable’, ‘2. Low Increasing’, ‘3. Moderate Stable’ and ‘4. High Increasing’ . Among tDistribution of participants’ characteristics in each trajectory is presented in This study found that group-based statistical modeling can be applied to data from longitudinal HIV care to characterize distinct CD4 trajectories. Among the patients included in this analysis, approximately 60% were in more favorable trajectories with median CD4 counts at or above 300 cells/μL throughout the study period. Patients in more favorable trajectories were younger, less likely to have TB, and reported fewer barriers to care. Among the patients who had low CD4 counts at the time of diagnosis (groups 1 and 2), approximately half failed to improve throughout the study period (group 1). Members of this group were twenty times less likely to initiate ART within three months of study enrollment compared to those whose CD4 counts improved. These results highlight the ongoing need for early diagnosis and the importance of linkage to ART following diagnosis. Further research is needed to better identify causes of late presentation and suboptimal linkage to care.We identified four trajectories of HIV care using group-based statistical modeling. These findings are somewhat different from those of trajectory modeling in other HIV care settings. In a study using state-wide surveillance data from North Carolina to characterize care engagement, five trajectories were identified . Some trOur reference group was characterized by advanced disease at study enrollment with a median CD4 count of 79 cells/μL. Compared to patients in trajectories with more preserved CD4 counts at enrollment, those in our reference group were older, more likely to have TB, and more likely to endorse barriers to health care. Characteristics of Sizanani patients with very low CD4 counts (<100 cells/μL) at HIV diagnosis have previously been described elsewhere . Our demAmong the two groups presenting with low CD4 counts, one group showed improvements in CD4 counts over the study period and one did not. The only measured factor that distinguished these two groups was ART initiation within three months. This finding highlights both the importance of early ART and the ongoing issue of pre-ART loss from care. Previous studies have also highlighted both the poor outcomes associated with delayed ART initiation and the high rates of pre-ART loss from care. A study in Durban in 2006 found that 16% of patients were lost to care prior to starting ART, and among them mortality exceeded 30% within one year . A studyNo other differences distinguished groups 1 and 2, including the number of barriers to care, despite ascertainment of many demographic, clinical, and contextual factors at study enrollment. This may partly be explained by the contradictory ways that contextual factors have been observed to impact HIV care in other studies. For example, while low education was seen as risk factor for loss to care prior to ART initiation in Uganda, having a college or university education was associated with loss to follow-up in Zambia , 26. EmpStrengths of this study include ascertainment of a broad range of demographic, clinical, and contextual factors from patients at the time of HIV diagnosis, and cross-matching study patients with national datasets to improve outcome ascertainment. A limitation of this study is the exclusion of 64% of Sizanani participants from trajectory analysis due to a lack of two CD4 measurements spanning more than one year during the follow-up period. While this loss is large, it is consistent with other studies. In a study of over 12,000 patients newly diagnosed with HIV in South Africa, over a third did not have a single CD4 count measured . In a syThis study found that group-based trajectory modeling adds information to longitudinal HIV data not captured with point-in-time assessments. In our study, we found that after diagnosis, most patients could be characterized by one of four trajectories. These trajectories demonstrated multiple areas for improved HIV care, including earlier diagnosis and improved linkage to care. Further work is needed to identify risk factors for early loss from care and poor ART uptake after diagnosis.


Treat All people with HIV, irrespective of CD4 count. However, people with CD4 counts >500 cells/µL may be asymptomatic and therefore less motivated to adhere to antiretroviral therapy (ART). We aimed to assess whether people initiated with CD4 counts >500 cells/µL had worse treatment outcomes compared to those initiated at lower CD4 counts.The World Health Organisation recommends to Treat All was implemented, and August 2017. We assessed whether initiation CD4 count >500 cells/µL was associated with the outcomes of attrition , and viraemia >1000 copies/mL, by twelve months using Cox proportional hazards and Poisson regression models.We performed a retrospective cohort study among non‐pregnant adults initiating ART at eight public clinics in South Africa between September 2016, when Among 4952 patients initiating ART, the median age was 32.4 years (interquartile range (IQR) 27.2 to 39.7), 58.9% were women and 30.3% had an initiation CD4 count >500 cells/µL. After twelve months, 3382 (68.3%) were retained in care, 303 (6.1%) had transferred to another clinic, 1010 (20.4%) were lost to follow‐up, 232 (4.7%) had a treatment interruption >180 days and 25 (0.5%) were known to have died. Overall, 1267 experienced attrition at a median time of 91 days (IQR 23 to 213), with 302 of these (23.8%) experiencing attrition immediately after their ART initiation visit. Among those in care at twelve months with viral load results, 4.6% had viraemia. In multivariable analysis, the hazard of attrition was similar between patients newly eligible for ART with CD4 counts >500 cells/µL compared to those with CD4 ≤500 cells/µL  0.90 to 1.17). The risk of viraemia was lower among patients with CD4 counts >500 cells/µL compared to those with CD4 ≤500 cells/µL .Treat All in South African public clinics, we found that patients newly eligible for ART with initiation CD4 counts >500 cells/µL had comparable or better outcomes compared to those with lower CD4 counts. These finding support ongoing implementation of Treat All in our setting.After implementation of  In tof LMICs . This coTreat All in public sector settings.Therefore, we aimed to compare outcomes among PLHIV initiating ART at CD4 counts >500 cells/µL, against those with lower CD4 counts, after the implementation of 22.1Treat All in September 2016 [We performed a retrospective cohort analysis using routinely collected data from eight public clinics in KwaZulu‐Natal, South Africa between 1 September 2016 and 30 June 2019. The Prince Cyril Zulu Clinic is a large urban clinic in central Durban, while Bethesda Hospital oversees seven primary care clinics in rural uMkhanyakude District, northern KwaZulu‐Natal. KwaZulu‐Natal has one of the highest HIV prevalences in the world at an estimated 27% among adults aged 15 to 49 [ber 2016 . Prior tber 2016 .2.2We included all adolescents and adults >15 years old who were initiated on ART at the above clinics from 1 September 2016 to 31 August 2017, and followed them up for eighteen months. We excluded known pregnant women from the main analysis, as they have been eligible for ART irrespective of CD4 count since 2013  and have2.3Demographic, clinical and laboratory data for all patients on ART in the South African public sector is routinely recorded at each clinical visit in a standardised clinical chart and subsequently into an electronic register (TIER.net) , from wh2.4The main exposure variable was CD4 count at ART initiation. We included potential confounding variables recorded at ART initiation including age, sex, district, current active tuberculosis, ART regimen and time from first CD4 count to ART initiation, which we used as a proxy for time in pre‐ART care.We used the outcome variable of attrition , by twelve months post ART initiation. We defined attrition as 180 days without a visit, as this definition has been previously validated in a number of settings , 16, 17.For the outcome of viraemia, we used the WHO threshold of >1000 copies/mL. South African guidelines recommend viral load testing at six and twelve months after ART initiation, but in this programmatic setting, not all patients had viral loads taken exactly at these timepoints. Therefore, among patients who were retained in care, we included viral load results taken up to twelve months after ART initiation, and used the result closest to six months.2.5a priori, for an interaction between time in pre‐ART care, and initiation CD4 count, and also performed sensitivity analyses using narrower CD4 count categories, and excluding two clinics with a high proportion of missing CD4 count data.We used descriptive statistics to assess baseline demographic and clinical characteristics, and missing data. We used univariable and multivariable Cox proportional hazard models to test associations between the exposure of initiation CD4 count, and the outcome of time to attrition, adjusted for potential confounders. We selected variables for the univariable analysis and included them in the multivariable model based on data availability and clinical significance. Proportionality was assessed by fitting time‐dependent covariates in a model created by interacting baseline variables with survival time. Among those who were retained in care at twelve months and who had a viral load result, we employed a similar modelling approach, using univariable and multivariable Poisson regression models with robust standard errors, to analyse associations between initiation CD4 count and the outcome of viraemia >1000 copies/mL. We tested, 2.6Approval was granted by the Biomedical Research Ethics Committee of the University of KwaZulu‐Natal for use of routinely collected, anonymized data with a waiver for informed consent.33.1Between 1 September 2016 and 31 August 2017, 5970 adolescents and adults started ART at the eight clinics  patients were missing CD4 data Table . At the 3.2A total of 4952 patients were followed up to end‐point or censoring date over 3933 person‐years at risk, a mean of 290.1 days. At twelve months after initiation, 3382 (68.3%) were retained in care, 303 (6.1%) had transferred care to another clinic, 1010 (20.4%) were lost to follow‐up, 232 (4.7%) had a treatment interruption >180 days, and 25 (0.5%) were known to have died. Among the 1267 who experienced loss to follow‐up, treatment interruption or death, median time to attrition was 91 days (IQR 23 to 213), with 302 (23.8%) experiencing attrition immediately after their ART initiation visit. Of those who had a treatment interruption, the median duration was 224 days (IQR 196 to 288). In univariable analysis there was no association between initiation CD4 count and attrition . In a second sensitivity analysis, there was some evidence that among people with longer time in pre‐ART care, there was a weak association between CD4 count >500 cells/µL and decreased attrition , compared to among people with shorter time in pre‐ART care . Of those with viral load results, 138 (4.6%) had viraemia >1000 copies/mL. In univariable analysis, the risk of viraemia was lower in patients with initiation CD4 count >500 cells/µL, and higher in patients with longer time in pre‐ART care, men, and those not on the standard first‐line regimen of tenofovir, emtricitabine and efavirenz  had a viral load at a median of 187 days (IQR 168 to 212) after ART initiation. The proportion with viral load results was similar between CD4 count groups (>500 cells/µL: 966/1063 (90.9%), ≤500 cells/µL: 1872/2078 (90.1%), 3.4In sensitivity analyses which excluded two clinics containing 69.8% of all missing initiation CD4 counts, 97.2% of patients had initiation CD4 results and we found no meaningful differences in our results Table .4Treat All implementation had similar attrition, and overall better viral load outcomes, compared to those with lower CD4 counts.In this analysis of public sector clinics in a high HIV prevalence setting in South Africa, we found that patients initiated on ART with CD4 counts >500 cells/µL after Treat All implementation, patients initiated with high CD4 counts and in pre‐ART care for a longer time, had slightly lower attrition. We hypothesise that some of these patients remained engaged in pre‐ART care while waiting to become eligible for ART before Treat All implementation, and were therefore more likely to remain in care after they were initiated under Treat All.So far, evaluations of ART treatment outcomes among patients initiated with CD4 counts >500 cells/µL in LMICs have mainly been reported from well‐resourced research settings and large clinical trials of universal ART. For example, early ART initiation was acceptable in a South African research cohort , and adhTreat All implementation. Third, initiation CD4 count was missing for some patients, and these patients had worse outcomes. This could have biased our findings, if patients with missing CD4 counts had a different CD4 count distribution. However, this is unlikely as missing data mainly occurred at two clinics, which had similar CD4 count distributions to the other six clinics. Staff may have placed less emphasis on CD4 count testing as it was no longer required to guide ART eligibility; a phenomenon reported in other programmatic studies of Treat All [Our findings are important as they provide reassurance that in programmatic settings people with high CD4 counts do not have significantly worse attrition, and have better viral suppression, which further supports earlier ART initiation. The inclusion of rural and urban public clinics, which provide care according to South African Department of Health guidelines, also supports the generalizability of our findings. Further strengths of our analysis include the large sample size, assessment of viral load outcomes and use of standard outcome definitions . Our stureat All . Additioreat All .Treat All [. However, among those retained in care in our study, viral suppression was high, which is similar to other LMIC settings [Treat All intensifies, strategies to improve outcomes among these groups will be required.Overall attrition at twelve months was slightly higher in our study 25.6%) compared to older studies in African settings (19.2%)  and occu.6% compareat All . Howeversettings . Furthersettings , 28, 29.5Treat All in eight routine South African clinics, people starting ART with high CD4 counts had similar or better treatment outcomes compared to those with lower CD4 counts. Efforts to improve retention in care and implementation of Treat All should continue in order to achieve 90‐90‐90.In summary, we demonstrate that after implementation of We declare that we have no conflicts of interest.JD, YS, KG and NG conceptualized the study. TK, NM, YS, KG, KM and HN oversaw data collection. TK, NM, KM and HN oversaw curation of the data. JD and NYZ analysed the data. JD drafted the manuscript. All authors critically reviewed and edited the manuscript.aHR, Adjusted hazard ratio; aRR, Adjusted risk ratio; ART, Antiretroviral therapy; CI, Confidence interval; HIV, Human Immunodeficiency Virus; IQR, Interquartile range; LMICs, Low‐ and middle‐income countries; PLHIV, People living with HIV; WHO, World Health Organization.Table S1. Distribution of known CD4 counts at clinics with near complete CD4 count data compared to clinics with high levels of missing dataTable S2. Attrition and viraemia by CD4 count, among patients initiated within six months of HIV diagnosis and patients initiated over six months after diagnosisTable S3. Sensitivity analysis of factors associated with attrition at six public clinics with near complete initiation CD4 count data (n = 4299)Table S4. Sensitivity analysis of factors associated with viraemia at six public clinics with near complete initiation CD4 count data (n = 2678)Click here for additional data file.