HIV infection is responsible for one the most devastating human pandemics. The advent of antiretroviral therapy has changed the course of the pandemic and saved millions of lives. Complex therapeutic regimens have been introduced since 1996 and have contributed to the transformation of HIV infection into a treatable chronic diseases. New types of potent antiretrovirals and their combinations, including “once daily” treatment, have simplified the regimens and diminished side effects. Nevertheless the adherence to antiretroviral therapy remains unsatisfactory and varies between 27 and 80% across different population in various studies, compared with the required level of 95%. The lack of adherence to antiretroviral therapy is a multi-factorial and dynamic process which raises considerable difficulties for long-term follow-up. Current solutions to this problem are complex. These should be applied by a multidisciplinary team and should take into account key features related to both the individual and social factors as well as to the population to whom it belongs . Importantly, adherence should continue to be monitored even in patients known to be compliant. In case of subsequent failure the team should identify the reasons for non-adherence and apply the appropriate methods. Where usual methods have no chance of success, a coordinated package of services also known as “harm reduction” can be offered in order to reduce the risks of transmission. The current article analyses the concept of adherence to antiretroviral therapy, the shortcomings of this medication and the methods that can be applied in practice to increase adherence. Emphasis is placed on the analysis of groups at high risk for HIV infection that currently represent the spearhead with which the HIV pandemic is spreading. The HIV pandemics has affected over 80 million people, half of which have succumbed to the infection. Current estimates indicate that 36.7 million people living with HIV/AIDS receive antiretroviral therapy (ART). The use of highly active antiretroviral treatment (HAART) has led to a major therapeutic success, gradually altering the course of the disease and transforming HIV/AIDS into a chronically manageable disease. The complex principles of HAART have been validated and subsequently applied in the treatment of chronic viral C hepatitis as well as in other chronic diseases. This therapeutic model is based on various combinations of antivirals (ARVs) belonging to different drug classes according to predefined rules. A strict adherence to HAART strategy is required to ensure treatment success.Currently the Joint United Nations Programme on HIV/AIDS (UNAIDS) and the World Health Organization (WHO) strive to achieve the target of 90% treatment coverage for all HIV patients as well as 90% virological success in treated patients UNAIDS, . ReachinThe current chapter reviews the concept of adherence to ART, practical obstacles to a high level of adherence and the appropriate solutions.The first cases of AIDS were described in 1981. At that time the HIV/AIDS infection had a high rate of transmission and was universally fatal. The advent of ART had led to the paramount advance of treating HIV/AIDS as a chronic and controllable infection. Today HIV patients who benefit from correct treatment are estimated to have similar survival rates to uninfected patients  or, on the contrary, to reject or discriminate the patient- Bringing together these 4 key factors represent an extremely arduous process that becomes even more difficult with the passing of time. In this regard, the adherence difficulties of HIV patients to a chronic treatment are common to other chronic diseases such as diabetes, heart or psychiatric diseases.The methods used to quantify the ARV adherence need address the dynamic nature of this concept. In this respect all the phases previously mentioned  should be thoroughly monitored on a long period of time. Using only one method or quantifying only one phase in a restrained period of time has been shown to lead to biased results. Nevertheless, due to the multiple methods of monitoring and to the evolving definition of this concept there is currently no gold standard for measuring adherence rates. Therefore the results frequently differ depending on the chosen methodology. For example, the adherence rates are higher in reports that focus on a short period of time (previous week or up to 4 weeks before starting the study (up to 90–100% adherence) whereas studies on larger time-frames offer a more pessimistic analysis  is an electronic monitoring system involving a wireless pillbox that tracks the exact date and time each time it is opened and closed. The technique is objective and it is more sensitive than self-reports .- This method is only adequate for determining the serum level of recently administered ARVs and offers no indication on previously administered drugs and neither does it help in the event that various ARVs have been periodically discontinued before the current administration.Notably, a study performed on 230 patients followed for 48 weeks suggested a better predictability for pharmacy refill data and electronic devices toward self-reports  of HIV positive patients achieved an adherence rate of 90%  represents an increasing population in the following years. In some areas this group has already reached 50% of the local HIV population UNAIDS,  and is pFemale sex workers represent a vulnerable group with a high and worrisome variability in what concerns the adherence to treatment. In a meta-analysis from 2014, Mountain et al. . NeverthOn the other hand other key groups such as men who have sex with men (MSM) as well as lesbian, gay, bisexual, transsexual, intersex (LGBTIQ) communities exhibit a global HIV prevalence up to 19 times higher than previous groups UNAIDS, . These gIt is estimated that 1 in every 10 new HIV infected patients globally is an injecting drug user (IDU). This key risk-group accounts for the increasing number of new HIV cases especially in Central Asia and Eastern Europe where it designates roughly half of the new cases. Due to drug dependency issues and due to the large diversity of illicit drugs, the management of this population is particularly challenging. The adherence is low even in optimistic studies, citing a 63% adherence at most  and with few interventional possibilities to reverse their deviant behavior , namely “efavirenz/emtricitabine/tenofovir,” “elvitegravir/cobicistat/emtricitabine/tenofovir disoproxilfumarate” and “elvitegravir/cobicistat/emtricitabine/tenofovir alafenamide.”Although the efficacy of ART is indisputable, no antiviral regimen can cure the disease. This aspect is explained by the inevitable resistance that occurs during ART, the HIV integration in the cellular genome and the presence of HIV “sanctuaries” that impede the complete elimination of HIV. Therefore, the goal of ART is to rebuild the immune response, and maintain the plasma viral load to an undetectable level (< 50 copies/mL), thus preventing the progression and transmission of HIV infection. In the absence of correct treatment and adequate prophylactic interventions, infected patients can further transmit the disease.Most of ART regimens of first intention combine two representatives from one ARV class with one of a different class. In this circumstance the total number of recommended tables per day varies from one to six. However, “fixed-dose combination” or “single tablet regimens” are available in few countries only, while low income countries with the highest number of cases continue to rely on regimens that entail a large pill-burden.ART regimens can be divided between “preferred regimens” considered as “first line regimens” that have high efficacy and low toxicity and “alternative regimens” that are usually cheaper but with higher toxicity and higher pill-burden. These classification take into account objective criteria such as the HIV/AIDS status and treatment costs. The ARV regimen once established needs to be strictly monitored in terms of effectiveness and relevant side-effects. It needs to be changed in the case of drug toxicity and ARV resistance. Furthermore various changes can be made depending on the patient . Therefore, ARV regimens need to be continuously changed and adapted to various external factors.Still, the large number of pills is probably the most common complaint of HIV-patients. A meta-analysis performed on studies between 2005 and 2014 shows a significantly higher adherence in patients with a once-daily fixed-dose (“single tablet regimen”) compared to any other treatment regimen . This physical transformation leads to depression and frustration, contributes to a poor self-image and ultimately results in the patient's abandonment of treatment and loss from care . Neuropsychiatric side effects to efavirenz were noted repeatedly as causes of non-adherence.Although these characteristic side effects of protease inhibitors class (PIs). are usually mild, their persistence could determine the refusal and disregard of treatment by children and pregnant women.There are various ARV drugs that target unpleasant effects, persist and worsen on the long-term due to the long-term use of ART. Some effects such as allergic and digestive side effects appear immediately and can be rapidly addressed. If solved promptly these issues do not alter the patient's adherence to treatment. Other side effects, such as lypodystrophy, appear after prolonged use of ART and result in upsetting physical transformations.All these situations require a trusting, efficient and permanent dialog with the health care provider.One example is that of the use of PIs. Efficient serum levels of PIs can be reached only in the presence of certain meals (such as those with a high level of fat). Ignoring these administration constrains leads to therapeutic failure and represents a form of non-adherence that is hard to be recognized. Furthermore the serum level of PIs can be reduced by a concomitant administration of various compounds such as garlic, hypoxis hemerocallidea and hypericum perforatum , sutherlandia  and some vitamins . At the same time, limited access to food is another objective reason for disrespecting the indications of ARVs administration in low-income countries. Otherwise, most dietary recommendations are disrespected and represent a type of non-adherence.Alcohol abuse also impacts adherence either directly  or indirectly by ARV interaction with alcohol consumption and the patient's lack of willingness to stop the alcohol , in which case the patient decides not to follow treatment or involuntarily  in which case the patient does not understand or cannot respect all the indications.Intentional non-adherence arises from a variety of causes such as denial of diagnosis, lack of trust in the health-care provider and in the treatment itself, fear of HIV stigma, restraints due to a life-long treatment, difficulties to integrate the treatment into the daily routine and disappointment due to the impossibility of cure HIV infection.Unintentional non-adherence frequently arises from misunderstanding or ignoring treatment indications. Such examples include the forgetting of doses or the voluntary change of frequency of administration. Predictors of unintentional non-adherence include the cognitive limitations, polypharmacy, the patient's personality as well as comorbidities and associated treatments. Drug and alcohol abuse are important factors leading to a decrease adherence  that could improve adherence in HIV-infected patients.Intentional non-adherence can be prevented through a good communication with the patient, motivational interviewing techniques and psychological therapy. The patient should be aware of the gravity of the disease and of the consequences arising from non-adherence.Unintentional Non-Adherence. Unintentional non-adherence is hard to encounter and needs a complex intervention. The common approaches to maintaining good adherence are listed below:Essentially is the Unambiguous and Thorough Education of the Patient about the Role of Art. In these circumstances the psychologist needs to cooperate with the physician in order to stress the role of ART for an adequate immunologic and virological control. Commonly used methods include educational resources either orally or in a written form according to the patient's level of knowledge. The patients willing to find adequate information on adherence can also use online resources such as http://www.aidsinfonet.org/fact_sheets/view/40561).- The Simplification of Current Regimens. This is a prerequisite especially in patients with multiple comorbidities and poly-pharmacy. In order to overcome the difficulties related to the pill-burden of HAART, HIV specialists have introduced the concept of monotherapy or dual maintenance regimens - drug combinations that entail single or dual drug combinations for some patients  and easy to integrate in the patient's daily routine. Further engaging the patient to devise and to individualize the treatment could help increase the adherence.- Technological reminders could be employed to help the patient to understand the importance of a rigorous schedule for the administration of ART. These tracking devised could be simple  or more complex .- Social protection is mandatory for certain groups , HIV support groups, parental supervision for adolescents etc.) . Harm reduction refers to a coordinated package of services  offered to drug abusers. Since the reduction of drug abuse is a difficult objective, it is considered that such actions could actively reduce the risks of transmission of HIV and other viral co-infections. When applied, these programmes improved the adherence to treatment and these positive results were confirmed throughout long periods of time, exceeding even 10 years in some studies  , difficulties to abandon various habits  and to adapt to ART side effects.The implementation phase (corresponding to “the retention in care” from the “HIV care continuum” model) has received the most intense analysis regarding the adherence. During this period the patient experiences various psychological and social barriers  as well as obstacles related to the costs of the treatment . Unfortunately, some of the obstacles and particularly those related to financial constraints cannot be easily solved and could cause treatment discontinuation (Wanchu et al., Recent debates stress the need to implement monotherapy in restricted HIV populations or to prevent HIV infection through harm reduction programmes. Suppositions that the high efficiency of modern therapy can be attained even with lower adherence rates such as 80% (Viswanathan et al., HIV/AIDS entails one of the most challenging therapies compared with other chronic diseases. The adherence of HIV patients to ART is hard to assess due to the multiple psychological and social implications characteristic to the diverse populations exposed to HIV. Each patient has an individual motivation to follow or not to follow ART. Added to this are factors related to the complexity of the therapeutic regimens, side effects, personal habits, consumption of illicit drugs, depression, other comorbidities or other complications specific for each patient. Adherence management should address to all of these aspects and must have a social, familial, personal and health care involvement. Finally, the adherence issues revolve around so many factors that it is an extremely difficult and complex assignment to achieve the required 95% adherence rate for an indefinite period of time.However, despite the large literature on the low adherence to ART, there are still a number of positive interventional measures that can sustain the patient's hope in a better life. The success of ART is highly dependent on the prospective application of these methods.SI, DI, GJ all contributed to the conceptualization, drafting, and editing of the manuscript. All authors read, critically revised and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Tenofovir (TDF) based regimen was reported to have better immunological outcomes. Unfortunately, there is limited information regarding the immunologic outcome associated with this regimen in Ethiopia, as its routine utilization in this setting begun since 2013.P < 0.05 for slopes of the random effect linear regression was used as indicators for presence of association.A 2 years retrospective cohort study was conducted at Jimma University Specialized Hospital, 346 km Southwest of Addis Ababa, Ethiopia. A total of 280 patients’ data from September 2012 to July 2014 was extracted from records from February 10, 2015 to March 10, 2015. Records were selected using a simple random sampling technique. Data on socio-demographic, clinical and drug related variables were collected; entered into EpiData 3.1 and analyzed by STATA 13.1. Mixed effect linear regression was performed to assess difference in CD4+ change between groups adjusting for baseline characteristics. The change in predicted CD4 count attributed to each regimen was also assessed by marginal analysis. P = 0.753) for TDF and AZT groups respectively. The minimum follow up duration was 7.4 and 8.9 months for TDF and AZT groups respectively. Most of TDF (93.6%) and AZT (91.4%) groups completed their follow up, 5 (3.6%) TDF and 6 (4.3%) AZT groups died and 4 (2.9%) TDF and 6 (4.3%) AZT groups were lost for follow-up (P = 0.769). There was statistically significant difference in immunologic recovery between the groups  over time. The predicted CD4+ count for TDF/3TC/EFV was  whereas that of AZT/3TC/EFV was .The mean (SD) duration of cohort follow up was 714.2 (69.6) and 708.8 (78.9) days  in this set-up among TDF users. Around 1980s, Acquired immunodeficiency syndrome (AIDS) was globally emerged as a major public health threat. The reaction against it has led to unprecedented attention and commitment from the international community to improve access to human immune virus(HIV) care, antiretroviral treatment (ART) and prevention . The intCurrently, there are more than 20 ARV compounds approved for use in United States (US) and Europe. Multiple adult HIV treatment guidelines recommend the nucleos(t)ide reverse transcriptase inhibitors; AZT or TDF based regimens and most are in favour of TDF based regimens as the safer regimen for patients with no contraindication due to its proven effectiveness, favourable toxicity profile, and demonstrated regimen durability , 7–9.Safe and efficacious ART regimens improve patient care through rapidly restoring the immune cells, promoting adherence and alleviating the hazards of mortality , 10, 11.Studies from developed regions showed that there were 18.0 and 18.8% immunologic failures in the EFV/FTC/TDF and EFV/3TC/AZT arms, respectively. There were no significant differences in the risk of HIV-1 disease progression or death . In otheThe study was conducted at Jimma University specialized Hospital which is located in Jimma town; Jimma Zone, 346 km Southwest of Addis Ababa, Ethiopia. The hospital has separate ART clinic with about 7486 clients. The ART clinic provides HIV and TB treatment and care. Patient data from September 2012 to July 2014 was extracted from records from February 10, 2015 to March 10, 2015.A retrospective hospital based cohort study was conducted on adult patients who were on TDF and AZT based regimens and fulfilled inclusion criteria. The study was conducted by dividing the total sample into two groups: TDF and AZT groups.We included patients who were older than 14 years, have at least 6 months follow-up, whose records were legible and complete, and who have at least baseline and sixth month CD4 count. We excluded pregnant women from the study because there is significant pharmacokinetic change that is enough to impact the treatment outcome in this group of population. Those whose regimen was changed were also excluded from the study.Sample size determination was guided by the number of patients on TDF/3TC/NVP where only 70 patients fulfilled the inclusion criteria. Patients from other regimens were selected based on the size of this group to satisfy 1:1 ratio of AZT to TDF group. Therefore, frequency matching was used to select a total of 280 subjects (140 TDF group and 140 AZT group). Records were selected by simple random sampling technique using computer generated random numbers.Data on demographic, clinical, laboratory, drug administered, comorbidities and adherence were collected by record review using English version checklist which was prepared after reviewing different relevant literatures. Baseline body mass-index of the subjects was calculated after collection of baseline height and weight of the patient from patients chart. Data from antiretroviral drugs sheet and patient information sheet were collected by pharmacists, while nurses collected data from ART intake and follow up forms.Data were double entered into Epi-Data 3.1 and exported to STATA 13.1 for cleaning and analysis. Descriptive analyses were performed and results were presented by text, tables and charts. Bi-variate and multivariable mixed effect linear regression for repeated measurements were performed to assess adjusted effect of the ART regimen and identify additional predictors of CD4 recovery. Coefficient of mean CD4 count with 95% confidence intervals was used as measure of strength of association and P < 0.05 was considered to declare a statistical significance. Marginal analysis was also conducted to see the difference among specific regimen category.A total of 1034 patients were on antiretroviral therapy (ART) for at least 6 months during the study period. Nine hundred eighty six had complete CD4+ count at 6 month of treatment. Fourteen records were used for pre-test, 22 and 110 records were excluded because of pregnancy and regimen change respectively. Only 70 patients remained on TDF/3TC/NVP and this governed the sample selection  for TDF and AZT groups respectively. The minimum follow up duration was 7.4 and 8.9 months for TDF and AZT groups respectively. Most of TDF (93.6%) and AZT (91.4%) groups completed their follow up, 5 (3.6%) TDF and 6 (4.3%) AZT groups died and 4 (2.9%) TDF and 6 (4.3%) AZT groups were lost for follow-up (P = 0.769).The cohort was followed for 2 years. The overall time the cohort was at risk was 539.39 years. The cohort contributed to a total of 2.74/100 and 2.72/100 person-years of follow-up for TDF and AZT groups respectively. The mean (SD) duration of follow up was 714.2 (69.6) and 708.8 (78.9) days (2 with mean (SD) of 19.7 (3.4) and 20.4 (3.0) respectively. Larger proportion of TDF (48.6%) and AZT (41.5%) groups were employed. Majority of TDF (69.3% and AZT (78.5%) groups were urban. Concerning alcohol use, most of TDF (80.7%) and AZT (72.9%) groups had history of alcohol use. Regarding between groups comparison of distribution of baseline socio-demographic and behavioural characteristics of patients, there was statistically significant difference between groups only in terms of religion (Table Majority of TDF (64.3%) and AZT (66.4%) groups were females. Majority of TDF 77.1%) and AZT (85.9%) groups were in the age group 25–45 years with mean (SD) of 32.3 (7.4) and 32.3 (9.2) years respectively. Majority of TDF (62.9%) and AZT (73.6%) groups had BMI ≥ 18 kg/m% and AZT3 with mean (SD) of 164.64 (83.36) and 175.21 (89.14) respectively. There was statistically significant difference between groups in terms of baseline CD4 count. Leading percentage (33.6%) both TDF and AZT groups were in WHO clinical stage III and II respectively. Most of TDF (78.6%) and majority of AZT (56.4%) groups had working functional status and there was statistically significant difference between groups. Twenty (15.3%) and 17 (12.1%) of patients were treated for TB from TDF and AZT groups respectively. CPT was prescribed for most of (87.9%) and nearly all of (92.14%) patients in TDF and AZT groups respectively, whereas INH was prescribed for only 26.4 and 21.5% of patients in TDF and AZT groups respectively (Table Majority of TDF (65.7%) and AZT (53.9%) groups had baseline CD4+ count <200 cells/mmThe mean change in CD4+ over study period is shown by Fig. At 6 month, the overall proportion of sub-optimal CD4+ response (net CD4+ gain <50 cells/µl) was 23.95% . Earlier at the initiation of ART, the CD4+ count showed a linear trend but it becomes more flat after 18th month with a very minimal gain irrespective of the regimen.Considering consecutive CD4+ count as an outcome variable, multilevel mixed effect linear regression was performed Table . The slo3  with the conditional correlation coefficient of 64.9%, i.e. 64.9% of the variability in CD4+ count between two visits was explained by unobserved patient specific factors. Among these, 38.99% of the variation in CD4+ change was explained by differences in the regimens where as 25.34% of the variation is attributed to other regression variables (P < 0.001), showing an important heterogeneity between patient groups.Accordingly, the average gain in CD4+ count achieved at every visit among the cohort was 38 cells/mm, P = 0.032).In the overall analysis, keeping other factors constant, older age was found to be one of the negative predictors of CD4+ count change. So younger patients (age <25 years) were found to have +66 gain in CD4+ count every 6 months as compared to those aged ≥45 years (B = −66.19 95% CI 2 had a significantly higher CD4+ change (+32 cell/mm3) over time than those who had BMI < 18.5 kg/m2 .Among the predictor variables, female sex was strongly associated with progressive CD4+ count gain at each visit. So, females had +39 CD4+ cells advantage over time  as compared to males. Patients with BMI ≥ 18.5 kg/mBaseline CD4+ count was also another independent predictor for CD4+ advantage over time . More importantly, patients in TDF group had a significant CD4+ count gain per visit compared with their AZT counterparts .In this study, other baseline patient factors such as WHO clinical stage, TB treatment, educational status, place of residence, religion, occupational status, marital status, alcoholic use and prophylaxis had no significant association with CD4+ change.To predict the expected change in CD4+ count in both groups at the end of treatment period, post-estimation marginal analysis was conducted.3 for patients treated with TDF/3TC/EFV and TDF/3TC/NVP respectively. In AZT group, the predicted mean CD4+ count changes were 319.11 and 281.54 cells/mm3 for patients treated with AZT/3TC/NVP and AZT/3TC/EFV respectively. These figures were exactly the expected increase in CD4+ count associated with each regimen and has a crucial clinical implication in guiding clinicians to choose which regimen to initiate on as the role of good immunologic recovery in treatment of HIV infection is multidimensional. So, this section of analysis . At first 6 months, majority of sub-optimal immunologic responders belonged to TDF/3TC/EFV (30%) and lowest proportion of sub-optimal immunologic responder was observed among AZT/3TC/EFV (17.9%).3) followed by AZT/3TC/EFV (237 cells/mm3) at 96 weeks. Another finding from Nigeria indicated that TDF/3TC/NVP is much more inferior (208 cells/mm3) to AZT/3TC/NVP (221.1 cells/mm3) at 12 months of therapy  in whiB = 0.879 95% CI , P < 0.001). This finding is consistent form study by Lawrence et al. , P = 0.001). This study is consistent with most of the previous findings that described TDF based regimens with better immunologic outcome [From this study, patients randomized to TDF group had a significant CD4+ count advantage per visit relative to patients randomized to AZT group ( outcome , 31, 32.3 and patients with pre-treatment BMI < 18.5 were poor immunologic responders, they need special attention while delivering care and treatment. However, the prevalence of sub-immunologic recovery among the TDF users in the resource constrained settings needs to be assessed further.The results of this study suggest that TDF based regimens especially, TDF/3TC/EFV had excellent immunologic recovery followed by AZT based NVP. Since aged patients, those with baseline CD4+ count <200 cells/mm


HIV care do not take into account that the frequency of attendance is related to changes in treatment and health status. This study developed a new measure of engagement in care (EIC) incorporating clinical factors.Commonly used measures of engagement in HIV physicians to identify factors associated with the timing of patients' next scheduled appointments. These factors informed the development of an algorithm to classify each month of follow‐up as “in care” (on or before the time of the next expected attendance) or “out of care” (after the time of the next expected attendance). The EIC algorithm was applied to data from the UK Collaborative HIV Cohort (UK CHIC) study, a large clinical cohort study.We conducted semi‐structured interviews with eight AIDS diagnosis, treatment status, CD4 count and viral load). The resulting EIC algorithm was applied to 44 432 patients; 83.9% of the 3 021 224 person‐months were “in care”. Greater EIC was independently associated with older age, white ethnicity, HIV acquisition through sex between men, current use of antiretroviral therapy (ART), a higher nadir CD4 count, later calendar year and being seen at the clinic for the first time within the last year.The interviews indicated that time to next appointment varied depending on psychosocial and physical comorbidities, and clinical factors (time since diagnosis, HIV care incorporates a time‐updated measure of patients' treatment and health status. It adds to the options available for measuring this key performance indicator.This algorithm describing engagement in  The introduction of combination antiretroviral therapy (ART) has led to a dramatic reduction in HIV‐associated morbidity and mortality Engagement in out‐patient HIV care is therefore a key measure of quality performance for HIV service providers There is no gold standard measure of engagement in HIV out‐patient care. While each of the above measures has its own strengths and weaknesses The Retention and Engagement Across Care Services for HIV (REACH) study set out to better understand HIV out‐patient attendance in order to develop cost‐effective interventions to optimize engagement in care (EIC). Taking into account that the frequency of monitoring is dependent on treatment and health status, and as gaps between clinic visits may vary quite considerably within the current guidelines Exploratory, semi‐structured, face‐to‐face interviews were conducted with eight HIV physicians with a range of clinical experience selected from five HIV out‐patient clinics in inner and outer London where the prevalence of HIV is high The interviews, which were conducted by AH, took 25–30 min and were recorded verbatim. Physicians were asked to describe the factors that prompted the timing of the next scheduled appointment for the last ten patients that they had seen: specifically, they were asked when they had asked to see the patient again (number of weeks/months) and why. Interviews took place from November 2013 to February 2014 and the findings therefore reflect guidelines in place at the time spss statistics 22  to produce a cross‐tabulation of time to appointment by factor. The findings from this analysis informed the development of an algorithm to measure EIC that was refined iteratively to the precision required for programming.We conducted a content analysis sas 9.3 . UK CHIC collates routine data on HIV‐positive people, aged 16 years or older, who have attended some of the largest HIV clinics in the UK since 1 January 1996. For this analysis, we included all patients who attended a participating UK CHIC clinic on two or more occasions between 1 January 2000 and 31 December 2012. In the absence of complete data on clinic attendances, CD4 counts, viral loads, haemoglobin measurements and ART start or switch dates were used as markers of clinic attendance. Follow‐up for each person was considered to continue until the last recorded laboratory marker or clinic visit prior to (or on) 31 December 2012.The algorithm was applied to data from the UK Collaborative HIV Cohort (UK CHIC) study and analyses were performed using Individuals may often have repeat laboratory tests performed within a short time interval to confirm unexpected findings, and this may result in clusters of measurements around a single “index” date. For our analysis, we did not want to consider each of the measurements within a cluster as independent visits, as only the index visit would have been scheduled at the previous visit. Thus, we grouped attendances into “care episodes”, defined as months (period of 30.4 days since entry into the study) where at least one visit occurred. For each care episode, we then established the lowest CD4 count measured in that month , the highest HIV viral load  and the patient's treatment status, and used this information to establish a likely date of next scheduled visit using our algorithm , ethnic group , mode of HIV acquisition , whether currently on ART, nadir and current CD4 counts , participating clinic, calendar year  and time since entry in the study . Note that we did not consider follow‐up after the patient's last reported care date, and therefore this algorithm focuses on intermittent periods of disengagement rather than ultimate loss to follow‐up after the person's last clinic visit. Each patient‐month was then treated as a separate entry in a multivariable logistic regression model with the aim of identifying demographic and clinical factors associated with that month being “in care”. These models were fitted using A total of 73 patients were discussed in the physician interviews. One patient was not included in the analysis because their next appointment was dependent on awaited test results. The time of the next scheduled appointment was missing for another patient and not available for a further five patients who had not attended their last scheduled appointment at the time of the physician interviews.The time of the next scheduled appointment in the remaining 66 patients ranged from 1 week to 6 months, with a median of 3 months. While physicians were acting within the current guidelines, they described the reasons for this variation in the timing of the next scheduled appointment. Five factors were identified from the content analysis of the interview data as instrumental. These factors were summarized as “routine” where patients were stable and required routine follow‐up, “virological” where the next appointment was based on change in viral load , “treatment” where the next appointment was related to starting ART or changing an existing ART regimen, “psychosocial” where mental health or psychosocial issues were identified as instrumental, and “physical comorbidities” where a range of physical comorbidities were given as the key reason for the timing of the next appointment.One‐third of patients were described as stable and given routine follow‐up appointments 4–6 months after their last visit. Routine follow‐up for one pregnant woman was arranged for 3 months' time. Physicians talked about extending routine visits to every 6 months when patients were well and stable, both on treatment and in their psychosocial circumstances. Changes in viral load brought the next scheduled appointment forward to 1–2 months after the last. Patients who were starting or changing treatment were given a next appointment date between 2 and 12 weeks later, depending on the treatment start date and virological response or when treatment was planned to start. Follow‐up appointments of between 1 week and 4 months later were arranged depending on a range of psychosocial issues  and comorbidities: both of which required earlier follow‐up when patients were often otherwise stable on treatment.We used the data from the physician interviews on the timing of next appointments as the basis for developing the EIC algorithm. Although psychosocial wellbeing and comorbidities were key factors in determining the expected time between patient visits to the HIV clinic, data on these variables are not generally captured electronically and are not often available in routinely collected cohort data. Thus, we used clinical data  only to determine the patient's treatment and health status. This was used to estimate the expected time to the next scheduled care episode, in accordance with the data collected in the physician interviews Table . The EICAccording to the EIC algorithm, the shortest expected gap between care episodes was 2 months. This is to allow for the fact that clinic visits might occur at any point during the month or care episode into which they are grouped. If the patient was within 1 month of diagnosis, had an AIDS diagnosis, or started ART or changed ART at the initial care episode, the next care episode was expected within 2 months. If the patient was not on ART at the initial care episode, the next care episode was expected within 2–6 months, depending mainly on CD4 count. If the patient had started ART, it was expected within 2–6 months, depending on viral load. We used 6 months as the maximum time between visits, as described in the physician interviews. If more than one condition applied at the time of the initial care episode, the next care episode was expected within the least number of months associated with those conditions.Fig. A total of 44 432 patients from UK CHIC (2000–2012) were included in the following analysis. Women represented 27.8% of the sample. Half were white (53.3%), one‐third were black African (28.9%), 8.7% were of other ethnicity and 9.2% had unknown ethnicity. Around half had acquired HIV through sex between men (50.5%), with 39.1% acquiring HIV through sex between men and women, 3.0% through injecting drug use and the remaining 7.4% through other or unknown routes. Their median age at entry into the study was 36 years [interquartile range (IQR) 30–42 years] and the median date of follow‐up start was December 2004 (range January 2000 to October 2012). The median CD4 count at start of follow‐up was 355 (IQR 214–520) cells/μL; patients were followed for a median of 61 (range 2–156) months with a total follow‐up of 3 021 224 patient‐months.Overall, patients were engaged in care for 83.9% of the total follow‐up of patient‐months. Table We have developed an algorithm which provides a flexible new approach to measuring engagement in out‐patient HIV care. It is, to our knowledge, the first measure that adapts to the changing treatment and health status of the patient, reflecting the reality described to us by physicians and giving it strong face validity The algorithm provides a dichotomous measure for each month of follow‐up as to whether the patient is in care or out of care. Poor EIC during the first year after diagnosis is associated with a higher rate of mortality We found that patients were engaged in care for 83.9% of months over a follow‐up period of up to 12 years. Consistent with findings from an analysis of loss to follow‐up in the annual Survey of Prevalent HIV Infections Diagnosed in England, Wales and Northern Ireland The EIC algorithm was developed from interviews with physicians who indicated that the timing between appointments is dependent on a range of factors. The interviews clearly illustrate that there is no one‐size‐fits‐all when it comes to the timing of HIV clinic appointments. Patients stable on treatment were seen for routine care every 4 months which was extended to every 6 months, as appropriate for the individual under care, guided by the therapeutic relationship. We have used 6 months as the maximum time between routine visits in the algorithm, as described by physicians in accordance with the UK guidelines for routine monitoring The majority (90%) of people who are being seen for HIV care in the UK are on ART In common with other analyses of EIC using HIV cohort data, we have used laboratory data and ART start dates as surrogate markers of clinic visits. It is possible, therefore, that we may have missed some visits where no laboratory test was performed. Further analyses of data from the group of clinics that are able to provide more detailed information on attendances will allow us to validate this approach. We grouped visits into care episodes to negate the effect of repeated laboratory measurements within short time intervals.We censored the data at the last recorded visit and, while our measure does not therefore include any ongoing periods of loss to follow‐up, it would be possible to incorporate this into the algorithm. It should also be noted that any algorithm is clearly only an approximation to a far more complex clinical process and it is difficult in an observational cohort setting to incorporate other factors, such as social factors, that may lead to more regular scheduled visits. This is, however, likely to result in an under‐estimation of EIC rather than an over‐estimation. While our algorithm has these limitations, we have created a measure of engagement in HIV care that will benefit from the advantages of using these data EIC is a key quality performance measure for HIV service providers and it is important that it is captured in a way that reflects whether patients are attending as frequently as indicated by their clinical needs. We have presented a concept of how to measure engagement in HIV care by incorporating a time‐updated measure of patients' treatment and health status and a prototype of this measure that we have tested on HIV cohort data. The EIC algorithm adds to the options available for measuring engagement in HIV care, and assessing this key performance indicator.


Baseline plasma samples of 490 randomly selected antiretroviral therapy (ART) naïve patients from seven hospitals participating in the first nationwide Ethiopian HIV-1 cohort were analysed for surveillance drug resistance mutations (sDRM) by population based Sanger sequencing (PBSS). Also next generation sequencing (NGS) was used in a subset of 109 baseline samples of patients. Treatment outcome after 6– and 12–months was assessed by on-treatment (OT) and intention-to-treat (ITT) analyses. Transmitted drug resistance (TDR) was detected in 3.9% (18/461) of successfully sequenced samples by PBSS. However, NGS detected sDRM more often  than PBSS  (p = 0.0001) and major integrase strand transfer inhibitors (INSTI) DRMs were also found in minor viral variants from five patients. Patients with sDRM had more frequent treatment failure in both OT and ITT analyses. The high rate of TDR by NGS and the identification of preexisting INSTI DRMs in minor wild-type HIV-1 subtype C viral variants infected Ethiopian patients underscores the importance of TDR surveillance in low– and middle–income countries and shows added value of high-throughput NGS in such studies. Antiretroviral therapy (ART) has been widely accessible since 20053. The first-line consists of fixed-dose combinations (FDC) of two nucleoside/nucleotide reverse transcriptase inhibitors  or tenofovir (TDF) plus lamivudine (3TC) or emtricitabine (FTC)), and a non-nucleoside RTI  or nevirapine (NVP))4. Prevention of mother-to-child transmission (PMTCT) was launched in 2003 using single-dose nevirapine (sdNVP). In 2014, 360,000 patients were estimated to receive ART5. However, more than a quarter of Ethiopian patients are lost-to-follow-up (LTFU), in some regions up to 40%6. Also, the absence of monitoring of viral load and the limited availability of second-line ART, can be expected to contribute further to a high rate of therapy failure with drug resistance, as seen in other low and middle income countries (LMIC)8.Ethiopia is heavily affected by the human immunodeficiency virus type 1 (HIV-1) epidemic with an estimated number of 700,000 infected persons, although the adult prevalence has decreased to 1.1% in 20169. In Ethiopia, there are no data so far of transmitted drug resistance (TDR) or PDR at the national level, except very limited information from some parts of the country. A study from Addis Ababa using a sensitive allele-specific polymerase chain reaction reported a 6.5% TDR prevalence10 and two studies from Northwest Ethiopia reported a 3.3%11 and a 5.6% TDR prevalence, respectively12. Due to this very limited information about the situation in Ethiopia with regard to HIV drug resistance, we assessed TDR by population-based Sanger sequencing (PBSS) among ART naïve patients, included in a large nationwide cohort study, and compared the results with next-generation sequencing (NGS). Thus, none of our patients were known to have been treated with ART before inclusion in the study. In addition, due to the recent introduction of integrase strand transfer inhibitors (INSTI) in certain African countries, we also analysed the NGS results for INSTI associated drug resistance mutations (DRM).A recent report from WHO revealed a global increase in pretreatment drug resistance (PDR)Among the 874 ART naïve HIV-1 infected patients enrolled in the study, 676 and 459 had VL data at month six and 12, respectively. Ninety (13.3%) and 61 (13.3%) had VL ≥150 copies/ml (detection limit of the assay) and 57 (8.4%) and 34 (7.4%) had VL ≥1000 copies/ml (WHO definition of virologic failure), respectively.As described in the methodology section, baseline samples of randomly selected 490 patients  were tested for PDR by PBSS and assessed mutations associated with NRTI−, NNRTI−, and PI− drug classes. In addition, baseline samples of 109 virologic treatment failure (n = 71) and virologic suppressor (n = 38) patients were analyzed by NGS , where PDR associated with NRTI-, NNRTI-, PI- and INSTI- drug classes were considered  were still on treatment at month six and the remaining were either LTFU (n = 33) or dead (n = 49) Fig. . Plasma pol-sequence was obtained in 461 out of 490 (94%) samples at baseline, 47 out of 51 (93%) at month six and 30 out of 33 (91%) at month 12  of the 461 patients with sequence data had sDRM   after month six and 12 than those without RTI-sDRM . Also when the WHO treatment failure definition (VL >1000 copies/ml) was used, those with RTI-sDRM had higher odds of failure both at month six and 12 . In the ITT analysis, patients with RTI-sDRM had significantly higher treatment failure rates at the six months, for both the 150 and 1000 copies/ml cut-off, than those without the mutations , but not at month 12 .At month six, 47 sequences were obtained from 51 patients who had a VL >1000 copies/ml and attempted for sequencing. Of those, 37 (79%) had one to seven major NRTI and/or NNRTI DRMs, and no major PI DRM (NRTIs + NNRTI: 25 (68%); only NRTI: seven (19%); only NNRTI: five (14%))  had undetectable viremia Table .All NGS attempts were successful and baseline sequences were thus obtained from 109 patients. Patients with virological treatment failure (n = 71) had lower CD4+ T-cells at baseline than the virologic suppressors (n = 38) . No significant differences were found for other biological and demographic parameters in relation to the virologic treatment outcome.Altogether NGS detected DRM at baseline in 28 patients . NGS detected RTI or PI sDRM (>1% frequency) significantly more often  than PBSS  (p < 0.0001). In addition, INSTI DRM was found in five subjects.The NGS DRMs (range one to three) were found in 23 (32.4%) of the 71 patients who at month six and/or 12 had a virological failure (>1000 copies/ml)  , Q148R , Q148H , and T66I   significantly more often  than PBSS   Table . PBSS faNext we checked whether sDRM detected by NGS appeared at virological treatment failure (>1000 copies/ml) at month six and/or 12, as determined by PBSS Table . Among 114. Analysing 461 pol sequences by PBSS, we found a low frequency, 3.9%, of treatment-naïve patients with sDRM. In a selected sub-set of 109 patients, additional DRMs were found by NGS, including major INSTI DRMs in five patients. Patients with TDR failed therapy more frequently both in OT and ITT analysis, suggesting a clinical impact of these mutations.The present study is the first countrywide representative survey of transmitted drug resistance (TDR), based on the first large national ART cohort study in Ethiopia9. In addition, it should be noted that our patients had low CD4 cell counts at start of ART and were most likely not newly infected. Therefore, the TDR rate might be underestimated in our study since some drug resistant variants frequently disappear from the major viral population after a period of no ART. The increase has been steepest in east Africa up to a 7.4% prevalence eight to nine years after rollout of ART. An update until 2016, but now including all PDR, confirms this trend and the predictions of the prevalence of NNRTI PDR for 2016 were 11% (95% CI 7.5–15.9) and 15.5% (95% CI 7.7–28.8) in Southern- and Eastern-Africa, respectively9. Data from Ethiopia was however not included in these reports. Smaller and regional studies using PBSS have reported low frequencies, 3.3% in 200311 and 0% in 200515, which increased in later studies, 5.6% in 200812, and 7.2% in 201016. Our nationwide data from 2009–2011 in a larger number of patients did not however suggest an increasing trend of TDR in Ethiopia up to then.By PBSS, NRTI and NNRTI sDRM were found as expected, but also non-polymorphic accessory PI sDRM in two patients, despite the infrequent use of PI in Ethiopia in 2009–2011. An inclusion criterion in the ACM cohort was self-reported no earlier use of ART. If correctly self-reported, the prevalence of TDR was 3.9% and no regional difference within Ethiopia was observed. However, it shall be emphasized that the patients were recruited in 2009–2011 and that the present situation of pretreatment resistance (PDR) may have been changed. TDR in LMIC has increased, primarily NNRTI TDR, over time in sub-Saharan Africa (SSA)10. Thus, additional DRMs were detected in 17 patients selected for the NGS assay. Of these, mutated viral populations representing more than 20% were found in four patients represented, which should have been possible to be able to detect with our PBSS assay. Although the selection of these patients were biased, the discrepancy between PBSS and NGS suggests that NGS facilitates detection of HIV-1 sDRMs in LMICs and reveals a higher prevalence of PDR to the same or lower cost if high-throughput approaches are used17.A higher number of sDRM was identified by NGS, which is in line with our earlier report of a high detection rate (6.5%) of NNRTI TDR in Addis Ababa, 2009–2010, using a sensitive allele-specific PCR18. Interestingly, in our study major INSTIs mutations  were found in five patients albeit at a low abundance. At the time when the study started (2009–2011), to our knowledge, no patient in Ethiopia had been treated with an INSTI and still these drugs are not an integrated part of the Ethiopian ART regimes. It cannot be excluded that INSTIs DRMs have been introduced in Ethiopia through patients who have been treated outside the country. However, our phylogenetic analysis showed no clustering of the strains with INSTIs DRM and the patients came from five different study sites all over Ethiopia. It seems therefore unlikely these strains have been transmitted from INSTI treated subjects. Also, we found no evidence of cross-contamination of INSTI-resistant strains in our laboratory, which is strictly separated from the clinical diagnostic laboratory. A possibility is that wild-type HIV-1C strains in Ethiopia may harbor low abundance of INSTI DRMs. All of the identified DRMs alone or in combination associated with resistance to raltegravir and/or elvitegravir.In a study conducted on small number of patients (n = 45) from Gondar, Ethiopia recruited in 2008, using PBSS, no major INSTI DRM was found20. Our finding warrants therefore expanded analysis of minor quasispecies with regard to INSTI DRMs in different African patient populations in order to identify how often such low abundance DRM can be find.Recently, dolutegravir (DTG) has been planned to be used in some African countries, as fixed dose combination given once daily. Importantly, the INSTI DRM E138K contributes to reduced susceptibility to DTG in combination with other INSTI DRM. Also, Q148R and Q148H are associated with low-level or intermediate resistance to DTG, which should be administered twice daily if these DRM are present. A similar pattern is found for cabotegravir and bictegravir22. E.g. the E157Q mutation has been reported in 1.7% and 5.6% of viral sequences from ART-naïve patients, depending on subtype23 and been implied to affect treatment response24. On the other hand, low abundance INSTI DRMs were not shown to have impact on treatment outcome22. However, these latter studies used allele-specific PCR detecting a significantly lower proportion of mutated virus than our NGS method, which has 1% cut-off. Therefore, a potential clinical impact of our findings still remains to be evaluated.The impact of preexisting INSTI DRMs on clinical treatment response has been discussed earlierpol-sDRM failed ART more frequently at month six. Also additional sDRM were identified pre-ART with the NGS assay. A dose-effect association between the level of low-abundance NNRTI-resistant mutants and a 5% threshold of mutant frequency has been suggested to be clinically relevant25. In our study, the number of patients with NGS sDRM was too small to allow identification of a threshold. However, among 16 patients who failed at month six, only sex out of 25 NGS NRTI or NNRTI sDRM at baseline were detected at month six by PBSS. All these six sDRM had been detected at a high proportion at baseline. The lack of detection of the minor sDRM in the follow-up samples could possibly indicate they had a limited or no impact on the emergence of drug resistance at the follow-up time points. However, further study is recommended to assess their impact as a secondary mutation for the emergence of DRM.Patients with baseline In conclusion, we have analysed TDR in the largest nationwide Ethiopian cohort so far and found that in 2009-2011 the rate was still low, 3.9%, using PBSS, but TDR before treatment was associated with a poorer treatment outcome. Also, our NGS results showed that the rate of 3.9% is an underestimation although we could not confirm that the low abundance DRM had a clinical impact. Interestingly, we identified preexisting INSTI DRM in wild-type HIV-1C from treatment naïve patients. Our data shows the importance of surveillance for TDR and PDR in LMIC and suggests an added value of using high-throughput NGS in such studies.4. The subjects were from seven universities14, distributed geographically all over the country: Tikur Anbessa Specialized Hospital in Addis Ababa- Central region; Gondar– Northwest; Jimma– West; Mekelle– North; Harrar– East; Hawassa– South; the Army unit providing service to mobile military staff, which is located in Addis Ababa  of ART in Ethiopia cohort, and started ART, as per the national guidelineaba Fig. . Our stu® HIV-1 Nucleic Acid Sequence-Based-Amplification (NASBA) (BioMérieux Diagnostics) with a detection limit of 150 HIV-1 RNA copies/ml. CD4 T-cell count was determined at the hospital laboratories by BD FACSCalibur machines . Data was entered into a site database and later uploaded to the central database at EHNRI, from which the following data were extracted: sex, age, WHO clinical stage, ART regimen, CD4 cell count and VL.Clinical and routine laboratory tests were performed at the study sites. Ten ml whole blood was collected and processed for each patient at baseline, month six and 12. Plasma samples were centrally stored at the Ethiopian Health and Nutrition Research Institute (EHNRI) at −80 °C after transport on dry ice. Quantification of VL was performed by NucliSENS easyQ® RNA extraction mini-kit . cDNA synthesis was done using RevertAid H-minus reagents . The first-round PCR was done using JA203F-C (forward) and JA206R-C (reverse) primer pair, followed by the second-round PCR, using JA204F-C (forward) and JA205R-C (reverse) primer pair26. The amplified fragments were purified  and sequenced with JA204F-C and JA205R-C PCR-primers plus PR2R (5′-GGATTTTCAGGCCCAATTTTTG-3′) and RT07 (5′-AAGCCAGGAATGGATGGCCCA-3′). This method has been used extensively at our laboratory. Positive PCR reactions are obtained in 100% of plasma samples containing the equivalent of 500 HIV-1 RNA copies per PCR reaction. In practice the assay gives positive results in the vast majority of plasma samples containing >500 copies/ml with a sensitivity to detect 20% mutated variants in the viral population. A comparison between the original assay26 and our slightly assay modified with primers specifically designed for HIV-1C has shown equal results.PBSS was attempted on 490 baseline samples as well as on 51 and 33 samples with VL ≥1000 copies/ml at month six and 12, respectively. HIV RNA was extracted from 140 µl plasma using the QIAamphttp://www.mbio.ncsu.edu/bioedit/bioedit.html). Primary DRM were identified by the calibrated population resistance tool (http://cpr.stanford.edu/cpr.cgi) at Stanford HIVDR Database. Acquired DRM were identified by the Stanford HIVdb Program (hivdb.stanford.edu). DRMs associated with NRTI-, NNRTI-, and PI- drug classes were considered in this assay.Sequences were aligned, edited and analysed using the BioEdit software version 7.2.6.1  covering Gag-pol was amplified, gel purified, and fragmented on the Coveris S200 followed by library preparation using NEBNext UltraTM DNA library Prep Kit. Forty-eight libraries were then pooled at equimolar (10 nM each) and run on Illumina HiSeq. 2500. The FASTQ file was demultiplexed and the consensus sequence was created for each sample followed by realignment again with the consensus sequence as input. The variant calling was performed at amino acid (AA) level. Only AA covering 5000× per position was considered quality passed. Based on the error calculation generated by PCR and NGS, any mutation >1% was considered. WHO list of DRM for surveillance of TDR was used to interpret sDRM for NRTIs, NNRTIs, PIs, and the Stanford drug resistance summaries for INSTIs (hivdb.stanford.edu).NGS was performed on 109 baseline samples of all patients, who had viremia at month six and/or 12 (n = 71), and from randomly selected patients with undetectable viremia (n = 38), as describedhttp://www.hiv.lanl.gov/content/sequence/RIP/RIP.html), REGA HIV Subtyping Tool v3, (http://dbpartners.stanford.edu:8080/RegaSubtyping/stanford-hiv/typingtool) and COMET HIV-1 (http://comet.retrovirology.lu). Maximum likelihood phylogenetic analysis was performed using Molecular Evolutionary Generics Analysis version 7.0 (MEGA 7) software.Subtyping was done by Recombinant Identification Program  and intention-to-treat (ITT) approaches. In the OT analysis, two VL cut offs were used for the definition of virological treatment failure; >150 copies/ml and >1000 copies/ml, respectively. For ITT, treatment failure was defined as either failure to attain undetectable viremia (either <150 copies/ml or <1000 copies/ml), LTFU or death.Descriptive statistics  were used to summarize sociodemographic, clinical, immunological, and virological parameters. Prevalence and types of DRM at baseline were investigated for their possible relationship with sociodemographic and clinical characteristics using t-test (for continuous variables), and Chi-square or Fisher’s exact test . The impact of pretreatment sDRM  detected by PBSS and NGS assays on virologic treatment outcome at month six and 12 was assessed by using a multivariable model testing for different confounding factors including gender, age, WHO clinical stage, functional status, TB, CD4 cell count, baseline VL, and NRTI regimens. P-value < 0.05 was considered statistically significant. Data analysis was performed using STATA software 14 .Scientific and ethical approvals were obtained from the National Research Ethics Review Committee in Ethiopia (3.10|528|06) and the Institutional Review Board (IRB) of EHNRI (Reference No. E.H.N.R.I 6.13/163). Written informed consent was obtained from all patients. All the methods were performed in accordance with approved institutional guidelines.The sequences generated by Sanger sequencing in this study are deposited in Gene Bank [accession numbers: MG009597-MG010057].Supplementary Table S1


Although efficacy of 36 months isoniazid preventive therapy (IPT) among HIV-positive individuals has been proven in trial settings, outcome, tolerance, and adherence have rarely been evaluated in real-life settings.This is a prospective observational cohort study conducted in 2 primary care rural clinics in Swaziland.After negative tuberculosis symptom screening, patients either with the positive tuberculin skin test (TST) or after tuberculosis treatment were initiated on IPT for 144 weeks. In addition to routine clinic visits, adherence was assessed every semester.2P = .01). Of 41 patients who interrupted IPT before 144 weeks, 21 defaulted ; 16 stopped because of adverse drug reactions; 2 were discontinued by clinicians’ mistake and 1 because of TB symptoms. Five patients (1.7%) died of causes not related to IPT, 5 (1.7%) developed TB of which 2 were isoniazid-resistant, and 9 (3.1%) were transferred to another clinic. As an indicator of adherence, isoniazid could be detected in the urine during 86.3% (302/350) and 73.6% (248/337) of patient visits in the 2 clinics, respectively (chi2P < .001).Of 288 eligible patients, 2 patients never started IPT , and 253 (87.8%), 234 (81.3%), and 228 (79.2%) were still on IPT after 48, 96, and 144 weeks, respectively (chiThe routine implementation of IPT 36 months was feasible and good patient outcomes were achieved, with low TB incidence, good tolerance, and sustained adherence. However, effectiveness of IPT has been shown to diminish 6 to 18 months after completion of such a regimen,–7 suggesting that IPT should be provided for longer. Indeed, a trial conducted in Botswana showed that TB incidence among TST-positive PLHIV was reduced by a further 43% if IPT was given for 36 months as compared to 6 months, although the reduction was not significant in PLHIV with negative or unknown TST results.In settings with high tuberculosis (TB) burden, isoniazid (INH) Preventive Therapy (IPT) is recommended for prevention of active tuberculosis in people living with HIV (PLHIV), particularly in individuals who are tuberculin skin test (TST)-positive.–11 Main concerns about long-term IPT were risk of side-effects, patient adherence, development of active TB while on IPT, and increased risk of INH-resistance. For example, in South Africa, up to 28% of cases suffered from a grade 3 or 4 transaminase elevation, after a median of one-and-a-half year on IPT and only 60% were retained on IPT at 3 years. Besides, although benefits of IPT are greatest in TST-positive patients, the introduction of widespread TST in resource-limited settings is limited by operational constraints such as cold chain requirements and the extra-visit required for TST reading. Although clinical trials have been essential to inform recommendations about 36 months IPT, there have been no observational studies documenting actual implementation. Confirming results from clinical trials in routine settings can help to convince decision-makers about the added value of 36 months IPT.Despite these results, uptake of 36 months’ IPT has been slow in many countries. National TB control has focused on early detection and treatment of TB, in parallel with rapid scaling up and integration of ART. Although IPT was recommended for 6 months, its implementation remained challenging in 2011, and extending IPT duration to 36 months seemed unfeasible. There was also the concern that adherence and outcomes under routine conditions would be less favorable than those reported in clinical trials. Therefore, the objective of this study was to assess the feasibility of TST-based 36 months IPT strategy in HIV-infected patients in programmatic conditions in 2 rural clinics of the Shiselweni region in Swaziland, in order to inform policy-makers in the country and in similar settings. This paper focuses on adherence, tolerability, and outcomes after 48, 96, and 144 weeks of follow-up. The results of this study on initial patient screening, implementation of tuberculin-skin test, and initiation of IPT have been published previously.Even though TB incidence has decreased in recent years, Swaziland is still the country with the highest TB and HIV burden reported in the world.2This prospective observational cohort included PLHIV eligible for IPT followed in 2 rural nurse-led primary care clinics in the Shiselweni region, Kingdom of Swaziland (OLOS clinic in the Hlatikulu zone and New Haven clinic in the Matsanjeni zone). The study was undertaken in compliance with the Declaration of Helsinki and was approved by the Social Welfare Scientific Ethical Committee of Swaziland and the Médecins Sans Frontières Ethical Review Board. Written informed consent was obtained from all study participants. Briefly, both clinics served an active ART cohort of about 700 patients. Nurses were in charge of providing HIV-TB care, which was fully integrated into general outpatient care. Expert clients (PLHIV trained to provide patient support education and counseling) assisted the nurses in managing patient files and clinic registers, as well as adherence support. Medical doctors visited the clinic once per week or every 2 weeks, according to needs, to attend to complicated cases and offer technical support.Details of study setting and screening process can be found elsewhere. The IPT study population, derived from the proportion of positive TST, consisted of all at-least-16-years-old PLHIV enrolled for HIV care at 1 of the 2 study clinics who were eligible for 36 months’ IPT based on either a positive TST (≥5 mm induration) or for secondary prophylaxis (after TB treatment). Exclusion criteria were kept to a minimum to be as close as possible to the routine program conditions. According to national recommendations for IPT provision, patients did not receive IPT when they were on TB treatment, where TB was suspected, or when INH was clinically contraindicated . Informed consent was obtained before TST screening.The sample size was calculated to estimate the proportion of positive TST.,16 Diagnosis of TB was initially based on auramine-stained microscopical examination and XpertMTB/RIF  testing performed at health-center level (secondary level), and later only on XpertMTB/RIF as per national recommendations. Samples from smear- or Xpert-positive patients were sent to reference laboratories at regional or national level for mycobacterial culture and drug susceptibility testing.Intensified TB case-finding was implemented at every contact between a PLHIV and the health facility, based on symptom screening  as per national recommendations. “default” was defined as a patient who had taken INH for at least 1 month, then interrupted for 60 consecutive days or more; “failure” was defined as someone developing active TB disease while on IPT; “treatment discontinuation” was used for someone whose IPT had been discontinued by a health care worker due to adverse effects or any other reason; “transfer out” was used for someone who transferred to another ART site or region to continue treatment; “death” were those on IPT who were reported to have died of any cause during the course of treatment; “completed IPT” was defined as a full course of 36 times 4 weeks  of INH.Patients were seen after 1 month after starting IPT. Subsequently, appointments followed the usual visit schedule for ART or cotrimoxazole refill, that is, every 1, 2, or 3 months depending on patient, clinic, and drug stocks. Laboratory monitoring followed the general recommendations for patients under HIV care in Swaziland, namely 6-monthly CD4, and quarterly liver function test. In 2012, viral-load testing was added to routine monitoring as per the national VL algorithm. Expert clients traced patients on HIV care by phone when clinical appointments were missed by 3 days. A renewed attempt was made by phone in cases where patients did not present at the clinic over a period of 90 days. IPT outcome definitions were adapted from the national standard definitions used to monitor 6 months’ IPT: The Morisky scale combines 4 questions related to different aspects of drug intake by patients on chronic treatment . One point is attributed for every positive answer. Adherence is judged high, intermediate, or low for scores of 0, 1 to 2, and 3 to 4, respectively.Pill count was systematically recorded at every patient contact. In addition, for all patients on IPT for 36 months, an in-depth evaluation was conducted twice yearly, consisting of a urine sample and a short questionnaire. Adherence was assessed through a combination of 4 parameters: pill count , the self-reported number of days of no INH intake in the past 14 days, the Morisky scale, and isoniazid testing in the urine. For this, isoniazid strip tests (BD TAXO INH Test) were performed on urine samples following the manufacturer's instructions. This test is mostly reliable for the presence of isoniazid in the urine if the drug was taken in the last 24 hours.Data were collected by the clinic staff on regular patient files during the routine follow-up visits, before extraction on study-specific case report forms by a study nurse. Occurrence of adverse drug reactions (ADR) was recorded in the patient file by the clinic nurse. Adverse drug reactions were defined as: “a response to a medicine which is noxious and unintended, and which occurs at doses normally used in man.” Additional information was requested in case of ADR, death, active TB, or treatment discontinuation. In addition, during adherence counseling, expert clients asked about side-effects experienced by the patients, without further precision on the definition of side-effect.Data were entered on site weekly using Epi-Data 3.0 software , initially by a data entry clerk and later by the study nurse. Data were analyzed in Stata 12.1 software . No imputation was done in the case of missing variables, apart from the date of death which was chosen randomly between date of last visit and date of information about deaths, in the absence of other information. Main outcome was described by the proportions that completed treatment, failed (developed TB), died, defaulted, discontinued, or transferred. The nonparametric test for trend across ordered groups was used to assess changes on adherence indicators over time. In the survival analysis of retention on IPT, death, TB, default and discontinuation were failures and transfers were censored. Predefined baseline characteristics that could represent risk factors for discontinuation , such as clinic, age, sex, ART status, initial baseline CD4 count at IPT initiation, and occurrence of adverse events, were tested in a non-parametric survival model, and rates of interruption per person-years were calculated. Variables associated with retention on IPT, defined as a log rank test <0.20, were further included in a multivariate Cox model in addition to age as a potential confounder.33.1 Patient characteristics are detailed in Table The study profile has been previously published.3.22P = .01, Table Out of a total of 288, 286 (99.3%) actually initiated IPT  and 253 (87.8%), 234 (81.3%), and 228 (79.2%) were still on IPT after 48, 96, and 144 weeks, respectively . Among them, there were 2 new pulmonary drug-sensitive cases, 1 extrapulmonary case (TB of the spine diagnosed by radiography), and 2 patients infected with INH-resistant mycobacteria.P < .001 for goodness-of-fit test). The proportional hazards assumption was not violated .Patients were followed up for a median of 149 weeks (IQR 146–163 weeks) after IPT start, for a total of 702 person-years , 2.0% (5/253), and 0.9% (1/234) patients during the first, second, and third year of follow-up, respectively. Three cases of hepatotoxicity were recorded (1.0%), of which 2 were severe  and 1 mild. All patients recovered. Other patients mentioned symptoms which may have been due to hepatotoxicity, such as abdominal pain (3 patients), or nausea and vomiting . Unfortunately, IPT was often stopped without liver tests to confirm the diagnosis. The other reported adverse reactions were 2 cases of rash, 1 of itching, 2 cases of neuropathy, 3 cases of nonspecific weight loss, 1 psychotic decompensation, and 1 case of vertigo and nystagmus.Treatment was discontinued for 16/22 patients reporting adverse-drug reactions. Of the 16 patients that discontinued IPT, 1 was found dead at home 2 months after IPT discontinuation, and 1 pregnancy resulted in stillbirth. The 2 patients with neuropathy recovered only partially. The remaining 13 patients were seen at a later appointment with no complaints raised.Side-effects reported to the expert client during the adherence assessments decreased from 19.0% (16/79) and 50.0% (25/52) at 6 months in OLOS and New Haven, respectively, to less than 1% after 30 months. These side-effects were mostly itching, symptoms of neuropathy (tingling in hands or feet), nonspecific pain (joint pains), and other complaints . None led to temporary treatment interruptions. Although the nurses reported few cases of neuropathy (1.4%), up to 4.9% (14/288) were reported during the interviews with the expert clients.3.4P < .001). Not all urine samples were actually tested, mainly because of the lack of available urine strips or of the staff either collecting the urine or performing the test. Of all assessments combined, the proportion of positive urine tests for isoniazid (INH) was 80.1% (95%CI 76.9–82.9%). Of the 17 patients who had the urine tested more than 24 hours after last INH intake, 14 (82.4%) were still positive. By contrast, out of the 141 negative urine tests, there were only 11 patients admitting no INH intake in the past 24 hours.Adherence was assessed at least once in 252 patients (87.5%), with a median of 3 assessments per patient (IQR 2–4). Urine was collected between 1 and 30 hours after reported INH intake  status, in resource-constrained settings with high TB incidence and transmission.The authors would like to thank the patients who participated in this study, the staff, and expert clients working in the clinics, and the entire MSF teams working in Swaziland. Special acknowledgment to Mathieu Bastard for statistical advice, to Clothilde Rambaud-Althaus for support in quality monitoring, and to Béatrice Vasquez and Calorine Mekiedje for help in data cleaning and project supervision.


Few low-income countries have virological monitoring widely available. We estimated the virological durability of first-line antiretroviral therapy (ART) after five years of follow-up among adult Ugandan and Zimbabwean patients in the DART study, in which virological assays were conducted retrospectively.DART compared clinically driven monitoring with/without routine CD4 measurement. Annual plasma viral load was measured on 1,762 patients. Analytical weights were calculated based on the inverse probability of sampling. Time to virological failure, defined as the first viral load measurement ≥200 copies/mL after 48 weeks of ART, was analysed using Kaplan-Meier plots and Cox regression models.p < 0.0001). In multivariate analyses, female patients , older patients  and patients with a higher pre-ART CD4 cell count  had a lower incidence of virological failure after adjusting for adherence to ART. No difference in failure rate between the two randomised monitoring strategies was observed (p= 0.25).Overall, 65% of DART trial patients were female. Patients initiated first-line ART at a median  age of 37 (32–42) and with a median CD4 cell count of 86 (32–140). After 240 weeks of ART, patients initiating dual-class nucleoside reverse-transcriptase inhibitor (NRTI) -non-nucleoside reverse-transcriptase (NNRTI) regimens containing nevirapine + zidovudine + lamivudine had a lower incidence of virological failure than patients on triple-NRTI regimens containing tenofovir + zidovudine + lamivudine  =0.48, 95% CI:0.38–0.62; The long-term durability of virological suppression on dual-class NRTI-NNRTI first-line ART without virological monitoring is remarkable and is enabled by high-quality clinical management and a consistent drug supply. To achieve higher rates of virological suppression viral-load-informed differentiated care may be required.ISRCTN13968779.Prospectively registered on 18/10/2000 as The online version of this article (doi:10.1186/s12879-017-2266-3) contains supplementary material, which is available to authorized users. The treatment of human immunodeficiency virus (HIV) in low-income countries has predominantly followed a “public health approach” as access to antiretroviral therapy (ART) has been scaled up , 2. ThisIndividual countries are deciding, within financially-restricted healthcare systems, whether they should invest in upgrading laboratory infrastructure to facilitate virological monitoring. Currently, despite 39/52 low and middle-income countries recommending viral load testing, in only 8/52 has testing become widely available . Cost-efIn this analysis, we report longitudinal findings from the DART trial on the virological durability of first-line ART over 240 weeks of follow-up among adult Ugandan and Zimbabwean patients without real-time viral load monitoring.3. DART enrolled from three clinical centres in Uganda and one in Zimbabwe. Recruitment was between January 2003 and October 2004 and patients were followed until the end of 2008 [3 (<50 cells/mm3 prior to July 2006). Switching treatment before 48 weeks was strongly discouraged for patients on both monitoring strategies. The DART trial was approved by research ethics committees in Uganda, Zimbabwe, and the UK. Patient consent included the storage of plasma samples and later testing.DART was a randomised open-label non-inferiority trial conducted in ART-naïve, symptomatic HIV-infected adults with a CD4 cell count ≤200 cells/mm of 2008 . Patientn = 300) or nevirapine . An additional 247 patients in Zimbabwe received open-label NVP. All other patients  received a triple-nucleoside reverse-transcriptase inhibitor (NRTI) regimen, which included the third drug tenofovir (TDF).Three different first-line ART regimens were used in the DART study. All patients received co-formulated zidovudine (ZDV) and lamivudine (3TC). In a Ugandan substudy , 600 patWhole bloods were collected in EDTA vacutainers at routine visits during DART follow up and plasma isolated by centrifugation within 2 to 6 h following local laboratory procedures. Plasma was distributed into 2 ml cryovials as 1 ml to 1.5 ml aliquots and stored frozen at minus 80 °C until retrieval for HIV viral load assays.n = 404) or ABC (n = 254) were selected, as well as a sample of patients who received TDF . This sample selectively included patients who received a viral load test under a national Ugandan viral load testing program shortly after trial closure [Viral load testing was conducted on approximately 3,500 of the 60,000 plasma samples held in the DART repository. Patients were excluded completely if (a) they either died or switched treatment prior to week 48, since early deaths were unlikely to be due to treatment failure  and earl closure . Further TDF n = ,104. ThiPlasma samples for viral load testing from this sample of patients were selected using a “walkback” procedure, beginning with the last sample on first-line ART. If viral load was <200 copies/mL no further samples were tested; if not, a sample from approximately 48 weeks earlier was tested. This process was repeated at approximate 48-week intervals until a result <200 copies/mL was obtained or until the week 48 sample was tested. In addition, samples from baseline (week 0) were tested in 74% of patients; the 24% baseline samples not tested were from those on TDF known to be suppressed at the end of the study via the national Ugandan testing program.To correct for non-random sampling, analytical probability weights based on the inverse probability of a patient being sampled, were used in all analyses to reflect the DART population as a whole . Time to10 scale were multiply imputed 30 times using a linear regression model which included all potential prognostic factors (terms of Cox model) and outcome variables  [To avoid a loss in efficiency, missing values for baseline viral loads on the logdicator) . This asdicator) .3. Overall 17% of patients received a dual-class NRTI/non-NRTI (NNRTI) regimen and 83% received a triple-NRTI regimen. Characteristics were broadly similar in the viral load substudy apart from first-line ART (patients prescribed NVP or ABC over-represented in the substudy by design) and study centre . However, the use of analytical weights . Overall, an estimated 28% (95% CI: 26–29%) of patients had experienced virological failure by 96 weeks, 32% (95% CI: 31–34%) by 144 weeks, 35% (95% CI: 33-37%) by 192 weeks and 37% (95% CI: 35–39%) by 240 weeks. The rate of virological failure was similar for patients receiving triple-NRTI regimens containing either TDF or ABC (40% (95% CI: 38–42%) and 45% (95% CI: 38–50%) respectively at 240 weeks; p = 0.37), but was substantially lower for patients who received a dual-class regimen containing NVP (21% (95% CI: 18–25%) at 240 weeks; p < 0.0001).Overall, one or more viral load measurements were available for 1,741/1,762 (99%) patients. The first sample tested (last time point on first-line ART) was after a median (IQR) 252 (224–280) weeks on first-line ART. In total, 606 patients (35%) were observed to fail virologically during follow-up. Figure p = 0.25). However, both gender and age were strong predictors of virological failure. Female patients had a 21% lower incidence of virological failure (p = 0.01) and each additional 10 year increase in a patient’s age reduced incidence of virological failure by 27% . Each additional 100 cell increase in patient’s baseline (pre-ART) CD4 cell count reduced incidence of virological failure by 36% (p < 0.0001). There was no evidence that baseline viral load affected the incidence of virological failure (p = 0.89). The multivariable fractional polynomial model revealed no evidence of non-linearity and there was no evidence of non-proportionality for either monitoring strategy or initial ART. Compared with the TDF reference group, patients who received a NVP-containing regimen had a 52% (p < 0.0001) lower incidence of virological failure and patients prescribed ABC a 27% (p = 0.03) higher incidence of virological failure. Adherence, as measured by the proportion of visits in the past 48 weeks where the drug possession ratio was >95%, showed clear association with virological failure, with 11% lower incidence of virological failure for every 10% increase in the proportion of adherent visits (p < 0.0001).There was no evidence that monitoring strategy affected long-term virological failure in the multivariable Cox model Table  p = 0.2p = 0.25.p = 0.02). Patients on ABC with a baseline viral load < 100,000 copies/mL had a 48% (95% CI: 18–68%) lower incidence of virological failure compared to those with a baseline viral load ≥ 100,000 copies/mL. However, this effect was much less marked for patients who received TDF  or NVP .Previous research suggests that ABC-based regimens may be more prone to failure for baseline viral loads ≥ 100,000 copies/mL . A test n = 86) after 48 weeks as virological failures, slightly increased the cumulative incidence of virological failure (41% by 240 weeks) but had a negligible effect on the multivariable hazard ratios (HR) (Table n = 172) were also virological failures increased the overall cumulative incidence of virological failure to 41% by 240 weeks and for patients on dual-class regimens containing nevirapine to 24%. Finally, alternative thresholds for virological failure were investigated. Using a threshold of >1,000 copies/mL did not materially change our findings but increasing the threshold to >10,000 copies/mL led to a similar incidence of virological failure for patients on ABC compared to TDF. This suggests that the differences in failure rates between patients on ABC and TDF are driven by a higher proportion of patients on ABC failing with a viral load between 200 and 10,000 copies/mL.The first sensitivity analysis, which considered all deaths and ART switches (R) Table . Secondl3 and a third had <50 cells/mm3. Persistent undetected virological failure was relatively low (20%); high virological failure rates are not an inevitable consequence of using only clinical or CD4 cell count monitoring. Within financially-restricted healthcare systems the lack of availability of virological monitoring should not limit countries when expanding access to ART. However, to achieve higher rates of virological suppression, viral-load-informed differentiated care may be required [This analysis found that at 240 weeks an estimated 79% of patients on dual-class regimens in the DART study were virologically suppressed. This was particularly noteworthy given that the overall median CD4 cell count when ART was initiated was 86 cells/mmThe rate of virological failure in patients who started ART with a triple-NRTI regimen was approximately twice that of dual-class regimens. Baseline CD4 cell count remained a strong predictor of virological failure after 48 weeks on first-line ART. Despite adjusting for differences in adherence, both female patients and older patients had a lower incidence of virological failure.p = 0.003), 76% were suppressed in the CDM arm compared to 83% in the LCM arm. Our research extends this study by including longitudinal data, data from Zimbabwe and patients who switched treatment or died during the study. Importantly, more patients in LCM switched to second-line and were excluded from this previous analysis: these patients were also more likely to virologically fail [A previous cross-sectional analysis of data from Ugandan centres at the end of the DART study found 80% of patients who remained on first-line ART had suppressed viral load (<400 copies/mL) . Virologlly fail . After in = 504) of adult patients on NNRTI-based regimens in four studies from low and middle income countries remained virologically suppressed in an intention-to-treat analysis after 48 months of ART. Of those on treatment, 83% (n = 909) of patients from six studies were virologically suppressed after 60 months of ART. Unlike our analysis, both of these estimates did not consider switches to second-line ART as virological failure. Cost-effectiveness analyses conducted by Phillips et al. [Even though most patients were receiving triple NRTIs first-line, we found more durable virological suppression than a 2015 meta-analysis , in whics et al.  assume tWe show that patients on ABC have a higher incidence of virological failure than patients on TDF, in line with previous research , 24 and Some studies , 27 haveWomen were shown to have significantly lower incidence of virological failure than men after adjusting for differences in adherence, which has not been widely shown before. A recent systematic review on sex differences in HIV outcomes  reportedThere was no evidence that baseline viral load was associated with the incidence of virological failure. In contrast, a meta-analysis  has demoThe majority of patients in DART used triple-NRTI regimens which are no longer used in low-income countries so findings for these patients are of less interest and included for completion. Nonetheless, this analysis contains virological outcome data for 404 patients who used a dual-class regimen containing nevirapine with 240 weeks of follow-up data. The recent systematic review  only conDue to funding, only a proportion of patients in DART could have virological testing conducted. This should not bias the results since the complete analysis population of interest on nevirapine and abacavir were sampled and a random sample was taken of patients on tenofovir. Patients were appropriately weighted in all analyses to account for the sampling method. It is likely that including patients who died prior to week 48 would increase the proportion detected with virological failure.The walkback approach to viral load sampling meant that intermittent or early virological failure in patients who subsequently re-suppressed is not detected. The clinical consequences of intermittent viremia in low-income countries are complex but with limited availability of second-line regimens in low-income countries the priority is to achieve long-term virological suppression on first-line regimens. Including patients with intermittent or virological failure before 48 weeks of ART would increase the proportion detected with virological failure.DART was a randomised clinical trial with a high quality of clinical care, so it could be argued that the sustained virological suppression observed is not generalizable to wider clinical settings in resource-limited countries. Nonetheless, this analysis demonstrates that long-term virological suppression on dual-class regimens containing nevirapine is feasible if patients receive regular clinic visits and have consistent drug supply, despite the absence of laboratory monitoring, sub-optimal treatment regimens and low baseline CD4 cell count.Analyses of drug resistance assays on the samples in this study are currently ongoing. Therefore at this stage we are not able to conclude whether virological failure is the result of non-adherence to ART or due to HIV-1 drug resistance mutations developing. Similarly, the clinical consequences of virological failure are also being investigated in ongoing analyses.Our analysis longitudinally examines virological failure in a setting without virological monitoring over five years of follow-up. The rate of virological failure is lower than a recent systematic review, particularly given that most patients received less potent triple-NRTI regimens. Our results suggest that within financially-restricted healthcare systems, virological control is achievable in the absence of real time viral load testing, and that a consistent drug supply, enabling high levels of adherence, is likely more crucial for sustained virological suppression than upgrading clinical and laboratory infrastructure. To achieve higher rates of long-term virological suppression, viral-load informed differentiated care may be required.