Suchergebnisse

BackgroundCurrent guidelines for providing antiretroviral therapy (ART) in South Africa's public sector programme call for switching patients from first‐line to second‐line treatment upon virologic failure as indicated by two consecutive viral loads above 5000 copies/ml, but without laboratory evidence of viral resistance. We modelled the net cost of adding resistance testing for patients with virological failure and retaining patients without resistance on first‐line therapy, rather than switching all failures to second‐line therapy.MethodsCosts were estimated for three scenarios: routine maintenance (standard care without resistance testing, switch all failures to second line); resistance testing (resistance test for patients with failure, switch those with resistance); and limited testing (resistance test for patients with failure in the first three years, switch those with resistance). A Markov model was used to estimate the cost of each arm over five years after first line initiation. Rates of treatment failure, viral resistance and treatment costs were estimated with primary data from a large HIV treatment cohort at a public facility in Johannesburg. Future costs were discounted at 3%.ResultsVirological failure rates over five years were 19.8% in routine maintenance and 20.2% in resistance testing and limited testing; 16.8% and 11.4% of failures in routine and limited testing, respectively, did not have any resistance mutations, resulting in 3.1% and 2.0% fewer patients switching to second‐line ART by the end of five years. Treatment costs were estimated at US$526 and $1268 per patient per year on first‐line and second‐line therapy, respectively; a resistance test cost $242. The total average cost per patient over five years was $2780 in routine maintenance; $2775 in resistance testing; and $2763 in limited testing.ConclusionsIncorporating resistance testing into treatment guidelines in South Africa is potentially cost‐neutral and can identify other reasons for failure, conserve treatment options, and generate information about emerging resistance patterns.

AbstractIntroductionSouth African youth and adolescents face a high burden of (Sexually Transmitted Infections) STIs, HIV and unintended pregnancies, but uptake of services remains low. To address this, tailored and scalable interventions are urgently needed. We developed a framework to fill the gap and translate the impact of facility‐level attributes into a cost‐effectiveness analysis for increasing HIV/contraceptive service uptake in adolescents using a discrete choice experiment (DCE).MethodsWe used a DCE (n = 805) conducted in Gauteng, South Africa, which found that staff attitude, confidentiality, Wi‐Fi, subsidized food, afternoon hours and youth‐only services were preferred attributes of health services. Based on this, we simulated the uptake of services adapted for these preferences. We divided preferences into modifiable attributes that could readily be adapted (e.g. Wi‐Fi), and challenging to modify (more nuanced attributes that are more challenging to cost and evaluate): staff attitude and estimated the incremental change in the uptake of services using adapted services. Costs for modifiable preferences were estimated using data from two clinics in South Africa (2019 US$). We determined the incremental cost‐effectiveness ratio (ICER) for additional adolescents using services of 15 intervention combinations, and report the results of interventions on the cost‐effectiveness frontier.ResultsGreatest projected impact on uptake was from friendly and confidential services, both of which were considered challenging to modify (18.5% 95% CI: 13.0%−24.0%; 8.4% 95% CI: 3.0%−14.0%, respectively). Modifiable factors on their own resulted in only small increases in expected uptake. (Food: 2.3% 95% CI: 4.0%−9.00%; Wi‐Fi: 3.0% 95% CI: −4.0% to 10.0%; Youth‐only services: 0.3% 95% CI: −6.0% to 7.0%; Afternoon services: 0.8% 95% CI: −6.0% to 7.0%). The order of interventions on the cost‐effectiveness frontier are Wi‐Fi and youth‐only services (ICER US$7.01−US$9.78 per additional adolescent utilizing HIV and contraceptive services), Wi‐Fi, youth‐only services and food (ICER US$9.32−US$10.45), followed by Wi‐Fi, youth‐only services and extended afternoon hours (ICER US$14.46–US$43.63).ConclusionsCombining DCE results and costing analyses within a modelling framework provides an innovative way to inform decisions on effective resource utilization. Modifiable preferences, such as Wi‐Fi provision, youth‐only services and subsidized food, have the potential to cost‐effectively increase the proportion of adolescents accessing HIV and contraceptive services.

AbstractIntroductionIn recent years, many countries have adopted evidence‐based budgeting (EBB) to encourage the best use of limited and decreasing HIV resources. The lack of data and evidence for hard to reach, marginalized and vulnerable populations could cause EBB to further disadvantage those who are already underserved and who carry a disproportionate HIV burden (USDB). We outline the critical data required to use EBB to support USDB people in the context of the generalized epidemics of sub‐Saharan Africa (SSA).DiscussionTo be considered in an EBB cycle, an intervention needs at a minimum to have an estimate of a) the average cost, typically per recipient of the intervention; b) the effectiveness of the intervention and c) the size of the intervention target population. The methods commonly used for general populations are not sufficient for generating valid estimates for USDB populations. USDB populations may require additional resources to learn about, access, and/or successfully participate in an intervention, increasing the cost per recipient. USDB populations may experience different health outcomes and/or other benefits than in general populations, influencing the effectiveness of the interventions. Finally, USDB population size estimation is critical for accurate programming but is difficult to obtain with almost no national estimates for countries in SSA. We explain these limitations and make recommendations for addressing them.ConclusionsEBB is a strong tool to achieve efficient allocation of resources, but in SSA the evidence necessary for USDB populations may be lacking. Rather than excluding USDB populations from the budgeting process, more should be invested in understanding the needs of these populations.

IntroductionThe prognostic role of CD4 response in the first six months of treatment in patients achieving early viral suppression during HIV treatment is unclear.MethodsThis was a cohort study of HIV‐positive adults initiating antiretroviral therapy (ART) between April 2004 and August 2007 who achieved viral suppression (<400 copies/ml) by six months on treatment in South Africa. Immunological response at six months was defined as: (1) absolute CD4 reached (<200 vs. ≥200 cells/ml); (2) absolute CD4 reached (0–49, 50–200 and ≥200 cells/ml); and (3) CD4 increase from ART initiation (<0, 0–49, 50–199 and ≥200 cells/ml). We used Cox regression models to determine the relationship between each definition and both new AIDS‐defining condition and death.ResultsA total of 4129 patients were eligible for analysis; 212 (5.1%) of those patients experienced a new AIDS‐defining condition and 154 (3.7%) died. Smaller CD4 gains by six months were associated with higher hazards of progression to AIDS (CD4<50 vs. ≥200 cells/ml; adjusted hazard ratio (aHR): 2.6; 95% CI: 1.2–2.1) and death (aHR: 2.8; 95% CI: 1.4–5.7). A decrease in CD4 count since ART initiation through six months (aHR: 2.4; 95% CI: 1.2–4.9) and smaller CD4 count gains (0–49 cells/ml; aHR: 2.0; 95% CI: 1.2–3.4 and 50–199 cells/ml; aHR: 1.5; 95% CI: 0.9–2.2) were also associated with greater risk of progression to AIDS compared to an increase of ≥200 cells/ml. When we examined mortality differences by gender among this virally suppressed cohort, a higher proportion of males died compared to females, 4.7% versus 3.2%, p=0.01. However, in multivariable analysis, we did not observe any significant differences: aHR: 1.39; 95% CI: 0.98–1.95.ConclusionsPatients on ART with poor CD4 recovery early in treatment are at greater risk of progression to new AIDS diagnosis or death despite viral suppression. Approaches to managing this sub‐group of patients need further investigation.

Abstract
IntroductionPolicies for Universal Test & Treat (UTT) and same‐day initiation (SDI) of antiretroviral therapy (ART) were instituted in South Africa in September 2016 and 2017 respectively. However, there is limited evidence on whether these changes have improved patient retention after HIV diagnosis.MethodsWe enrolled three cohorts of newly diagnosed HIV‐infected adults from two primary health clinics in Johannesburg from April to November 2015 (Pre‐UTT, N = 144), May‐September 2017 (UTT, N = 178) and October‐December 2017 (SDI, N = 88). A baseline survey was administered immediately after HIV diagnosis after which follow‐up using clinical records (paper charts, electronic health records and laboratory data) ensued for 12 months. The primary outcome was patient loss to follow‐up (being >90 days late for the last scheduled appointment) at 12 months post‐HIV diagnosis. We modelled attrition across HIV policy periods with Cox proportional hazard regression.ResultsOverall, 410 of 580 screened HIV‐positive patients were enrolled. Overall, attrition at 12 months was 30% lower in the UTT guideline period (38.2%) compared to pre‐UTT (47.2%, aHR 0.7, 95% CI: 0.5 to 1.0). However, the total attrition was similar between the SDI (47.7%) and pre‐UTT cohorts (aHR 1.0, 95% CI: 0.7 to 1.5). Older age at HIV diagnosis (aHR 0.5 for ≥40 vs. 25 to 29 years, 95% CI: 0.3 to 0.8) and being in a non‐marital relationship (aHR 0.5 vs. being single, 95% CI: 0.3 to 0.8) protected against LTFU at 12 months, whereas LTFU rates increased with longer travel time to the diagnosing clinic (aHR 1.8 for ≥30 minutes vs. ≤15 minutes, 95% CI: 1.1 to 3.1). In analyses adjusted for the time‐varying ART initiation status, compared to the pre‐ART period of care, the hazard of on‐ART LTFU was 90% higher among participants diagnosed under the SDI policy compared to pre‐UTT (aHR 1.9, 95% CI: 1.1 to 2.9).ConclusionsOverall, nearly two‐fifths of HIV positive patients are likely to disengage from care by 12 months after HIV diagnosis under the new SDI policy. Furthermore, the increase in on‐ART patient attrition after the introduction of the SDI policy is cause for concern. Further research is needed to determine the best way for rapidly initiating patients on ART and also reducing long‐term attrition from care.

IntroductionPrevious research has raised concerns that patients given nevirapine (NVP)‐based regimens experience more virologic failure than patients given efavirenz (EFV)‐based regimens. We investigated this hypothesis in a cohort of HIV‐positive patients at a large HIV treatment clinic in South Africa.MethodsAll antiretroviral therapy (ART)‐naïve non‐pregnant patients, ≥18 years old, without tuberculosis, who initiated treatment with either NVP or EFV from April 2004 to August 2011 at the Themba Lethu Clinic in Johannesburg, South Africa, were included. Log‐binomial regression and modified Poisson regression were used to estimate risk ratios (RR) with 95% confidence intervals (CI) for predictors of virologic failure, virologic suppression, and loss to follow‐up (LTF), whereas a Cox proportional hazards model was used to estimate the risk of death, all within one year.ResultsOf 12,840 included patients, 62.0% were female and the median baseline CD4 count was 98 cells/mm3 (36–169). Of these patients, 93.2% initiated an EFV‐based regimen. After adjusting for baseline characteristics, no difference in death (adjusted Hazards Ratio (aHR): 0.92; 95% CI: 0.68–1.25), LTF (adjusted Risk Ratio (aRR): 1.00; 95% CI: 0.79–1.25), nor suppression (aRR: 0.98; 95% CI: 0.95–1.00) at one year was found between regimens. Among patients with ≥1 viral load ≥4 months after ART initiation, 4% (n=350) experienced virologic failure within 12 months of initiation. Patients initiating NVP‐based regimens were 60% more likely to fail than patients initiating EFV‐based regimens (aRR: 1.58; 95% CI: 1.13–2.22).ConclusionsIn this cohort, patients initiating NVP‐based regimens experienced more virologic failure than patients initiating EFV‐based regimens. Future guidelines should consider the implications of different efficacy profiles when making recommendations for which drugs to prioritize.

IntroductionIn April 2010, tenofovir replaced stavudine in public‐sector first‐line antiretroviral therapy (ART) in South Africa. The association of tenofovir with fewer side effects and toxicities compared to stavudine could translate to increased durability of tenofovir‐based regimens. We evaluated changes over time in regimen durability at the Themba Lethu Clinic, Johannesburg, South Africa.MethodsThis was a cohort analysis of treatment‐naïve, non‐pregnant adult patients initiated on ART between April 2004 and December 2011. First‐line ART regimens before April 2010 consisted of stavudine or zidovudine with lamivudine and either efavirenz or nevirapine. Tenofovir was substituted for stavudine after April 2010. We evaluated the frequency and type of single‐drug substitutions (excluding switches to second‐line therapy). Cox models were used to evaluate the association of ART initiation year and antiretroviral drug type with single‐drug substitutions in the first 12 months on treatment.ResultsOne thousand nine hundred and sixty‐four (10%) substitutions occurred amongst 19,699 patients. Excluding 2004 (year of treatment roll‐out), before 2010 one‐year single‐drug substitutions ranged from 10.0 to 13.1%. In 2011, well after integration of tenofovir, substitutions decreased to 5.6%. Single‐drug substitution was lowest amongst patients on tenofovir (5.1%) versus zidovudine (11.3%), 30 mg stavudine (10.5%) or 40 mg stavudine (14.4%). Adjusted Cox models showed that patients initiating treatment between 2005 and 2010 (vs. 2011) had a twofold increased hazard of single‐drug substitution, while those on zidovudine or stavudine had a two to threefold increase in single‐drug substitution versus tenofovir patients in the first 12 months on ART.ConclusionsThe decline in single‐drug substitutions is associated with the introduction of tenofovir. Tenofovir use could improve regimen durability and treatment outcomes in resource‐limited settings.

AbstractIntroductionSouth Africa is moving into a new era of HIV treatment with "treat all" policies where people may be on treatment for most of their lives. We need to understand treatment outcomes and facilitators of long‐term antiretroviral treatment (ART) adherence and retention‐in‐care in the South African context. In one of the first studies to investigate long‐term treatment outcomes in South Africa, we aimed to describe ten‐year patient outcomes at a large public‐sector HIV clinic in Johannesburg and explore patient experiences of the treatment programme over this time in order to ascertain factors that may aid or hinder long‐term adherence and retention.MethodsWe conducted a cohort analysis (n = 6644) and in‐depth interviews (n = 24) among HIV‐positive adults initiating first‐line ART between April 2004 and March 2007. Using clinical records, we ascertained twelve‐month and ten‐year all‐cause mortality and loss to follow‐up (LTF). Cox proportional hazards regression was used to identify baseline predictors of attrition (mortality and LTF (>3 months late for the last scheduled visit)) at twelve months and ten years. Twenty‐four patients were purposively selected and interviewed to explore treatment programme experiences over ten years on ART.ResultsExcluding transfers, 79.5% (95% confidence intervals (CI): 78.5 to 80.5) of the cohort were alive, in care at twelve months dropping to 35.1% (95% CI: 33.7 to 36.4) at ten years. Over 44% of deaths occurred within 12 months. Ten‐year all‐cause mortality increased, while LTF decreased slightly, with age. Year and age at ART initiation, sex, nationality, baseline CD4 count, anaemia, body mass index and initiating regimen were predictors of ten‐year attrition. Among patients interviewed, the pretreatment clinic environment, feelings of gratitude and good fortune, support networks, and self‐efficacy were facilitators of care; side effects, travel and worsening clinical conditions were barriers. Participants were generally optimistic about their futures and were committed to continued care.ConclusionsThis study demonstrates the complexities of long‐term chronic HIV treatment with declining all‐cause mortality and increasing LTF over ten years. Barriers to long‐term retention still present a significant challenge. As more people become eligible for ART in South Africa under "treatment for all," new healthcare delivery challenges will arise; interventions are needed to ensure long‐term programme successes continue.

AbstractIntroductionMen are missing along the HIV care continuum. However, the estimated proportions of men in sub‐Saharan Africa meeting the UNAIDS 95‐95‐95 goals vary substantially between studies. We sought to estimate proportions of men meeting each of the 95‐95‐95 goals across studies in sub‐Saharan Africa, describe heterogeneity, and summarize qualitative evidence on factors influencing care engagement.MethodsWe systematically searched PubMed and Embase for peer‐reviewed articles published between 1 January 2014 and 16 October 2020. We included studies involving men ≥15 years old, with data from 2009 onward, reporting on at least one 95‐95‐95 goal in sub‐Saharan Africa. We estimated pooled proportions of men meeting these goals using DerSimonion‐Laird random effects models, stratifying by study population (e.g. studies focusing exclusively on men who have sex with men vs. studies that did not), facility setting (healthcare vs. community site), region (eastern/southern Africa vs. western/central Africa), outcome measurement (e.g. threshold for viral load suppression), median year of data collection (before vs. during or after 2017) and quality criteria. Data from qualitative studies exploring barriers to men's HIV care engagement were summarized using meta‐synthesis.Results and discussionWe screened 14,896 studies and included 129 studies in the meta‐analysis, compiling data over the data collection period. Forty‐seven studies reported data on knowledge of serostatus, 43 studies reported on antiretroviral therapy use and 74 studies reported on viral suppression. Approximately half of men with HIV reported not knowing their status (0.49 [95% CI, 0.41–0.58; range, 0.09–0.97]) or not being on treatment (0.58 [95% CI, 0.51–0.65; range, 0.07–0.97]), while over three‐quarters of men achieved viral suppression on treatment (0.79 [95% CI, 0.77–0.81; range, 0.39–0.97]. Heterogeneity was high, with variation in estimates across study populations, settings and outcomes. The meta‐synthesis of 40 studies identified three primary domains in which men described risks associated with engagement in HIV care: perceived social norms, health system challenges and poverty.ConclusionsPsychosocial and systems‐level interventions that change men's perceptions of social norms, improve trust in and accessibility of the health system, and address costs of accessing care are needed to better engage men, especially in HIV testing and treatment.

AbstractIntroductionSouth Africa's National Department of Health launched the National Adherence Guidelines for Chronic Diseases in 2015. These guidelines include adherence clubs (AC) and decentralized medication delivery (DMD) as two differentiated models of care for stable HIV patients on antiretroviral therapy. While the adherence guidelines do not suggest that provider costs (costs to the healthcare system for medications, laboratory tests and visits to clinics or alternative locations) for stable patients in these differentiated models of care will be lower than conventional, clinic‐based care, recent modelling exercises suggest that such differentiated models could substantially reduce provider costs. In the context of continued implementation of the guidelines, we discuss the conditions under which provider costs of care for stable HIV patients could fall, or rise, with AC and DMD models of care in South Africa.DiscussionIn prior studies of HIV care and treatment costs, three main cost categories are antiretroviral medications, laboratory tests and general interaction costs based on encounters with health workers. Stable patients are likely to be on the national first‐line regimen (Tenofovir/Entricitabine/Efavarinz (TDF/FTC/EFV)), so no difference in the costs of medications is expected. Laboratory testing guidelines for stable patients are the same regardless of the model of care, so no difference in laboratory costs is expected as well. Based on existing information regarding the costs of clinic visits, AC visits and DMD drug pickups, we expect that for some clinics, visit costs for DMD or AC models of care could be less, but modestly so, than for conventional, clinic‐based care. For other clinics, however, DMD or AC models could have higher visit costs (see Table 2).ConclusionsThe standard of care for stable patients has already been "differentiated" for years in South Africa, prior to the roll out of the new adherence guidelines. AC and DMD models of care, when implemented as envisioned in the guidelines, are unlikely to generate substantive reductions or increases in provider costs of care.

AbstractIntroductionDifferentiated service delivery (DSD) models for antiretroviral treatment (ART) for HIV are being scaled up in the expectation that they will better meet the needs of patients, improve the quality and efficiency of treatment delivery and reduce costs while maintaining at least equivalent clinical outcomes. We reviewed the recent literature on DSD models to describe what is known about clinical outcomes.MethodsWe conducted a rapid systematic review of peer‐reviewed publications in PubMed, Embase and the Web of Science and major international conference abstracts that reported outcomes of DSD models for the provision of ART in sub‐Saharan Africa from January 1, 2016 to September 12, 2019. Sources reporting standard clinical HIV treatment metrics, primarily retention in care and viral load suppression, were reviewed and categorized by DSD model and source quality assessed.Results and discussionTwenty‐nine papers and abstracts describing 37 DSD models and reporting 52 discrete outcomes met search inclusion criteria. Of the 37 models, 7 (19%) were facility‐based individual models, 12 (32%) out‐of‐facility‐based individual models, 5 (14%) client‐led groups and 13 (35%) healthcare worker‐led groups. Retention was reported for 29 (78%) of the models and viral suppression for 22 (59%). Where a comparison with conventional care was provided, retention in most DSD models was within 5% of that for conventional care; where no comparison was provided, retention generally exceeded 80% (range 47% to 100%). For viral suppression, all those with a comparison to conventional care reported a small increase in suppression in the DSD model; reported suppression exceeded 90% (range 77% to 98%) in 11/21 models. Analysis was limited by the extensive heterogeneity of study designs, outcomes, models and populations. Most sources did not provide comparisons with conventional care, and metrics for assessing outcomes varied widely and were in many cases poorly defined.ConclusionsExisting evidence on the clinical outcomes of DSD models for HIV treatment in sub‐Saharan Africa is limited in both quantity and quality but suggests that retention in care and viral suppression are roughly equivalent to those in conventional models of care.

AbstractIntroductionHIV self‐testing (HIVST) in outpatient departments (OPD) is a promising strategy for HIV testing in Malawi, given high OPD patient volumes and substantial wait times. To evaluate the relative cost and expected impact of facility‐based HIVST (FB‐HIVST) at OPDs in Malawi for increasing HIV status awareness, we conducted an economic evaluation of an HIVST cluster‐randomized controlled trial.MethodsA cluster‐randomized trial was conducted at 15 sites in Malawi from September 2017 to February 2018 with three arms: 1) Standard provider‐initiated‐testing‐and‐counselling (PITC); 2) Optimized PITC (additional provider training and job‐aids) and 3) FB‐HIVST (HIVST demonstration, distribution and kit use in OPD, private kit interpretation and optional HIV counselling). The total production cost per newly identified positive and per person newly initiated on ART were calculated by study arm. These were calculated as the total cost of testing everyone divided by the number of newly identified positives; and the total cost of testing everyone divided by the number of those initiated on ART. Cost‐outcomes were calculated under three cost scenarios: (1) full study costs, (2) routine implementation costs and (3) routine implementation + reduced cost for HIVST kits.ResultsThe average cost per person newly diagnosed in the full study cost scenario was $101, $156 and $189, and cost per person initiated on ART was $121, $156 and $279 for Standard PITC, Optimized PITC and FB‐HIVST respectively. In the routine implementation cost scenario, the average cost per person newly diagnosed was reduced to $83, and $93, and cost per person initiated on ART to $83, and $137 for Optimized PITC and FB‐HIVST respectively. In the negotiated HIVST cost scenario, the average cost per person newly diagnosed was reduced to $55 and cost per person newly initiated on ART reduced to $81 in the FB‐HIVST arm.ConclusionsWhile the cost per new ART initiation through FB‐HIVST was higher than Standard PITC, FB‐HIVST could become cost‐saving compared to PITC if the cost of kits is reduced or if treatment linkage rate were increased in the FB‐HIVST arm. For high volume OPDs, HIVST may increase facility capacity and increase the number of newly diagnosed positives.

IntroductionA substantial number of patients with HIV in South Africa have failed first‐line antiretroviral therapy (ART). Although individual predictors of first‐line ART failure have been identified, few studies in resource‐limited settings have been large enough for predictive modelling. Understanding the absolute risk of first‐line failure is useful for patient monitoring and for effectively targeting limited resources for second‐line ART. We developed a predictive model to identify patients at the greatest risk of virologic failure on first‐line ART, and to estimate the proportion of patients needing second‐line ART over five years on treatment.MethodsA cohort of patients aged ≥18 years from nine South African HIV clinics on first‐line ART for at least six months were included. Viral load measurements and baseline predictors were obtained from medical records. We used stepwise selection of predictors in accelerated failure‐time models to predict virologic failure on first‐line ART (two consecutive viral load levels >1000 copies/mL). Multiple imputations were used to assign missing baseline variables. The final model was selected using internal‐external cross‐validation maximizing model calibration at five years on ART, and model discrimination, measured using Harrell's C‐statistic. Model covariates were used to create a predictive score for risk group of ART failure.ResultsA total of 72,181 patients were included in the analysis, with an average of 21.5 months (IQR: 8.8–41.5) of follow‐up time on first‐line ART. The final predictive model had a Weibull distribution and the final predictors of virologic failure were men of all ages, young women, nevirapine use in first‐line regimen, low baseline CD4 count, high mean corpuscular volume, low haemoglobin, history of TB and missed visits during the first six months on ART. About 24.4% of patients in the highest quintile and 9.4% of patients in the lowest quintile of risk were predicted to experience treatment failure over five years on ART.ConclusionsAge, sex, CD4 count and having any missed visits during the first six months on ART were the strongest predictors of ART failure. The predictive model identified patients at high risk of failure, and the predicted failure rates over five years closely reflected actual rates of failure.