Suchergebnisse

BackgroundMortality of HIV‐infected patients initiating antiretroviral therapy in the developing world is very high immediately after the start of ART therapy and drops sharply thereafter. It is necessary to use models of survival time that reflect this change.MethodsIn this endeavor, parametric models with changepoints such as Weibull models can be useful in order to explicitly model the underlying failure process, even in the case where abrupt changes in the mortality rate are present. Estimation of the temporal location of possible mortality changepoints has important implications on the effective management of these patients. We briefly describe these models and apply them to the case of estimating survival among HIV‐infected patients who are initiating antiretroviral therapy in a care and treatment programme in sub‐Saharan Africa.ResultsAs a first reported data‐driven estimate of the existence and location of early mortality changepoints after antiretroviral therapy initiation, we show that there is an early change in risk of death at three months, followed by an intermediate risk period lasting up to 10 months after therapy.ConclusionBy explicitly modelling the underlying abrupt changes in mortality risk after initiation of antiretroviral therapy we are able to estimate their number and location in a rigorous, data‐driven manner. The existence of a high early risk of death after initiation of antiretroviral therapy and the determination of its duration has direct implications for the optimal management of patients initiating therapy in this setting.

BackgroundUpdated World Health Organization guidelines have amplified debate about how resource constraints should impact monitoring strategies for HIV‐infected persons on combination antiretroviral therapy (cART). We estimated the incremental benefit and cost effectiveness of alternative monitoring strategies for east Africans with known HIV infection.MethodsUsing a validated HIV computer simulation based on resource‐limited data (USAID and AMPATH) and circumstances (east Africa), we compared alternative monitoring strategies for HIV‐infected persons newly started on cART. We evaluated clinical, immunologic and virologic monitoring strategies, including combinations and conditional logic (e.g., only perform virologic testing if immunologic testing is positive). We calculated incremental cost‐effectiveness ratios (ICER) in units of cost per quality‐adjusted life year (QALY), using a societal perspective and a lifetime horizon. Costs were measured in 2008 US dollars, and costs and benefits were discounted at 3%. We compared the ICER of monitoring strategies with those of other resource‐constrained decisions, in particular earlier cART initiation (at CD4 counts of 350 cells/mm3rather than 200 cells/mm3).ResultsMonitoring strategies employing routine CD4 testing without virologic testing never maximized health benefits, regardless of budget or societal willingness to pay for additional health benefits. Monitoring strategies employing virologic testing conditional upon particular CD4 results delivered the most benefit at willingness‐to‐pay levels similar to the cost of earlier cART initiation (approximately $2600/QALY). Monitoring strategies employing routine virologic testing alone only maximized health benefits at willingness‐to‐pay levels (> $4400/QALY) that greatly exceeded the ICER of earlier cART initiation.ConclusionsCD4 testing alone never maximized health benefits regardless of resource limitations. Programmes routinely performing virologic testing but deferring cART initiation may increase health benefits by reallocating monitoring resources towards earlier cART initiation.

AbstractIntroductionOlder adolescents aged 15–19 years continue to have high rates of loss to follow up (LTFU), and high rates of virologic non‐suppression (VNS) compared to younger adolescents and adults. Adolescent females are at risk of pregnancy, which puts those living with HIV at a dual vulnerability. Our study assessed the factors associated with VNS and LTFU in older adolescents (including pregnant females) who initiated antiretroviral therapy (ART) in South Africa.MethodsWe included adolescents aged 15–19 years initiating ART between 2004 and 2019, with ≥ one viral load (VL) measurement between 4 and 24.5 months, and ≥ 6 months follow‐up, from six South African cohorts of the International epidemiology Databases to Evaluate AIDS‐Southern Africa (IeDEA‐SA). We defined VNS as VL ≥400 copies/ml and LTFU as not being in care for ≥180 days from ART start and not known as transferred out of the clinic or dead in the first 24 months on ART. We examined factors associated with VNS and LTFU using Fine&Gray competing risk models.ResultsWe included a total of 2733 adolescents, 415 (15.2%) males, median (IQR) age at ART start of 18.6 (17.3, 19.4) years. Among females, 585/2318 (25.2%) were pregnant. Over the 24‐month follow‐up, 424 (15.5%) of all adolescents experienced VNS: range (11.1% pregnant females and 20.5% males). Over half of all adolescents were LTFU before any other event could occur. The hazard of VNS reduced with increasing age and CD4 count above 200 cells/μl at ART initiation among all adolescents having adjusted for all measured patient characteristics [adjusted sub‐distribution hazard ratio (aSHR) 19 vs. 15 years: 0.50 (95% CI: 0.36, 0.68), aSHR: >500 vs. ≤200 cells/μl: 0.22 (95% CI: 0.16, 0.31)]. The effect of CD4 count persisted in pregnant females. Increasing age and CD4 count >200 cells/μl were risk factors for LTFU among all adolescents.ConclusionsOlder adolescents had a high risk of LTFU shortly after ART start and a low risk of VNS, especially those initiating treatment during pregnancy. Interventions addressing adherence and retention should be incorporated into adolescent‐friendly services to prevent VNS and LTFU and endeavour to trace lost adolescents as soon as they are identified.

ObjectiveEstimates of CD4 response to antiretroviral therapy (ART) obtained by averaging data from patients in care, overestimate population CD4 response and treatment program effectiveness because they do not consider data from patients who are deceased or not in care. We use mathematical methods to assess and adjust for this bias based on patient characteristics.DesignWe examined data from 25,261 HIV‐positive patients from the East Africa IeDEA Consortium.MethodsWe used inverse probability of censoring weighting (IPCW) to represent patients not in care by patients in care with similar characteristics. We address two questions: What would the median CD4 be "had everyone starting ART remained on observation?" and "were everyone starting ART maintained on treatment?"ResultsRoutine CD4 count estimates were higher than adjusted estimates even under the best‐case scenario of maintaining all patients on treatment. Two years after starting ART, differences between estimates diverged from 30 cells/µL, assuming similar mortality and treatment access among dropouts as patients in care, to over 100 cells/µL assuming 20% lower survival and 50% lower treatment access among dropouts. When considering only patients in care, the proportion of patients with CD4 above 350 cells/µL was 50% adjusted to below 30% when accounting for patients not in care. One‐year mortality diverged 6–14% from the naïve estimates depending on assumptions about access to care among lost patients.ConclusionsIgnoring mortality and loss to care results in over‐estimation of ART response for patients starting treatment and exaggerates the efficacy of treatment programs administering it.

AbstractIntroductionContraceptive implants containing etonogestrel and levonorgestrel have emerged as popular contraceptive options among women in areas of high HIV burden in sub‐Saharan Africa. However, recent pharmacokinetic data have shown drug–drug interactions between implants and efavirenz‐containing antiretroviral therapy (ART), reducing the effectiveness of the implants. Here, we evaluated pregnancy incidence in 6‐month intervals following implant initiation among women using efavirenz and contraceptive implants to assess whether the risk of breakthrough pregnancy is higher after specific periods of implant use.MethodsWe used data from a retrospective longitudinal analysis of women living with HIV ages 18–45 years in western Kenya who attended HIV‐care facilities between 2011 and 2015. We used Cox proportional hazard models to compute hazard ratios (HRs) for breakthrough pregnancy by implant type and ART regimen. Depending on the model, we adjusted for socio‐demographic and clinical factors, programme, site and interaction between calendar time and ART regimen. We utilized inverse probability weights (IPWs) to account for three sampling phases (electronic medical record [EMR], chart review and phone interview) and calculated overall parameter estimates.ResultsWomen contributed 14,768 woman‐years from the largest sampling phase (EMR). The median age was 31 years. Women used etonogestrel implants for 26–69% of the time and levonorgestrel implants for 7–31% of the time, depending on the sampling phase. Women used efavirenz, nevirapine or no ART for 27–33%, 40–46% and 15–26% of follow‐ups, respectively. When combining sampling phases, there was little evidence to suggest that the relative hazard of pregnancy among efavirenz‐containing ART users relative to nevirapine‐containing ART changed with length of time on implants: IPW‐adjusted HR of 3.1 (CI: [1.5; 6.4]) at 12 months, 3.4 (CI: [1.8; 6.3]) at 24 months, 3.8 (CI: [1.9; 7.7]) at 36 months and 4.2 (CI: [1.6; 11.1]) at 48 months (interaction p‐value = 0.88). Similarly, no significant change in HRs over time was found when comparing women not using ART to nevirapine‐containing ART users (interaction p‐value = 0.49).ConclusionsWe did not find evidence to suggest implants being more fallible from drug–drug interactions with efavirenz at later time intervals of implant use. Thus, we would not recommend shortening the duration of implant use or replacing implants sooner when concomitantly used with efavirenz.

AbstractIntroductionAdolescence and pregnancy are potential risk factors for loss to follow‐up (LTFU) while on antiretroviral therapy (ART). We compared adolescent and adult LTFU after ART initiation to quantify the impact of age, pregnancy, and site‐level factors on LTFU.MethodsWe used routine clinical data for patients initiating ART as young adolescents (YA; 10 to 14 years), older adolescents (OA; 15 to 19 years) and adults (≥20 years) from 2000 to 2014 at 52 health facilities affiliated with the International epidemiology Databases to Evaluate AIDS (IeDEA) East Africa collaboration. We estimated cumulative incidence (95% confidence interval, CI) of LTFU (no clinic visit for ≥6 months after ART initiation) and identified patient and site‐level correlates of LTFU, using multivariable Cox proportional hazards models for all patients as well as individual age groups.ResultsA total of 138,387 patients initiated ART, including 2496 YA, 2955 OA and 132,936 adults. Of these, 55%, 78% and 66%, respectively, were female and 0.7% of YA, 22.3% of OA and 8.3% of adults were pregnant at ART initiation. Cumulative incidence of LTFU at five years was 26.6% (24.6 to 28.6) among YA, 44.1% (41.8 to 46.3) among OA and 29.3% (29.1 to 29.6) among adults. Overall, compared to adults, the adjusted hazard ratio, aHR, (95% CI) of LTFU for OA was 1.54 (1.41 to 1.68) and 0.77 (0.69 to 0.86) for YA. Compared to males, pregnant females had higher hazard of LTFU, aHR 1.20 (1.14 to 1.27), and nonpregnant women had lower hazard aHR 0.90 (0.88 to 0.93). LTFU hazard among the OA was primarily driven by both pregnant and nonpregnant females, aHR 2.42 (1.98 to 2.95) and 1.51 (1.27 to 1.80), respectively, compared to men. The LTFU hazard ratio varied by IeDEA program. Site‐level factors associated with overall lower LTFU hazard included receiving care in tertiary versus primary‐care clinics aHR 0.61 (0.56 to 0.67), integrated adult and adolescent services and food ration provision aHR 0.93 (0.89 to 0.97) versus nonintegrated clinics with food ration provision, having patient support groups aHR 0.77 (0.66 to 0.90) and group adherence counselling aHR 0.61 (0.57 to 0.67).ConclusionsOlder adolescents experienced higher risk of LTFU compared to YA and adults. Interventions to prevent LTFU among older adolescents are critically needed, particularly for female and/or pregnant adolescents.

AbstractIntroductionThe third of the Joint United Nations Programme on HIV/AIDS (UNAIDS) 90‐90‐90 targets is to achieve a 90% rate of viral suppression (HIV viral load <1000 HIV‐1 RNA copies/ml) in patients on antiretroviral treatment (ART) by 2020. However, some countries use different thresholds when reporting viral suppression, and there is thus a need for an adjustment to standardize estimates to the <1000 threshold. We aim to propose such an adjustment, to support consistent monitoring of progress towards the "third 90" target.MethodsWe considered three possible distributions for viral loads in ART patients: Weibull, Pareto and reverse Weibull (imposing an upper limit but no lower limit on the log scale). The models were fitted to data on viral load distributions in ART patients in the International epidemiology Databases to Evaluate AIDS (IeDEA) collaboration (representing seven global regions) and the ART Cohort Collaboration (representing Europe), using separate random effects models for adults and children. The models were validated using data from the World Health Organization (WHO) HIV drug resistance report and the Brazilian national ART programme.ResultsModels were calibrated using 921,157 adult and 37,431 paediatric viral load measurements, over 2010–2019. The Pareto and reverse Weibull models provided the best fits to the data, but for all models, the "shape" parameters for the viral load distributions differed significantly between regions. The Weibull model performed best in the validation against the WHO drug resistance survey data, while the Pareto model produced uncertainty ranges that were too narrow, relative to the validation data. Based on these analyses, we recommend using the reverse Weibull model. For example, if a country reports an 80% rate of viral suppression at <200 copies/ml, this model estimates the proportion virally suppressed at <1000 copies/ml is 88.3% (0.800.56), with uncertainty range 85.5–90.6% (0.800.70–0.800.44).ConclusionsEstimates of viral suppression can change substantially depending on the threshold used in defining viral suppression. It is, therefore, important that viral suppression rates are standardized to the same threshold for the purpose of assessing progress towards UNAIDS targets. We have proposed a simple adjustment that allows this, and this has been incorporated into UNAIDS modelling software.

AbstractIntroductionThe Joint United Nations Programme on HIV/AIDS (UNAIDS) projections of paediatric HIV prevalence and deaths rely on the International epidemiology Databases to Evaluate AIDS (IeDEA) consortium for mortality estimates among children living with HIV (CHIV) receiving antiretroviral therapy (ART). Previous estimates, based on data through 2014, may no longer be accurate due to expanded paediatric HIV care and treatment eligibility, and the possibility of unreported deaths in CHIV considered lost to follow‐up (LTFU). We therefore estimated all‐cause mortality and its trends in CHIV (<15 years old) on ART using extended and new IeDEA data.MethodsWe analysed (i) IeDEA observational data from CHIV in routine care globally, and (ii) novel data from an IeDEA tracing study that determined outcomes in a sample of CHIV after being LTFU in southern Africa. We included 45,711 CHIV on ART during 2004 to 2017 at 72 programmes in Africa, Asia‐Pacific and Latin America. We used mixed effects Poisson regression to estimate mortality by age, sex, CD4 at ART start, time on ART, region and calendar year. For Africa, in an adjusted analysis that accounts for unreported deaths among those LTFU, we first modified the routine data by simulating mortality outcomes within six months after LTFU, based on a Gompertz survival model fitted to the tracing data (n = 221).ResultsObserved mortality rates were 1.8 (95% CI: 1.7 to 1.9) and 9.4 (6.3 to 13.4) deaths per 100 person‐years in the routine and tracing data, respectively. We found strong evidence of higher mortality at shorter ART durations, lower CD4 values, and in infancy. Averaging over covariate patterns, the adjusted mortality rate was 54% higher than the unadjusted rate. In unadjusted analyses, mortality reduced by an average 60% and 73% from 2005 to 2017, within and outside of Africa, respectively. In the adjusted analysis for Africa, this temporal reduction was 42%.ConclusionsMortality rates among CHIV have decreased substantially over time. However, when accounting for worse outcomes among those LTFU, mortality estimates increased and temporal improvements were slightly reduced, suggesting caution in interpreting analyses based only on programme data. The improved and updated IeDEA estimates on mortality among CHIV on ART support UNAIDS efforts to accurately model global HIV statistics.

BackgroundEast Africa has experienced a rapid expansion in access to antiretroviral therapy (ART) for HIV‐infected patients. Regionally representative socio‐demographic, laboratory and clinical characteristics of patients accessing ART over time and across sites have not been well described.MethodsWe conducted a cross‐sectional analysis of characteristics of HIV‐infected adults initiating ART between 2002 and 2009 in Kenya, Uganda and Tanzania and in the International Epidemiologic Databases to Evaluate AIDS Consortium. Characteristics associated with advanced disease (defined as either a CD4 cell count level of less than 50 cells/mm3 or a WHO Stage 4 condition) at the time of ART initiation and use of stavudine (D4T) or nevirapine (NVP) were identified using a log‐link Poisson model with robust standard errors.ResultsAmong 48, 658 patients (69% from Kenya, 22% from Uganda and 9% from Tanzania) accessing ART at 30 clinic sites, the median age at the time of ART initiation was 37 years (IQR: 31‐43) and 65% were women. Pre‐therapy CD4 counts rose from 87 cells/mm3 (IQR: 26‐161) in 2002‐03 to 154 cells/mm3 (IQR: 71‐233) in 2008‐09 (p < 0.001). Accessing ART at advanced disease peaked at 35% in 2005‐06 and fell to 27% in 2008‐09. D4T use in the initial regimen fell from a peak of 88% in 2004‐05 to 59% in 2008‐09, and a greater extent of decline was observed in Uganda than in Kenya and Tanzania. Self‐pay for ART peaked at 18% in 2003, but fell to less than 1% by 2005. In multivariable analyses, accessing ART at advanced immunosuppression was associated with male sex, women without a history of treatment for prevention of mother to child transmission (both as compared with women with such a history) and younger age after adjusting for year of ART initiation and country of residence. Receipt of D4T in the initial regimen was associated with female sex, earlier year of ART initiation, higher WHO stage, and lower CD4 levels at ART initiation and the absence of co‐prevalent tuberculosis.ConclusionsPublic health ART services in east Africa have improved over time, but the fraction of patients accessing ART with advanced immunosuppression is still high, men consistently access ART with more advanced disease, and D4T continues to be common in most settings. Strategies to facilitate access to ART, overcome barriers among men and reduce D4T use are needed.

AbstractIntroduction"Treat All" – the treatment of all people with HIV, irrespective of disease stage or CD4 cell count – represents a paradigm shift in HIV care that has the potential to end AIDS as a public health threat. With accelerating implementation of Treat All in sub‐Saharan Africa (SSA), there is a need for a focused agenda and research to identify and inform strategies for promoting timely uptake of HIV treatment, retention in care, and sustained viral suppression and addressing bottlenecks impeding implementation.MethodsThe Delphi approach was used to develop consensus around research priorities for Treat All implementation in SSA. Through an iterative process (June 2017 to March 2018), a set of research priorities was collectively formulated and refined by a technical working group and shared for review, deliberation and prioritization by more than 200 researchers, implementation experts, policy/decision‐makers, and HIV community representatives in East, Central, Southern and West Africa.Results and discussionThe process resulted in a list of nine research priorities for generating evidence to guide Treat All policies, implementation strategies and monitoring efforts. These priorities highlight the need for increased focus on adolescents, men, and those with mental health and substance use disorders – groups that remain underserved in SSA and for whom more effective testing, linkage and care strategies need to be identified. The priorities also reflect consensus on the need to: (1) generate accurate national and sub‐national estimates of the size of key populations and describe those who remain underserved along the HIV‐care continuum; (2) characterize the timeliness of HIV care and short‐ and long‐term HIV care continuum outcomes, as well as factors influencing timely achievement of these outcomes; (3) estimate the incidence and prevalence of HIV‐drug resistance and regimen switching; and (4) identify cost‐effective and affordable service delivery models and strategies to optimize uptake and minimize gaps, disparities, and losses along the HIV‐care continuum, particularly among underserved populations.ConclusionsReflecting consensus among a broad group of experts, researchers, policy‐ and decision‐makers, PLWH, and other stakeholders, the resulting research priorities highlight important evidence gaps that are relevant for ministries of health, funders, normative bodies and research networks.