Suchergebnisse

Background: Having 90% of patients on antiretroviral therapy (ART) and achieving an undetectable viral load (VL) is 1 of the 90: 90: 90 by 2020 targets. In this global analysis, we investigated the proportions of adult and paediatric patients with VL suppression in the first 3 years after ART initiation. Methods: Patients from the IeDEA cohorts who initiated ART between 2010 and 2014 were included. Proportions with VL suppression (<1000 copies/ mL) were estimated using (1) strict intention to treat (ITT)-loss to follow-up (LTFU) and dead patients counted as having detectable VL; and (2) modified ITT-LTFU and dead patients were excluded. Logistic regression was used to identify predictors of viral suppression at 1 year after ART initiation using modified ITT. Results: A total of 35,561 adults from 38 sites/16 countries and 2601 children from 18 sites/6 countries were included. When comparing strict with modified ITT methods, the proportion achieving VL suppression at 3 years from ART initiation changed from 45.1% to 90.2% in adults, and 60.6% to 80.4% in children. In adults, older age, higher CD4 count preART, and homosexual/bisexual HIV exposure were associated with VL suppression. In children, older age and higher CD4 percentage pre-ART showed significant associations with VL suppression. Conclusions: Large increases in the proportion of VL suppression in adults were observed when we excluded those who were LTFU or had died. The increases were less pronounced in children. Greater emphasis should be made to minimize LTFU and maximize patient retention in HIV-infected patients of all age groups. ; U.S. National Institutes of Health's National Institute of Allergy and Infectious Diseases ; Eunice Kennedy Shriver National Institute of Child Health and Human Development ; National Cancer Institute ; Centers for Disease Control and Prevention, USA ; Agency for Healthcare Research and Quality, USA ; Health Resources and Services Administration, USA ; Canadian Institutes of Health Research, Canada ; Ontario Ministry of Health and Long Term Care ; Government of Alberta, Canada ; Intramural Research Program of the National Cancer Institute ; Australian Government Department of Health and Ageing ; UNSW, Kirby Inst, Sydney, NSW 2052, Australia ; Johns Hopkins Bloomberg Sch Publ Hlth, Dept Epidemiol, Baltimore, MD USA ; Fdn Huesped, Buenos Aires, DF, Argentina ; Univ Chile, Sch Med, Santiago, Chile ; Fdn Arriaran, Santiago, Chile ; Univ Cape Town, Sch Publ Hlth & Family Med, Cape Town, South Africa ; Childrens Hosp 2, Ho Chi Minh City, Vietnam ; Univ Cape Town, Dept Paediat & Child Hlth, Cape Town, South Africa ; Univ Calgary, Calgary, AB, Canada ; YRGCARE Med Ctr, Madras, Tamil Nadu, India ; Univ Fed Sao Paulo, Pediat Infect Dis Div, Escola Paulista Med, Sao Paulo, Brazil ; Johns Hopkins Univ, Dept Med, Div Infect Dis, Baltimore, MD USA ; Univ Stellenbosch, Dept Med, Div Infect Dis, Cape Town, South Africa ; Tygerberg Hosp, Cape Town, South Africa ; Univ Bern, Inst Social & Prevent Med, Bern, Switzerland ; Univ Fed Sao Paulo, Pediat Infect Dis Div, Escola Paulista Med, Sao Paulo, Brazil ; NCI: U01AI035004 ; NCI: U01AI035039 ; NCI: U01AI035040 ; NCI: U01AI035041 ; NCI: U01AI035042 ; NCI: U01AI037613 ; NCI: U01AI037984 ; NCI: U01AI038855 ; NCI: U01AI038858 ; NCI: U01AI042590 ; NCI: U01AI068634 ; NCI: U01AI068636 ; NCI: U01AI069432 ; NCI: U01AI069434 ; Centers for Disease Control and Prevention, USA: CDC-200-2006-18797 ; Centers for Disease Control and Prevention, USA: CDC-200-2015-63931 ; Agency for Healthcare Research and Quality, USA: 90047713 ; Health Resources and Services Administration, USA: 90051652 ; Canadian Institutes of Health Research, Canada: CBR-86906 ; Canadian Institutes of Health Research, Canada: CBR-94036 ; Canadian Institutes of Health Research, Canada: HCP-97105 ; Canadian Institutes of Health Research, Canada: TGF-96118 ; NCI: P30AI027757 ; NCI: P30AI027763 ; NCI: P30AI027767 ; NCI: P30AI036219 ; NCI: P30AI050410 ; NCI: P30AI094189 ; NCI: P30AI110527 ; NCI: P30MH62246 ; NCI: R01AA016893 ; NCI: R01CA165937 ; NCI: R01DA004334 ; NCI: R01DA011602 ; NCI: R01DA012568 ; NCI: R24AI067039 ; NCI: U01AA013566 ; NCI: U01AA020790 ; NCI: U01AI1031834 ; NCI: U01AI034989 ; NCI: U01AI034993 ; NCI: U01AI034994 ; NCI: M01RR000052 ; NCI: U54MD007587 ; NCI: UL1RR024131 ; NCI: UL1TR000004 ; NCI: UL1TR000083 ; NCI: UL1TR000454 ; NCI: UM1AI035043 ; NCI: Z01CP010214 ; NCI: Z01CP010176 ; NCI: U01AI069907 ; NCI: U01AI069923 ; NCI: U01AI069924 ; NCI: U01AI069918 ; NCI: F31DA037788 ; NCI: G12MD007583 ; NCI: K01A1093197 ; NCI: K23EY013707 ; NCI: K24DA000432 ; NCI: K24AI065298 ; NCI: KL2TR000421 ; NCI: N02CP055504 ; NCI: U01AI103390 ; NCI: U01AI103397 ; NCI: U01AI103401 ; NCI: U01AI103408 ; NCI: U01DA036935 ; NCI: U01HD032632 ; NCI: U10EY008057 ; NCI: U10EY008052 ; NCI: U10EY008067 ; NCI: U24AA020794 ; Web of Science

AbstractIntroductionThe World Health Organization (WHO) recommends a CD4 cell count before starting antiretroviral therapy (ART) to detect advanced HIV disease, and routine viral load (VL) testing following ART initiation to detect treatment failure. Donor support for CD4 testing has declined to prioritize access to VL monitoring. We examined trends in CD4 and VL testing among adults (≥15 years of age) starting ART in Southern Africa.MethodsWe analysed data from 14 HIV treatment programmes in Lesotho, Malawi, Mozambique, South Africa, Zambia and Zimbabwe in 2005 to 2018. We examined the frequency of CD4 and VL testing, the percentage of adults with CD4 or VL tests, and among those having a test, the percentage starting ART with advanced HIV disease (CD4 count <200 cells/mm3) or failing to suppress viral replication (>1000 HIV‐RNA copies/mL) after ART initiation. We used mixed effect logistic regression to assess time trends adjusted for age and sex.ResultsAmong 502,456 adults, the percentage with CD4 testing at ART initiation decreased from a high of 78.1% in 2008 to a low of 38.0% in 2017; the probability declined by 14% each year (odds ratio (OR) 0.86; 95% CI 0.86 to 0.86). Frequency of CD4 testing also declined. The percentage starting ART with advanced HIV disease declined from 83.3% in 2005 to 23.5% in 2018; each year the probability declined by 20% (OR 0.80; 95% CI 0.80 to 0.81). VL testing after starting ART varied; 61.0% of adults in South Africa and 10.7% in Malawi were tested, but fewer than 2% were tested in the other four countries. The probability of VL testing after ART start increased only modestly each year (OR 1.06; 95% CI 1.05 to 1.06). The percentage with unsuppressed VL was 8.6%. There was no evidence of a decrease in unsuppressed VL over time (OR 1.00; 95% CI 0.99 to 1.01).ConclusionsCD4 cell counting declined over time, including testing at the start of ART, despite the fact that many patients still initiated ART with advanced HIV disease. Without CD4 testing and expanded VL testing many patients with advanced HIV disease and treatment failure may go undetected, threatening the effectiveness of ART in sub‐Saharan Africa.

AbstractIntroductionBy 2020, 90% of all people diagnosed with HIV should receive long‐term combination antiretroviral therapy (ART). In sub‐Saharan Africa, this target is threatened by loss to follow‐up in ART programmes. The proportion of people retained on ART long‐term cannot be easily determined, because individuals classified as lost to follow‐up, may have self‐transferred to another HIV treatment programme, or may have died. We describe retention on ART in sub‐Saharan Africa, first based on observed data as recorded in the clinic databases, and second adjusted for undocumented deaths and self‐transfers.MethodsWe analysed data from HIV‐infected adults and children initiating ART between 2009 and 2014 at a sub‐Saharan African HIV treatment programme participating in the International epidemiology Databases to Evaluate AIDS (IeDEA). We used the Kaplan–Meier method to calculate the cumulative incidence of retention on ART and the Aalen–Johansen method to calculate the cumulative incidences of death, loss to follow‐up, and stopping ART. We used inverse probability weighting to adjust clinic data for undocumented mortality and self‐transfer, based on estimates from a recent systematic review and meta‐analysis.ResultsWe included 505,634 patients: 12,848 (2.5%) from Central Africa, 109,233 (21.6%) from East Africa, 347,343 (68.7%) from Southern Africa and 36,210 (7.2%) from West Africa. In crude analyses of observed clinic data, 52.1% of patients were retained on ART, 41.8% were lost to follow‐up and 6.0% had died 5 years after ART initiation. After accounting for undocumented deaths and self‐transfers, we estimated that 66.6% of patients were retained on ART, 18.8% had stopped ART and 14.7% had died at 5 years.ConclusionsImproving long‐term retention on ART will be crucial to attaining the 90% on ART target. Naïve analyses of HIV cohort studies, which do not account for undocumented mortality and self‐transfer of patients, may severely underestimate both mortality and retention on ART.

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.