Public-health and individual approaches to antiretroviral therapy: township South Africa and Switzerland compared

BACKGROUND: The provision of highly active antiretroviral therapy (HAART) in resource-limited settings follows a public health approach, which is characterised by a limited number of regimens and the standardisation of clinical and laboratory monitoring. In industrialized countries doctors prescribe from the full range of available antiretroviral drugs, supported by resistance testing and frequent laboratory monitoring. We compared virologic response, changes to first-line regimens, and mortality in HIV-infected patients starting HAART in South Africa and Switzerland. METHODS AND FINDINGS: We analysed data from the Swiss HIV Cohort Study and two HAART programmes in townships of Cape Town, South Africa. We included treatment-naïve patients aged 16 y or older who had started treatment with at least three drugs since 2001, and excluded intravenous drug users. Data from a total of 2,348 patients from South Africa and 1,016 patients from the Swiss HIV Cohort Study were analysed. Median baseline CD4+ T cell counts were 80 cells/mul in South Africa and 204 cells/mul in Switzerland. In South Africa, patients started with one of four first-line regimens, which was subsequently changed in 514 patients (22%). In Switzerland, 36 first-line regimens were used initially, and these were changed in 539 patients (53%). In most patients HIV-1 RNA was suppressed to 500 copies/ml or less within one year: 96% (95% confidence interval [CI] 95%-97%) in South Africa and 96% (94%-97%) in Switzerland, and 26% (22%-29%) and 27% (24%-31%), respectively, developed viral rebound within two years. Mortality was higher in South Africa than in Switzerland during the first months of HAART: adjusted hazard ratios were 5.90 (95% CI 1.81-19.2) during months 1-3 and 1.77 (0.90-3.50) during months 4-24. CONCLUSIONS: Compared to the highly individualised approach in Switzerland, programmatic HAART in South Africa resulted in similar virologic outcomes, with relatively few changes to initial regimens. Further innovation and resources are required in South Africa to both achieve more timely access to HAART and improve the prognosis of patients who start HAART with advanced disease.

Outcomes of the South African National Antiretroviral Treatment Programme for children: the IeDEA Southern Africa collaboration

OBJECTIVES: To assess paediatric antiretroviral treatment (ART) outcomes and their associations from a collaborative cohort representing 20% of the South African national treatment programme. DESIGN AND SETTING: Multi-cohort study of 7 public sector paediatric ART programmes in Gauteng, Western Cape and KwaZulu-Natal provinces. SUBJECTS: ART-naive children (< or = 16 years) who commenced treatment with > or = 3 antiretroviral drugs before March 2008. OUTCOME MEASURES: Time to death or loss to follow-up were assessed using the Kaplan-Meier method. Associations between baseline characteristics and mortality were assessed with Cox proportional hazards models stratified by site. Immune status, virological suppression and growth were described in relation to duration of ART. RESULTS: The median (interquartile range) age of 6 078 children with 9 368 child-years of follow-up was 43 (15 - 83) months, with 29% being < 18 months. Most were severely ill at ART initiation. More than 75% of children were appropriately monitored at 6-monthly intervals with viral load suppression (< 400 copies/ml) being 80% or above throughout 36 months of treatment. Mortality and retention in care at 3 years were 7.7% (95% confidence interval 7.0 - 8.6%) and 81.4% (80.1 - 82.6%), respectively. Together with young age, all markers of disease severity (low weight-for-age z-score, high viral load, severe immune suppression, stage 3/4 disease and anaemia) were independently associated with mortality. CONCLUSIONS: Dramatic clinical benefit for children accessing the national ART programme is demonstrated. Higher mortality in infants and those with advanced disease highlights the need for early diagnosis of HIV infection and commencement of ART.

CD4 count slope and mortality in HIV-infected patients on antiretroviral therapy: multicohort analysis from South Africa

BACKGROUND In many resource-limited settings monitoring of combination antiretroviral therapy (cART) is based on the current CD4 count, with limited access to HIV RNA tests or laboratory diagnostics. We examined whether the CD4 count slope over 6 months could provide additional prognostic information. METHODS We analyzed data from a large multicohort study in South Africa, where HIV RNA is routinely monitored. Adult HIV-positive patients initiating cART between 2003 and 2010 were included. Mortality was analyzed in Cox models; CD4 count slope by HIV RNA level was assessed using linear mixed models. RESULTS About 44,829 patients (median age: 35 years, 58% female, median CD4 count at cART initiation: 116 cells/mm) were followed up for a median of 1.9 years, with 3706 deaths. Mean CD4 count slopes per week ranged from 1.4 [95% confidence interval (CI): 1.2 to 1.6] cells per cubic millimeter when HIV RNA was <400 copies per milliliter to -0.32 (95% CI: -0.47 to -0.18) cells per cubic millimeter with >100,000 copies per milliliter. The association of CD4 slope with mortality depended on current CD4 count: the adjusted hazard ratio (aHRs) comparing a >25% increase over 6 months with a >25% decrease was 0.68 (95% CI: 0.58 to 0.79) at <100 cells per cubic millimeter but 1.11 (95% CI: 0.78 to 1.58) at 201-350 cells per cubic millimeter. In contrast, the aHR for current CD4 count, comparing >350 with <100 cells per cubic millimeter, was 0.10 (95% CI: 0.05 to 0.20). CONCLUSIONS Absolute CD4 count remains a strong risk for mortality with a stable effect size over the first 4 years of cART. However, CD4 count slope and HIV RNA provide independently added to the model.

Monitoring of antiretroviral therapy and mortality in HIV programmes in Malawi, South Africa and Zambia: mathematical modelling study

OBJECTIVES Mortality in patients starting antiretroviral therapy (ART) is higher in Malawi and Zambia than in South Africa. We examined whether different monitoring of ART (viral load [VL] in South Africa and CD4 count in Malawi and Zambia) could explain this mortality difference. DESIGN Mathematical modelling study based on data from ART programmes. METHODS We used a stochastic simulation model to study the effect of VL monitoring on mortality over 5 years. In baseline scenario A all parameters were identical between strategies except for more timely and complete detection of treatment failure with VL monitoring. Additional scenarios introduced delays in switching to second-line ART (scenario B) or higher virologic failure rates (due to worse adherence) when monitoring was based on CD4 counts only (scenario C). Results are presented as relative risks (RR) with 95% prediction intervals and percent of observed mortality difference explained. RESULTS RRs comparing VL with CD4 cell count monitoring were 0.94 (0.74-1.03) in scenario A, 0.94 (0.77-1.02) with delayed switching (scenario B) and 0.80 (0.44-1.07) when assuming a 3-times higher rate of failure (scenario C). The observed mortality at 3 years was 10.9% in Malawi and Zambia and 8.6% in South Africa (absolute difference 2.3%). The percentage of the mortality difference explained by VL monitoring ranged from 4% (scenario A) to 32% (scenarios B and C combined, assuming a 3-times higher failure rate). Eleven percent was explained by non-HIV related mortality. CONCLUSIONS VL monitoring reduces mortality moderately when assuming improved adherence and decreased failure rates.

Life expectancies of South African adults starting antiretroviral treatment: collaborative analysis of cohort studies

BACKGROUND Few estimates exist of the life expectancy of HIV-positive adults receiving antiretroviral treatment (ART) in low- and middle-income countries. We aimed to estimate the life expectancy of patients starting ART in South Africa and compare it with that of HIV-negative adults. METHODS AND FINDINGS Data were collected from six South African ART cohorts. Analysis was restricted to 37,740 HIV-positive adults starting ART for the first time. Estimates of mortality were obtained by linking patient records to the national population register. Relative survival models were used to estimate the excess mortality attributable to HIV by age, for different baseline CD4 categories and different durations. Non-HIV mortality was estimated using a South African demographic model. The average life expectancy of men starting ART varied between 27.6 y (95% CI: 25.2-30.2) at age 20 y and 10.1 y (95% CI: 9.3-10.8) at age 60 y, while estimates for women at the same ages were substantially higher, at 36.8 y (95% CI: 34.0-39.7) and 14.4 y (95% CI: 13.3-15.3), respectively. The life expectancy of a 20-y-old woman was 43.1 y (95% CI: 40.1-46.0) if her baseline CD4 count was ≥ 200 cells/µl, compared to 29.5 y (95% CI: 26.2-33.0) if her baseline CD4 count was <50 cells/µl. Life expectancies of patients with baseline CD4 counts ≥ 200 cells/µl were between 70% and 86% of those in HIV-negative adults of the same age and sex, and life expectancies were increased by 15%-20% in patients who had survived 2 y after starting ART. However, the analysis was limited by a lack of mortality data at longer durations. CONCLUSIONS South African HIV-positive adults can have a near-normal life expectancy, provided that they start ART before their CD4 count drops below 200 cells/µl. These findings demonstrate that the near-normal life expectancies of HIV-positive individuals receiving ART in high-income countries can apply to low- and middle-income countries as well. Please see later in the article for the Editors' Summary.

OSL and TL dating of the Middle Stone Age sequence at Diepkloof Rock Shelter (South Africa): a clarification

Diepkloof Rock Shelter offers an exceptional opportunity to study the onset and evolution of both Still Bay (SB) and Howiesons Poort (HP) techno-complexes. However, previous age estimates based on luminescence dating of burnt quartzites (Tribolo et al., 2009) and of sediments (Jacobs et al., 2008) were not in agreement. Here, we present new luminescence ages for 17 rock samples (equivalent dose estimated with a SAR-ITL protocol instead of classical MAAD-TL) as well as for 5 sediment samples (equivalent dose estimated with SAR-single grain OSL protocol) and an update of the 22 previous age estimates for burnt lithics (modified calibration and beta dose estimates). While a good agreement between the rock and sediment ages is obtained, these estimates are still significantly older than those reported by Jacobs et al. (2008). After our own analyses of the sediment from Diepkloof, it is suspected that these authors did not correctly chose the parameters for the equivalent dose determination, leading to an underestimate of the equivalent doses, and thus of the ages. From bottom to top, the mean ages are 100 ± 10 ka for stratigraphic unit (SU) Noël and 107 ± 11 ka for SU Mark (uncharacterized Lower MSA), 100 ± 10 ka for SU Lynn-Leo (Pre-SB type Lynn), 109 ± 10 ka for SUs Kim-Larry (SB), 105 ± 10 ka for SUs Kerry-Kate and 109 ± 10 ka for SU Jess (Early HP), 89 ± 8 ka for SU Jude (MSA type Jack), 77 ± 8 ka for SU John, 85 ± 9 ka for SU Fox, 83 ± 8 ka for SU Fred and 65 ± 8 ka for SU OB5 (Intermediate HP), 52 ± 5 ka for SUs OB2-4 (Late HP). This chronology, together with the technological analyses, greatly modifies the current chrono-cultural model regarding the SB and the HP and has important archaeological implications. Indeed, SB and HP no longer appear as short-lived techno-complexes with synchronous appearances for each and restricted to Oxygen Isotopic Stage (OIS) 4 across South Africa, as suggested by Jacobs et al. (2008, 2012). Rather, the sequence of Diepkloof supports a long chronology model with an early appearance of both SB and HP in the first half of OIS 5 and a long duration of the HP into OIS 3. These new dates imply that different technological traditions coexisted during OIS 5 and 4 in southern Africa and that SB and HP can no longer be considered as horizon markers.

HIV testing and burden of HIV infection in black cancer patients in Johannesburg, South Africa: a cross-sectional study.

BACKGROUND HIV infection is a known risk factor for cancer but little is known about HIV testing patterns and the burden of HIV infection in cancer patients. We did a cross-sectional analysis to identify predictors of prior HIV testing and to quantify the burden of HIV in black cancer patients in Johannesburg, South Africa. METHODS The Johannesburg Cancer Case-control Study (JCCCS) recruits newly-diagnosed black cancer patients attending public referral hospitals for oncology and radiation therapy in Johannesburg . All adult cancer patients enrolled into the JCCCS from November 2004 to December 2009 and interviewed on previous HIV testing were included in the analysis. Patients were independently tested for HIV-1 using a single ELISA test . The prevalence of prior HIV testing, of HIV infection and of undiagnosed HIV infection was calculated. Multivariate logistic regression models were fitted to identify factors associated with prior HIV testing. RESULTS A total of 5436 cancer patients were tested for HIV of whom 1833[33.7% (95% CI=32.5-35.0)] were HIV-positive. Three-quarters of patients (4092 patients) had ever been tested for HIV. The total prevalence of undiagnosed HIV infection was 11.5% (10.7-12.4) with 34% (32.0-36.3) of the 1833 patients who tested HIV-positive unaware of their infection. Men >49 years [OR 0.49(0.39-0.63)] and those residing in rural areas [OR 0.61(0.39-0.97)] were less likely to have been previously tested for HIV. Men with at least a secondary education [OR 1.79(1.11-2.90)] and those interviewed in recent years [OR 4.13(2.62 - 6.52)] were likely to have prior testing. Women >49 years [OR 0.33(0.27-0.41)] were less likely to have been previously tested for HIV. In women, having children <5 years [OR 2.59(2.04-3.29)], hormonal contraceptive use [OR 1.33(1.09-1.62)], having at least a secondary education [OR:2.08(1.45-2.97)] and recent year of interview [OR 6.04(4.45-8.2)] were independently associated with previous HIV testing. CONCLUSIONS In a study of newly diagnosed black cancer patients in Johannesburg, over a third of HIV-positive patients were unaware of their HIV status. In South Africa black cancer patients should be targeted for opt-out HIV testing.