Abstract Background Ethnic différences have the potential to confound associations between HIV-1 subtype and immunologie progression. We compared declines in CD4 cell counts during untreated ...infection for the most prevalent HIV-1 subtypes, focusing on distinguishing between the effects of viral subtype and ethnicity. Methods We combined data from 4 European and 6 Canadian cohorts, selecting adults in the stable chronic phase of untreated HIV infection. We estimated the change in square root CD4 cell count over time for subtypes and ethnicities using mixed models, adjusting for covariates selected for their potential effect on initial CD4 cell count or its decline. Results Data from 9772 patients were analyzed, contributing 79 175 measurements of CD4 cell count and 24 157 person-years of follow-up. Overall, there were no appreciable differences in CD4 cell count decline for viral subtypes A, CRF01_AE, CRF02_AG, C and G compared with viral subtype B; whereas the decline in CD4 cell count in patients of African ancestry was considerably slower than in patients of other ethnicity. When ethnic groups were studied separately, there was evidence for slower declines in CD4 cell count in viral subtypes C, and possibly A and G, compared with viral subtype B in patients of African ancestry but not among patients of other ethnicities, suggesting an interaction between subtype and ethnicity. Interpretation Ethnicity is a major determinant of CD4 cell count decline; viral subtype differences may have existed but were small compared with the effect of ethnicity and were most apparent in patients of African ancestry. In developing countries, slower CD4 cell count declines among individuals of African descent may translate to a longer asymptomatic phase and increase the opportunity for HIV transmission.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Summary Background Prognostic models have been developed for patients infected with HIV-1 who start combination antiretroviral therapy (ART) in high-income countries, but not for patients in ...sub-Saharan Africa. We developed two prognostic models to estimate the probability of death in patients starting ART in sub-Saharan Africa. Methods We analysed data for adult patients who started ART in four scale-up programmes in Côte d'Ivoire, South Africa, and Malawi from 2004 to 2007. Patients lost to follow-up in the first year were excluded. We used Weibull survival models to construct two prognostic models: one with CD4 cell count, clinical stage, bodyweight, age, and sex (CD4 count model); and one that replaced CD4 cell count with total lymphocyte count and severity of anaemia (total lymphocyte and haemoglobin model), because CD4 cell count is not routinely measured in many African ART programmes. Death from all causes in the first year of ART was the primary outcome. Findings 912 (8·2%) of 11 153 patients died in the first year of ART. 822 patients were lost to follow-up and not included in the main analysis; 10 331 patients were analysed. Mortality was strongly associated with high baseline CD4 cell count (≥200 cells per μL vs <25; adjusted hazard ratio 0·21, 95% CI 0·17–0·27), WHO clinical stage (stages III–IV vs I–II; 3·45, 2·43–4·90), bodyweight (≥60 kg vs <45 kg; 0·23, 0·18–0·30), and anaemia status (none vs severe: 0·27, 0·20–0·36). Other independent risk factors for mortality were low total lymphocyte count, advanced age, and male sex. Probability of death at 1 year ranged from 0·9% (95% CI 0·6–1·4) to 52·5% (43·8–61·7) with the CD4 model, and from 0·9% (0·5–1·4) to 59·6% (48·2–71·4) with the total lymphocyte and haemoglobin model. Both models accurately predict early mortality in patients starting ART in sub-Saharan Africa compared with observed data. Interpretation Prognostic models should be used to counsel patients, plan health services, and predict outcomes for patients with HIV-1 infection in sub-Saharan Africa. Funding US National Institute of Allergy And Infectious Diseases, Eunice Kennedy Shriver National Institute of Child Health and Human Development, and National Cancer Institute.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Clinical guidelines vary with respect to the optimal monitoring frequency of HIV-positive individuals. We compared dynamic monitoring strategies based on time-varying CD4 cell counts in virologically ...suppressed HIV-positive individuals.
In this observational study, we used data from prospective studies of HIV-positive individuals in Europe (France, Greece, the Netherlands, Spain, Switzerland, and the UK) and North and South America (Brazil, Canada, and the USA) in The HIV-CAUSAL Collaboration and The Centers for AIDS Research Network of Integrated Clinical Systems. We compared three monitoring strategies that differ in the threshold used to measure CD4 cell count and HIV RNA viral load every 3-6 months (when below the threshold) or every 9-12 months (when above the threshold). The strategies were defined by the threshold CD4 counts of 200 cells per μL, 350 cells per μL, and 500 cells per μL. Using inverse probability weighting to adjust for baseline and time-varying confounders, we estimated hazard ratios (HRs) of death and of AIDS-defining illness or death, risk ratios of virological failure, and mean differences in CD4 cell count.
47 635 individuals initiated an antiretroviral therapy regimen between Jan 1, 2000, and Jan 9, 2015, and met the eligibility criteria for inclusion in our study. During follow-up, CD4 cell count was measured on average every 4·0 months and viral load every 3·8 months. 464 individuals died (107 in threshold 200 strategy, 157 in threshold 350, and 200 in threshold 500) and 1091 had AIDS-defining illnesses or died (267 in threshold 200 strategy, 365 in threshold 350, and 459 in threshold 500). Compared with threshold 500, the mortality HR was 1·05 (95% CI 0·86-1·29) for threshold 200 and 1·02 (0·91·1·14) for threshold 350. Corresponding estimates for death or AIDS-defining illness were 1·08 (0·95-1·22) for threshold 200 and 1·03 (0·96-1·12) for threshold 350. Compared with threshold 500, the 24 month risk ratios of virological failure (viral load more than 200 copies per mL) were 2·01 (1·17-3·43) for threshold 200 and 1·24 (0·89-1·73) for threshold 350, and 24 month mean CD4 cell count differences were 0·4 (-25·5 to 26·3) cells per μL for threshold 200 and -3·5 (-16·0 to 8·9) cells per μL for threshold 350.
Decreasing monitoring to annually when CD4 count is higher than 200 cells per μL compared with higher than 500 cells per μL does not worsen the short-term clinical and immunological outcomes of virally suppressed HIV-positive individuals. However, more frequent virological monitoring might be necessary to reduce the risk of virological failure. Further follow-up studies are needed to establish the long-term safety of these strategies.
National Institutes of Health.
Recommendations have differed nationally and internationally with respect to the best time to start antiretroviral therapy (ART). We compared effectiveness of three strategies for initiation of ART ...in high-income countries for HIV-positive individuals who do not have AIDS: immediate initiation, initiation at a CD4 count less than 500 cells per μL, and initiation at a CD4 count less than 350 cells per μL.
We used data from the HIV-CAUSAL Collaboration of cohort studies in Europe and the USA. We included 55,826 individuals aged 18 years or older who were diagnosed with HIV-1 infection between January, 2000, and September, 2013, had not started ART, did not have AIDS, and had CD4 count and HIV-RNA viral load measurements within 6 months of HIV diagnosis. We estimated relative risks of death and of death or AIDS-defining illness, mean survival time, the proportion of individuals in need of ART, and the proportion of individuals with HIV-RNA viral load less than 50 copies per mL, as would have been recorded under each ART initiation strategy after 7 years of HIV diagnosis. We used the parametric g-formula to adjust for baseline and time-varying confounders.
Median CD4 count at diagnosis of HIV infection was 376 cells per μL (IQR 222-551). Compared with immediate initiation, the estimated relative risk of death was 1·02 (95% CI 1·01-1·02) when ART was started at a CD4 count less than 500 cells per μL, and 1·06 (1·04-1·08) with initiation at a CD4 count less than 350 cells per μL. Corresponding estimates for death or AIDS-defining illness were 1·06 (1·06-1·07) and 1·20 (1·17-1·23), respectively. Compared with immediate initiation, the mean survival time at 7 years with a strategy of initiation at a CD4 count less than 500 cells per μL was 2 days shorter (95% CI 1-2) and at a CD4 count less than 350 cells per μL was 5 days shorter (4-6). 7 years after diagnosis of HIV, 100%, 98·7% (95% CI 98·6-98·7), and 92·6% (92·2-92·9) of individuals would have been in need of ART with immediate initiation, initiation at a CD4 count less than 500 cells per μL, and initiation at a CD4 count less than 350 cells per μL, respectively. Corresponding proportions of individuals with HIV-RNA viral load less than 50 copies per mL at 7 years were 87·3% (87·3-88·6), 87·4% (87·4-88·6), and 83·8% (83·6-84·9).
The benefits of immediate initiation of ART, such as prolonged survival and AIDS-free survival and increased virological suppression, were small in this high-income setting with relatively low CD4 count at HIV diagnosis. The estimated beneficial effect on AIDS is less than in recently reported randomised trials. Increasing rates of HIV testing might be as important as a policy of early initiation of ART.
National Institutes of Health.
HIV-1 viral load testing is recommended to monitor antiretroviral therapy (ART) but is not universally available. The aim of our study was to assess monitoring of first-line ART and switching to ...second-line ART in sub-Saharan Africa.
We did a collaborative analysis of cohort studies from 16 countries in east Africa, southern Africa, and west Africa that participate in the international epidemiological database to evaluate AIDS (IeDEA). We included adults infected with HIV-1 who started combination ART between January, 2004, and January, 2013. We defined switching of ART as a change from a non-nucleoside reverse-transcriptase inhibitor (NNRTI)-based regimen to one including a protease inhibitor, with adjustment of one or more nucleoside reverse-transcriptase inhibitors (NRTIs). Virological and immunological failures were defined according to WHO criteria. We calculated cumulative probabilities of switching and hazard ratios with 95% CIs comparing routine viral load monitoring, targeted viral load monitoring, CD4 monitoring, and clinical monitoring, adjusting for programme and individual characteristics.
Of 297,825 eligible patients, 10,352 (3%) switched to second-line ART during 782 ,412 person-years of follow-up. Compared with CD4 monitoring, hazard ratios for switching were 3·15 (95% CI 2·92-3·40) for routine viral load monitoring, 1·21 (1·13-1·30) for targeted viral load monitoring, and 0·49 (0·43-0·56) for clinical monitoring. Of 6450 patients with confirmed virological failure, 58·0% (95% CI 56·5-59·6) switched by 2 years, and of 15,892 patients with confirmed immunological failure, 19·3% (18·5-20·0) switched by 2 years. Of 10,352 patients who switched, evidence of treatment failure based on one CD4 count or viral load measurement ranged from 86 (32%) of 268 patients with clinical monitoring to 3754 (84%) of 4452 with targeted viral load monitoring. Median CD4 counts at switching were 215 cells per μL (IQR 117-335) with routine viral load monitoring, but were lower with other types of monitoring (range 114-133 cells per μL).
Overall, few patients switched to second-line ART and switching happened late in the absence of routine viral load monitoring. Switching was more common and happened earlier after initiation of ART with targeted or routine viral load testing.
National Institute of Allergy and Infectious Diseases, Swiss National Science Foundation.
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