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Effects of early versus delayed initiation of antiretroviral treatment on clinical outcomes of HIV-1 infection: results from the phase 3 HPTN 052 randomised controlled trial

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TLDR
The clinical benefits recorded, combined with the striking reduction in HIV-1 transmission risk previously reported, provides strong support for earlier initiation of antiretroviral treatment.
Abstract
Summary Background Use of antiretroviral treatment for HIV-1 infection has decreased AIDS-related morbidity and mortality and prevents sexual transmission of HIV-1. H owever, the best time to initiate antiretroviral treatment to reduce progression of HIV-1 infection or non-AIDS clinical events is unknown. We reported previously that early antiretroviral treatment reduced HIV-1 transmission by 96%. We aimed to compare the eff ects of early and delayed initiation of antiretroviral treatment on clinical outcomes. Methods The HPTN 052 trial is a randomised controlled trial done at 13 sites in nine countries. We enrolled HIV-1-serodiscordant couples to the study and randomly allocated them to either early or delayed antiretroviral treatment by use of permuted block randomisation, stratifi ed by site. Random assignment was unblinded. The HIV-1-infected member of every couple initiated antiretroviral treatment either on entry into the study (early treatment group) or after a decline in CD4 count or with onset of an AIDS-related illness (delayed treatment group). Primary events were AIDS clinical events (WHO stage 4 HIV-1 disease, tuberculosis, and severe bacterial infections) and the following serious medical conditions unrelated to AIDS: serious cardiovascular or vascular disease, serious liver disease, end-stage renal disease, new-onset diabetes mellitus, and non-AIDS malignant disease. Analysis was by intention-to-treat. This trial is registered with ClinicalTrials.gov, number NCT00074581. Findings 1763 people with HIV-1 infection and a serodiscordant partner were enrolled in the study; 886 were assigned early antiretroviral treatment and 877 to the delayed treatment group (two individuals were excluded from this group af ter randomisation). Median CD4 counts at randomisation were 442 (IQR 373–522) cells per μL in patients assigned to the early treatment group and 428 (357–522) cells per μL in those allocated delayed antiretroviral treatment. In the delayed group, antiretroviral treatment was initiated at a median CD4 count of 230 (IQR 197–249) cells per μL. Primary clinical events were reported in 57 individuals assigned to early treatment initiation versus 77 people allocated to delayed antiretroviral treatment (hazard ratio 0·73, 95% CI 0·52–1·03; p=0·074). New-onset AIDS events were recorded in 40 participants assigned to early antiretroviral treatment versus 61 allocated delayed initiation (0·64, 0·43–0·96; p=0·031), tuberculosis developed in 17 versus 34 patients, respectively (0·49, 0·28–0·89, p=0·018), and primary nonAIDS events were rare (12 in the early group vs nine with delayed treatment). In total, 498 primary and secondary outcomes occurred in the early treatment group (incidence 24·9 per 100 person-years, 95% CI 22·5–27·5) versus 585 in the delayed treatment group (29·2 per 100 person-years, 26·5–32·1; p=0·025). 26 people died, 11 who were allocated to early antiretroviral treatment and 15 who were assigned to the delayed treatment group.

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Antiretroviral therapy: when to start.

TL;DR: The scientific evidence and professional guidelines regarding the timing of antiretroviral therapy initiation are reviewed, with discussion of the increasingly persuasive evidence in favor of starting treatment early in the course of human immunodeficiency virus disease.
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References
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Journal ArticleDOI

Prevention of HIV-1 infection with early antiretroviral therapy

TL;DR: The exciting evidence generated by this paper – that antiretroviral treatment of HIV-1 infection definitively reduces the risk of onward transmission of the virus by 96% – was rightly dubbed Science magazine's ‘Breakthrough of the Year’ in 2011.
Journal ArticleDOI

Overadjustment bias and unnecessary adjustment in epidemiologic studies.

TL;DR: This work uses causal diagrams and an empirical example (the effect of maternal smoking on neonatal mortality) to illustrate and clarify the definition of overadjustment bias, and to distinguish over adjustment bias from unnecessary adjustment.
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