2014
DOI: 10.9778/cmajo.20140017
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The effects of HIV-1 subtype and ethnicity on the rate of CD4 cell count decline in patients naive to antiretroviral therapy: a Canadian-European collaborative retrospective cohort study

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Cited by 17 publications
(10 citation statements)
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“…The majority of studies examining association of HIV-1 subtype with patient outcomes have largely focused on subtype B, the commonest variant in the USA and Western Europe and one that represents less than 15% of HIV-1 infections worldwide. Few studies have PLOS ONE evaluated the effect of HIV subtypes for periods longer than 48 weeks and these were on ARV naïve HIV infected subjects [13,[24][25][26]. In this study, we examined the subtype distribution and the effect of these subtypes on disease outcome over a 5-year period in a cohort of patients receiving ART in a large teaching hospital location in southwest Nigeria.…”
Section: Resultsmentioning
confidence: 99%
“…The majority of studies examining association of HIV-1 subtype with patient outcomes have largely focused on subtype B, the commonest variant in the USA and Western Europe and one that represents less than 15% of HIV-1 infections worldwide. Few studies have PLOS ONE evaluated the effect of HIV subtypes for periods longer than 48 weeks and these were on ARV naïve HIV infected subjects [13,[24][25][26]. In this study, we examined the subtype distribution and the effect of these subtypes on disease outcome over a 5-year period in a cohort of patients receiving ART in a large teaching hospital location in southwest Nigeria.…”
Section: Resultsmentioning
confidence: 99%
“…HIV subtypes may also have differential characteristics, such as replication fitness and biology of transmission, which could impact disease progression and response to therapy [21,22,[24][25][26]. However, to date this has not been definitively proven in clinical cohorts due to confounders such as sex, ethnicity and heterogeneity in time intervals since seroconversion [46][47][48]. Gender-matched studies will be necessary to determine whether sex or viral subtype is the major driver of our results as our non-African cohort were all male.…”
Section: Discussionmentioning
confidence: 98%
“…+ T-cell slope trajectories (referred to as 'the slope') for people with known last negative and first positive HIV tests were built on the square root of CD4 + T-cell counts modelled through a maximum likelihood multilevel linear approach[19][20][21][22][23]. Since people in this cohort might present at the time of seroconversion, an 'anchor' date 3 months after HIV diagnosis was set as the CD4 + T-cell count (where the person remained treatment-naive) to remove the bias of capturing a seroconversion-induced low CD4 + T-cell count (Supplement).…”
mentioning
confidence: 99%