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A randomised trial comparing genotypic and virtual phenotypic interpretation of HIV drug resistance: the CREST study.

Hales G, Birch C, Crowe S, Workman C, Hoy JF, Law MG, Kelleher AD, Lincoln D, Emery S, CREST investigators

  • Journal PLoS clinical trials

  • Published 28 Jul 2006

  • Volume 1

  • ISSUE 3

  • Pagination e18

  • DOI 10.1371/journal.pctr.0010018


The aim of this study was to compare the efficacy of different HIV drug resistance test reports (genotype and virtual phenotype) in patients who were changing their antiretroviral therapy (ART).

Randomised, open-label trial with 48-week followup.

The study was conducted in a network of primary healthcare sites in Australia and New Zealand.

Patients failing current ART with plasma HIV RNA > 2000 copies/mL who wished to change their current ART were eligible. Subjects were required to be > 18 years of age, previously treated with ART, have no intercurrent illnesses requiring active therapy, and to have provided written informed consent.

Eligible subjects were randomly assigned to receive a genotype (group A) or genotype plus virtual phenotype (group B) prior to selection of their new antiretroviral regimen.

Patient groups were compared for patterns of ART selection and surrogate outcomes (plasma viral load and CD4 counts) on an intention-to-treat basis over a 48-week period.

Three hundred and twenty seven patients completing >or= one month of followup were included in these analyses. Resistance tests were the primary means by which ART regimens were selected (group A: 64%, group B: 62%; p = 0.32). At 48 weeks, there were no significant differences between the groups for mean change from baseline plasma HIV RNA (group A: 0.68 log copies/mL, group B: 0.58 log copies/mL; p = 0.23) and mean change from baseline CD4+ cell count (group A: 37 cells/mm(3), group B: 50 cells/mm(3); p = 0.28).

In the absence of clear demonstrated benefits arising from the use of the virtual phenotype interpretation, this study suggests resistance testing using genotyping linked to a reliable interpretive algorithm is adequate for the management of HIV infection.