Prevalence of transmitted HIV-1 drug resistance and the role of resistance algorithms: data from seroconverters in the CASCADE collaboration from 1987 to 2003.
OBJECTIVE
To examine factors influencing the rate of transmitted drug resistance (TDR) among seroconverters, with particular emphasis on 3 widely used genotypic drug resistance algorithms.


METHODS
The study used data from CASCADE (Concerted Action on Seroconversion to AIDS and Death in Europe), a collaboration of seroconverter cohorts in Europe and Canada. Genotypic resistance data were derived within 18 months of the last seronegative test or date of laboratory evidence of acute infection and before the initiation of antiretroviral therapy. The Stanford algorithm was used to analyze each individual's nucleotide sequence. A multivariate logistic model was used to assess independent relationships between the presence of TDR and exposure category, sex, age at seroconversion, and year of seroconversion. The paper also describes 3 alternative definitions of resistance: the Stanford algorithm, the key resistance mutations defined by the International AIDS Society, and the Agence Nationale de Recherches sur le Sida (ANRS) algorithm.


RESULTS
Forty-five of 438 patients (10.3%) seroconverting between 1987 and 2003 were infected with a drug-resistant HIV-1 variant. Forty patients (9.1%) showed resistance mutations to only 1 class of antiretroviral drugs, 2 (0.5%) to 2 classes, and 3 (0.7%) to 3 classes of antiretroviral therapy. It was suggested that individuals seroconverting later in calendar time were more likely to have TDR (relative risk 3.89 and 95% CI: 0.84 to 18.02, and relative risk 4.69 and 95% CI: 1.03 to 21.31, for 1996-1999 and 2000-2003, respectively, compared with pre-1996; P trend = 0.08). This trend was apparent regardless of the definition of TDR used. The total estimated proportion of individuals with TDR varied between 10.3% and 15.5% according to which definition was used.


CONCLUSIONS
Evidence was found for the rise of TDR over time. A specific definition of what constitutes TDR rather than a simple list of mutations is needed.
Masquelier
Bernard
B
Département de Virologie et Immunologie Biologique, CHU Bordeaux, France. bernard.masquelier@chu-bordeaux.fr
Bhaskaran
Krishnan
K
Pillay
Deenan
D
Gifford
Robert
R
Balestre
Eric
E
Jørgensen
Louise Bruun
LB
Pedersen
Court
C
van der Hoek
Lia
L
Prins
Maria
M
Balotta
Claudia
C
Longo
Benedetta
B
Kücherer
Claudia
C
Poggensee
Gabriele
G
Ortiz
Marta
M
de Mendoza
Carmen
C
Gill
John
J
Fleury
Hervé
H
Porter
Kholoud
K
D000293:Adolescent; D000328:Adult; D000368:Aged; D000465:Algorithms; D019380:Anti-HIV Agents / Q000494:pharmacology; D002170:Canada / Q000453:epidemiology; D015331:Cohort Studies; D024882:Drug Resistance, Viral / Q000235:genetics*; D005060:Europe / Q000453:epidemiology; D005260:Female; D005838:Genotype; D006679:HIV Seropositivity / Q000453:epidemiology* / Q000635:transmission* / Q000821:virology; D015497:HIV-1 / Q000145:classification / Q000187:drug effects* / Q000235:genetics; D006801:Humans; D007391:International Cooperation; D008297:Male; D008875:Middle Aged; D009154:Mutation; D010802:Phylogeny; D018894:Reverse Transcriptase Inhibitors / Q000494:pharmacology
D019380:Anti-HIV Agents; D018894:Reverse Transcriptase Inhibitors