Literature DB >> 16284524

Prevalence of transmitted HIV-1 drug resistance and the role of resistance algorithms: data from seroconverters in the CASCADE collaboration from 1987 to 2003.

Bernard Masquelier1, Krishnan Bhaskaran, Deenan Pillay, Robert Gifford, Eric Balestre, Louise Bruun Jørgensen, Court Pedersen, Lia van der Hoek, Maria Prins, Claudia Balotta, Benedetta Longo, Claudia Kücherer, Gabriele Poggensee, Marta Ortiz, Carmen de Mendoza, John Gill, Hervé Fleury, Kholoud Porter.   

Abstract

OBJECTIVES: 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.

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Year:  2005        PMID: 16284524     DOI: 10.1097/01.qai.0000186361.42834.61

Source DB:  PubMed          Journal:  J Acquir Immune Defic Syndr        ISSN: 1525-4135            Impact factor:   3.731


  17 in total

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2.  Comparison of algorithms that interpret genotypic HIV-1 drug resistance to determine the prevalence of transmitted drug resistance.

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5.  Impact of Changes Over Time in the Stanford University Genotypic Resistance Interpretation Algorithm.

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Journal:  J Acquir Immune Defic Syndr       Date:  2018-09-01       Impact factor: 3.731

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8.  Persistence of transmitted drug resistance among subjects with primary human immunodeficiency virus infection.

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9.  Opportunities for sexual transmission of antiretroviral drug resistance among HIV-infected patients in care.

Authors:  Heidi M Soeters; Sonia Napravnik; Oksana M Zakharova; Joseph J Eron; Christopher B Hurt
Journal:  AIDS       Date:  2013-11-28       Impact factor: 4.177

10.  Prevalence of HIV Drug Resistance Mutations in HIV Type 1 Isolates in Antiretroviral Therapy Naïve Population from Northern India.

Authors:  S Sinha; H Ahmad; R C Shekhar; N Kumar; L Dar; J C Samantaray; S K Sharma; A Bhargava; R M Pandey; R L Mitsuyasu; J L Fahey
Journal:  AIDS Res Treat       Date:  2012-03-15
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