Knowledge of Genotypic Resistance Mutations Among Providers of Care to Patients with Human Immunodeficiency Virus

Salama, Carlos; Policar, Maurice; Cervera, Christina

doi:10.1086/344909

Cited by 9 publications

(7 citation statements)

References 9 publications

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“…HIV practitioners' knowledge of HIV resistance patterns is incomplete [99]. One study that compared the utility of genotypic resistance testing, expert advice, or both with standard of care in selecting regimens for patients whose infections fail to respond to antiretroviral therapy showed that genotypic testing and expert advice each resulted in significantly better virological responses [95].…”

Section: Prospective Studies Of Drug Resistance Testingmentioning

confidence: 99%

Antiretroviral Drug Resistance Testing in Adults Infected with Human Immunodeficiency Virus Type 1: 2003 Recommendations of an International AIDS Society–USA Panel

et al. 2003

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New information about the benefits and limitations of testing for resistance to human immunodeficiency virus (HIV) type 1 (HIV-1) drugs has emerged. The International AIDS Society-USA convened a panel of physicians and scientists with expertise in antiretroviral drug management, HIV-1 drug resistance, and patient care to provide updated recommendations for HIV-1 resistance testing. Published data and presentations at scientific conferences, as well as strength of the evidence, were considered. Properly used resistance testing can improve virological outcome among HIV-infected individuals. Resistance testing is recommended in cases of acute or recent HIV infection, for certain patients who have been infected as long as 2 years or more prior to initiating therapy, in cases of antiretroviral failure, and during pregnancy. Limitations of resistance testing remain, and more study is needed to refine optimal use and interpretation.

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Section: Prospective Studies Of Drug Resistance Testingmentioning

confidence: 99%

Antiretroviral Drug Resistance Testing in Adults Infected with Human Immunodeficiency Virus Type 1: 2003 Recommendations of an International AIDS Society–USA Panel

et al. 2003

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“…For example, results from a questionnaire distributed at an International AIDS Society meeting in New York City in 2001 indicated that only 17% of the health care providers queried were able to correctly identify mutations associated with resistance to six drug groups. 14 Genotypic data can be obtained quickly by sequencing viral samples, but understanding the clinical significance of the observed drug-resistance mutations can be more difficult. Studies have demonstrated the advantages of having genotyping results interpreted by experts in understanding the impact of these mutations on combination regimens in order to obtain clinical benefit beyond standard of care.…”

Section: Discussionmentioning

confidence: 99%

Comparison of HIV Type 1 Protease Inhibitor Susceptibility Results in Viral Samples Analyzed by Phenotypic Drug Resistance Assays and by Six Resistance Algorithms: An Analysis of a Subpopulation of the CHORUS Cohort

Ross

Boulmé

Fusco

et al. 2005

AIDS Research and Human Retroviruses

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Drug resistance testing is increasingly used to guide treatment decisions in patients infected with HIV-1. A number of rules-based algorithms have been designed to predict drug resistance profiles based on the HIV-1 genotypic data. Drug-resistance mutations in 206 viral samples from protease inhibitor (PI)-experienced subjects with HIV-1 infection were assessed, and the level of susceptibility of the samples predicted using seven unique algorithms. kappa scores were used to compare agreement of results obtained using each of the predictive algorithms with the phenotypic assay results. Good overall agreement between the different algorithms and the phenotypic results was observed. Good or excellent agreement was observed between the results obtained by the predictive algorithms and the phenotypic assay results for ritonavir, indinavir, saquinavir, and nelfinavir. For amprenavir and lopinavir, there were marked differences between the different algorithms, with poor agreement (kappa < 0.40) obtained with four of the seven algorithms for amprenavir. For lopinavir, poor agreement was obtained with three of seven algorithms using the 2.5-fold biological cut-off and four of seven with the clinical cut-off of 10. Atazanavir susceptibility was evaluated for concordance among six algorithms, with a range of 23-50% of the samples maintaining susceptibility. Although this cohort of patients included many who were highly antiretroviral experienced, predictive algorithms demonstrated good agreement with phenotype for several Pls. For those where discordance among algorithms existed, further improvement will likely occur as drug resistance pathways for the more recently approved PIs are elucidated.

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“…Unfortunately, other aspects such as standardization of the techniques to avoid intra-laboratory (Shafer et al, 2000;Galli et al, 2003) and inter-laboratory variability (Demeter et al, 1998;Schuurman et al, 1999Schuurman et al, , 2002 as well as interpretation of the results, not only by the Microbiology laboratory staff (Korn et al, 2003) but also by the clinicians (Salama et al, 2003) and a consensus in such interpretations are still pending.…”

Section: Discussionmentioning

confidence: 99%

RNA extraction prior to HIV-1 resistance detection using Line Probe Assay (LiPA): comparison of three methods

Labayru

Eirós

Hernández³

et al. 2005

Journal of Clinical Virology

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Knowledge of Genotypic Resistance Mutations Among Providers of Care to Patients with Human Immunodeficiency Virus

Cited by 9 publications

References 9 publications

Antiretroviral Drug Resistance Testing in Adults Infected with Human Immunodeficiency Virus Type 1: 2003 Recommendations of an International AIDS Society–USA Panel

Antiretroviral Drug Resistance Testing in Adults Infected with Human Immunodeficiency Virus Type 1: 2003 Recommendations of an International AIDS Society–USA Panel

Comparison of HIV Type 1 Protease Inhibitor Susceptibility Results in Viral Samples Analyzed by Phenotypic Drug Resistance Assays and by Six Resistance Algorithms: An Analysis of a Subpopulation of the CHORUS Cohort

RNA extraction prior to HIV-1 resistance detection using Line Probe Assay (LiPA): comparison of three methods

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