Predictive Value of HIV‐1 Genotypic Resistance Test Interpretation Algorithms
| Autor: | Francçoise Brun-Vezinet, Robert W. Shafer, W. Jeffrey Fessel, Jonathan Taylor, Michael A. Horberg, Anne-Mieke Vandamme, Natalia Marlowe, Vincent Calvez, Charles M. Rowland, Soo-Yon Rhee, Leo B. Hurley, Kristel Van Laethem, Tommy F. Liu, Richard A. Rode |
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| Rok vydání: | 2009 |
| Předmět: |
Adult
Male Genotype Anti-HIV Agents Molecular Sequence Data Salvage therapy Drug resistance Biology Article Young Adult Predictive Value of Tests Drug Resistance Viral Humans Immunology and Allergy Young adult Aged Retrospective cohort study Middle Aged biology.organism_classification Regimen Infectious Diseases Data Interpretation Statistical Predictive value of tests Lentivirus HIV-1 Female Algorithm Algorithms |
| Zdroj: | The Journal of Infectious Diseases. 200:453-463 |
| ISSN: | 1537-6613 0022-1899 |
| DOI: | 10.1086/600073 |
| Popis: | Retrospective studies have shown that the presence of human immunodeficienc virus type 1 (HIV-1) drug resistance before the start of a new antiretroviral (ARV) regimen is an independent predictor of the virologic response (VR) to that regimen [1]. Prospective controlled studies have shown that patients whose physicians have access to drug-resistance data respond better to therapy than those whose physicians do not [2–5]. The accumulation of such retrospective and prospective data has led to the routine use of genotypic resistance testing in the management of HIV-1–infected patients [6–8]. However, interpreting the results of HIV-1 genotypic drug-resistance tests is one of the most diffi ult challenges facing clinicians who care for HIV-1–infected patients. First, there are many mutations associated with drug resistance [9]. Second, there are synergistic and antagonistic interactions among these drug-resistance mutations [10]. Third, some mutations may not reduce susceptibility by themselves but may compensate for the effect of other mutations [11] or may be sentinel indicators of emerging drug resistance. As a result, several different algorithms have been developed for interpreting HIV-1 genotypic drug-resistance test results. Several studies have compared the predictive ability of different genotypic drug-resistance algorithms using retrospective clinical data sets [12–17]. In the present study, we evaluate the predictive value of 4 genotypic drug-resistance test interpretation algorithms in a patient population undergoing a wide range of salvage ARV therapy. |
| Databáze: | OpenAIRE |
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