A direct comparison of drug susceptibility to HIV type 1 from antiretroviral experienced subjects as assessed by the antivirogram and phenosense assays and by seven resistance algorithms
HIV-1 drug resistance methodologies are being increasingly utilized to guide treatment decisions; however, information comparing the various assays is limited. Duplicate plasma samples from 70 ART-experienced subjects were analyzed by both the Antivirogram and PhenoSense phenotypic assays and the re...
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Veröffentlicht in: | AIDS research and human retroviruses 2005-11, Vol.21 (11), p.933-939 |
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description | HIV-1 drug resistance methodologies are being increasingly utilized to guide treatment decisions; however, information comparing the various assays is limited. Duplicate plasma samples from 70 ART-experienced subjects were analyzed by both the Antivirogram and PhenoSense phenotypic assays and the results compared. HIV genotypes were also obtained and analyzed using seven different resistance algorithms. These results were also compared with the phenotypic assay results. Concordances between the phenotypic tests and between each algorithm, and between the two phenotypic assays were calculated and kappa coefficients (KC) determined. Overall agreement between the two phenotypic assays was good (86.9% concordance; KC 0.621). The highest concordance by drug class was seen for protease inhibitors (93.4%; KC 0.679) and the lowest (79.8%; KC 0.549) for nucleoside reverse transcriptase inhibitors. Concordance between the two phenotypic assays, when evaluating individual drugs, was good for all drugs tested except for abacavir, zalcitabine, and indinavir. Agreement between the seven algorithms and each phenotypic assay was variable, though most had good or excellent agreement. The highest overall level of agreement for an individual drug was observed when comparing lamivudine susceptibility to either assay. Concordance for abacavir, didanosine, zalcitabine, and saquinavir was generally problematic when comparing one or more phenotypic assays to the drug resistance predictive algorithms. In conclusion, results comparing these two phenotypic tests were mostly similar, but comparisons of the predictive resistance algorithms for specific drugs, as well as to specific phenotypic assays, were more inconsistent. |
doi_str_mv | 10.1089/aid.2005.21.933 |
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Duplicate plasma samples from 70 ART-experienced subjects were analyzed by both the Antivirogram and PhenoSense phenotypic assays and the results compared. HIV genotypes were also obtained and analyzed using seven different resistance algorithms. These results were also compared with the phenotypic assay results. Concordances between the phenotypic tests and between each algorithm, and between the two phenotypic assays were calculated and kappa coefficients (KC) determined. Overall agreement between the two phenotypic assays was good (86.9% concordance; KC 0.621). The highest concordance by drug class was seen for protease inhibitors (93.4%; KC 0.679) and the lowest (79.8%; KC 0.549) for nucleoside reverse transcriptase inhibitors. Concordance between the two phenotypic assays, when evaluating individual drugs, was good for all drugs tested except for abacavir, zalcitabine, and indinavir. Agreement between the seven algorithms and each phenotypic assay was variable, though most had good or excellent agreement. The highest overall level of agreement for an individual drug was observed when comparing lamivudine susceptibility to either assay. Concordance for abacavir, didanosine, zalcitabine, and saquinavir was generally problematic when comparing one or more phenotypic assays to the drug resistance predictive algorithms. In conclusion, results comparing these two phenotypic tests were mostly similar, but comparisons of the predictive resistance algorithms for specific drugs, as well as to specific phenotypic assays, were more inconsistent.</description><identifier>ISSN: 0889-2229</identifier><identifier>EISSN: 1931-8405</identifier><identifier>DOI: 10.1089/aid.2005.21.933</identifier><identifier>PMID: 16386109</identifier><identifier>CODEN: ARHRE7</identifier><language>eng</language><publisher>Larchmont, NY: Liebert</publisher><subject>Adult ; AIDS/HIV ; Algorithms ; Biological and medical sciences ; Drug Resistance, Viral ; Female ; Fundamental and applied biological sciences. Psychology ; Genotype ; HIV Infections - drug therapy ; HIV Infections - virology ; HIV-1 - drug effects ; HIV-1 - genetics ; Human immunodeficiency virus 1 ; Human viral diseases ; Humans ; Infectious diseases ; Male ; Medical sciences ; Microbial Sensitivity Tests - methods ; Microbiology ; Miscellaneous ; Phenotype ; Predictive Value of Tests ; Sequence Analysis, DNA ; Viral diseases ; Viral Proteins - genetics ; Virology</subject><ispartof>AIDS research and human retroviruses, 2005-11, Vol.21 (11), p.933-939</ispartof><rights>2006 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c356t-c2ff83f6c3d7c197221a9d63676b4da9e2229fc6eba0d99894a26dcbccf51fff3</citedby><cites>FETCH-LOGICAL-c356t-c2ff83f6c3d7c197221a9d63676b4da9e2229fc6eba0d99894a26dcbccf51fff3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,782,786,3046,27933,27934</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=17353010$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/16386109$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>ROSS, Lisa</creatorcontrib><creatorcontrib>BOULME, Ronan</creatorcontrib><creatorcontrib>FISHER, Robin</creatorcontrib><creatorcontrib>HERNANDEZ, Jaime</creatorcontrib><creatorcontrib>FLORANCE, Allison</creatorcontrib><creatorcontrib>SCHMIT, Jean-Claude</creatorcontrib><creatorcontrib>WILLIAMS, Vanessa</creatorcontrib><title>A direct comparison of drug susceptibility to HIV type 1 from antiretroviral experienced subjects as assessed by the antivirogram and phenosense assays and by seven resistance algorithms</title><title>AIDS research and human retroviruses</title><addtitle>AIDS Res Hum Retroviruses</addtitle><description>HIV-1 drug resistance methodologies are being increasingly utilized to guide treatment decisions; however, information comparing the various assays is limited. Duplicate plasma samples from 70 ART-experienced subjects were analyzed by both the Antivirogram and PhenoSense phenotypic assays and the results compared. HIV genotypes were also obtained and analyzed using seven different resistance algorithms. These results were also compared with the phenotypic assay results. Concordances between the phenotypic tests and between each algorithm, and between the two phenotypic assays were calculated and kappa coefficients (KC) determined. Overall agreement between the two phenotypic assays was good (86.9% concordance; KC 0.621). The highest concordance by drug class was seen for protease inhibitors (93.4%; KC 0.679) and the lowest (79.8%; KC 0.549) for nucleoside reverse transcriptase inhibitors. Concordance between the two phenotypic assays, when evaluating individual drugs, was good for all drugs tested except for abacavir, zalcitabine, and indinavir. Agreement between the seven algorithms and each phenotypic assay was variable, though most had good or excellent agreement. The highest overall level of agreement for an individual drug was observed when comparing lamivudine susceptibility to either assay. Concordance for abacavir, didanosine, zalcitabine, and saquinavir was generally problematic when comparing one or more phenotypic assays to the drug resistance predictive algorithms. In conclusion, results comparing these two phenotypic tests were mostly similar, but comparisons of the predictive resistance algorithms for specific drugs, as well as to specific phenotypic assays, were more inconsistent.</description><subject>Adult</subject><subject>AIDS/HIV</subject><subject>Algorithms</subject><subject>Biological and medical sciences</subject><subject>Drug Resistance, Viral</subject><subject>Female</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Genotype</subject><subject>HIV Infections - drug therapy</subject><subject>HIV Infections - virology</subject><subject>HIV-1 - drug effects</subject><subject>HIV-1 - genetics</subject><subject>Human immunodeficiency virus 1</subject><subject>Human viral diseases</subject><subject>Humans</subject><subject>Infectious diseases</subject><subject>Male</subject><subject>Medical sciences</subject><subject>Microbial Sensitivity Tests - methods</subject><subject>Microbiology</subject><subject>Miscellaneous</subject><subject>Phenotype</subject><subject>Predictive Value of Tests</subject><subject>Sequence Analysis, DNA</subject><subject>Viral diseases</subject><subject>Viral Proteins - genetics</subject><subject>Virology</subject><issn>0889-2229</issn><issn>1931-8405</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkU1r3DAURUVpaaZp190VbZqdJ_oYy9YyhDYJBLppuzWy9DSjYFuunhwyf62_rnIykGXhgUCcexb3EvKZsy1nrb40wW0FY_VW8K2W8g3ZcC151e5Y_ZZsWNvqSgihz8gHxAfGmBaifk_OuJKt4kxvyN8r6kICm6mN42xSwDjR6KlLy57ighbmHPowhHykOdLbu980H2egnPoUR2qmXNI5xceQzEDhaYYUYLLgSrh_KF6kZj2Eco72xXKA51hJxH0yq8PR-QBTRJgQVtYc8fm30AiPMNEEGDCb4qVm2McU8mHEj-SdNwPCp9N7Tn59__bz-ra6_3Fzd311X1lZq1xZ4X0rvbLSNZbrRghutFNSNarfOaNhLchbBb1hTutW74xQzvbW-pp77-U5uXjxzin-WQBzN4bSyzCYCeKCndKsZg2T_wV5sxNSKV3AyxfQpoiYwHdzCqNJx46zbt21K7t2666d4F3ZtSS-nNRLP4J75U9DFuDrCTBozeBTKSvgK9fIWjLO5D8X9bEv</recordid><startdate>20051101</startdate><enddate>20051101</enddate><creator>ROSS, Lisa</creator><creator>BOULME, Ronan</creator><creator>FISHER, Robin</creator><creator>HERNANDEZ, Jaime</creator><creator>FLORANCE, Allison</creator><creator>SCHMIT, Jean-Claude</creator><creator>WILLIAMS, Vanessa</creator><general>Liebert</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7U9</scope><scope>H94</scope><scope>7X8</scope></search><sort><creationdate>20051101</creationdate><title>A direct comparison of drug susceptibility to HIV type 1 from antiretroviral experienced subjects as assessed by the antivirogram and phenosense assays and by seven resistance algorithms</title><author>ROSS, Lisa ; BOULME, Ronan ; FISHER, Robin ; HERNANDEZ, Jaime ; FLORANCE, Allison ; SCHMIT, Jean-Claude ; WILLIAMS, Vanessa</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c356t-c2ff83f6c3d7c197221a9d63676b4da9e2229fc6eba0d99894a26dcbccf51fff3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Adult</topic><topic>AIDS/HIV</topic><topic>Algorithms</topic><topic>Biological and medical sciences</topic><topic>Drug Resistance, Viral</topic><topic>Female</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Genotype</topic><topic>HIV Infections - drug therapy</topic><topic>HIV Infections - virology</topic><topic>HIV-1 - drug effects</topic><topic>HIV-1 - genetics</topic><topic>Human immunodeficiency virus 1</topic><topic>Human viral diseases</topic><topic>Humans</topic><topic>Infectious diseases</topic><topic>Male</topic><topic>Medical sciences</topic><topic>Microbial Sensitivity Tests - methods</topic><topic>Microbiology</topic><topic>Miscellaneous</topic><topic>Phenotype</topic><topic>Predictive Value of Tests</topic><topic>Sequence Analysis, DNA</topic><topic>Viral diseases</topic><topic>Viral Proteins - genetics</topic><topic>Virology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>ROSS, Lisa</creatorcontrib><creatorcontrib>BOULME, Ronan</creatorcontrib><creatorcontrib>FISHER, Robin</creatorcontrib><creatorcontrib>HERNANDEZ, Jaime</creatorcontrib><creatorcontrib>FLORANCE, Allison</creatorcontrib><creatorcontrib>SCHMIT, Jean-Claude</creatorcontrib><creatorcontrib>WILLIAMS, Vanessa</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Virology and AIDS Abstracts</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>AIDS research and human retroviruses</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>ROSS, Lisa</au><au>BOULME, Ronan</au><au>FISHER, Robin</au><au>HERNANDEZ, Jaime</au><au>FLORANCE, Allison</au><au>SCHMIT, Jean-Claude</au><au>WILLIAMS, Vanessa</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A direct comparison of drug susceptibility to HIV type 1 from antiretroviral experienced subjects as assessed by the antivirogram and phenosense assays and by seven resistance algorithms</atitle><jtitle>AIDS research and human retroviruses</jtitle><addtitle>AIDS Res Hum Retroviruses</addtitle><date>2005-11-01</date><risdate>2005</risdate><volume>21</volume><issue>11</issue><spage>933</spage><epage>939</epage><pages>933-939</pages><issn>0889-2229</issn><eissn>1931-8405</eissn><coden>ARHRE7</coden><abstract>HIV-1 drug resistance methodologies are being increasingly utilized to guide treatment decisions; however, information comparing the various assays is limited. Duplicate plasma samples from 70 ART-experienced subjects were analyzed by both the Antivirogram and PhenoSense phenotypic assays and the results compared. HIV genotypes were also obtained and analyzed using seven different resistance algorithms. These results were also compared with the phenotypic assay results. Concordances between the phenotypic tests and between each algorithm, and between the two phenotypic assays were calculated and kappa coefficients (KC) determined. Overall agreement between the two phenotypic assays was good (86.9% concordance; KC 0.621). The highest concordance by drug class was seen for protease inhibitors (93.4%; KC 0.679) and the lowest (79.8%; KC 0.549) for nucleoside reverse transcriptase inhibitors. Concordance between the two phenotypic assays, when evaluating individual drugs, was good for all drugs tested except for abacavir, zalcitabine, and indinavir. Agreement between the seven algorithms and each phenotypic assay was variable, though most had good or excellent agreement. The highest overall level of agreement for an individual drug was observed when comparing lamivudine susceptibility to either assay. Concordance for abacavir, didanosine, zalcitabine, and saquinavir was generally problematic when comparing one or more phenotypic assays to the drug resistance predictive algorithms. In conclusion, results comparing these two phenotypic tests were mostly similar, but comparisons of the predictive resistance algorithms for specific drugs, as well as to specific phenotypic assays, were more inconsistent.</abstract><cop>Larchmont, NY</cop><pub>Liebert</pub><pmid>16386109</pmid><doi>10.1089/aid.2005.21.933</doi><tpages>7</tpages></addata></record> |
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subjects | Adult AIDS/HIV Algorithms Biological and medical sciences Drug Resistance, Viral Female Fundamental and applied biological sciences. Psychology Genotype HIV Infections - drug therapy HIV Infections - virology HIV-1 - drug effects HIV-1 - genetics Human immunodeficiency virus 1 Human viral diseases Humans Infectious diseases Male Medical sciences Microbial Sensitivity Tests - methods Microbiology Miscellaneous Phenotype Predictive Value of Tests Sequence Analysis, DNA Viral diseases Viral Proteins - genetics Virology |
title | A direct comparison of drug susceptibility to HIV type 1 from antiretroviral experienced subjects as assessed by the antivirogram and phenosense assays and by seven resistance algorithms |
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