Literature DB >> 18427201

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

Lin Liu1, Susanne May, Douglas D Richman, Frederick M Hecht, Martin Markowitz, Eric S Daar, Jean-Pierre Routy, Joseph B Margolick, Ann C Collier, Christopher H Woelk, Susan J Little, Davey M Smith.   

Abstract

OBJECTIVE: We compared eight genotypic interpretation methods to determine whether the method used would affect the rates of reported transmitted drug resistance.
DESIGN: Retrospective cohort study.
METHODS: For the International AIDS Society-USA method we classified a mutation as resistant if it was a 'major' resistance-associated mutation. For the Stanford algorithm, we classified a mutation as resistant if the score was at least 60 (Stanford 60), and alternatively, if the score was at least 30 (Stanford 30). For Agence Nationale de Recherches sur le SIDA and Rega, we interpreted resistance as either 'intermediate resistance' or 'resistance' (ANRS 1 and Rega 1), and 'resistance' only (ANRS 2 and Rega 2). We also used the calibrated population resistance algorithm. We then determined the rates of transmitted drug resistance within the Acute Infection Early Disease Research Program cohort (n = 1311) enrolled between March 1995 and August 2006 using each method; agreement was assessed using kappa coefficients.
RESULTS: Differences in estimated rates of transmitted drug resistance using International AIDS Society-USA, calibrated population resistance, Stanford 30, ANRS 1, Rega 1 and Rega 2 methods were mostly minor for resistance to protease and non-nucleoside reverse transcriptase inhibitors (1% range) and more pronounced for nucleoside reverse transcriptase inhibitors (5% range). For these methods kappa agreement was substantial or almost perfect across all drug classes. The Stanford 60 was most conservative.
CONCLUSIONS: The persistent high rates of transmitted drug resistance support the need for continued genotypic surveillance. The currently available interpretation algorithms can be used for this purpose.

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Year:  2008        PMID: 18427201      PMCID: PMC2716722          DOI: 10.1097/QAD.0b013e3282f5ff71

Source DB:  PubMed          Journal:  AIDS        ISSN: 0269-9370            Impact factor:   4.177


  19 in total

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Authors:  Robert W Shafer; Soo-Yon Rhee; Deenan Pillay; Veronica Miller; Paul Sandstrom; Jonathan M Schapiro; Daniel R Kuritzkes; Diane Bennett
Journal:  AIDS       Date:  2007-01-11       Impact factor: 4.177

2.  Discordances between interpretation algorithms for genotypic resistance to protease and reverse transcriptase inhibitors of human immunodeficiency virus are subtype dependent.

Authors:  Joke Snoeck; Rami Kantor; Robert W Shafer; Kristel Van Laethem; Koen Deforche; Ana Patricia Carvalho; Brian Wynhoven; Marcelo A Soares; Patricia Cane; John Clarke; Candice Pillay; Sunee Sirivichayakul; Koya Ariyoshi; Africa Holguin; Hagit Rudich; Rosangela Rodrigues; Maria Belen Bouzas; Françoise Brun-Vézinet; Caroline Reid; Pedro Cahn; Luis Fernando Brigido; Zehava Grossman; Vincent Soriano; Wataru Sugiura; Praphan Phanuphak; Lynn Morris; Jonathan Weber; Deenan Pillay; Amilcar Tanuri; Richard P Harrigan; Ricardo Camacho; Jonathan M Schapiro; David Katzenstein; Anne-Mieke Vandamme
Journal:  Antimicrob Agents Chemother       Date:  2006-02       Impact factor: 5.191

3.  Clinical utility of HIV standard genotyping among antiretroviral-naive individuals with unknown duration of infection.

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Journal:  Clin Infect Dis       Date:  2006-12-28       Impact factor: 9.079

4.  Update of the drug resistance mutations in HIV-1: Fall 2006.

Authors:  Victoria A Johnson; Francoise Brun-Vezinet; Bonaventura Clotet; Daniel R Kuritzkes; Deenan Pillay; Jonathan M Schapiro; Douglas D Richman
Journal:  Top HIV Med       Date:  2006 Aug-Sep

5.  Routine surveillance for the detection of acute and recent HIV infections and transmission of antiretroviral resistance.

Authors:  Hong-Ha M Truong; Robert M Grant; Willi McFarland; Timothy Kellogg; Charlotte Kent; Brian Louie; Ernest Wong; Jeffrey D Klausner
Journal:  AIDS       Date:  2006-11-14       Impact factor: 4.177

6.  Increased ability for selection of zidovudine resistance in a distinct class of wild-type HIV-1 from drug-naive persons.

Authors:  J G Garcia-Lerma; S Nidtha; K Blumoff; H Weinstock; W Heneine
Journal:  Proc Natl Acad Sci U S A       Date:  2001-11-06       Impact factor: 11.205

7.  Phenotypic or genotypic resistance testing for choosing antiretroviral therapy after treatment failure: a randomized trial.

Authors:  Jean-Luc Meynard; Muriel Vray; Laurence Morand-Joubert; Esther Race; Diane Descamps; Gilles Peytavin; Sophie Matheron; Claire Lamotte; Sonia Guiramand; Dominique Costagliola; Françoise Brun-Vézinet; François Clavel; Pierre-Marie Girard
Journal:  AIDS       Date:  2002-03-29       Impact factor: 4.177

8.  Antiretroviral-drug resistance among patients recently infected with HIV.

Authors:  Susan J Little; Sarah Holte; Jean-Pierre Routy; Eric S Daar; Marty Markowitz; Ann C Collier; Richard A Koup; John W Mellors; Elizabeth Connick; Brian Conway; Michael Kilby; Lei Wang; Jeannette M Whitcomb; Nicholas S Hellmann; Douglas D Richman
Journal:  N Engl J Med       Date:  2002-08-08       Impact factor: 91.245

9.  Time trends in primary HIV-1 drug resistance among recently infected persons.

Authors:  Robert M Grant; Frederick M Hecht; Maria Warmerdam; Lea Liu; Teri Liegler; Christos J Petropoulos; Nicholas S Hellmann; Margaret Chesney; Michael P Busch; James O Kahn
Journal:  JAMA       Date:  2002-07-10       Impact factor: 56.272

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

Authors:  Bernard Masquelier; 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
Journal:  J Acquir Immune Defic Syndr       Date:  2005-12-15       Impact factor: 3.731

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  8 in total

1.  Comparison of genotypic and virtual phenotypic drug resistance interpretations with laboratory-based phenotypes among CRF01_AE and subtype B HIV-infected individuals.

Authors:  Awachana Jiamsakul; Romanee Chaiwarith; Nicolas Durier; Sunee Sirivichayakul; Sasisopin Kiertiburanakul; Peter Van Den Eede; Rossana Ditangco; Adeeba Kamarulzaman; Patrick C K Li; Winai Ratanasuwan; Thira Sirisanthana
Journal:  J Med Virol       Date:  2015-07-17       Impact factor: 2.327

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

Authors:  Stephen A Hart; Saran Vardhanabhuti; Sarah A Strobino; Linda J Harrison
Journal:  J Acquir Immune Defic Syndr       Date:  2018-09-01       Impact factor: 3.731

3.  Are all subtypes created equal? The effectiveness of antiretroviral therapy against non-subtype B HIV-1.

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4.  The relatedness of HIV epidemics in the United States-Mexico border region.

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Journal:  AIDS Res Hum Retroviruses       Date:  2010-10-26       Impact factor: 1.723

5.  Transmitted Drug Resistance Mutations in Antiretroviral-Naïve Injection Drug Users with Chronic HIV-1 Infection in Iran.

Authors:  Arash Memarnejadian; Shahoo Menbari; Seyed Ali Mansouri; Leila Sadeghi; Rouhollah Vahabpour; Mohammad Reza Aghasadeghi; Ehsan Mostafavi; Mohammad Abdi
Journal:  PLoS One       Date:  2015-05-11       Impact factor: 3.240

6.  IDEPI: rapid prediction of HIV-1 antibody epitopes and other phenotypic features from sequence data using a flexible machine learning platform.

Authors:  N Lance Hepler; Konrad Scheffler; Steven Weaver; Ben Murrell; Douglas D Richman; Dennis R Burton; Pascal Poignard; Davey M Smith; Sergei L Kosakovsky Pond
Journal:  PLoS Comput Biol       Date:  2014-09-25       Impact factor: 4.475

7.  High levels of virological failure with major genotypic resistance mutations in HIV-1-infected children after 5 years of care according to WHO-recommended 1st-line and 2nd-line antiretroviral regimens in the Central African Republic: A cross-sectional study.

Authors:  Christian Diamant Mossoro-Kpinde; Jean-Chrysostome Gody; Ralph-Sydney Mboumba Bouassa; Olivia Mbitikon; Mohammad-Ali Jenabian; Leman Robin; Mathieu Matta; Kamal Zeitouni; Jean De Dieu Longo; Cecilia Costiniuk; Gérard Grésenguet; Ndèye Coumba Touré Kane; Laurent Bélec
Journal:  Medicine (Baltimore)       Date:  2017-03       Impact factor: 1.889

8.  Comparison of predicted susceptibility between genotype and virtual phenotype HIV drug resistance interpretation systems among treatment-naive HIV-infected patients in Asia: TASER-M cohort analysis.

Authors:  Awachana Jiamsakul; Rami Kantor; Patrick C K Li; Sunee Sirivichayakul; Thira Sirisanthana; Pacharee Kantipong; Christopher K C Lee; Adeeba Kamarulzaman; Winai Ratanasuwan; Rossana Ditangco; Thida Singtoroj; Somnuek Sungkanuparph
Journal:  BMC Res Notes       Date:  2012-10-24
  8 in total

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