Comparison of algorithms that interpret genotypic HIV-1 drug resistance to determine the prevalence of transmitted drug resistance
Comparison of algorithms that interpret genotypic HIV-1 drug resistance to determine the prevalence of transmitted drug resistance
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.
algorithms, HIV, prevalence, transmitted drug resistance
1-5
Liu, L.
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Richman, D.D.
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Hecht, F.M.
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Markowitz, M.
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Daar, E.S.
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Routy, J-P.
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Margolick, J.B.
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Collier, A.C.
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Woelk, C.H.
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Little, S.J.
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Smith, D.M.
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23 April 2008
Liu, L.
586d7bba-a75f-4a3f-afc0-f0b93ef2b6b1
Richman, D.D.
1d5f38e4-c778-4b0b-b542-9d1160e63041
Hecht, F.M.
fc71d16e-99eb-4322-a6c1-afa2c32abe05
Markowitz, M.
e35c87fd-8da6-45ca-8bb0-e564d42173b2
Daar, E.S.
838d1d19-1802-49b1-954f-a98c26a7a372
Routy, J-P.
fb7ff6aa-bfb1-4ace-9ba0-b94058f492f1
Margolick, J.B.
89abe4a0-5ca4-4764-b1a7-d27f495b9053
Collier, A.C.
24a611d3-7525-41d1-9cf1-cb674a4042ad
Woelk, C.H.
4d3af0fd-658f-4626-b3b5-49a6192bcf7d
Little, S.J.
97d16cb1-b00a-40f8-9746-2300b5f7174d
Smith, D.M.
88dfac94-ed7d-438d-9581-3dce369e9882
Liu, L., Richman, D.D., Hecht, F.M., Markowitz, M., Daar, E.S., Routy, J-P., Margolick, J.B., Collier, A.C., Woelk, C.H., Little, S.J. and Smith, D.M.
(2008)
Comparison of algorithms that interpret genotypic HIV-1 drug resistance to determine the prevalence of transmitted drug resistance.
AIDS, 22 (7), .
(doi:10.1097/QAD.0b013e3282f5ff71).
(PMID:18427201)
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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Published date: 23 April 2008
Keywords:
algorithms, HIV, prevalence, transmitted drug resistance
Organisations:
Clinical & Experimental Sciences
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Local EPrints ID: 352765
URI: http://eprints.soton.ac.uk/id/eprint/352765
PURE UUID: b1a74083-f54c-4ed8-a4b0-b956c3794e59
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Date deposited: 20 May 2013 14:44
Last modified: 14 Mar 2024 13:55
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Contributors
Author:
L. Liu
Author:
D.D. Richman
Author:
F.M. Hecht
Author:
M. Markowitz
Author:
E.S. Daar
Author:
J-P. Routy
Author:
J.B. Margolick
Author:
A.C. Collier
Author:
C.H. Woelk
Author:
S.J. Little
Author:
D.M. Smith
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