Rules-based HIV-1 genotypic resistance interpretation systems predict 8 week and 24 week virological antiretroviral treatment outcome and benefit from drug potency weighting

Journal of Antimicrobial Chemotherapy

Volumn 64, Issue 3, 2009, Pages 616-624

  Zazzi, Maurizio ^a   Prosperi, Mattia ^b,c   Vicenti, Ilaria ^a   Di Giambenedetto, Simona ^d   Callegaro, Annapaola ^e   Bruzzone, Bianca ^f   Baldanti, Fausto ^g   Gonnelli, Angela ^a   Boeri, Enzo ^h   Paolini, Elisabetta ⁱ   Rusconi, Stefano ^j   Giacometti, Andrea ^k   Maggiolo, Franco ^e   Menzo, Stefano ^l   De Luca, Andrea ^d  

^a UNIVERSITY HOSPITAL OF SIENA   (Italy)

^b NATIONAL INSTITUTE FOR INFECTIOUS DISEASES L SPALLANZANI   (Italy)

^c Informa   (Italy)

^d CATHOLIC UNIVERSITY   (Italy)

^e OSPEDALI RIUNITI   (Italy)

^f UNIVERSITY OF GENOA   (Italy)

^g FONDAZIONE IRCCS POLICLINICO SAN MATTEO   (Italy)

^h Diagnostica and Ricerca San Raffaele   (Italy)

ⁱ CREMONA HOSPITAL   (Italy)

^j UNIVERSITY OF MILAN   (Italy)

^k OSPEDALI RIUNITI   (Italy)

^l UNIVERSITÀ POLITECNICA DELLE MARCHE   (Italy)

more..

Author keywords

Algorithm; Drug resistance; Genotype

Indexed keywords

ABACAVIR; AMPRENAVIR; ATAZANAVIR; DARUNAVIR; DIDANOSINE; EFAVIRENZ; EMTRICITABINE; ENFUVIRTIDE; LAMIVUDINE; LOPINAVIR; NELFINAVIR; NEVIRAPINE; PROTEINASE INHIBITOR; RALTEGRAVIR; RNA DIRECTED DNA POLYMERASE INHIBITOR; SAQUINAVIR; STAVUDINE; TENOFOVIR; TIPRANAVIR; ZIDOVUDINE;

ACCURACY; ADULT; ANRS; ANTIRETROSCAN; ANTIRETROVIRAL RESISTANCE COHORT ANALYSIS DATABASE; ANTIVIRAL RESISTANCE; ARTICLE; DATA BASE; DRUG POTENCY; EVALUATION RESEARCH; EXPERT SYSTEM; FEMALE; GENOTYPE; GENOTYPE INTERPRETATION SYSTEMS; HIGHLY ACTIVE ANTIRETROVIRAL THERAPY; HIVDB; HUMAN; HUMAN IMMUNODEFICIENCY VIRUS 1 INFECTION; INFORMATION SYSTEM; INTERNET; ITALY; MAJOR CLINICAL STUDY; MALE; OUTCOME ASSESSMENT; PROGNOSIS; REGA; SENSITIVITY ANALYSIS; TREATMENT DURATION; TREATMENT RESPONSE;

ADULT; ANIMALS; ANTI-HIV AGENTS; FEMALE; GENOTYPE; HIV INFECTIONS; HIV-1; HUMANS; ITALY; LOGISTIC MODELS; MALE; MICROBIAL SENSITIVITY TESTS; MIDDLE AGED; PROGNOSIS; RETROSPECTIVE STUDIES; RNA, VIRAL; ROC CURVE; TREATMENT OUTCOME;

EID: 69049111044     PISSN: 03057453     EISSN: 14602091     Source Type: Journal    
DOI: 10.1093/jac/dkp252     Document Type: Article

References (17)

1. Hammer SM, Eron JJ Jr, Reiss P et al. Antiretroviral treatment of adult HIV infection: 2008 recommendations of the International AIDS Society-USA panel. JAMA 2008; 300: 555-70.
2. Liu TF, Shafer RW. Web resources for HIV type 1 genotypic-resistance test interpretation. Clin Infect Dis 2006; 42: 1608-18.
3. Van Laethem K, Vandamme AM. Interpreting resistance data for HIV-1 therapy management - know the limitations. AIDS Rev 2006; 8: 37-43.
4. De Luca A, Cingolani A, Di Giambenedetto S et al. Variable prediction of antiretroviral treatment outcome by different systems for interpreting genotypic human immunodeficiency virus type 1 drug resistance. J Infect Dis 2003; 187: 1934-43.
5. King MS, Rode R, Cohen-Codar I et al. Predictive genotypic algorithm for virologic response to lopinavir-ritonavir in protease inhibitor-experienced patients. Antimicrob Agents Chemother 2007; 51: 3067-74.
6. De Luca A, Giambenedetto SD, Trotta MP et al. Improved interpretation of genotypic changes in the HIV-1 reverse transcriptase coding region that determine the virological response to didanosine. J Infect Dis 2007; 196: 1645-53.
7. Marcelin AG, Flandre P, Molina JM et al. Genotypic resistance analysis of the virological response to fosamprenavir-ritonavir in protease inhibitor-experienced patients in CONTEXT and TRIAD clinical trials. Antimicrob Agents Chemother 2008; 52: 4251-7.
8. Cozzi-Lepri A. Initiatives for developing and comparing genotype interpretation systems: External validation of existing rule-based interpretation systems for abacavir against virological response. HIV Med 2008; 9: 27-40.
9. Assoumou L, Brun-Ve' zinet F, Cozzi-Lepri A et al. Initiatives for developing and comparing genotype interpretation systems: External validation of existing systems for didanosine against virological response. J Infect Dis 2008; 198: 470-80.
10. Johnson VA, Brun-Vezinet F, Clotet B et al. Update of the drug resistance mutations in HIV-1: Spring 2008. Top HIV Med 2008; 16: 62-8.
11. Zazzi M, Romano L, Venturi G et al. Comparative evaluation of three computerized algorithms for prediction of antiretroviral susceptibility from HIV type 1 genotype. J Antimicrob Chemother 2004; 53: 356-60.
12. Shen L, Peterson S, Sedaghat AR, McMahon MA et al. Dose-response curve slope sets class-specific limits on inhibitory potential of anti-HIV drugs. Nat Med 2008; 14: 762-6.
13. Gupta R, Hill A, Sawyer AW et al. Emergence of drug resistance in HIV type 1-infected patients after receipt of first-line highly active antiretroviral therapy: A systematic review of clinical trials. Clin Infect Dis 2008; 47: 712-22.
14. Lengauer T, Sing T. Bioinformatics-assisted anti-HIV therapy. Nat Rev Microbiol 2006; 4: 790-7.
15. Altmann A, Beerenwinkel N, Sing T et al. Improved prediction of response to antiretroviral combination therapy using the genetic barrier to drug resistance. Antivir Ther 2007; 12: 169-78.
16. Larder B, Wang D, Revell A et al. The development of artificial neural networks to predict virological response to combination HIV therapy. Antivir Ther 2007; 12: 15-24.
17. Rosen-Zvi M, Altmann A, Prosperi M et al. Selecting anti-HIV therapies based on a variety of genomic and clinical factors. Bioinformatics 2008; 24: I399-406.