title: A study of seven rule-based algorithms for the interpretation of HIV-1 genotypic resistance data in Thailand.
abstract: Since the free therapy program was started by the Thai government, the number of patients infected by HIV-1 with access to antiretroviral drugs has increased. The selection of effective interpretation algorithms for antiretroviral drug resistance has become even more important for clinical management. In this retrospective study, the level of agreement was evaluated in 721 antiretroviral-therapy failing HIV-1 subjects. Regarding genetic diversity, about 89% was recognized as non-B variants (CRF01_AE). The level of complete concordant interpretation score in all seven algorithms was recognized in non-nucleoside reverse transcriptase inhibitors (NNRTIs) and protease inhibitors (PIs) (67%), but not in nucleoside reverse transcriptase inhibitors (NRTIs) (52%). Over 10% of the major discordance score with TRUGENE was revealed in didanosine (Agence Nationale de Recherches sur le SIDA[ANRS]; Detroit Medical Centre [DMC]), abacavir (ANRS; Centre Hospitalier de Luxembourg [CHL]), and also with delavirdine, indinavir and amprenavir (Grupo de Aconselhamento Virológico [GAV]). A good to excellent agreement range of kappa scores was detected for most antiretroviral drugs. However, poor agreement with the TRUGENE system (k<0.40) was seen in the ANRS system with didanosine, abacavir and lopinavir; GAV system in indinavir and amprenavir; and DMC system in ritonavir. These might be an option for resource limited countries when selecting the use of a low cost or free algorithm interpretation, which has excellent agreement as the U.S. Food and Drug Administration (FDA)-approved TRUGENE commercial system.
authors.affiliation: Department of Pathology, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand. newvsk@yahoo.com
authors.forename: Vongsakorn
authors.initials: V
authors.lastname: Poonpiriya
authors.forename: Somnuek
authors.initials: S
authors.lastname: Sungkanuparph
authors.forename: Pranee
authors.initials: P
authors.lastname: Leechanachai
authors.forename: Ekawat
authors.initials: E
authors.lastname: Pasomsub
authors.forename: Chotip
authors.initials: C
authors.lastname: Watitpun
authors.forename: Sirichan
authors.initials: S
authors.lastname: Chunhakan
authors.forename: Wasun
authors.initials: W
authors.lastname: Chantratita
mesh_terms: D000465:Algorithms; D019380:Anti-HIV Agents / Q000494:pharmacology; D024882:Drug Resistance, Viral / Q000235:genetics*; D005838:Genotype; D015658:HIV Infections / Q000188:drug therapy / Q000453:epidemiology / Q000821:virology; D016333:HIV Protease / Q000235:genetics; D017320:HIV Protease Inhibitors; D054303:HIV Reverse Transcriptase / Q000235:genetics; D015497:HIV-1 / Q000145:classification / Q000187:drug effects* / Q000201:enzymology / Q000235:genetics; D006801:Humans; D008826:Microbial Sensitivity Tests; D018894:Reverse Transcriptase Inhibitors; D013785:Thailand / Q000453:epidemiology
chemical_list: D019380:Anti-HIV Agents; D017320:HIV Protease Inhibitors; D018894:Reverse Transcriptase Inhibitors; C514824:reverse transcriptase, Human immunodeficiency virus 1; D054303:HIV Reverse Transcriptase; D016333:HIV Protease