title: Clinically relevant interpretation of genotype for resistance to abacavir.
abstract: OBJECTIVE
  To develop a stepwise methodology for the development and validation of clinically relevant genotypic score for resistance to antiretroviral drugs and to apply this approach to the genotypic resistance to abacavir.
  
  
  METHODS
  All patients having received abacavir during the Narval trial were included in this study. The impact of each nucleoside analogue resistance mutation on the virologic response to abacavir was studied in a univariate analysis. Mutations with a P value < 0.20 and those selected by abacavir were retained. According to the number of mutations three levels of resistance were defined. A multivariate analysis accounting for confonding variables assessed whether the genotypic score was an independent predictor of the response. The robustness of the score was analysed using the bootstrap resampling method.
  
  
  RESULTS
  In the 175 patients exposed to abacavir, the strongest association between the decrease in viral load and the number of mutations was observed with a set of six mutations at codons 41, 67, 210, 215, 74 and 184 of the reverse transcriptase gene. In patients with fewer than four mutations (no evidence of resistance) the median decrease in viral load was -1.64 log(10) copies/ml while it was -0.69 log(10) and -0.19 log(10) in those with four (possible resistance) and five or six (resistance) mutations respectively. In the multivariate analysis this score was an independent predictor of the response. The bootstrap analysis showed the robustness of the score.
  
  
  CONCLUSIONS
  We developed a new strategy for the analysis of correlation between genotype profile at baseline and virologic response.
authors.affiliation: Department of Virology, Bichat-Claude Bernard Hospital, Paris, France.
authors.forename: Françoise
authors.initials: F
authors.lastname: Brun-Vézinet
authors.forename: Diane
authors.initials: D
authors.lastname: Descamps
authors.forename: Annick
authors.initials: A
authors.lastname: Ruffault
authors.forename: Bernard
authors.initials: B
authors.lastname: Masquelier
authors.forename: Vincent
authors.initials: V
authors.lastname: Calvez
authors.forename: Gilles
authors.initials: G
authors.lastname: Peytavin
authors.forename: Fabienne
authors.initials: F
authors.lastname: Telles
authors.forename: Laurence
authors.initials: L
authors.lastname: Morand-Joubert
authors.forename: Jean-Luc
authors.initials: JL
authors.lastname: Meynard
authors.forename: Muriel
authors.initials: M
authors.lastname: Vray
authors.forename: Dominique
authors.initials: D
authors.lastname: Costagliola
mesh_terms: D000465:Algorithms; D015224:Dideoxynucleosides / Q000627:therapeutic use*; D024882:Drug Resistance, Viral / Q000235:genetics*; D005838:Genotype; D015658:HIV Infections / Q000188:drug therapy* / Q000821:virology; D015497:HIV-1 / Q000235:genetics*; D006801:Humans; D015999:Multivariate Analysis; D009154:Mutation; D012367:RNA, Viral / Q000097:blood; D018894:Reverse Transcriptase Inhibitors / Q000627:therapeutic use*; D018709:Statistics, Nonparametric; D000099227:Abacavir
chemical_list: D015224:Dideoxynucleosides; D012367:RNA, Viral; D018894:Reverse Transcriptase Inhibitors; D000099227:Abacavir