title: Identification of new genotypic cut-off levels to predict the efficacy of lopinavir/ritonavir and darunavir/ritonavir in the TITAN trial.
abstract: BACKGROUND
  Genotypic algorithms used to predict the clinical efficacy of lopinavir/ritonavir (LPV/r) have included a range of mutation lists and efficacy endpoints. Normally, HIV clinical trials are powered to detect a difference between treatment arms of 10-12% for the endpoint of viral load suppression <50 HIV-1 RNA copies/mL. The TITAN trial evaluated LPV/r vs. darunavir/ritonavir (DRV/r) in treatment-experienced patients with viral load >1000 copies/mL. This analysis aimed to re-evaluate resistance algorithms for LPV/r in the TITAN trial.
  
  
  METHODS
  Baseline genotype data were classified using seven genotypic resistance algorithms: International AIDS Society USA (IAS-USA) LPV mutations (current cut-off=6), Abbott 2007 mutation list (cut-off=3), ANRS mutations (cut-off=4), FDA mutations (cut-off=3), Stanford, REGA and IAS-USA major protease inhibitor (PI) mutations. Efficacy in the TITAN trial (HIV-1 RNA <50 copies/mL at week 48) was correlated with the number of mutations from each list, to show the 'efficacy advantage cut-off level': the number of mutations from each list associated with a difference in efficacy between treatment arms of at least 12%.
  
  
  RESULTS
  Multivariate logistic regression analysis identified lower genotypic cut-off levels than previously reported where there was at least 12% lower efficacy for LPV/r vs. DRV/r. These efficacy advantage cut-off levels were: IAS-USA LPV mutations, cut-off=3; Abbott 2007, cut-off=2; ANRS LPV, cut-off=3; FDA LPV mutations, cut-off=2; major IAS-USA PI mutations, cut-off=1; Stanford algorithm, cut-off=low-level LPV resistance; REGA algorithm, cut-off=intermediate-level LPV resistance. There were linear falls in HIV-1 RNA suppression rates with rising mutation counts in the TITAN, French LPV ATU, BMS-045 and RESIST trials.
  
  
  CONCLUSIONS
  The analysis identified more sensitive cut-off levels for LPV genotypic algorithms, below those currently used.
authors: Pharmacology Research Laboratories, University of Liverpool, Liverpool, UK. microhaart@aol.com
authors: A
authors: A
authors: Hill
authors: A-G
authors: AG
authors: Marcelin
authors: V
authors: V
authors: Calvez
mesh_terms: D000328:Adult; D000465:Algorithms; D019380:Anti-HIV Agents / Q000627:therapeutic use*; D018791:CD4 Lymphocyte Count; D000069454:Darunavir; D024882:Drug Resistance, Viral / Q000235:genetics*; D004359:Drug Therapy, Combination; D005260:Female; D005838:Genotype; D015658:HIV Infections / Q000097:blood / Q000188:drug therapy* / Q000821:virology; D017320:HIV Protease Inhibitors / Q000627:therapeutic use*; D015497:HIV-1 / Q000235:genetics*; D006801:Humans; D057194:Intention to Treat Analysis; D016015:Logistic Models; D061466:Lopinavir; D008297:Male; D009154:Mutation / Q000235:genetics; D011744:Pyrimidinones / Q000627:therapeutic use; D012367:RNA, Viral / Q000097:blood; D019438:Ritonavir / Q000627:therapeutic use; D012680:Sensitivity and Specificity; D013449:Sulfonamides / Q000627:therapeutic use; D016896:Treatment Outcome; D019562:Viral Load
chemical_list: D019380:Anti-HIV Agents; D017320:HIV Protease Inhibitors; D011744:Pyrimidinones; D012367:RNA, Viral; D013449:Sulfonamides; D061466:Lopinavir; D019438:Ritonavir; D000069454:Darunavir