title: Outcomes following virological failure and predictors of switching to second-line antiretroviral therapy in a South African treatment program.
abstract: OBJECTIVE
  Without resistance tests, deciding which patients with virological failure should switch to second-line antiretroviral therapy (ART) is difficult. The factors influencing this decision are poorly understood. We assess predictors of switching regimens after virological failure.
  
  
  METHODS
  Retrospective cohort study using clinical data from a South African ART program with 6-monthly viral load (VL) monitoring.
  
  
  METHODS
  We constructed a dataset of patient visits occurring following first-line virological failure, and used random effects logistic regression (accounting for individual-level and clinic-level clustering) to assess predictors of switching at each visit.
  
  
  RESULTS
  One thousand six hundred sixty-eight patients with virological failure (73% male, mean age 41 years, median CD4 184 cells/mm, mean log10 VL 4.3) contributed 1922 person-years of viremia. 12 months after failure, the cumulative incidence of switching regimen, viral resuppression, or death was 16.9%, 13.2%, and 4.6%, respectively. In adjusted analysis, switching was more likely at the third or subsequent visit after failure; in visits occurring in 2008 versus 2003 to 2007; and in patients with ART experience pre-programme, current high VL or low CD4 count. Switching was less likely in patients with no clinic contact for 4 months, or declining VL. Switching rates varied between clinics with clinic-level clustering evident in the final model (P <0.001).
  
  
  CONCLUSIONS
  Despite 6-monthly virological monitoring and recommendations to switch after adherence interventions and confirmed viremia, patients experienced delayed switching. Individual-level covariates influenced switching but did not account for variable switching rates between clinics, suggesting differences in guideline implementation. In certain circumstances delays may be warranted; however understanding barriers to guideline implementation will limit unnecessary delays.
authors: London School of Hygiene and Tropical Medicine, Keppel Street, London, United Kingdom. victoria.johnston@lshtm.ac.uk
authors: Victoria
authors: V
authors: Johnston
authors: Katherine L
authors: KL
authors: Fielding
authors: Salome
authors: S
authors: Charalambous
authors: Gavin
authors: G
authors: Churchyard
authors: Andrew
authors: A
authors: Phillips
authors: Alison D
authors: AD
authors: Grant
mesh_terms: D000328:Adult; D019380:Anti-HIV Agents / Q000627:therapeutic use*; D023241:Antiretroviral Therapy, Highly Active; D024882:Drug Resistance, Viral; D005260:Female; D015658:HIV Infections / Q000188:drug therapy*; D006801:Humans; D016015:Logistic Models; D008297:Male; D012189:Retrospective Studies; D013019:South Africa; D017211:Treatment Failure; D016896:Treatment Outcome; D019562:Viral Load
chemical_list: D019380:Anti-HIV Agents