title: Long-term patterns in CD4 response are determined by an interaction between baseline CD4 cell count, viral load, and time: The Asia Pacific HIV Observational Database (APHOD).
abstract: BACKGROUND
  Random effects models were used to explore how the shape of CD4 cell count responses after commencing combination antiretroviral therapy (cART) develop over time and, in particular, the role of baseline and follow-up covariates.
  
  
  METHODS
  Patients in Asia Pacific HIV Observational Database who first commenced cART after January 1, 1997, and who had a baseline CD4 cell count and viral load measure and at least 1 follow-up measure between 6 and 24 months, were included. CD4 cell counts were determined at every 6-month period after the commencement of cART for up to 6 years.
  
  
  RESULTS
  A total of 1638 patients fulfilled the inclusion criteria with a median follow-up time of 58 months. Lower post-cART mean CD4 cell counts were found to be associated with increasing age (P < 0.001), pre-cART hepatitis C coinfection (P = 0.038), prior AIDS (P = 0.019), baseline viral load < or equal to 100,000 copies per milliliter (P < 0.001), and the Asia Pacific region compared with Australia (P = 0.005). A highly significant 3-way interaction between the effects of time, baseline CD4 cell count, and post-cART viral burden (P < 0.0001) was demonstrated. Higher long-term mean CD4 cell counts were associated with lower baseline CD4 cell count and consistently undetectable viral loads. Among patients with consistently detectable viral load, CD4 cell counts seemed to converge for all baseline CD4 levels.
  
  
  CONCLUSIONS
  Our analysis suggest that the long-term shape of post-cART CD4 cell count changes depends only on a 3-way interaction between baseline CD4 cell count, viral load response, and time.
authors.affiliation: Cancer Council New South Wales, Woolloomooloo, Sydney, New South Wales, Australia.
authors.forename: Sam
authors.initials: S
authors.lastname: Egger
authors.forename: Kathy
authors.initials: K
authors.lastname: Petoumenos
authors.forename: Adeeba
authors.initials: A
authors.lastname: Kamarulzaman
authors.forename: Jennifer
authors.initials: J
authors.lastname: Hoy
authors.forename: Somnuek
authors.initials: S
authors.lastname: Sungkanuparph
authors.forename: John
authors.initials: J
authors.lastname: Chuah
authors.forename: Kathleen
authors.initials: K
authors.lastname: Falster
authors.forename: Jialun
authors.initials: J
authors.lastname: Zhou
authors.forename: Matthew G
authors.initials: MG
authors.lastname: Law
mesh_terms: D000328:Adult; D044966:Anti-Retroviral Agents / Q000627:therapeutic use*; D018791:CD4 Lymphocyte Count; D015496:CD4-Positive T-Lymphocytes / Q000276:immunology*; D015331:Cohort Studies; D004359:Drug Therapy, Combination; D005260:Female; D015658:HIV Infections / Q000188:drug therapy / Q000276:immunology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D013997:Time Factors; D019562:Viral Load
chemical_list: D044966:Anti-Retroviral Agents