title: Trends in CD4 counts in HIV-infected patients with HIV viral load monitoring while on combination antiretroviral treatment: results from The TREAT Asia HIV Observational Database.
abstract: BACKGROUND
  The aim of this study was to examine the relationship between trends in CD4 counts (slope) and HIV viral load (VL) after initiation of combination antiretroviral treatment (cART) in Asian patients in The TREAT Asia HIV Observational Database (TAHOD).
  
  
  METHODS
  Treatment-naive HIV-infected patients who started cART with three or more and had three or more CD4 count and HIV VL tests were included. CD4 count slopes were expressed as changes of cells per microliter per year. Predictors of CD4 count slopes from 6 months after initiation were assessed by random-effects linear regression models.
  
  
  RESULTS
  A total of 1676 patients (74% male) were included. The median time on cART was 4.2 years (IQR 2.5-5.8 years). In the final model, CD4 count slope was associated with age, concurrent HIV VL and CD4 count, disease stage, hepatitis B or C co-infection, and time since cART initiation. CD4 count continues to increase with HIV VL up to 20,000 copies/mL during 6-12 months after cART initiation. However, the HIV VL has to be controlled below 5,000, 4,000 and 500 copies/mL for the CD4 count slope to remain above 20 cells/microliter per year during 12-18, 18-24, and beyond 24 months after cART initiation.
  
  
  CONCLUSIONS
  After cART initiation, CD4 counts continued to increase even when the concurrent HIV VL was detectable. However, HIV VL needed to be controlled at a lower level to maintain a positive CD4 count slope when cART continues. The effect on long-term outcomes through the possible development of HIV drug resistance remains uncertain.
authors.affiliation: National Centre in HIV Epidemiology and Clinical Research, The University of New South Wales, Sydney, Australia. jzhou@nchecr.unsw.edu.au
authors.forename: Jialun
authors.initials: J
authors.lastname: Zhou
authors.forename: Thira
authors.initials: T
authors.lastname: Sirisanthana
authors.forename: Sasisopin
authors.initials: S
authors.lastname: Kiertiburanakul
authors.forename: Yi-Ming A
authors.initials: YM
authors.lastname: Chen
authors.forename: Ning
authors.initials: N
authors.lastname: Han
authors.forename: Poh Lian
authors.initials: PL
authors.lastname: Lim
authors.forename: Nagalingeswaran
authors.initials: N
authors.lastname: Kumarasamy
authors.forename: Jun Yong
authors.initials: JY
authors.lastname: Choi
authors.forename: Tuti Parwati
authors.initials: TP
authors.lastname: Merati
authors.forename: Evy
authors.initials: E
authors.lastname: Yunihastuti
authors.forename: Shinichi
authors.initials: S
authors.lastname: Oka
authors.forename: Adeeba
authors.initials: A
authors.lastname: Kamarulzaman
authors.forename: Praphan
authors.initials: P
authors.lastname: Phanuphak
authors.forename: Christopher K C
authors.initials: CK
authors.lastname: Lee
authors.forename: Patrick C K
authors.initials: PC
authors.lastname: Li
authors.forename: Sanjay
authors.initials: S
authors.lastname: Pujari
authors.forename: Vanthanak
authors.initials: V
authors.lastname: Saphonn
authors.forename: Matthew G
authors.initials: MG
authors.lastname: Law
mesh_terms: D000328:Adult; D023241:Antiretroviral Therapy, Highly Active; D001208:Asia; D018791:CD4 Lymphocyte Count / Q000639:trends*; D005260:Female; D015658:HIV Infections / Q000188:drug therapy / Q000276:immunology* / Q000821:virology; D006801:Humans; D016014:Linear Models; D008297:Male; D019562:Viral Load