title: Early loss of HIV-infected patients on potent antiretroviral therapy programmes in lower-income countries.
abstract: OBJECTIVE
  To analyse the early loss of patients to antiretroviral therapy (ART) programmes in resource-limited settings.
  
  
  METHODS
  Using data on 5491 adult patients starting ART (median age 35 years, 46% female) in 15 treatment programmes in Africa, Asia and South America with (3) 12 months of follow-up, we investigated risk factors for no follow-up after treatment initiation, and loss to follow-up or death in the first 6 months.
  
  
  RESULTS
  Overall, 211 patients (3.8%) had no follow-up, 880 (16.0%) were lost to follow-up and 141 (2.6%) were known to have died in the first 6 months. The probability of no follow-up was higher in 2003-2004 than in 2000 or earlier (odds ratio, OR: 5.06; 95% confidence interval, CI: 1.28-20.0), as was loss to follow-up (hazard ratio, HR: 7.62; 95% CI: 4.55-12.8) but not recorded death (HR: 1.02; 95% CI: 0.44-2.36). Compared with a baseline CD4-cell count (3) 50 cells/microl, a count < 25 cells/microl was associated with a higher probability of no follow-up (OR: 2.49; 95% CI: 1.43-4.33), loss to follow-up (HR: 1.48; 95% CI: 1.23-1.77) and death (HR: 3.34; 95% CI: 2.10-5.30). Compared to free treatment, fee-for-service programmes were associated with a higher probability of no follow-up (OR: 3.71; 95% CI: 0.97-16.05) and higher mortality (HR: 4.64; 95% CI: 1.11-19.41).
  
  
  CONCLUSIONS
  Early patient losses were increasingly common when programmes were scaled up and were associated with a fee for service and advanced immunodeficiency at baseline. Measures to maximize ART programme retention are required in resource-poor countries.
authors.affiliation: Institute of Social and Preventive Medicine, Bern, Switzerland.
authors.forename: Martin W G
authors.initials: MW
authors.lastname: Brinkhof
authors.forename: François
authors.initials: F
authors.lastname: Dabis
authors.forename: Landon
authors.initials: L
authors.lastname: Myer
authors.forename: David R
authors.initials: DR
authors.lastname: Bangsberg
authors.forename: Andrew
authors.initials: A
authors.lastname: Boulle
authors.forename: Denis
authors.initials: D
authors.lastname: Nash
authors.forename: Mauro
authors.initials: M
authors.lastname: Schechter
authors.forename: Christian
authors.initials: C
authors.lastname: Laurent
authors.forename: Olivia
authors.initials: O
authors.lastname: Keiser
authors.forename: Margaret
authors.initials: M
authors.lastname: May
authors.forename: Eduardo
authors.initials: E
authors.lastname: Sprinz
authors.forename: Matthias
authors.initials: M
authors.lastname: Egger
authors.forename: Xavier
authors.initials: X
authors.lastname: Anglaret
mesh_terms: D000293:Adolescent; D000328:Adult; D000349:Africa / Q000453:epidemiology; D023241:Antiretroviral Therapy, Highly Active / Q000145:classification / Q000191:economics / Q000706:statistics & numerical data*; D001208:Asia / Q000453:epidemiology; D018791:CD4 Lymphocyte Count; D003266:Continuity of Patient Care / Q000706:statistics & numerical data*; D003906:Developing Countries; D005260:Female; D015658:HIV Infections / Q000188:drug therapy* / Q000276:immunology / Q000401:mortality*; D015497:HIV-1; D006297:Health Services Accessibility; D006801:Humans; D007391:International Cooperation; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010342:Patient Acceptance of Health Care / Q000706:statistics & numerical data*; D015397:Program Evaluation; D016016:Proportional Hazards Models; D040442:Public Health Informatics; D012307:Risk Factors; D013020:South America / Q000453:epidemiology