title: Prognosis of patients with HIV-1 infection starting antiretroviral therapy in sub-Saharan Africa: a collaborative analysis of scale-up programmes.
abstract: BACKGROUND
  Prognostic models have been developed for patients infected with HIV-1 who start combination antiretroviral therapy (ART) in high-income countries, but not for patients in sub-Saharan Africa. We developed two prognostic models to estimate the probability of death in patients starting ART in sub-Saharan Africa.
  
  
  METHODS
  We analysed data for adult patients who started ART in four scale-up programmes in Côte d'Ivoire, South Africa, and Malawi from 2004 to 2007. Patients lost to follow-up in the first year were excluded. We used Weibull survival models to construct two prognostic models: one with CD4 cell count, clinical stage, bodyweight, age, and sex (CD4 count model); and one that replaced CD4 cell count with total lymphocyte count and severity of anaemia (total lymphocyte and haemoglobin model), because CD4 cell count is not routinely measured in many African ART programmes. Death from all causes in the first year of ART was the primary outcome.
  
  
  RESULTS
  912 (8.2%) of 11 153 patients died in the first year of ART. 822 patients were lost to follow-up and not included in the main analysis; 10 331 patients were analysed. Mortality was strongly associated with high baseline CD4 cell count (>/=200 cells per muL vs <25; adjusted hazard ratio 0.21, 95% CI 0.17-0.27), WHO clinical stage (stages III-IV vs I-II; 3.45, 2.43-4.90), bodyweight (>/=60 kg vs <45 kg; 0.23, 0.18-0.30), and anaemia status (none vs severe: 0.27, 0.20-0.36). Other independent risk factors for mortality were low total lymphocyte count, advanced age, and male sex. Probability of death at 1 year ranged from 0.9% (95% CI 0.6-1.4) to 52.5% (43.8-61.7) with the CD4 model, and from 0.9% (0.5-1.4) to 59.6% (48.2-71.4) with the total lymphocyte and haemoglobin model. Both models accurately predict early mortality in patients starting ART in sub-Saharan Africa compared with observed data.
  
  
  CONCLUSIONS
  Prognostic models should be used to counsel patients, plan health services, and predict outcomes for patients with HIV-1 infection in sub-Saharan Africa.
  
  
  BACKGROUND
  US National Institute of Allergy And Infectious Diseases, Eunice Kennedy Shriver National Institute of Child Health and Human Development, and National Cancer Institute.
authors.affiliation: Department of Social Medicine, University of Bristol, Bristol, UK.
authors.forename: Margaret
authors.initials: M
authors.lastname: May
authors.forename: Andrew
authors.initials: A
authors.lastname: Boulle
authors.forename: Sam
authors.initials: S
authors.lastname: Phiri
authors.forename: Eugene
authors.initials: E
authors.lastname: Messou
authors.forename: Landon
authors.initials: L
authors.lastname: Myer
authors.forename: Robin
authors.initials: R
authors.lastname: Wood
authors.forename: Olivia
authors.initials: O
authors.lastname: Keiser
authors.forename: Jonathan A C
authors.initials: JA
authors.lastname: Sterne
authors.forename: Francois
authors.initials: F
authors.lastname: Dabis
authors.forename: Matthias
authors.initials: M
authors.lastname: Egger
mesh_terms: D000293:Adolescent; D000328:Adult; D017954:Africa South of the Sahara / Q000453:epidemiology; D044966:Anti-Retroviral Agents / Q000627:therapeutic use*; D003906:Developing Countries; D005260:Female; D015658:HIV Infections / Q000188:drug therapy* / Q000453:epidemiology / Q000401:mortality / Q000821:virology; D015497:HIV-1; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011379:Prognosis; D015996:Survival Rate; D019562:Viral Load; D055815:Young Adult
chemical_list: D044966:Anti-Retroviral Agents