title: Immunodeficiency and the risk of serious clinical endpoints in a well studied cohort of treated HIV-infected patients.
abstract: OBJECTIVE
  To investigate the relative predictive value of CD4(+) metrics for serious clinical endpoints.
  
  
  METHODS
  Observational.
  
  
  METHODS
  Patients (3012; 20 317 person-years) from control arms of ESPRIT and SILCAAT were followed prospectively. We used Cox regression to identify CD4(+) metrics (latest, baseline and nadir CD4(+) cell count, latest CD4(+)%, time spent with CD4(+) count below certain thresholds and CD4(+) slopes) independently predictive of all-cause mortality, non-AIDS deaths, non-AIDS (cardiovascular, hepatic, renal and non-AIDS malignancy) and AIDS events. Akaike information criteria (AIC) were calculated for each model. Significant metrics (P < 0.05) were then additionally adjusted for latest CD4(+) cell count.
  
  
  RESULTS
  Non-AIDS deaths occurred at a higher rate than AIDS deaths [rate ratio: 6.48, 95% confidence interval (CI) 5.1-8.1], and non-AIDS events likewise (rate ratio: 1.72, 95% CI 1.65-1.79). Latest CD4(+) cell count was strongly predictive of lower risk of death (hazard ratio per log2 rise: 0.48, 95% CI 0.43-0.54), with lowest AIC of all metrics. CD4(+) slope over seven visits, after additional adjustment for latest CD4(+) cell count, was the only metric to be an independent predictor for all-cause (hazard ratio for slope <-10 cells/microl per month vs. 0 +/- 10: 3.04, 95% CI 1.98-4.67) and non-AIDS deaths (hazard ratio for slope <-10 cells/microl per month vs. 0 +/- 10: 2.62, 95% CI 1.62-4.22). Latest CD4(+) cell count (per log(2) rise) was the best predictor across all four endpoints and predicted hepatic (hazard ratio 0.46, 95% CI 0.33-0.63) and renal events (hazard ratio 0.39, 95% CI 0.21-0.70), but not cardiovascular events (hazard ratio 1.05, 95% CI 0.77-1.43) or non-AIDS cancers (hazard ratio 0.78, 95% CI 0.59-1.03).
  
  
  CONCLUSIONS
  Latest CD4(+) cell count is the best predictor of serious endpoints. CD4(+) slope independently predicts all-cause and non-AIDS deaths.
authors.affiliation: National Centre in HIV Epidemiology and Clinical Research, Faculty of Medicine, University of New South Wales, Cliffbrook Campus, Coogee, Sydney, New South Wales, Australia. aachhra@nchecr.unsw.edu.au
authors.forename: Amit C
authors.initials: AC
authors.lastname: Achhra
authors.forename: Janaki
authors.initials: J
authors.lastname: Amin
authors.forename: Matthew G
authors.initials: MG
authors.lastname: Law
authors.forename: Sean
authors.initials: S
authors.lastname: Emery
authors.forename: Jan
authors.initials: J
authors.lastname: Gerstoft
authors.forename: Fred M
authors.initials: FM
authors.lastname: Gordin
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Vjecha
authors.forename: James D
authors.initials: JD
authors.lastname: Neaton
authors.forename: David A
authors.initials: DA
authors.lastname: Cooper
mesh_terms: D000328:Adult; D023241:Antiretroviral Therapy, Highly Active; D018791:CD4 Lymphocyte Count; D015496:CD4-Positive T-Lymphocytes / Q000276:immunology*; D018450:Disease Progression; D023381:Endpoint Determination; D005260:Female; D015658:HIV Infections / Q000188:drug therapy / Q000276:immunology* / Q000401:mortality; D015497:HIV-1 / Q000276:immunology*; D006801:Humans; D007153:Immunologic Deficiency Syndromes / Q000188:drug therapy / Q000276:immunology* / Q000401:mortality; D008297:Male; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D011446:Prospective Studies