title: Comparative effectiveness of two anemia management strategies for complex elderly dialysis patients.
abstract: BACKGROUND
  Randomized trials found that use of erythropoiesis-stimulating agents to target normal hematocrit (Hct) levels (>39%) compared with 27%-34.5% increases cardiovascular risk and mortality among chronic kidney disease patients. However, the effects of the most widely used Hct target in the past 2 decades, 34.5%-39%, have never been examined.
  
  
  OBJECTIVE
  To compare the effects of 2 Hct target strategies-30.0%-34.5% (low) and 34.5%-39.0% (mid) in a high-risk population: elderly dialysis patients with significant comorbidities.
  
  
  METHODS
  Observational data from the US Renal Data System were used to emulate a randomized trial in which patients were assigned to either Hct strategy. Follow-up started after completing 3 months of hemodialysis and ended 6 months later. We conducted the observational analogs of intention-to-treat and per-protocol analyses. Inverse-probability weighting was used to adjust for measured time-dependent confounding by indication.
  
  
  METHODS
  A total of 22,474 elderly patients with both diabetes and cardiovascular disease who initiated hemodialysis in 2006-2008.
  
  
  METHODS
  Hazard ratios (HRs) and survival probabilities for all-cause mortality and a composite cardiovascular and mortality endpoint.
  
  
  RESULTS
  The intention-to-treat HR (95% confidence interval) for mid versus low Hct strategy was 1.05 (0.99-1.11) for all-cause mortality and 1.03 (0.98-1.08) for the composite endpoint. The per-protocol HR (95% confidence interval) for mid versus low Hct strategy was 0.98 (0.78-1.24) for all-cause mortality and 1.00 (0.81-1.24) for the composite outcome.
  
  
  CONCLUSIONS
  Among hemodialysis patients, we did not find differences in 6-month survival or cardiovascular risk between clinical strategies that target Hct at 30.0%-34.5% versus 34.5%-39.0%.
authors.affiliation: *Medical Technology and Practice Patterns Institute (MTPPI), Bethesda, MD †VA NY Harbor Healthcare System, New York, NY Departments of ‡Epidemiology §Biostatistics, Harvard School of Public Health ∥Harvard-MIT Division of Health Sciences and Technology, Boston, MA.
authors.forename: Yi
authors.initials: Y
authors.lastname: Zhang
authors.forename: Mae
authors.initials: M
authors.lastname: Thamer
authors.forename: James
authors.initials: J
authors.lastname: Kaufman
authors.forename: Dennis
authors.initials: D
authors.lastname: Cotter
authors.forename: Miguel A
authors.initials: MA
authors.lastname: Hernán
mesh_terms: D000368:Aged; D018798:Anemia, Iron-Deficiency / Q000188:drug therapy* / Q000453:epidemiology*; D002318:Cardiovascular Diseases / Q000453:epidemiology* / Q000628:therapy; D015897:Comorbidity; D004305:Dose-Response Relationship, Drug; D054796:Drug Dosage Calculations; D000068817:Epoetin Alfa; D004921:Erythropoietin / Q000008:administration & dosage*; D005260:Female; D006397:Hematinics / Q000008:administration & dosage; D006801:Humans; D007676:Kidney Failure, Chronic / Q000453:epidemiology* / Q000628:therapy; D008297:Male; D011994:Recombinant Proteins / Q000008:administration & dosage; D006435:Renal Dialysis / Q000706:statistics & numerical data*; D012307:Risk Factors; D016019:Survival Analysis; D016896:Treatment Outcome; D014481:United States
chemical_list: D006397:Hematinics; D011994:Recombinant Proteins; D004921:Erythropoietin; D000068817:Epoetin Alfa