title: Relationship between epoetin alfa dose and mortality: findings from a marginal structural model.
abstract: OBJECTIVE
  Observational studies relating epoetin alfa (EPO) dose and mortality frequently use analytic methods that do not control time-dependent confounding by indication (CBI). The relationship between EPO dose and 1-year mortality, adjusting for the effects of time-dependent CBI, was examined using a marginal structural model.
  
  
  METHODS
  This retrospective cohort study included 27,791 hemodialysis patients between July 2000 and June 2002. Patients were grouped at successive 2-wk intervals into a zero-dose category or four nonzero-dose categories. Ordinal regression was used to calculate inverse probability of treatment weights of patients receiving their own dose level given their covariate and treatment history. Three treatment models with an increasing number of treatment predictors were evaluated to assess the effect of model specification. A small number of excessively large patient weights were truncated. Relative hazards for higher-dose groups compared with the lowest nonzero-dose group varied by treatment model specification and by level of weight truncation.
  
  
  RESULTS
  Results differed appreciably between the simplest treatment model, which incorporated only hemoglobin and EPO dosing history with 2% weight truncation (hazard ratio: 1.51; 95% confidence interval: 1.09, 1.89 for highest-dose patients), and the most comprehensive treatment model with 1% weight truncation (hazard ratio: 0.98; 95% confidence interval: 0.76, 1.74).
  
  
  CONCLUSIONS
  There is appreciable CBI at higher EPO doses, and EPO dose was not associated with increased mortality in marginal structural model analyses that more completely addressed this confounding.
authors.affiliation: Department of Global Biostatistics & Epidemiology, Amgen Inc., Thousand Oaks, California 91320, USA.
authors.forename: Ouhong
authors.initials: O
authors.lastname: Wang
authors.forename: Ryan D
authors.initials: RD
authors.lastname: Kilpatrick
authors.forename: Cathy W
authors.initials: CW
authors.lastname: Critchlow
authors.forename: Xiang
authors.initials: X
authors.lastname: Ling
authors.forename: Brian D
authors.initials: BD
authors.lastname: Bradbury
authors.forename: David T
authors.initials: DT
authors.lastname: Gilbertson
authors.forename: Allan J
authors.initials: AJ
authors.lastname: Collins
authors.forename: Kenneth J
authors.initials: KJ
authors.lastname: Rothman
authors.forename: John F
authors.initials: JF
authors.lastname: Acquavella
mesh_terms: D000328:Adult; D000368:Aged; D015415:Biomarkers / Q000097:blood; D015986:Confounding Factors, Epidemiologic; D004305:Dose-Response Relationship, Drug; D000068817:Epoetin Alfa; D004921:Erythropoietin / Q000008:administration & dosage*; D005260:Female; D006397:Hematinics / Q000008:administration & dosage*; D006454:Hemoglobins / Q000378:metabolism; D006801:Humans; D007674:Kidney Diseases / Q000097:blood / Q000188:drug therapy / Q000401:mortality* / Q000628:therapy*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011994:Recombinant Proteins; D006435:Renal Dialysis; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D016896:Treatment Outcome; D014481:United States / Q000453:epidemiology
chemical_list: D015415:Biomarkers; D006397:Hematinics; D006454:Hemoglobins; D011994:Recombinant Proteins; D004921:Erythropoietin; D000068817:Epoetin Alfa