title: Influenza vaccine effectiveness in patients on hemodialysis: an analysis of a natural experiment.
abstract: BACKGROUND
  Although the influenza vaccine is recommended for patients with end-stage renal disease, little is known about its effectiveness. Observational studies of vaccine effectiveness (VE) are challenging because vaccinated subjects may be healthier than unvaccinated subjects.
  
  
  METHODS
  Using US Renal Data System data, we estimated VE for influenza-like illness, influenza/pneumonia hospitalization, and mortality in adult patients undergoing hemodialysis by using a natural experiment created by the year-to-year variation in the match of the influenza vaccine to the circulating virus. We compared vaccinated patients in matched years (1998, 1999, and 2001) with a mismatched year (1997) using Cox proportional hazards models. Ratios of hazard ratios compared vaccinated patients between 2 years and unvaccinated patients between 2 years. We calculated VE as 1 - effect measure.
  
  
  RESULTS
  Vaccination rates were less than 50% each year. Conventional analysis comparing vaccinated with unvaccinated patients produced average VE estimates of 13%, 16%, and 30% for influenza-like illness, influenza/pneumonia hospitalization, and mortality, respectively. When restricted to the preinfluenza period, results were even stronger, indicating bias. The pooled ratio of hazard ratios comparing matched seasons with a placebo season resulted in a VE of 0% (95% CI, -3% to 2%) for influenza-like illness, 2% (-2% to 5%) for hospitalization, and 0% (-3% to 3%) for death.
  
  
  CONCLUSIONS
  Relative to a mismatched year, we found little evidence of increased VE in subsequent well-matched years, suggesting that the current influenza vaccine strategy may have a smaller effect on morbidity and mortality in the end-stage renal disease population than previously thought. Alternate strategies (eg, high-dose vaccine, adjuvanted vaccine, and multiple doses) should be investigated.
authors.affiliation: Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599-7435, USA.
authors.forename: Leah J
authors.initials: LJ
authors.lastname: McGrath
authors.forename: Abhijit V
authors.initials: AV
authors.lastname: Kshirsagar
authors.forename: Stephen R
authors.initials: SR
authors.lastname: Cole
authors.forename: Lily
authors.initials: L
authors.lastname: Wang
authors.forename: David J
authors.initials: DJ
authors.lastname: Weber
authors.forename: Til
authors.initials: T
authors.lastname: Stürmer
authors.forename: M Alan
authors.initials: MA
authors.lastname: Brookhart
mesh_terms: D000328:Adult; D000368:Aged; D015982:Bias; D015986:Confounding Factors, Epidemiologic; D005260:Female; D006801:Humans; D007252:Influenza Vaccines / Q000008:administration & dosage* / Q000276:immunology*; D007251:Influenza, Human / Q000453:epidemiology* / Q000401:mortality / Q000517:prevention & control*; D053208:Kaplan-Meier Estimate; D007676:Kidney Failure, Chronic / Q000401:mortality / Q000628:therapy*; D008297:Male; D008875:Middle Aged; D016016:Proportional Hazards Models; D006435:Renal Dialysis; D012621:Seasons; D014481:United States / Q000453:epidemiology; D014611:Vaccination / Q000706:statistics & numerical data
chemical_list: D007252:Influenza Vaccines