title: Relationship between haemagglutination-inhibiting antibody titres and clinical protection against influenza: development and application of a bayesian random-effects model.
abstract: BACKGROUND
  Antibodies directed against haemagglutinin, measured by the haemagglutination inhibition (HI) assay are essential to protective immunity against influenza infection. An HI titre of 1:40 is generally accepted to correspond to a 50% reduction in the risk of contracting influenza in a susceptible population, but limited attempts have been made to further quantify the association between HI titre and protective efficacy.
  
  
  METHODS
  We present a model, using a meta-analytical approach, that estimates the level of clinical protection against influenza at any HI titre level. Source data were derived from a systematic literature review that identified 15 studies, representing a total of 5899 adult subjects and 1304 influenza cases with interval-censored information on HI titre. The parameters of the relationship between HI titre and clinical protection were estimated using Bayesian inference with a consideration of random effects and censorship in the available information.
  
  
  RESULTS
  A significant and positive relationship between HI titre and clinical protection against influenza was observed in all tested models. This relationship was found to be similar irrespective of the type of viral strain (A or B) and the vaccination status of the individuals.
  
  
  CONCLUSIONS
  Although limitations in the data used should not be overlooked, the relationship derived in this analysis provides a means to predict the efficacy of inactivated influenza vaccines when only immunogenicity data are available. This relationship can also be useful for comparing the efficacy of different influenza vaccines based on their immunological profile.
authors.affiliation: Sanofi pasteur, 2 avenue Pont Pasteur F-69367 Lyon cedex 07 France. laurent.coudeville@sanofipasteur.com
authors.forename: Laurent
authors.initials: L
authors.lastname: Coudeville
authors.forename: Fabrice
authors.initials: F
authors.lastname: Bailleux
authors.forename: Benjamin
authors.initials: B
authors.lastname: Riche
authors.forename: Françoise
authors.initials: F
authors.lastname: Megas
authors.forename: Philippe
authors.initials: P
authors.lastname: Andre
authors.forename: René
authors.initials: R
authors.lastname: Ecochard
mesh_terms: D000328:Adult; D000914:Antibodies, Viral / Q000097:blood*; D001499:Bayes Theorem; D006388:Hemagglutinins / Q000276:immunology*; D006801:Humans; D007251:Influenza, Human / Q000276:immunology*; D008962:Models, Theoretical
chemical_list: D000914:Antibodies, Viral; D006388:Hemagglutinins