title: Novel health economic evaluation of a vaccination strategy to prevent HPV-related diseases: the BEST study.
abstract: BACKGROUND
  The development of human papillomavirus (HPV)-related diseases is not understood perfectly and uncertainties associated with commonly utilized probabilistic models must be considered. The study assessed the cost-effectiveness of a quadrivalent-based multicohort HPV vaccination strategy within a Bayesian framework.
  
  
  METHODS
  A full Bayesian multicohort Markov model was used, in which all unknown quantities were associated with suitable probability distributions reflecting the state of currently available knowledge. These distributions were informed by observed data or expert opinion. The model cycle lasted 1 year, whereas the follow-up time horizon was 90 years. Precancerous cervical lesions, cervical cancers, and anogenital warts were considered as outcomes.
  
  
  RESULTS
  The base case scenario (2 cohorts of girls aged 12 and 15 y) and other multicohort vaccination strategies (additional cohorts aged 18 and 25 y) were cost-effective, with a discounted cost per quality-adjusted life-year gained that corresponded to €12,013, €13,232, and €15,890 for vaccination programs based on 2, 3, and 4 cohorts, respectively. With multicohort vaccination strategies, the reduction in the number of HPV-related events occurred earlier (range, 3.8-6.4 y) when compared with a single cohort. The analysis of the expected value of information showed that the results of the model were subject to limited uncertainty (cost per patient = €12.6).
  
  
  CONCLUSIONS
  This methodological approach is designed to incorporate the uncertainty associated with HPV vaccination. Modeling the cost-effectiveness of a multicohort vaccination program with Bayesian statistics confirmed the value for money of quadrivalent-based HPV vaccination. The expected value of information gave the most appropriate and feasible representation of the true value of this program.
authors.affiliation: Department of Accounting and Finance, Kingston University, London, UK.
authors.forename: Giampiero
authors.initials: G
authors.lastname: Favato
authors.forename: Gianluca
authors.initials: G
authors.lastname: Baio
authors.forename: Alessandro
authors.initials: A
authors.lastname: Capone
authors.forename: Andrea
authors.initials: A
authors.lastname: Marcellusi
authors.forename: Silvano
authors.initials: S
authors.lastname: Costa
authors.forename: Giorgia
authors.initials: G
authors.lastname: Garganese
authors.forename: Mauro
authors.initials: M
authors.lastname: Picardo
authors.forename: Mike
authors.initials: M
authors.lastname: Drummond
authors.forename: Bengt
authors.initials: B
authors.lastname: Jonsson
authors.forename: Giovanni
authors.initials: G
authors.lastname: Scambia
authors.forename: Peter
authors.initials: P
authors.lastname: Zweifel
authors.forename: Francesco S
authors.initials: FS
authors.lastname: Mennini
mesh_terms: D000293:Adolescent; D000328:Adult; D001499:Bayes Theorem; D002648:Child; D003362:Cost-Benefit Analysis; D005260:Female; D006801:Humans; D008390:Markov Chains; D030361:Papillomavirus Infections / Q000191:economics* / Q000517:prevention & control*; D053918:Papillomavirus Vaccines / Q000008:administration & dosage* / Q000191:economics*; D019057:Quality-Adjusted Life Years; D012107:Research Design; D014611:Vaccination / Q000191:economics* / Q000379:methods; D055815:Young Adult
chemical_list: D053918:Papillomavirus Vaccines