Literature DB >> 23796295

Estimating the effectiveness of HPV vaccination in the open population: a Bayesian approach.

Willem Woertman1, Gert Jan van der Wilt.   

Abstract

OBJECTIVES: Estimation of the effectiveness of human papillomavirus (HPV) vaccination in the open population on the basis of published data from various sources.
METHODS: A Bayesian approach was used to reanalyze the data underlying a guidance by the Dutch National Health Insurance Board about the quadrivalent HPV vaccine Gardasil. Several studies document the vaccine's effectiveness in preventing cases in different subpopulations. None of these (sub)populations, however, is representative of the actual target population that the vaccination program will be applied to. We used a Bayesian approach for restructuring the data by means of reweighting the subpopulations by using HPV prevalence data, to estimate the effectiveness that can be expected in the actual target population.
RESULTS: The original data show an effectiveness of 44% in the entire population and an effectiveness of 98% for women who were compliant and were HPV-free at the start of the study. In the study population, the HPV prevalence was below 4%. In the relevant target population, however, the actual prevalence could be very different. In fact, some publications find an HPV prevalence of around 10%. We used Bayesian techniques to estimate the effectiveness in the actual target population. We found a mean effectiveness of 25%, and the probability that the effectiveness in the target population exceeds 50% is virtually zero. The results are very sensitive to the HPV prevalence that is used.
CONCLUSIONS: A supplementary analysis can put together the bits and pieces of information to arrive at more relevant answers. A Bayesian approach allows for integrating all the evidence into one model in a straightforward way and results in very intuitive probability statements.
Copyright © 2013 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

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Year:  2013        PMID: 23796295     DOI: 10.1016/j.jval.2013.01.001

Source DB:  PubMed          Journal:  Value Health        ISSN: 1098-3015            Impact factor:   5.725


  1 in total

1.  Bayesian Network Model to Evaluate the Effectiveness of Continuous Positive Airway Pressure Treatment of Sleep Apnea.

Authors:  Olli-Pekka Ryynänen; Timo Leppänen; Pekka Kekolahti; Esa Mervaala; Juha Töyräs
Journal:  Healthc Inform Res       Date:  2018-10-31
  1 in total

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