Estimating the Effectiveness of HPV Vaccination in the Open Population: A Bayesian Approach

Value in Health                  
Vol 16 | No. 4 | June 2013 | Pages 453-698
http://www.valueinhealthjournal.com/current

Estimating the Effectiveness of HPV Vaccination in the Open Population: A Bayesian Approach
Willem Woertman, Gert Jan van der Wilt, PhD
published online 27 February 2013.

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.