Fabio Valeri: Sample Size Calculation for Malaria Vaccine Trials with Attributable Morbidity as Outcome

Adviser: Prof. Dr. Marloes Maathuis

August 2010

Abstract:

Malaria is a ma jor public health issue. Big efforts have been put into research to develop a vaccine against malaria. Problems arises in estimating vaccine efficacy. Standard methods as the cutoff method and logistic regression may have biased efficacy estimates. An alternative approach which avoid bias is to apply a Bayes latent class model to estimate attributable risk. One problem using this probabilistic approach is that it is not clear how big a trial would need to be in order to have comparable power to that of the cutoff method.

To assess the size of a trial using this approach a hypothetical parasite density of a population has been constructed based on a latent class model and some other constraints. Samples have been drawn from these true values, measurement errors simulated and vaccine efficacy estimated. This has been done for three different vaccine type mechanism.

For the vaccine we considered, to get a power of 80% the probabilistic method needs 3 to 12 times more individuals as in the cutoff method. Whereas the probabilistic has no biased efficacy estimates, two vaccine types have large or very large bias.

If vaccine type is not well defined standard methods to estimate vaccine efficacy could produce large biased estimates which can result in a rejection of the vaccine. The probabilistic approach would avoid bias but due to larger size for the same power the costs will be higher.

Download: PDF (912 KB)