The use of gatekeeping procedures in the statistical planning of animal experiments

Statistical sample size calculation is essential when planning animal experiments in basic medical research. Usually, such trials involve the testing of multiple hypotheses, and interpreting them in a confirmative manner would require the appropriate adjustment of the Type 1 error. This has to be taken into account as early as possible during sample size estimation - otherwise, all the results obtained would be exploratory, i.e. without cogency. In this paper, the concept of gatekeeping is introduced, along with alternative approaches for Type 1 error adjustment. The application of gatekeeping to the calculation of sample size is demonstrated by using data sets from case studies. Overall, the evaluation of these examples showed that gatekeeping is able to keep the required number of animals comparatively small. In contrast to exploratory planning, which led to the lowest sample sizes, gatekeeping suggested a mean increase of 12% in sample size, while conservative Bonferroni adjustment raised the sample size by 34% on average. Gatekeeping is a prominent strategy for handling the multiple testing problem, and has been proven to keep the required sample sizes in animal studies comparatively low. Therefore, it is a suitable approach to a compromise between the Three Rs principle of reduction and the appropriate handling of the multiplicity issue in animal trials with a confirmative focus.