Modelling to extract more information from clinical trials data: On some roles for the bootstrap

Abstract

Despite its importance in the theoretical literature, the bootstrap appears to play a negligible role in pharmaceutical research, as will be demonstrated by a brief literature review. As will be shown by examples, the bootstrap is a useful tool in the planning and analysis of clinical trials. The first example shows that some important information required in the design of a study can best be gained by using the bootstrap. It is argued from two further examples that more information can be extracted from large clinical trials by data-dependent modelling. This is shown by identifying a prognostic factor that may play a role as an inclusion criterion of a new study and by an interaction of a continuous predictor with treatment. To protect against erroneous conclusions from data-dependent modelling in a multivariable context, detailed checks of the results and stability analyses should be performed by the bootstrap. To conclude, a discussion of the future of modelling and the future of the bootstrap is given.