Modelling to extract more information from clinical trials data: On some roles for the bootstrap.
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.
Sauerbrei
Willi
W
Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Stefan-Meier-Strasse 26, 79104 Freiburg, Germany. wfs@imbi.uni-freiburg.de
Royston
Patrick
P
D000328:Adult; D000368:Aged; D000970:Antineoplastic Agents / Q000627:therapeutic use; D002986:Clinical Trials as Topic / Q000379:methods*; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D008875:Middle Aged; D015233:Models, Statistical; D010051:Ovarian Neoplasms / Q000188:drug therapy; D011379:Prognosis
D000970:Antineoplastic Agents