Integrated planning of pilot studies and confirmatory studies in clinical research

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In clinical research, pilot studies are frequently performed to obtain information about the treatment effect of a new therapy. On the basis of the results, it is decided whether to perform a subsequent confirmatory trial and, if the answer is positive, which treatment effect is assumed for sample size calculation. Currently available methods for determining the sample size of a pilot study show severe disadvantages. One class of procedures is based on ad hoc rules that are not justified by quantitative criteria. As an alternative approach, the sample size of the pilot study is determined analogously to that of confirmatory trials but, due to feasibility considerations, with higher values for the type I and type II error rate. This, however, strictly contradicts to the non-confirmatory nature of pilot studies. A further deficit lies in the fact that none of the methods proposed in the literature takes the subsequent confirmatory trial and the overall sample size for the program into account when fixing the sample size of the pilot. The planned project intends to develop methods for an integrated planning of pilot and confirmatory study for a broad range of design scenarios. The new methods allow determining the probability of a successful overall program (pilot study + confirmatory study) depending on defined parameter values and sample sizes. Furthermore, utility functions are constructed including the required resources for performing the program as well as the gains in case of a successful program. By maximizing the expected utility, optimal decision rules and optimal sample sizes for pilot studies are derived. Applying the results of this research will allow for a planning of study programs that optimally balances costs and gains.