Integrated planning of pilot studies and confirmatory studies in clinical research

在临床研究中，经常进行先导性研究，以获得有关新疗法的治疗效果的信息。根据结果，决定是否进行随后的验证性试验，如果答案是肯定的，则在计算样本量时假定哪种处理效果。目前确定先导研究样本量的现有方法显示出严重的缺点。一类程序是基于特别规则，而这些规则不能用量化标准来证明是合理的。作为一种替代方法，试点研究的样本量与验证性试验的样本量确定类似，但由于可行性考虑，第一类和第二类错误率的值较高。然而，这与先导研究的非验证性严格背道而驰。另一个缺陷在于，在确定试点的样本量时，文献中提出的方法都没有考虑随后的验证性试验和项目的总体样本量。计划中的项目旨在为广泛的设计方案制定综合规划试点和验证性研究的方法。新方法允许根据确定的参数值和样本大小确定成功的总体计划(试点研究+验证性研究)的概率。此外，还构造了效用函数，包括执行程序所需的资源以及在程序成功的情况下的收益。通过最大化期望效用，得到了用于试点研究的最优决策规则和最优样本量。应用这项研究的结果将允许规划研究计划，以最佳地平衡成本和收益。

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.