In standard clinical trial designs, the required sample size is fixed in the planning stage based on initial parameter assumptions. It is intuitive that the correct choice of the sample size is of major importance for an ethical justification of the trial. The required parameter assumptions should be based on previously published results from the literature. In clinical practice, however, historical data often do not exist or show highly variable results. Adaptive group sequential designs allow a sample size recalculation after a planned unblinded interim analysis in order to adjust the sample size during the ongoing trial. So far, there exist no unique standards to assess the performance of sample size recalculation rules. Single performance criteria commonly reported are given by the power and the average sample size; the variability of the recalculated sample size and the conditional power distribution are usually ignored. Therefore, the need for an adequate performance score combining these relevant performance criteria is evident. To judge the performance of an adaptive design, there exist two possible perspectives, which might also be combined: Either the global performance of the design can be addressed, which averages over all possible interim results, or the conditional performance is addressed, which focuses on the remaining performance conditional on a specific interim result. In this work, we give a compact overview of sample size recalculation rules and performance measures. Moreover, we propose a new conditional performance score and apply it to various standard recalculation rules by means of Monte‐Carlo simulations.

中文翻译：

---

新的条件性能评分，用于通过重新计算样本量来评估自适应组顺序设计。

在标准临床试验设计中，根据初始参数假设，所需的样本量在计划阶段是固定的。直观地知道，样本数量的正确选择对于试验的伦理依据至关重要。所需的参数假设应基于先前发表的文献结果。但是，在临床实践中，历史数据通常不存在或显示出高度可变的结果。自适应组顺序设计允许在计划的无盲期中期分析之后重新计算样本量，以便在进行中的试验期间调整样本量。到目前为止，还没有唯一的标准来评估样本量重新计算规则的性能。通常报告的单个性能标准由功效和平均样本量给出；重新计算的样本大小的可变性和条件功率分布通常被忽略。因此，显然需要结合这些相关性能标准的适当性能评分。为了判断自适应设计的性能，有两种可能的观点，也可以将它们组合起来：要么可以解决设计的整体性能，即对所有可能的中期结果取平均值，要么解决有条件的性能，重点在于剩余表现取决于具体的中期结果。在这项工作中，我们简要概述了样本量的重新计算规则和性能指标。此外，我们提出了一个新的条件性能评分，并通过蒙特卡洛模拟将其应用于各种标准的重新计算规则。