In clinical research, power analysis is often performed for sample size calculation. The purpose is to achieve a desired power of correctly detecting a clinically meaningful difference at a pre-specified level of significance if such a difference truly exists. However, in some situations such as (i) clinical trials with extremely low incidence rates and (ii) for rare disease drug development clinical trials, power analysis for sample size calculation may not be feasible because (i) it may require a huge sample size for detecting a relatively small difference and (ii) eligible patients may not be available for a small target patient population. In these cases, other procedures for sample size determination with certain statistical assurance are needed. In this article, an innovative method based on a probability monitoring procedure is proposed for sample size determination. The concept is to select an appropriate sample size for controlling the probability of crossing safety and/or efficacy boundaries. For rare disease clinical development, an adaptive probability monitoring procedure may be applied if a multiple-stage adaptive trial design is used.

在临床研究中，通常进行功效分析以计算样本量。目的是获得期望的能力，以在预先指定的显着性水平上正确检测临床上有意义的差异（如果确实存在这种差异）。但是，在某些情况下，例如（i）发生率极低的临床试验和（ii）罕见病药物开发临床试验，用于样本量计算的功效分析可能不可行，因为（i）可能需要大量的样本用于检测相对较小的差异，并且（ii）合格的患者可能不适用于较小的目标患者群体。在这些情况下，需要其他具有一定统计保证的确定样本量的程序。在这篇文章中，提出了一种基于概率监测程序的创新方法来确定样本量。概念是选择合适的样本量，以控制跨越安全性和/或功效边界的可能性。对于罕见疾病的临床发展，如果使用了多阶段自适应试验设计，则可以应用自适应概率监测程序。