Miller Frank, Zohar Sarah, Stallard Nigel, Madan Jason, Posch Martin, Hee Siew Wan, Pearce Michael, Vågerö Mårten, Day Simon
Department of Statistics, Stockholm University, Stockholm, Sweden.
INSERM, U1138, Team 22, Centre de Recherche des Cordeliers, Université Paris 5, Université Paris 6, Paris, France.
Pharm Stat. 2018 May;17(3):214-230. doi: 10.1002/pst.1848. Epub 2018 Jan 10.
We discuss 3 alternative approaches to sample size calculation: traditional sample size calculation based on power to show a statistically significant effect, sample size calculation based on assurance, and sample size based on a decision-theoretic approach. These approaches are compared head-to-head for clinical trial situations in rare diseases. Specifically, we consider 3 case studies of rare diseases (Lyell disease, adult-onset Still disease, and cystic fibrosis) with the aim to plan the sample size for an upcoming clinical trial. We outline in detail the reasonable choice of parameters for these approaches for each of the 3 case studies and calculate sample sizes. We stress that the influence of the input parameters needs to be investigated in all approaches and recommend investigating different sample size approaches before deciding finally on the trial size. Highly influencing for the sample size are choice of treatment effect parameter in all approaches and the parameter for the additional cost of the new treatment in the decision-theoretic approach. These should therefore be discussed extensively.
基于显示统计学显著效应的功效的传统样本量计算、基于保证率的样本量计算以及基于决策理论方法的样本量计算。在罕见病的临床试验情况下，对这些方法进行了直接比较。具体而言，我们考虑了3个罕见病的案例研究（莱尔病、成人斯蒂尔病和囊性纤维化），目的是为即将进行的临床试验规划样本量。我们详细概述了针对这3个案例研究中每种方法的参数合理选择，并计算了样本量。我们强调，在所有方法中都需要研究输入参数的影响，并建议在最终确定试验规模之前研究不同的样本量方法。在所有方法中，治疗效果参数的选择以及决策理论方法中新治疗额外成本的参数对样本量有很大影响。因此，应该对此进行广泛讨论。
