Sample sizes and negative studies in clinical vaccine research.
Sample sizes and negative studies in clinical vaccine research.
复制标题
临床疫苗研究中的样本量和阴性研究。
DOI：
10.1016/j.vaccine.2005.01.029
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发表时间：
2005
期刊：
影响因子：
5.5
通讯作者：
Poland,GregoryA
中科院分区：
文献类型：
--
作者：
Jacobson,RobertM;Poland,GregoryA
在已发表的文献中，疫苗不良事件的阴性研究以一定的频率出现。它们在抵御反疫苗运动提出的主张和加强预防疾病的公共卫生努力方面发挥着重要作用。尽管如此，负面研究经常受到足够的样本量的关注。现在流行的用于样本量计算的双显著性Neyman-Pearson公式导致巨大的样本量，这可能导致不合逻辑的解释。已故教授阿尔万·R。定量临床流行病学之父范斯坦提出了一种更符合逻辑的方法，可以减少混乱，并要求更适度的样本量。了解样本量计算中涉及的问题对设计临床疫苗研究的人很重要。计算的影响对可行性因素有深远的影响，例如研究的费用、招募足够人数的能力，甚至研究是否会进行。
Negative studies of vaccine adverse events occur with some frequency in the published literature. They serve important roles in fending off claims posed by the anti-vaccine movement and in reinforcing public health efforts to prevent diseases. Still, negative studies frequently suffer from concerns of adequate sample size. The double-significance Neyman–Pearson formula for sample size calculation that is now in vogue results in immense sample sizes that can lead to illogical interpretations. The late Professor Alvan R. Feinstein, the father of quantitative clinical epidemiology, proposed a more logical approach that would reduce the confusion and call for more moderate sample sizes. Understanding the issues involved in sample size calculations is important to those who design clinical vaccine studies. The implications of the calculations have far-reaching effects upon elements of feasibility such as the expense of the study, the ability to recruit adequate numbers, and even whether the study will be done at all.