National Institute of Public Health, University of Southern Denmark, Studiestræde 6, DK-1455, Copenhagen K, Denmark.
Department of Nutrition, Exercise and Sports, University of Copenhagen, Rolighedsvej 26, DK-1958, Frederiksberg C, Denmark.
Eur J Clin Nutr. 2022 Dec;76(12):1682-1689. doi: 10.1038/s41430-022-01169-4. Epub 2022 Jul 8.
In nutrition research, sample size calculations for continuous outcomes are important for the planning phase of many randomized trials and could also be relevant for some observational studies such as cohort and cross-sectional studies. However, only little literature dedicated to this topic exists within nutritional science. This article reviews the most common methods for sample size calculations in nutrition research. Approximate formulas are used for explaining concepts and requirements and for working through examples from the literature. Sample size calculations for the various study designs, which are covered, may all be seen as extensions of the sample size calculation for the basic two-group comparison through the application of suitable scaling factors and, possibly, modification of the significance level. The latter is needed for sample size calculations for multi-group designs and designs involving multiple primary outcomes. Like cluster-randomized designs, these types of study designs may be more challenging than standard sample size calculations. In such non-standard scenarios, there may be a need for consulting a biostatistician. Finally, it should be stressed that there may be many ways to plan a study. The final sample size calculation provided for a grant applicant, study protocol, or publication will often not only depend on considerations and input information as described in this article but will also involve restrictions in terms of logistics and/or resources.
在营养研究中，连续结局的样本量计算对于许多随机试验的规划阶段很重要，对于一些观察性研究（如队列研究和横断面研究）也可能相关。然而，营养科学领域对此主题的文献很少。本文综述了营养研究中样本量计算的最常用方法。近似公式用于解释概念和要求，并通过文献中的示例进行说明。所涵盖的各种研究设计的样本量计算都可以被视为通过应用适当的缩放因子和（可能）修改显著性水平，对基本的两比较组样本量计算的扩展。对于多组设计和涉及多个主要结局的设计，需要进行后者的样本量计算。与集群随机设计一样，这些类型的研究设计可能比标准的样本量计算更具挑战性。在这种非标准情况下，可能需要咨询生物统计学家。最后，应该强调的是，可能有很多方法可以计划研究。为赠款申请人、研究方案或出版物提供的最终样本量计算不仅将取决于本文所述的考虑因素和输入信息，还将受到后勤和/或资源方面的限制。
