Department of Anesthesiology and Pain Medicine, Dongguk University Ilsan Hospital, Goyang, Korea.
Korean J Anesthesiol. 2024 Jun;77(3):316-325. doi: 10.4097/kja.23630. Epub 2024 Apr 29.
The statistical significance of a clinical trial analysis result is determined by a mathematical calculation and probability based on null hypothesis significance testing. However, statistical significance does not always align with meaningful clinical effects; thus, assigning clinical relevance to statistical significance is unreasonable. A statistical result incorporating a clinically meaningful difference is a better approach to present statistical significance. Thus, the minimal clinically important difference (MCID), which requires integrating minimum clinically relevant changes from the early stages of research design, has been introduced. As a follow-up to the previous statistical round article on P values, confidence intervals, and effect sizes, in this article, we present hands-on examples of MCID and various effect sizes and discuss the terms statistical significance and clinical relevance, including cautions regarding their use.
临床试验分析结果的统计学意义是通过基于零假设显著性检验的数学计算和概率来确定的。然而,统计学意义并不总是与有意义的临床效果一致;因此,将统计学意义与临床相关性联系起来是不合理的。将具有临床意义差异的统计学结果结合起来是一种更好的方法来呈现统计学意义。因此,最小临床重要差异(MCID)已经被引入,它需要从研究设计的早期阶段整合最小的临床相关变化。作为之前关于 P 值、置信区间和效应大小的统计轮次文章的后续,在本文中,我们提供了 MCID 和各种效应大小的实际示例,并讨论了统计学意义和临床相关性这两个术语,包括使用它们时的注意事项。