Division of Clinical Epidemiology, Geneva University Hospitals, and Faculty of Medicine, University of Geneva, Geneva, Switzerland.
JAMA. 2023 Jun 20;329(23):2050-2056. doi: 10.1001/jama.2023.8549.
Many randomized clinical trials yield statistically nonsignificant results. Such results are difficult to interpret within the dominant statistical framework.
To estimate the strength of evidence in favor of the null hypothesis of no effect vs the prespecified effectiveness hypothesis among nonsignificant primary outcome results of randomized clinical trials by application of the likelihood ratio.
DESIGN, SETTING, AND PARTICIPANTS: Cross-sectional study of statistically nonsignificant results for primary outcomes of randomized clinical trials published in 6 leading general medical journals in 2021.
The likelihood ratio for the null hypothesis of no effect vs the effectiveness hypothesis stated in the trial protocol (alternate hypothesis). The likelihood ratio quantifies the support that the data provide to one hypothesis vs the other.
In 130 articles that reported 169 statistically nonsignificant results for primary outcomes, 15 results (8.9%) favored the alternate hypothesis (likelihood ratio, <1), and 154 (91.1%) favored the null hypothesis of no effect (likelihood ratio, >1). For 117 (69.2%), the likelihood ratio exceeded 10; for 88 (52.1%), it exceeded 100; and for 50 (29.6%), it exceeded 1000. Likelihood ratios were only weakly correlated with P values (Spearman r, 0.16; P = .045).
A large proportion of statistically nonsignificant primary outcome results of randomized clinical trials provided strong support for the hypothesis of no effect vs the alternate hypothesis of clinical efficacy stated a priori. Reporting the likelihood ratio may improve the interpretation of clinical trials, particularly when observed differences in the primary outcome are statistically nonsignificant.
许多随机临床试验得出的结果在统计学上并不显著。在占主导地位的统计框架内，很难解释这些结果。
通过应用似然比，估计在随机临床试验主要结局结果无统计学意义的情况下，支持无效假设与预先指定的有效性假设的证据强度。
设计、设置和参与者：这是一项横断面研究，研究了 2021 年 6 种主要普通医学期刊上发表的随机临床试验主要结局无统计学意义的结果。
无效假设与试验方案中规定的有效性假设（备择假设）的似然比。似然比量化了数据对一个假设的支持程度与另一个假设的支持程度。
在 130 篇报告了 169 项主要结局无统计学意义的结果的文章中，有 15 项结果（8.9%）支持备择假设（似然比<1），而 154 项（91.1%）支持无效应的无效假设（似然比>1）。对于 117 项（69.2%），似然比超过 10；对于 88 项（52.1%），超过 100；对于 50 项（29.6%），超过 1000。似然比与 P 值仅呈弱相关（Spearman r，0.16；P=0.045）。
大量随机临床试验的主要结局无统计学意义的结果强烈支持无效假设，而不是预先指定的临床疗效的备择假设。报告似然比可能会改善临床试验的解释，特别是当主要结局的观察差异在统计学上无显著差异时。
