本文由小咖机器人翻译整理

期刊来源：JAMA

文献发表时间：2023-06-20

原文链接：https://jamanetwork.com/journals/jama/article-abstract/2806151

关键点内容如下：

问题

随机临床试验的无统计学意义的结果能否提供新疗法无效的确凿证据？

调查结果

在2021年发表的随机试验的169个统计学上无意义的主要结果结果中，使用似然比来比较缺乏效果的假设（零假设）和临床上有意义的有效性的假设（替代假设），以量化观察到的试验结果为一种假设与另一种假设提供的支持强度。大约一半（52.1%）的人得出了缺乏效应的零假设与替代假设的似然比超过100。

意义

许多统计学上不显著的临床试验结果证明了新疗法缺乏效果的确凿证据。

摘要内容如下：

重要性

许多随机临床试验产生了统计学上不显著的结果。这样的结果很难在主流统计框架内进行解释。

研究对象

在随机临床试验的非显著主要结果结果中，通过应用似然比来估计支持无效假设与预先指定的有效性假设的证据强度。

2021年发表在6种主要普通医学期刊上的随机临床试验主要结果的统计学上无显著性结果的横断面研究。

成果指标

试验方案中规定的无效假设与有效性假设的似然比（替代假设）。似然比量化了数据对一个假设与另一个假设的支持。

结果

在130篇报道169个主要结果在统计学上不显著的文章中，15个结果（8.9%）支持替代假设（似然比＜1），154个结果（91.1%）支持无效假设（似然率＞1）。117人（69.2%）的可能性比率超过10；88例（52.1%）超过100例；50人（29.6%）超过1000人。似然比仅与P值呈弱相关（Spearman r，0.16；P = .045中）。

结论

随机临床试验的大部分无统计学意义的主要结果结果为无影响假设与先验陈述的临床疗效替代假设提供了强有力的支持。报告似然比可以改善临床试验的解释，特别是当主要结果中观察到的差异在统计学上不显著时。

英文原文如下：

Key Points

Question  Can a statistically nonsignificant result of a randomized clinical trial provide conclusive evidence of lack of effect of the new treatment?

Findings  Among 169 statistically nonsignificant primary outcome results of randomized trials published in 2021, the hypotheses of lack of effect (null hypothesis) and of clinically meaningful effectiveness (alternate hypothesis) were compared using a likelihood ratio to quantify the strength of support the observed trial findings provide for one hypothesis vs the other; about half (52.1%) yielded a likelihood ratio of more than 100 for the null hypothesis of lack of effect vs the alternate.

Meaning  Many statistically nonsignificant clinical trial results demonstrate conclusive evidence of lack of effect of the new treatment.

Abstract

Importance  Many randomized clinical trials yield statistically nonsignificant results. Such results are difficult to interpret within the dominant statistical framework.

Objective  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.

Outcome measures  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.

Results  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).

Conclusions  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.