Wang Y, Lang X Y, Zhu Y B, Liu X Y, Zhao Y Y, Li S D, Li W
Medical Research and Biometrics Center, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China.
Zhonghua Liu Xing Bing Xue Za Zhi. 2021 Jul 10;42(7):1280-1285. doi: 10.3760/cma.j.cn112338-20201015-01235.
Statistical significance plays an important role in the interpretation of clinical trial results. However, on the basis of obtaining statistical significance, the assessment of clinical significance is often neglected. This study attempted to propose a simple and unambiguous new classification method for study results, focusing on studies with statistical positive findings to evaluate whether the results have clinical significance. Our study subjects were the clinical studies in 2019 ACC and ESC annual meetings. Meta-epidemiology methods were used to extract the characteristic variable from each study. The primary evaluation indicators included target effect-size and observed effect-size. Based on the difference between the two indicators, the studies that had statistical significance were subdivided to identify studies with possible insufficient clinical significance; Furthermore, the theoretical threshold based on power analysis was proposed, which was used as the basis for the interpretation of study results. There were 12 clinical studies included in the final analysis. All of them were published on top journals. Those studies had relative high quality on both study design and reporting. The correlation coefficient between the observed and target effect-size was 0.892. Among the 7 studies with statistical significance, two of them were classified as insufficient clinical significance. The counts was 1 (1/3) and 1 (1/4) for the studies reported in ACC and ESC respectively. The achievement of clinical significance is critical even in the study with positive results. This paper proposes a new classification standard that combines clinical significance with statistical significance and further suggests a method to evaluate the reliability of clinical study results in order to assist researchers in identifying potential risks caused by insufficient clinical significance, and provide some reference and help for the reasonable interpretation of clinical study results.
统计学意义在临床试验结果的解释中起着重要作用。然而,在获得统计学意义的基础上,临床意义的评估常常被忽视。本研究试图针对研究结果提出一种简单明确的新分类方法,重点关注具有统计学阳性结果的研究,以评估结果是否具有临床意义。我们的研究对象是2019年美国心脏病学会(ACC)和欧洲心脏病学会(ESC)年会中的临床研究。采用元流行病学方法从每项研究中提取特征变量。主要评估指标包括目标效应量和观察到的效应量。基于这两个指标之间的差异,对具有统计学意义的研究进行细分,以识别临床意义可能不足的研究;此外,还提出了基于效能分析的理论阈值,作为研究结果解释的依据。最终分析纳入了12项临床研究。所有这些研究均发表于顶级期刊。这些研究在研究设计和报告方面都具有较高质量。观察到的效应量与目标效应量之间的相关系数为0.892。在7项具有统计学意义的研究中,有两项被归类为临床意义不足。ACC和ESC报道的研究中此类情况的数量分别为1(1/3)和1(1/4)。即使在结果为阳性的研究中,实现临床意义也至关重要。本文提出了一种将临床意义与统计学意义相结合的新分类标准,并进一步提出了一种评估临床研究结果可靠性的方法,以帮助研究人员识别由临床意义不足导致的潜在风险,并为临床研究结果的合理解释提供一些参考和帮助。