LUO Minjing 1,2,3,4 , LIU Zhihan 1,2,3,4 , HUANG Jinghan 4 , WANG Yingqiao 4 , LI Yilin 4 , LIU Meijun 1,2,3,4 , TAO Yunci 1,2,3,4 , CAO Rui 1,2,3,4 , WANG Yaqi 1,2,3,4 , LIU Jianping 1,2,3,4 , ZHANG Ying 1,2,3,4 , FEI Yutong 1,2,3,4
  • 1. Centre for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100029, P. R. China;
  • 2. International Institute of Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100029, P. R. China;
  • 3. Beijing GRADE Center, Beijing 100029, P. R. China;
  • 4. Beijing University of Chinese Medicine, Beijing 100029, P. R. China;
FEI Yutong, Email: feiyt@bucm.edu.cn
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After the completion of a clinical trial, its conclusion generally depends on the results of statistical analysis of the main outcome, that is, whether the P-value in the hypothesis test is less than the α level of the hypothesis test, usually α=0.05. The size of the P-value indicates the sufficient degree of reason for making the hypothesis judgment, and can be interpreted as to determine whether a conclusion is statistically significant but does not involve the difference in the degree of drug effects or other effects. Fragility index, which is, the minimum number of patients required to change the occurrence of a target outcome event to a non-target outcome event from a statistically significant outcome to a non-significant outcome, can be used to assist in understanding of clinical trial statistical inference results and assisting in clinical decision making This paper discusses the concept, calculation method and clinical application of the fragility index, and recommends that the fragility index be routinely reported in all future randomized controlled trials to help patient clinicians and policymakers make appropriate and optimal decisions.

Citation: LUO Minjing, LIU Zhihan, HUANG Jinghan, WANG Yingqiao, LI Yilin, LIU Meijun, TAO Yunci, CAO Rui, WANG Yaqi, LIU Jianping, ZHANG Ying, FEI Yutong. Fragility index for assessing the robustness of randomized controlled trials. Chinese Journal of Evidence-Based Medicine, 2024, 24(2): 243-248. doi: 10.7507/1672-2531.202307022 Copy

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