Zhou Xiaoqin, Ruan Weiqiang, Zhang Guiying, Liu Huizhen, Wang Ting, Li Jing, Du Liang, Huang Jin
Department of Cardiovascular Surgery, West China Hospital, Sichuan University, Chengdu, P.R. China.
Research Center of Clinical Epidemiology and Evidence-Based Medicine, West China Hospital, Sichuan University, Chengdu, P.R. China.
Ann Med. 2024 Dec;56(1):2427909. doi: 10.1080/07853890.2024.2427909. Epub 2024 Dec 3.
This study aims to assess the robustness of cardiovascular disease randomized controlled trials (RCTs) with primary continuous outcomes from a clinical perspective, utilizing the concepts of continuous fragility index (CFI), reverse continuous fragility index (RCFI) and their corresponding quotients (CFQ, RCFQ).
A cross-sectional study was conducted, searching PubMed for cardiovascular RCTs published between January 1, 2018, to December 31, 2022, in eight high-impact journals. Inclusion criteria were phase III or IV trials with 1:1 randomization, reporting at least one primary continuous outcome. Data analysis involved altering each outcome until achieving the reversal of significance (ɑ = 0.05) to determine the CFI or RCFI. The fragility quotients were then calculated by dividing the CFI or RCFI by the sample size, and Spearman's correlation assessed correlation analyses.
Of 3983 records were screened, and 64 RCTs (76 outcomes) were included. The fragility index was analysed with 72 outcomes. The overall median CFI was 7, with an associated median CFQ of 0.032. Nonsignificant values exhibited greater statistical instability (median RCFI = 5, RCFQ = 0.023) than significant values (median CFI = 14, CFQ = 0.062). Interestingly, "fragile" values were found in 36% (9/25) of CFI or 46.7% (7/15) of RCFI. Additionally, fragility index showed a significant association with several variables.
The findings suggest that changing only a small number of interventions (median of 7) could alter outcome significance. Reporting the fragility index alongside values is recommended to provide a clearer understanding of statistical findings' robustness.HighlightsThe continuous fragility index (CFI) represents the minimum patient count needed to modify significance by altering their intervention.Among 72 primary continuous outcomes in 64 cardiovascular RCTs, the overall median CFI was 7, with a corresponding CFQ of 0.032.CFI demonstrated moderate to strong correlations with sample size, total dropouts, and patient numbers analyzed.
本研究旨在从临床角度评估具有主要连续性结局的心血管疾病随机对照试验（RCT）的稳健性，运用连续脆弱性指数（CFI）、反向连续脆弱性指数（RCFI）及其相应商数（CFQ、RCFQ）的概念。
进行了一项横断面研究，在8种高影响力期刊中检索2018年1月1日至2022年12月31日发表的心血管RCT。纳入标准为III期或IV期试验，随机化比例为1:1，报告至少一项主要连续性结局。数据分析包括改变每个结局，直至达到显著性反转（ɑ = 0.05）以确定CFI或RCFI。然后通过将CFI或RCFI除以样本量来计算脆弱性商数，并进行Spearman相关性分析。
共筛选3983条记录，纳入64项RCT（76个结局）。对72个结局进行了脆弱性指数分析。总体CFI中位数为7，相应的CFQ中位数为0.032。非显著性值比显著性值表现出更大的统计不稳定性（RCFI中位数 = 5，RCFQ = 0.023）（CFI中位数 = 14，CFQ = 0.062）。有趣的是，在36%（9/25）的CFI或46.7%（7/15）的RCFI中发现了“脆弱”值。此外，如果脆弱性指数与几个变量存在显著关联。
研究结果表明，仅改变少量干预措施（中位数为7）就能改变结局的显著性。建议在报告P值的同时报告脆弱性指数，以便更清楚地了解统计结果的稳健性。要点连续脆弱性指数（CFI）表示通过改变干预来改变显著性所需的最小患者数量。在64项心血管RCT的72个主要连续性结局中，总体CFI中位数为7，相应的CFQ为0.032。CFI与样本量、总失访率和分析的患者数量呈中度至强相关性。
