Gouraud Henri, Wallach Joshua D, Boussageon Rémy, Ross Joseph S, Naudet Florian
Inserm, CIC 1414 (Centre d'Investigation Clinique de Rennes), Rennes 1 University, Rennes, France.
Inserm, Irset (Institut de recherche en santé, environnement et travail), Rennes 1 University, Rennes, France.
BMJ Med. 2022 Sep 14;1(1):e000154. doi: 10.1136/bmjmed-2022-000154. eCollection 2022.
To evaluate the impact of conducting all possible pooled analyses across different combinations of randomised controlled trials and endpoints.
Multiverse analysis, consisting of numerous pooled analyses of individual participant data.
Individual patient data from 12 randomised controlled trials comparing canagliflozin treatment with placebo, shared on the Yale University Open Data Access project (https://yoda.yale.edu/) platform, up to 16 April 2021.
15 094 people with type 2 diabetes mellitus.
Pooled analyses estimated changes in serum glycated haemoglobin (HbA1c), major adverse cardiovascular events, and serious adverse events at weeks 12, 18, 26, and 52. The distribution of effect estimates was calculated for all possible combinations, and the direction and magnitude of the first and 99th centiles of effect estimates were compared.
Across 16 332 distinct pooled analyses comparing canagliflozin with placebo for changes in HbA1c, standardised effect estimates were in favour of canagliflozin treatment at both the first centile (-0.75%) and 99th centile (-0.48%); 15 994 (97.93%) analyses showed significant results (P<0.05) in favour of canagliflozin. For major adverse cardiovascular events, estimated hazard ratios were 0.20 at the first centile and 0.90 at the 99th centile; 2705 of 8144 analyses (33.21%) were significant, all of which were in favour of canagliflozin treatment. For serious adverse events, estimated hazard ratios were 0.59 at the first centile and 1.14 at the 99th centile; 5793 of 16 332 (35.47%) analyses were significant, with 5754 in favour of canagliflozin and 39 in favour of placebo.
Results from pooled analyses can be subject to vibration of effects and should be critically appraised, especially regarding the risk for selection and availability bias in individual participant data retrieved.
评估对随机对照试验和终点的不同组合进行所有可能的汇总分析的影响。
多宇宙分析，由对个体参与者数据的大量汇总分析组成。
截至2021年4月16日，来自耶鲁大学开放数据访问项目（https://yoda.yale.edu/）平台上12项比较卡格列净治疗与安慰剂的随机对照试验的个体患者数据。
15094例2型糖尿病患者。
汇总分析估计了第12、18、26和52周时血清糖化血红蛋白（HbA1c）、主要不良心血管事件和严重不良事件的变化。计算所有可能组合的效应估计值分布，并比较效应估计值第1百分位数和第99百分位数的方向和大小。
在16332项比较卡格列净与安慰剂对HbA1c变化的不同汇总分析中，标准化效应估计值在第1百分位数（-0.75%）和第99百分位数（-0.48%）均有利于卡格列净治疗；15994项（97.93%）分析显示有利于卡格列净的显著结果（P<0.05）。对于主要不良心血管事件，估计风险比在第1百分位数为0.20，在第99百分位数为0.90；8144项分析中的2705项（33.21%）具有显著性，所有这些均有利于卡格列净治疗。对于严重不良事件，估计风险比在第1百分位数为0.59，在第99百分位数为1.14；1633两万项分析中的5793项（35.47%）具有显著性，其中5754项有利于卡格列净，39项有利于安慰剂。
汇总分析的结果可能会受到效应波动的影响，应进行严格评估，尤其是在检索的个体参与者数据中存在选择和可得性偏倚的风险方面。
