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一种探索随机对照试验中主要结局的基线随机值报告中不平衡和潜在缺失模式的方法,以便进行荟萃分析。

An approach to exploring patterns of imbalance and potential missingness in reports of the randomized baseline values for primary outcomes measurable at baseline in randomized controlled trials for meta-analyses.

机构信息

Interdisciplinary Program in Medical Informatics, Seoul National University College of Medicine, Seoul, South Korea.

Department of Human Systems Medicine, Seoul National University College of Medicine, Seoul, South Korea.

出版信息

BMC Med Res Methodol. 2022 May 28;22(1):154. doi: 10.1186/s12874-022-01620-x.

Abstract

BACKGROUND

This study evaluated the adequacy of randomization in randomized controlled trials by investigating baseline differences in the primary outcome when a meta-analysis employed an outcome whose baseline level was measurable.

METHODS

We retrieved Cochrane reviews published during one year. We calculated the proportion of studies that reported randomized baseline values for the primary outcome. The standardized mean difference (SMD) was used to assess baseline imbalance and heterogeneity. We explored ranking-ordered forest plots using a normal cumulative probability curve as a guideline representing well-performed randomized trials. When skewness was suggested, a funnel plot was drawn to assess whether there was a significant linear trend.

RESULTS

In 10 of 18 meta-analyses, more than 25% of trials did not report randomized baseline values of the primary outcomes. Three meta-analyses indicated baseline imbalance (P < 0.1) and three showed substantial heterogeneity (I > 60%). Four meta-analyses with forest plots suggesting a skewed SMD distribution also showed a linear trend on their standard errors on the funnel plot.

CONCLUSIONS

If the primary outcome is measured at baseline, it is essential to explore the full scope of baseline imbalance among the trials. This could help understand patterns of bias, including missingness, for designing adjustment.

摘要

背景

本研究通过考察当荟萃分析采用基线水平可测量的结局指标时,主要结局指标的基线差异,评估随机对照试验中随机分组的充分性。

方法

我们检索了一年内发表的 Cochrane 综述。我们计算了报告主要结局指标随机基线值的研究比例。标准化均数差(SMD)用于评估基线不平衡和异质性。我们使用正态累积概率曲线作为指南,探索有序森林图,代表表现良好的随机试验。当出现偏度时,绘制漏斗图以评估是否存在显著的线性趋势。

结果

在 18 项荟萃分析中的 10 项中,超过 25%的试验未报告主要结局指标的随机基线值。3 项荟萃分析表明存在基线不平衡(P<0.01),3 项显示出显著的异质性(I>60%)。4 项具有森林图提示 SMD 分布偏态的荟萃分析,在漏斗图上的标准误差上也显示出线性趋势。

结论

如果主要结局指标在基线时进行测量,则必须探索试验中基线不平衡的全部范围。这有助于了解包括缺失在内的偏倚模式,以便进行调整设计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fa0/9148458/1b50279e26d0/12874_2022_1620_Fig1_HTML.jpg

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