SynthesisBMC medical research methodology2022
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.
Synthesis in BMC medical research methodology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis 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.
methodsWe 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.
resultsIn 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
conclusionsIf 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.
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