Abstract
BackgroundIndividual participant data (IPD) meta-analyses that obtain “raw” data from studies rather than summary data typically adopt a “two-stage” approach to analysis whereby IPD within trials generate summary measures, which are combined using standard meta-analytical methods. Recently, a range of “one-stage” approaches which combine all individual participant data in a single meta-analysis have been suggested as providing a more powerful and flexible approach. However, they are more complex to implement and require statistical support. This study uses a dataset to compare “two-stage” and “one-stage” models of varying complexity, to ascertain whether results obtained from the approaches differ in a clinically meaningful way.Methods and FindingsWe included data from 24 randomised controlled trials, evaluating antiplatelet agents, for the prevention of pre-eclampsia in pregnancy. We performed two-stage and one-stage IPD meta-analyses to estimate overall treatment effect and to explore potential treatment interactions whereby particular types of women and their babies might benefit differentially from receiving antiplatelets. Two-stage and one-stage approaches gave similar results, showing a benefit of using anti-platelets (Relative risk 0.90, 95% CI 0.84 to 0.97). Neither approach suggested that any particular type of women benefited more or less from antiplatelets. There were no material differences in results between different types of one-stage model.ConclusionsFor these data, two-stage and one-stage approaches to analysis produce similar results. Although one-stage models offer a flexible environment for exploring model structure and are useful where across study patterns relating to types of participant, intervention and outcome mask similar relationships within trials, the additional insights provided by their usage may not outweigh the costs of statistical support for routine application in syntheses of randomised controlled trials. Researchers considering undertaking an IPD meta-analysis should not necessarily be deterred by a perceived need for sophisticated statistical methods when combining information from large randomised trials.
Highlights
Individual participant data (IPD) systematic review and metaanalysis in which the original ‘‘raw’’ data from each participant in the relevant trials are centrally collected, checked, re-analysed and combined [1,2], is considered to be a gold standard approach to evidence synthesis
For these data, two-stage and one-stage approaches to analysis produce similar results
One-stage models offer a flexible environment for exploring model structure and are useful where across study patterns relating to types of participant, intervention and outcome mask similar relationships within trials, the additional insights provided by their usage may not outweigh the costs of statistical support for routine application in syntheses of randomised controlled trials
Summary
Individual participant data (IPD) systematic review and metaanalysis in which the original ‘‘raw’’ data from each participant in the relevant trials are centrally collected, checked, re-analysed and combined [1,2], is considered to be a gold standard approach to evidence synthesis. In the second stage these results from each trial are combined across trials using conventional meta-analytical methods [6,7].The two-stage approach is relatively straightforward to implement, and produces interpretable and communicable results for those familiar with meta-analyses of aggregate data. Individual participant data (IPD) meta-analyses that obtain ‘‘raw’’ data from studies rather than summary data typically adopt a ‘‘two-stage’’ approach to analysis whereby IPD within trials generate summary measures, which are combined using standard meta-analytical methods. A range of ‘‘one-stage’’ approaches which combine all individual participant data in a single meta-analysis have been suggested as providing a more powerful and flexible approach. They are more complex to implement and require statistical support. This study uses a dataset to compare ‘‘two-stage’’ and ‘‘one-stage’’ models of varying complexity, to ascertain whether results obtained from the approaches differ in a clinically meaningful way
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