Background: Process-of-care time measures provide vital information about hyperacute stroke interventions. These measures are often highly skewed, and relevant mean-based statistics may be misleading. Percentile-based statistics (e.g. median) conveniently and unbiasedly summarise the proportion of patients treated within a given timeframe. Despite this, mean-based synthesis methods are primarily recommended by the Cochrane Handbook for Systematic Reviews of Interventions for conducting meta-analyses. It’s also recommended that percentile-based outcomes are either excluded from meta-analyses or included by imputing mean-based measures using transformation methods.
Aims: To provide methodological foundation for the appropriate meta-analysis of process-of-care time measures in hyperacute stroke systematic reviews and meta-analyses.
Methods: We evaluated the performance of transformation-based methods using process-of-care time data from hyperacute stroke clinical trials of thrombolysis, thrombectomy and MSU interventions. We also compared the performance of various mean- and percentile-based meta-analysis techniques for process-of-care time measures.
Results: Transformation-based methods showed strong agreement in estimating the true mean from different sets of percentile-based summary statistics (LCCC = 0.9987). These methods became less reliable as the skew of the underlying distribution increased. Mean-based and percentile-based meta-analysis methods provided comparable results when analysing summary measures of between-arm treatment effects and varied results when analysing individual-arm summary measures.
Conclusion: As the observed variability affects the interpretability of the results, we recommend that stroke researchers utilise percentile-based approaches for the reporting, analysis, and meta-analysis of process-of-care time measures in hyperacute stroke studies.