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The value of the aggregate data approach in meta‐analysis with time‐to‐event outcomes
Author(s) -
Tudur Catrin,
Williamson Paula R.,
Khan Saboor,
Best Lesley Y.
Publication year - 2001
Publication title -
journal of the royal statistical society: series a (statistics in society)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.103
H-Index - 84
eISSN - 1467-985X
pISSN - 0964-1998
DOI - 10.1111/1467-985x.00207
Subject(s) - meta analysis , aggregate (composite) , aggregate data , event (particle physics) , statistic , computer science , event data , event study , econometrics , randomized controlled trial , value (mathematics) , statistics , data mining , medicine , mathematics , history , machine learning , analytics , composite material , materials science , physics , context (archaeology) , archaeology , surgery , quantum mechanics
Collecting individual patient data has been described as the ‘gold standard’ for undertaking meta‐analysis. If studies involve time‐to‐event outcomes, conducting a meta‐analysis based on aggregate data can be problematical. Two meta‐analyses of randomized controlled trials with time‐to‐event outcomes are used to illustrate the practicality and value of several proposed methods to obtain summary statistic estimates. In the first example the results suggest that further effort should be made to find unpublished trials. In the second example the use of aggregate data for trials where no individual patient data have been supplied allows the totality of evidence to be assessed and indicates previously unrecognized heterogeneity.