Abstract
Many of the reservations that might attach to the use of meta-analysis generally (for example, regarding publication bias) do not apply in the specific context of drug development. A meta-analysis is, in fact, a highly natural and appropriate way to summarize the results of a drug development program, as has been recognized in the International Conference on Harmonization (ICH) E9 guideline. Since a sponsor will have access to all original data, the data from a set of clinical trials in a drug development program have a very similar (hierarchical) structure to the data from a set of centers in a single multicenter trial. Curiously, however, the controversies over analyzing multicenter trials have often been different from those in the field of meta-analysis. In this paper, the options open to the meta-analyst in drug development are examined and comparisons to approaches used in analyzing multicenter trials are made in an attempt to provide some unifying insights, in particular as regards the handling of models with interactions.
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