To the Editor: Dr Ioannidis and colleagues
performed a meta-analysis of previously published meta-analyses to address
the results of randomized vs nonrandomized studies.1
For clinicians who are not familiar with this method, a number of questions
are likely to arise.
First, do meta-analyses yield reliable results? If so, this implies
that biases of various studies cancel each other out through meta-analysis.
Is this assumption generally accepted? Second, how does meta-analysis avoid
compounding previous errors, especially in an environment in which peer influence
is considerable? It appears that a meta-analysis may serve only to make scientists
aware of their colleagues' research and may not substitute for original work.
In this case, what does a meta-analysis of meta-analyses stand for? The meta-analyses
presented by the authors originate from a small spectrum of medical specialties
and institutions. They are certainly neither random in their inception nor
cross-sectional in their representation. Is it possible that meta-analyses
ad infinitum only perpetuate or even amplify faults of the original studies?
Finally, was all this analysis really worth the effort just to reach the conclusion
that there are discrepancies between randomized and nonrandomized studies?
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