Making too much of too little
We were pleased to see that Nuesch and colleagues examined the effect
of small studies in meta-analyses of osteoarthritis trials . The
conclusion, that small study effects can distort results of meta-analyses,
is not particularly new . For example, in a large analysis of mortality
in patients experiencing a gastrointestinal bleed or perforation, the
event rate in smaller studies with fewer than 200 cases each was often
markedly different from the event rate in larger studies with many more
More important than this, though, is not the potential for distortion
of small trials in a meta-analysis that contains larger trials, but the
potential for getting the wrong answer completely in a meta-analysis that
contains ONLY small trials. The potential for the random play of chance to
have big effects when the number of events is fewer than 200 has also been
pointed out before [4-6], and the propensity for meta-analysis of small
trials to produce misleading results is contained in a much-cited recent
The problem, of course, is that many, if not most, meta-analyses are
comprised of small trials and even in aggregate they do not amount to
sufficient numbers from which to draw conclusions even if everything else
were perfect. Our experience is that whether one looks at complementary
therapies like acupuncture , or conventional therapies in difficult
situations like palliative care , too much is often made of too little.
The time is long past when meta-analyses of small studies can be
allowed to reach conclusions without pointing out the hole at the heart of
their analysis - too little information to be sure of a result. One
approach would be to agree a minimum number of events - beneficial and
harmful - below which a result cannot be trusted. Two hundred events is a
useful rule of thumb for believability. Size is an important source of
bias that needs to be considered alongside study quality and validity, as
we have recently suggested . Size is not routinely covered in the
Cochrane risk of bias table; perhaps it should be.
The focus on events has one further benefit in pain studies: it
concentrates on clinically useful outcomes, particularly important where
the distribution of results is anything but Gaussian, where the average
result is obtained by few, and where substantial duration bias is known
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DG, Egger M, Juni P. Small study effects in meta-analyses of
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McQuay H; for the ACTINPAIN writing group of the IASP Special Interest
Group (SIG) on Systematic Reviews in Pain Relief and the Cochrane Pain,
Palliative and Supportive Care Systematic Review Group editors. "Evidence"
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Competing interests: No competing interests