Large trials vs meta-analysis of smaller trials: how do their results compare?
OBJECTIVE
To evaluate the results of large clinical trials vs the pooled results of smaller trials.


METHODS
Meta-analyses with at least 1 "large" study were identified from the Cochrane Pregnancy and Childbirth Database and from MEDLINE (1966-1995).


METHODS
We used a sample size approach to select 79 meta-analyses with at least 1 large study of 1000 or more patients. We used a statistical power approach to select 61 meta-analyses with at least 1 large study based on statistical power considerations.


METHODS
The outcome of interest for each meta-analysis was the primary one stated in the original publication or, when not clearly specified, was decided on clinically.


RESULTS
By random effects calculations, we found agreement between large and smaller trials in 90% of the meta-analyses selected by the sample size approach and in 82% of the meta-analyses selected by the statistical power approach. Twice as many disagreements appeared when the variability among large studies and among smaller studies was not considered (ie, fixed effects calculations). Of the 15 disagreements between results of large and smaller trials using the random effects model, plausible explanations were identified in 10 meta-analyses: 5 with differences in the control rate of events between large and smaller trials, 4 with specific protocol or study differences, and 1 with potential publication bias. Two other disagreements were not clinically important, and tentative reasons could be identified for 2 of the remaining 3 disagreements.


CONCLUSIONS
Results of smaller studies are usually compatible with the results of large studies, but discrepancies do occur even when the diversity among both large studies and smaller studies is considered. Clinically important differences without a potential explanation are extremely uncommon. Future research should further examine sources of heterogeneity between the results of large and smaller trials.
Cappelleri
J C
JC
Division of Clinical Care Research, New England Medical Center, Boston, Mass. 02111, USA.
Ioannidis
J P
JP
Schmid
C H
CH
de Ferranti
S D
SD
Aubert
M
M
Chalmers
T C
TC
Lau
J
J
D015982:Bias; D002986:Clinical Trials as Topic; D003627:Data Interpretation, Statistical; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D012044:Regression Analysis