Misleading Use of I2 in Meta-Analysis
Author Information
Author(s): Gerta Rücker, Guido Schwarzer, James R. Carpenter, Martin Schumacher
Primary Institution: Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Germany
Hypothesis
I2 is of limited use in assessing clinically relevant heterogeneity in meta-analyses.
Conclusion
The clinical relevance of heterogeneity should guide decisions on pooling treatment estimates in meta-analyses, with τ2 being the appropriate measure.
Supporting Evidence
- I2 increases with the number of patients included in studies.
- I2 is interpreted as the percentage of variability due to heterogeneity rather than sampling error.
- The study used data from a large meta-analysis of 70 trials to illustrate findings.
Takeaway
When looking at studies, we should be careful about how we measure differences between them, as bigger studies can make it look like there are more differences than there really are.
Methodology
The study involved simulating sample size inflation in a meta-analysis to observe its effect on the I2 statistic.
Potential Biases
There may be a risk of misinterpretation of I2 leading to incorrect conclusions about the necessity of pooling studies.
Limitations
The study primarily focuses on statistical heterogeneity and does not address clinical baseline heterogeneity.
Participant Demographics
The study analyzed a sample of 157 meta-analyses with binary endpoints.
Statistical Information
P-Value
0.000
Confidence Interval
[0%; 40.1%]
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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