Combining aggregate data and individual patient data in meta-analysis: an alternative method
It has been shown that, in cases where both the AD and IPD studies are available, combining these two levels of data could improve the overall meta-analysis estimates, compared to utilizing AD studies alone. However, the coverage probability of estimates based on combined studies are relatively l...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Global Research and Development Services Publishing
2015
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/57179/ http://irep.iium.edu.my/57179/ http://irep.iium.edu.my/57179/ http://irep.iium.edu.my/57179/1/GRDS.conf.2015.pdf |
| Summary: | It has been shown that, in cases where both the AD and IPD studies are available, combining
these two levels of data could improve the overall meta-analysis estimates, compared to utilizing
AD studies alone. However, the coverage probability of estimates based on combined studies are
relatively low compared to the AD-only meta-analysis, when the existing standard method was
used to combine these studies. The aim of this paper is to introduce some modifications to the
existing two-stage method for combining the aggregate data (AD) and individual patient data
(IPD) studies in meta-analysis. We evaluated the effects of these modifications on the estimates
of the overall treatment effect, and compared them with those from the standard method. The
influence of the number of studies included in a meta-analysis, N, and the ratio of AD: IPD on
these estimates were also examined. We used percentage relative bias (PRB), root mean-squareerror
(RMSE), and coverage probability to assess the overall efficiency of these estimates. The
results revealed that the proposed method had been able to improve the coverage probability
while maintaining the level of bias and RMSE at par to their existing counterpart. These findings
demonstrated that the technique for combining different levels of studies influenced the efficacy
of the overall estimates, which in turn is crucial for drawing reliable and valid conclusions |
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