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Donegan, Sarah, Williamson, Paula, D'Alessandro, Umberto, Garner, Paul 
ORCID: https://orcid.org/0000-0002-0607-6941 and Smith, Catrin Tudur
(2013)
'Combining individual patient data and aggregate data in mixed treatment comparison meta-analysis: Individual patient data may be beneficial if only for a subset of trials'. Statistics in Medicine, Vol 32, Issue 6, pp. 914-930.
Abstract
Background
Individual patient data (IPD) meta-analysis is the gold standard. Aggregate data (AD) and IPD can be combined using conventional pairwise meta-analysis when IPD cannot be obtained for all relevant studies. We extend the methodology to combine IPD and AD in a mixed treatment comparison (MTC) meta-analysis.
Methods
The proposed random-effects MTC models combine IPD and AD for a dichotomous outcome. We study the benefits of acquiring IPD for a subset of trials when assessing the underlying consistency assumption by including treatment-by-covariate interactions in the model. We describe three different model specifications that make increasingly stronger assumptions regarding the interactions. We illustrate the methodology through application to real data sets to compare drugs for treating malaria by using the outcome unadjusted treatment success at day 28. We compare results from AD alone, IPD alone and all data.
Results
When IPD contributed (i.e. either using IPD alone or combining IPD and AD), the chains converged, and we identified statistically significant regression coefficients for the interactions. Using IPD alone, we were able to compare only three of the six treatments of interest. When models were fitted to AD, the treatment effects and regression coefficients for the interactions were far more imprecise, and the chains did not converge.
Conclusions
The models combining IPD and AD encapsulated all available evidence. When exploring interactions, it can be beneficial to obtain IPD for a subset of trials and to combine IPD with additional AD
| Item Type: | Article |
|---|---|
| Subjects: | W General Medicine. Health Professions > W 20.5 Biomedical research WA Public Health > WA 20.5 Research (General) WA Public Health > Statistics. Surveys > WA 950 Theory or methods of medical statistics. Epidemiologic methods |
| Faculty: Department: | Clinical Sciences & International Health > Clinical Sciences Department |
| Digital Object Identifer (DOI): | https://doi.org/10.1002/sim.5584 |
| Depositing User: | Lynn Roberts-Maloney |
| Date Deposited: | 19 Feb 2015 12:20 |
| Last Modified: | 06 Sep 2019 10:15 |
| URI: | https://archive.lstmed.ac.uk/id/eprint/4927 |
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