title: 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.
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.
authors.affiliation: Department of Biostatistics, Faculty of Health and Life Sciences, University of Liverpool, Shelley's Cottage, Brownlow Street, Liverpool, L69 3GS, UK. sarah.donegan@liverpool.ac.uk
authors.forename: Sarah
authors.initials: S
authors.lastname: Donegan
authors.forename: Paula
authors.initials: P
authors.lastname: Williamson
authors.forename: Umberto
authors.initials: U
authors.lastname: D'Alessandro
authors.forename: Paul
authors.initials: P
authors.lastname: Garner
authors.forename: Catrin Tudur
authors.initials: CT
authors.lastname: Smith
mesh_terms: D006801:Humans; D037621:Artemisinins / Q000627:therapeutic use; D003627:Data Interpretation, Statistical; D004359:Drug Therapy, Combination; D016778:Malaria, Falciparum / Q000188:drug therapy / Q000469:parasitology; D015233:Models, Statistical; D010963:Plasmodium falciparum / Q000254:growth & development; D016032:Randomized Controlled Trials as Topic / Q000379:methods; D016896:Treatment Outcome; D000071076:Network Meta-Analysis as Topic
chemical_list: C031327:artemisinin; D037621:Artemisinins