title: Exploring treatment by covariate interactions using subgroup analysis and meta-regression in cochrane reviews: a review of recent practice.
abstract: BACKGROUND
  Treatment by covariate interactions can be explored in reviews using interaction analyses (e.g., subgroup analysis). Such analyses can provide information on how the covariate modifies the treatment effect and is an important methodological approach for personalising medicine. Guidance exists regarding how to apply such analyses but little is known about whether authors follow the guidance.
  
  
  METHODS
  Using published recommendations, we developed criteria to assess how well interaction analyses were designed, applied, interpreted, and reported. The Cochrane Database of Systematic Reviews was searched (8th August 2013). We applied the criteria to the most recently published review, with an accessible protocol, for each Cochrane Review Group. We excluded review updates, diagnostic test accuracy reviews, withdrawn reviews, and overviews of reviews. Data were summarised regarding reviews, covariates, and analyses.
  
  
  RESULTS
  Each of the 52 included reviews planned or did interaction analyses; 51 reviews (98%) planned analyses and 33 reviews (63%) applied analyses. The type of analysis planned and the type subsequently applied (e.g., sensitivity or subgroup analysis) was discrepant in 24 reviews (46%). No review reported how or why each covariate had been chosen; 22 reviews (42%) did state each covariate a priori in the protocol but no review identified each post-hoc covariate as such. Eleven reviews (21%) mentioned five covariates or less. One review reported planning to use a method to detect interactions (i.e., interaction test) for each covariate; another review reported applying the method for each covariate. Regarding interpretation, only one review reported whether an interaction was detected for each covariate and no review discussed the importance, or plausibility, of the results, or the possibility of confounding for each covariate.
  
  
  CONCLUSIONS
  Interaction analyses in Cochrane Reviews can be substantially improved. The proposed criteria can be used to help guide the reporting and conduct of analyses.
authors.affiliation: Department of Biostatistics, University of Liverpool, Liverpool, United Kingdom.
authors.forename: Sarah
authors.initials: S
authors.lastname: Donegan
authors.affiliation: Department of Biostatistics, University of Liverpool, Liverpool, United Kingdom.
authors.forename: Lisa
authors.initials: L
authors.lastname: Williams
authors.affiliation: School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom.
authors.forename: Sofia
authors.initials: S
authors.lastname: Dias
authors.affiliation: Department of Biostatistics, University of Liverpool, Liverpool, United Kingdom.
authors.forename: Catrin
authors.initials: C
authors.lastname: Tudur-Smith
authors.affiliation: School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom.
authors.forename: Nicky
authors.initials: N
authors.lastname: Welton
mesh_terms: D003627:Data Interpretation, Statistical; D003955:Diagnostic Tests, Routine / Q000379:methods; D006801:Humans; D057285:Precision Medicine / Q000379:methods