title: Citation networks of related trials are often disconnected: implications for bidirectional citation searches.
abstract: OBJECTIVE
  Reports of randomized controlled trials (RCTs) should set findings within the context of previous research. The resulting network of citations would also provide an alternative search method for clinicians, researchers, and systematic reviewers seeking to base decisions on all available evidence. We sought to determine the connectedness of citation networks of RCTs by examining direct (referenced trials) and indirect (through references of referenced trials, etc) citation of trials to one another.
  
  
  METHODS
  Meta-analyses were used to create citation networks of RCTs addressing the same clinical questions. The primary measure was the proportion of networks where following citation links between RCTs identifies the complete set of RCTs, forming a single connected citation group. Other measures included the number of disconnected groups (islands) within each network, the number of citations in the network relative to the maximum possible, and the maximum number of links in the path between two connected trials (a measure of indirectness of citations).
  
  
  RESULTS
  We included 259 meta-analyses with a total of 2,413 and a median of seven RCTs each. For 46% (118 of 259) of networks, the RCTs formed a single connected citation group-one island. For the other 54% of networks, where at least one RCT group was not cited by others, 39% had two citation islands and 4% (10 of 257) had 10 or more islands. On average, the citation networks had 38% of the possible citations to other trials (if each trial had cited all earlier trials). The number of citation islands and the maximum number of citation links increased with increasing numbers of trials in the network.
  
  
  CONCLUSIONS
  Available evidence to answer a clinical question may be identified by using network citations created with a small initial corpus of eligible trials. However, the number of islands means that citation networks cannot be relied on for evidence retrieval.
authors.affiliation: Department of Medicine, Johns Hopkins University School of Medicine, 1830 East Monument St., Suite 8068, Baltimore, MD 21287, USA; Department of Epidemiology, Johns Hopkins University School of Public Health, 1830 East Monument St., Suite 8068, Baltimore, MD 21287, USA; Department of Health Policy and Management, Johns Hopkins University School of Public Health, 1830 East Monument St., Suite 8068, Baltimore, MD 21287, USA. Electronic address: krobin@jhmi.edu.
authors.forename: Karen A
authors.initials: KA
authors.lastname: Robinson
authors.affiliation: Centre for Health Informatics, University of New South Wales, Sydney, NSW 2052, Australia.
authors.forename: Adam G
authors.initials: AG
authors.lastname: Dunn
authors.affiliation: Centre for Health Informatics, University of New South Wales, Sydney, NSW 2052, Australia.
authors.forename: Guy
authors.initials: G
authors.lastname: Tsafnat
authors.affiliation: Centre for Research in Evidence-Based Practice, Bond University, Gold Coast, QLD 4229, Australia.
authors.forename: Paul
authors.initials: P
authors.lastname: Glasziou
mesh_terms: D015706:Bibliometrics; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods* / Q000592:standards; D015201:Meta-Analysis as Topic; D011643:Publishing; D016032:Randomized Controlled Trials as Topic / Q000379:methods* / Q000592:standards; D012196:Review Literature as Topic
keywords: Citation networks; Clinical trials; Meta-analysis; Network analysis; Searching; Systematic reviews