title: Search filters for finding prognostic and diagnostic prediction studies in Medline to enhance systematic reviews.
abstract: BACKGROUND
  The interest in prognostic reviews is increasing, but to properly review existing evidence an accurate search filer for finding prediction research is needed. The aim of this paper was to validate and update two previously introduced search filters for finding prediction research in Medline: the Ingui filter and the Haynes Broad filter.
  
  
  RESULTS
  Based on a hand search of 6 general journals in 2008 we constructed two sets of papers. Set 1 consisted of prediction research papers (n = 71), and set 2 consisted of the remaining papers (n = 1133). Both search filters were validated in two ways, using diagnostic accuracy measures as performance measures. First, we compared studies in set 1 (reference) with studies retrieved by the search strategies as applied in Medline. Second, we compared studies from 4 published systematic reviews (reference) with studies retrieved by the search filter as applied in Medline. Next--using word frequency methods--we constructed an additional search string for finding prediction research. Both search filters were good in identifying clinical prediction models: sensitivity ranged from 0.94 to 1.0 using our hand search as reference, and 0.78 to 0.89 using the systematic reviews as reference. This latter performance measure even increased to around 0.95 (range 0.90 to 0.97) when either search filter was combined with the additional string that we developed. Retrieval rate of explorative prediction research was poor, both using our hand search or our systematic review as reference, and even combined with our additional search string: sensitivity ranged from 0.44 to 0.85.
  
  
  CONCLUSIONS
  Explorative prediction research is difficult to find in Medline, using any of the currently available search filters. Yet, application of either the Ingui filter or the Haynes broad filter results in a very low number missed clinical prediction model studies.
authors.affiliation: Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands. g.j.geersing@umcutrecht.nl
authors.forename: Geert-Jan
authors.initials: GJ
authors.lastname: Geersing
authors.forename: Walter
authors.initials: W
authors.lastname: Bouwmeester
authors.forename: Peter
authors.initials: P
authors.lastname: Zuithoff
authors.forename: Rene
authors.initials: R
authors.lastname: Spijker
authors.forename: Mariska
authors.initials: M
authors.lastname: Leeflang
authors.forename: Karel G M
authors.initials: KG
authors.lastname: Moons
authors.forename: Karel
authors.initials: K
authors.lastname: Moons
mesh_terms: D000465:Algorithms; D035843:Biomedical Research; D019295:Computational Biology / Q000379:methods*; D003201:Computers; D016208:Databases, Factual; D006801:Humans; D016239:MEDLINE; D015999:Multivariate Analysis; D011379:Prognosis; D012372:ROC Curve; D015203:Reproducibility of Results; D012984:Software