title: Graphical displays for effective reporting of evidence quality tables in research syntheses.
abstract: BACKGROUND
  When generating guidelines, quality of the evidence is tabulated to capture its several domains, often using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach. We developed a graphic display to capture deficiencies, outliers and similarities across comparisons contained in GRADE tables.
  
  
  METHODS
  Based on a systematic literature review capturing the effects of 32 different therapeutic comparisons on dysmenorrhoea, we synthesised evidence quality in tables and graphs. We evaluated time taken to accurately assess evident quality and preference for tables vs. graphs.
  
  
  RESULTS
  The plots provided visually striking displays of strengths and weaknesses of the evidence across the spectrum of comparisons on a single page. Equivalent tabulated information spread over 4 pages. Participants preferred and interpreted graphs quicker and more accurately than tables.
  
  
  CONCLUSIONS
  The graphic approach we developed makes interpreting evidence easier. Large tables are dry and cumbersome to read and assimilate. When guideline statements are accompanied by these plots, they have the scope for improving the credibility of the recommendations made, as the strength of the evidence used can be clearly seen. Further empirical research will establish the place for graphic displays.
authors.affiliation: Centro Rosarino de Estudios Perinatales, Rosario, Santa Fe, Argentina. lmignini@gmail.com.
authors.forename: Luciano
authors.initials: L
authors.lastname: Mignini
authors.affiliation: Birmingham Clinical Trials Unit, School of Cancer Sciences, College of Medicine and Dentistry, University of Birmingham, Birmingham, UK.
authors.forename: Rita
authors.initials: R
authors.lastname: Champaneria
authors.affiliation: Colchester University Hospital, Colchester, UK.
authors.forename: Ekaterina
authors.initials: E
authors.lastname: Mishanina
authors.affiliation: Centre for Health Sciences, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK. k.s.khan@qmul.ac.uk.
authors.forename: Khalid S
authors.initials: KS
authors.lastname: Khan
mesh_terms: D003196:Computer Graphics; D000068598:Data Accuracy; D019317:Evidence-Based Medicine / Q000379:methods*; D006801:Humans; D017410:Practice Guidelines as Topic; D012196:Review Literature as Topic