title: GRADE guidelines: 13. Preparing summary of findings tables and evidence profiles-continuous outcomes.
abstract: Presenting continuous outcomes in Summary of Findings tables presents particular challenges to interpretation. When each study uses the same outcome measure, and the units of that measure are intuitively interpretable (e.g., duration of hospitalization, duration of symptoms), presenting differences in means is usually desirable. When the natural units of the outcome measure are not easily interpretable, choosing a threshold to create a binary outcome and presenting relative and absolute effects become a more attractive alternative. When studies use different measures of the same construct, calculating summary measures requires converting to the same units of measurement for each study. The longest standing and most widely used approach is to divide the difference in means in each study by its standard deviation and present pooled results in standard deviation units (standardized mean difference). Disadvantages of this approach include vulnerability to varying degrees of heterogeneity in the underlying populations and difficulties in interpretation. Alternatives include presenting results in the units of the most popular or interpretable measure, converting to dichotomous measures and presenting relative and absolute effects, presenting the ratio of the means of intervention and control groups, and presenting the results in minimally important difference units. We outline the merits and limitations of each alternative and provide guidance for meta-analysts and guideline developers.
authors.affiliation: Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario L8N 3Z5, Canada. guyatt@mcmaster.ca
authors.forename: Gordon H
authors.initials: GH
authors.lastname: Guyatt
authors.forename: Kristian
authors.initials: K
authors.lastname: Thorlund
authors.forename: Andrew D
authors.initials: AD
authors.lastname: Oxman
authors.forename: Stephen D
authors.initials: SD
authors.lastname: Walter
authors.forename: Donald
authors.initials: D
authors.lastname: Patrick
authors.forename: Toshi A
authors.initials: TA
authors.lastname: Furukawa
authors.forename: Bradley C
authors.initials: BC
authors.lastname: Johnston
authors.forename: Paul
authors.initials: P
authors.lastname: Karanicolas
authors.forename: Elie A
authors.initials: EA
authors.lastname: Akl
authors.forename: Gunn
authors.initials: G
authors.lastname: Vist
authors.forename: Regina
authors.initials: R
authors.lastname: Kunz
authors.forename: Jan
authors.initials: J
authors.lastname: Brozek
authors.forename: Lawrence L
authors.initials: LL
authors.lastname: Kupper
authors.forename: Sandra L
authors.initials: SL
authors.lastname: Martin
authors.forename: Joerg J
authors.initials: JJ
authors.lastname: Meerpohl
authors.forename: Pablo
authors.initials: P
authors.lastname: Alonso-Coello
authors.forename: Robin
authors.initials: R
authors.lastname: Christensen
authors.forename: Holger J
authors.initials: HJ
authors.lastname: Schunemann
mesh_terms: D004812:Epidemiologic Methods; D019317:Evidence-Based Medicine / Q000592:standards*; D019983:Guideline Adherence / Q000592:standards; D006801:Humans; D009864:Ontario; D017063:Outcome Assessment, Health Care; D017410:Practice Guidelines as Topic / Q000592:standards*; D015203:Reproducibility of Results; D017749:Total Quality Management