Literature DB >> 23116689

GRADE guidelines: 13. Preparing summary of findings tables and evidence profiles-continuous outcomes.

Gordon H Guyatt1, Kristian Thorlund, Andrew D Oxman, Stephen D Walter, Donald Patrick, Toshi A Furukawa, Bradley C Johnston, Paul Karanicolas, Elie A Akl, Gunn Vist, Regina Kunz, Jan Brozek, Lawrence L Kupper, Sandra L Martin, Joerg J Meerpohl, Pablo Alonso-Coello, Robin Christensen, Holger J Schunemann.   

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.
Copyright © 2013 Elsevier Inc. All rights reserved.

Mesh:

Year:  2012        PMID: 23116689     DOI: 10.1016/j.jclinepi.2012.08.001

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  181 in total

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