TY - JOUR
T1 - GRADE guidelines
T2 - 13. Preparing summary of findings tables and evidence profiles-continuous outcomes
AU - Guyatt, Gordon H
AU - Thorlund, Kristian
AU - Oxman, Andrew D
AU - Walter, Stephen D
AU - Patrick, Donald
AU - Furukawa, Toshi A
AU - Johnston, Bradley C
AU - Karanicolas, Paul
AU - Akl, Elie A
AU - Vist, Gunn
AU - Kunz, Regina
AU - Brozek, Jan
AU - Kupper, Lawrence L
AU - Martin, Sandra L
AU - Meerpohl, Joerg J
AU - Alonso-Coello, Pablo
AU - Christensen, Robin
AU - Schunemann, Holger J
N1 - Copyright © 2013 Elsevier Inc. All rights reserved.
PY - 2013/2
Y1 - 2013/2
N2 - 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.
AB - 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.
KW - Epidemiologic Methods
KW - Evidence-Based Medicine/standards
KW - Guideline Adherence/standards
KW - Humans
KW - Ontario
KW - Outcome Assessment, Health Care
KW - Practice Guidelines as Topic/standards
KW - Reproducibility of Results
KW - Total Quality Management
KW - Effect size
KW - Standardized mean difference
KW - Meta-analysis
KW - GRADE
KW - Continuous outcomes
KW - Minimal important difference
U2 - 10.1016/j.jclinepi.2012.08.001
DO - 10.1016/j.jclinepi.2012.08.001
M3 - Journal article
C2 - 23116689
SN - 0895-4356
VL - 66
SP - 173
EP - 183
JO - Journal of Clinical Epidemiology
JF - Journal of Clinical Epidemiology
IS - 2
ER -