GRADE guidelines: 13. Preparing Summary of Findings tables and evidence profiles-continuous outcomes
Por:
Guyatt, GH, Thorlund, K, Oxman, AD, Walter, SD, Patrick, D, Furukawa, TA, Johnston, BC, Karanicolas, P, Akl, EA, Vist, G, Kunz, R, Brozek, J, Kupper, LL, Martin, SL, Meerpohl, JJ, Alonso-Coello, P, Christensen, R, Schunemann, HJ
Publicada:
1 feb 2013
Resumen:
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. (C) 2013 Elsevier Inc. All rights reserved.
Filiaciones:
Guyatt, GH:
McMaster Univ, Dept Clin Epidemiol & Biostat, Hamilton, ON L8N 3Z5, Canada
McMaster Univ, Dept Med, Hamilton, ON L8N 3Z5, Canada
Thorlund, K:
McMaster Univ, Dept Clin Epidemiol & Biostat, Hamilton, ON L8N 3Z5, Canada
Oxman, AD:
Norwegian Knowledge Ctr Hlth Serv, N-0130 Oslo, Norway
Walter, SD:
McMaster Univ, Dept Clin Epidemiol & Biostat, Hamilton, ON L8N 3Z5, Canada
Patrick, D:
Univ Washington, Ctr Disabil Policy & Res, Seattle Qual Life Grp, Dept Hlth Serv, Seattle, WA 98195 USA
Furukawa, TA:
Kyoto Univ, Grad Sch Med, Sch Publ Hlth, Dept Hlth Promot & Human Behav,Sakyo Ku, Kyoto 6068501, Japan
Johnston, BC:
McMaster Univ, Dept Clin Epidemiol & Biostat, Hamilton, ON L8N 3Z5, Canada
Karanicolas, P:
Univ Toronto, Dept Surg, Toronto, ON, Canada
Akl, EA:
SUNY Buffalo, Dept Med, Buffalo, NY 14260 USA
Vist, G:
Norwegian Knowledge Ctr Hlth Serv, N-0130 Oslo, Norway
Kunz, R:
Univ Basel Hosp, Basel Inst Clin Epidemiol, CH-4031 Basel, Switzerland
Brozek, J:
McMaster Univ, Dept Clin Epidemiol & Biostat, Hamilton, ON L8N 3Z5, Canada
Kupper, LL:
Univ N Carolina, Dept Biostat, Gillings Sch Global Publ Hlth, Chapel Hill, NC USA
Martin, SL:
Univ N Carolina, Dept Maternal & Child Hlth, Gillings Sch Global Publ Hlth, Chapel Hill, NC USA
Meerpohl, JJ:
Univ Med Ctr Freiburg, Inst Med Biometry & Med Informat, German Cochrane Ctr, D-79110 Freiburg, Germany
Univ Med Ctr Freiburg, Ctr Pediat & Adolescent Med, D-79106 Freiburg, Germany
Alonso-Coello, P:
Univ Autonoma Barcelona, Hosp St Pau, Iberoamer Cochrane Ctr, Serv Epidemiol Clin & Salud Publ, Barcelona 08041, Spain
Univ Autonoma Barcelona, Hosp St Pau, CIBER Epidemiol & Salud Publ CIBERESP, Barcelona 08041, Spain
Christensen, R:
Copenhagen Univ Hosp, Parker Inst, Musculoskeletal Stat Unit, Frederiksberg, Denmark
Schunemann, HJ:
McMaster Univ, Dept Clin Epidemiol & Biostat, Hamilton, ON L8N 3Z5, Canada
McMaster Univ, Dept Med, Hamilton, ON L8N 3Z5, Canada
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