Details

Autor(en) / Beteiligte

• Guyatt, Gordon H
• Ebrahim, Shanil
• Alonso-Coello, Pablo
• Johnston, Bradley C
• Mathioudakis, Alexander G
• Briel, Matthias
• Mustafa, Reem A
• Sun, Xin
• Walter, Stephen D
• Heels-Ansdell, Diane
• Neumann, Ignacio
• Kahale, Lara A
• Iorio, Alfonso
• Meerpohl, Joerg
• Schünemann, Holger J
• Akl, Elie A

Titel

GRADE guidelines 17: Assessing the Risk of Bias Associated with Missing Participant Outcome Data in a body of evidence

Ist Teil von

• Journal of clinical epidemiology, 2017-07, Vol.87, p.14-22

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2017

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• Abstract Objective To provide GRADE guidance for assessing risk of bias across an entire body of evidence consequent on missing data for systematic reviews of both binary and continuous outcomes. Study design Systematic survey of published methodological research, iterative discussions, testing in systematic reviews, and feedback from the GRADE Working Group. Results Approaches begin with a primary meta-analysis using a complete case analysis followed by sensitivity meta-analyses imputing, in each study, data for those with missing data, and then pooling across studies. For binary outcomes we suggest use of “plausible worst case” in which review authors assume that those with missing data in treatment arms have proportionally higher event rates than those followed successfully. For continuous outcomes, imputed mean values come from other studies within the systematic review, and the standard deviation from the median standard deviations of the control arms of all studies. Conclusions If the results of the primary meta-analysis are robust to the most extreme assumptions viewed as plausible, one does not rate down certainty in the evidence for risk of bias due to missing participant outcome data. If the results prove not robust to plausible assumptions, one would rate down certainty in the evidence for risk of bias.