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Related Experiment Videos

Gero Langer1, Gerald Gartlehner2, Lukas Schwingshackl3

  • 1Martin-Luther-Universität Halle-Wittenberg, Medizinische Fakultät, Institut für Gesundheits- und Pflegewissenschaft, Halle (Saale), Deutschland.

Zeitschrift Fur Evidenz, Fortbildung Und Qualitat Im Gesundheitswesen
|March 4, 2020
PubMed
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This study offers GRADE guidance for assessing risk of bias from missing data in systematic reviews. If meta-analysis results are robust to plausible assumptions, certainty in evidence is not reduced.

Area of Science:

  • Evidence-based medicine
  • Systematic reviews
  • Meta-analysis

Background:

  • Missing data is a common challenge in systematic reviews.
  • Assessing risk of bias due to missing data is crucial for GRADE certainty assessments.
  • Current methods for handling missing data in meta-analyses require standardized guidance.

Purpose of the Study:

  • To develop GRADE (Grading of Recommendations Assessment, Development and Evaluation) guidance for evaluating risk of bias from missing data.
  • To provide a framework for systematic reviews with both binary and continuous outcomes.

Main Methods:

  • Conducted a systematic survey of methodological research.
  • Engaged in iterative discussions and testing within systematic reviews.
  • Incorporated feedback from the GRADE Working Group.
Keywords:
Bias-RisikoFehlende TeilnehmerdatenGRADEMissing participant dataRisk of biasSystematic reviewsSystematische ÜbersichtsarbeitenTrials

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Main Results:

  • Proposed a two-stage approach: primary meta-analysis (complete case) followed by sensitivity meta-analyses (imputing missing data).
  • Suggested 'plausible worst case' for binary outcomes and imputation from other studies/median SD for continuous outcomes.
  • Demonstrated methods for assessing robustness of meta-analysis results to missing data.

Conclusions:

  • If primary meta-analysis results remain robust under plausible worst-case assumptions, certainty in evidence is not downgraded for missing data.
  • If results are sensitive to plausible assumptions, certainty in evidence should be downgraded.
  • Provides a practical framework for GRADE certainty assessment in the presence of missing data.