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A model-based correction for outcome reporting bias in meta-analysis

John Copas1, Kerry Dwan, Jamie Kirkham

  • 1Department of Statistics, University of Warwick, Coventry CV4 7AL, UK.

Biostatistics (Oxford, England)
|November 12, 2013
PubMed

Insights

Outcome reporting bias (ORB) in medical trials can significantly skew results. This study proposes a model to correct for ORB, showing that adjusted findings move towards the null, potentially overturning significance claims.

Area of Science:

  • Medical Research Methodology
  • Biostatistics
  • Evidence Synthesis

Background:

  • Selective outcome reporting is a known issue in medical trials.
  • This bias can lead systematic reviews to omit studies with non-significant results for certain outcomes.
  • Existing systematic reviews may overestimate treatment effects due to this bias.

Purpose of the Study:

  • To develop a statistical model for estimating the impact of outcome reporting bias (ORB) on meta-analysis results.
  • To quantify the effect of ORB on confidence intervals and p-values.
  • To provide a method for correcting ORB in systematic reviews.

Main Methods:

  • Utilized the methodology from the Outcome Reporting Bias (ORB) in Trials study.
  • Developed a likelihood-based statistical model to estimate bias.
  • Re-analyzed two contrasting examples of meta-analyses.

Main Results:

  • Correcting for ORB shifts estimated treatment effects towards the null hypothesis.
  • The bias can be substantial, potentially reversing conclusions of statistical significance.
  • A simple fixed-effects approximation was derived for practical estimation of ORB effects.

Conclusions:

  • Outcome reporting bias significantly impacts the reliability of meta-analyses.
  • Adjusting for ORB leads to more conservative and accurate assessments of treatment efficacy.
  • The proposed model and approximation offer tools to mitigate the effects of ORB in evidence synthesis.
Keywords:
Bias correctionMeta-analysisORBIT classificationOutcome reporting biasSelective reporting

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