Matthew J. Page, Douglas G. Altman, Matthias Egger
Abstract
Studies at high risk of bias may distort the results of systematic reviews and meta-analyses. Based on empirical evidence and theoretical considerations, the following sources of bias should be assessed when including randomized trials in a review: bias arising from the randomization process, bias due to deviations from the intended interventions, bias due to missing outcome data, bias in measurement of the outcome, and bias due to selective reporting. The use of summary scores from quality scales is problematic. Results depend on the choice of scale, and the interpretation of the results is difficult. Therefore, judging risk of bias within separate specified bias domains and recording the information on which each judgment is based – the domain-based approach – are preferred. Assessments of risk of bias of included studies should routinely be incorporated in systematic reviews and meta-analyses. Currently, this is best done using sensitivity analyses.
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Author affiliations
Matthew J. Page
School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
Douglas G. Altman
Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
Matthias Egger
Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
Centre for Infectious Diseases, Epidemiology and Research, University of Cape Town, South Africa
How to cite this chapter?
For the printed version of the book
Page, M.J., Altman, D.G. and Egger, M. (2022). Chapter 4. Assessing the risk of bias in randomized trials. In: Systematic Reviews in Health Research: Meta-analysis in Context (eds M. Egger, J.P.T. Higgins and G. Davey Smith), pp 55-73. Hoboken, NJ : Wiley.
For the electronic version of the book
Page, M.J., Altman, D.G. and Egger, M. (2022). Chapter 4. Assessing the risk of bias in randomized trials. In: Systematic Reviews in Health Research: Meta-analysis in Context (eds M. Egger, J.P.T. Higgins and G. Davey Smith). https://doi.org/10.1002/9781119099369.ch4