Assessing risk of bias: a proposal for a unified framework for observational studies and randomized trials
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(2020) 20:237
TECHNICAL ADVANCE
Open Access
Assessing risk of bias: a proposal for a unified framework for observational studies and randomized trials Hendrika J. Luijendijk1* , Matthew J. Page2, Huibert Burger1 and Xander Koolman3
Abstract Background: Evidence based medicine aims to integrate scientific evidence, clinical experience, and patient values and preferences. Individual health care professionals need to appraise the evidence from randomized trials and observational studies when guidelines are not yet available. To date, tools for assessment of bias and terminologies for bias are specific for each study design. Moreover, most tools appeal only to methodological knowledge to detect bias, not to subject matter knowledge, i.e. in-depth medical knowledge about a topic. We propose a unified framework that enables the coherent assessment of bias across designs. Methods: Epidemiologists traditionally distinguish between three types of bias in observational studies: confounding, information bias, and selection bias. These biases result from a common cause, systematic error in the measurement or common effect of the intervention and outcome respectively. We applied this conceptual framework to randomized trials and show how it can be used to identify bias. The three sources of bias were illustrated with graphs that visually represent researchers’ assumptions about the relationships between the investigated variables (causal diagrams). Results: Critical appraisal of evidence started with the definition of the research question in terms of the population of interest, the compared interventions and the main outcome. Next, we used causal diagrams to illustrate how each source of bias can lead to over- or underestimated treatment effects. Then, we discussed how randomization, blinded outcome measurement and intention-to-treat analysis minimize bias in trials. Finally, we identified study aspects that can only be appraised with subject matter knowledge, irrespective of study design. Conclusions: The unified framework encompassed the three main sources of bias for the effect of an assigned intervention on an outcome. It facilitated the integration of methodological and subject matter knowledge in the assessment of bias. We hope that graphical diagrams will help clarify debate among professionals by reducing misunderstandings based on different terminology for bias. Keywords: Critical appraisal, Risk of bias, Validity, Randomized trial, Cohort study, Review
* Correspondence: [email protected] 1 University of Groningen, University Medical Center Groningen, Department ofGeneral Practice and Elderly Care Medicine, Groningen, The Netherlands Full list of author information is available at the end of the article
© The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a
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