4.6 Review

Recommendations for assessing the risk of bias in systematic reviews of health-care interventions

Journal

JOURNAL OF CLINICAL EPIDEMIOLOGY
Volume 97, Issue -, Pages 26-34

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.jclinepi.2017.12.004

Keywords

Risk-of-bias guidance; Critical appraisal; Systematic reviews; Meta-analyses; Health-care interventions; Evidence-based practice

Funding

  1. Agency for Healthcare Research and Quality, US Department of Health and Human Services (RTI) [290 2015 000111]
  2. Agency for Healthcare Research and Quality, US Department of Health and Human Services (University of Alberta) [290 2015 000011]
  3. Agency for Healthcare Research and Quality, US Department of Health and Human Services (ECRI-Penn) [290 2015 000051]
  4. Agency for Healthcare Research and Quality, US Department of Health and Human Services (Johns Hopkins University) [290 2015 000061]
  5. Agency for Healthcare Research and Quality, US Department of Health and Human Services (Mayo Clinic) [290 2015 000131]
  6. Agency for Healthcare Research and Quality, US Department of Health and Human Services (Minnesota University) [290 2015 000081]
  7. Agency for Healthcare Research and Quality, US Department of Health and Human Services (Kaiser Permanente Center for Health Research) [290 2015 000091]

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Objectives: Risk-of-bias assessment is a central component of systematic reviews, but little conclusive empirical evidence exists on the validity of such assessments. In the context of such uncertainty, we present pragmatic recommendations that promote transparency and reproducibility in processes, address methodological advances in the risk-of-bias assessment, and can be applied consistently across review topics. Study Design and Setting: Epidemiological study design principles; available empirical evidence, risk-of-bias tools, and guidance; and workgroup consensus. Results: We developed recommendations for assessing the risk of bias of studies of health-care interventions specific to framing the focus and scope of risk-of-bias assessment; selecting the risk-of-bias categories; choosing assessment instruments; and conducting, analyzing, and presenting results of risk-of-bias assessments. Key recommendations include transparency and reproducibility of judgments, separating risk of bias from other constructs such as applicability and precision, and evaluating the risk of bias per outcome. We recommend against certain past practices, such as focusing on reporting quality, relying solely on study design or numerical quality scores, and automatically downgrading for industry sponsorship. Conclusion: Risk-of-bias assessment remains a challenging but essential step in systematic reviews. We presented standards to promote transparency of judgments. (C) 2017 Elsevier Inc. All rights reserved.

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