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Risk of bias versus quality assessment of randomised controlled trials: cross sectional study

BMJ 2009; 339 doi: (Published 19 October 2009) Cite this as: BMJ 2009;339:b4012
  1. Lisa Hartling, assistant professor,
  2. Maria Ospina, project manager,
  3. Yuanyuan Liang, research scientist and biostatistician,
  4. Donna M Dryden, assistant professor,
  5. Nicola Hooton, project coordinator,
  6. Jennifer Krebs Seida, project coordinator,
  7. Terry P Klassen, professor
  1. 1Alberta Research Centre for Health Evidence, Department of Pediatrics, University of Alberta, Aberhart Centre One, Edmonton, AB, Canada T6G 2J3
  1. Correspondence to: L Hartling hartling{at}
  • Accepted 26 December 2008


Objectives To evaluate the risk of bias tool, introduced by the Cochrane Collaboration for assessing the internal validity of randomised trials, for inter-rater agreement, concurrent validity compared with the Jadad scale and Schulz approach to allocation concealment, and the relation between risk of bias and effect estimates.

Design Cross sectional study.

Study sample 163 trials in children.

Main outcome measures Inter-rater agreement between reviewers assessing trials using the risk of bias tool (weighted κ), time to apply the risk of bias tool compared with other approaches to quality assessment (paired t test), degree of correlation for overall risk compared with overall quality scores (Kendall’s τ statistic), and magnitude of effect estimates for studies classified as being at high, unclear, or low risk of bias (metaregression).

Results Inter-rater agreement on individual domains of the risk of bias tool ranged from slight (κ=0.13) to substantial (κ=0.74). The mean time to complete the risk of bias tool was significantly longer than for the Jadad scale and Schulz approach, individually or combined (8.8 minutes (SD 2.2) per study v 2.0 (SD 0.8), P<0.001). There was low correlation between risk of bias overall compared with the Jadad scores (P=0.395) and Schulz approach (P=0.064). Effect sizes differed between studies assessed as being at high or unclear risk of bias (0.52) compared with those at low risk (0.23).

Conclusions Inter-rater agreement varied across domains of the risk of bias tool. Generally, agreement was poorer for those items that required more judgment. There was low correlation between assessments of overall risk of bias and two common approaches to quality assessment: the Jadad scale and Schulz approach to allocation concealment. Overall risk of bias as assessed by the risk of bias tool differentiated effect estimates, with more conservative estimates for studies at low risk.


  • We thank Robin Leicht for help with retrieving the articles; Sarah Curtis for help with classification of study outcomes; Natasha Wiebe, Kelly Russell, and Kelly Stevens for their contributions to data extraction, quality assessment, and data analysis, and David Moher for instruction and guidance in applying the risk of bias tool.

  • Contributors: LH, MO, and TPK designed the study. LH coordinated the project and is guarantor. MO contributed to the conception of the study along with LH. LH, MO, DD, NH, and JS carried out the risk of bias assessments. YL analysed the data. LH, MO, DD, and TPK interpreted the data. NH carried out quality assessments. LH, MO, YL, DD, NH, and JS drafted and critically reviewed the manuscript. TPK critically revised the manuscript. All authors read and approved the manuscript.

  • Funding: None.

  • Competing interests: None declared.

  • Ethical approval: Not required.

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