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

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          Abstract

          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.

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          Most cited references19

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          Empirical evidence of bias. Dimensions of methodological quality associated with estimates of treatment effects in controlled trials.

          To determine if inadequate approaches to randomized controlled trial design and execution are associated with evidence of bias in estimating treatment effects. An observational study in which we assessed the methodological quality of 250 controlled trials from 33 meta-analyses and then analyzed, using multiple logistic regression models, the associations between those assessments and estimated treatment effects. Meta-analyses from the Cochrane Pregnancy and Childbirth Database. The associations between estimates of treatment effects and inadequate allocation concealment, exclusions after randomization, and lack of double-blinding. Compared with trials in which authors reported adequately concealed treatment allocation, trials in which concealment was either inadequate or unclear (did not report or incompletely reported a concealment approach) yielded larger estimates of treatment effects (P < .001). Odds ratios were exaggerated by 41% for inadequately concealed trials and by 30% for unclearly concealed trials (adjusted for other aspects of quality). Trials in which participants had been excluded after randomization did not yield larger estimates of effects, but that lack of association may be due to incomplete reporting. Trials that were not double-blind also yielded larger estimates of effects (P = .01), with odds ratios being exaggerated by 17%. This study provides empirical evidence that inadequate methodological approaches in controlled trials, particularly those representing poor allocation concealment, are associated with bias. Readers of trial reports should be wary of these pitfalls, and investigators must improve their design, execution, and reporting of trials.
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            Systematic reviews in health care: Assessing the quality of controlled clinical trials.

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              The hazards of scoring the quality of clinical trials for meta-analysis.

              Although it is widely recommended that clinical trials undergo some type of quality review, the number and variety of quality assessment scales that exist make it unclear how to achieve the best assessment. To determine whether the type of quality assessment scale used affects the conclusions of meta-analytic studies. Meta-analysis of 17 trials comparing low-molecular-weight heparin (LMWH) with standard heparin for prevention of postoperative thrombosis using 25 different scales to identify high-quality trials. The association between treatment effect and summary scores and the association with 3 key domains (concealment of treatment allocation, blinding of outcome assessment, and handling of withdrawals) were examined in regression models. Pooled relative risks of deep vein thrombosis with LMWH vs standard heparin in high-quality vs low-quality trials as determined by 25 quality scales. Pooled relative risks from high-quality trials ranged from 0.63 (95% confidence interval [CI], 0.44-0.90) to 0.90 (95% CI, 0.67-1.21) vs 0.52 (95% CI, 0.24-1.09) to 1.13 (95% CI, 0.70-1.82) for low-quality trials. For 6 scales, relative risks of high-quality trials were close to unity, indicating that LMWH was not significantly superior to standard heparin, whereas low-quality trials showed better protection with LMWH (P<.05). Seven scales showed the opposite: high quality trials showed an effect whereas low quality trials did not. For the remaining 12 scales, effect estimates were similar in the 2 quality strata. In regression analysis, summary quality scores were not significantly associated with treatment effects. There was no significant association of treatment effects with allocation concealment and handling of withdrawals. Open outcome assessment, however, influenced effect size with the effect of LMWH, on average, being exaggerated by 35% (95% CI, 1%-57%; P= .046). Our data indicate that the use of summary scores to identify trials of high quality is problematic. Relevant methodological aspects should be assessed individually and their influence on effect sizes explored.
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                Author and article information

                Contributors
                Role: assistant professor
                Role: project manager
                Role: research scientist and biostatistician
                Role: assistant professor
                Role: project coordinator
                Role: project coordinator
                Role: professor
                Journal
                BMJ
                bmj
                BMJ : British Medical Journal
                BMJ Publishing Group Ltd.
                0959-8138
                1468-5833
                2009
                2009
                19 October 2009
                : 339
                Affiliations
                [1 ]Alberta Research Centre for Health Evidence, Department of Pediatrics, University of Alberta, Aberhart Centre One, Edmonton, AB, Canada T6G 2J3
                Author notes
                Correspondence to: L Hartling hartling@ 123456ualberta.ca
                Article
                harl610535
                10.1136/bmj.b4012
                2764034
                19841007
                89bee615-a652-4d1c-9c01-e5914f312c11

                This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode.

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                Research
                Epidemiologic studies

                Medicine
                Medicine

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