574
views
1
recommends
+1 Recommend
0 collections
    1
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials

      other

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Flaws in the design, conduct, analysis, and reporting of randomised trials can cause the effect of an intervention to be underestimated or overestimated. The Cochrane Collaboration’s tool for assessing risk of bias aims to make the process clearer and more accurate

          Related collections

          Most cited references11

          • Record: found
          • Abstract: not found
          • Article: not found

          Systematic reviews in health care: Assessing the quality of controlled clinical trials.

            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            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.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Bias in clinical intervention research.

              Research on bias in clinical trials may help identify some of the reasons why investigators sometimes reach the wrong conclusions about intervention effects. Several quality components for the assessment of bias control have been suggested, but although they seem intrinsically valid, empirical evidence is needed to evaluate their effects on the extent and direction of bias. This narrative review summarizes the findings of methodological studies on the influence of bias in clinical trials. A number of methodological studies suggest that lack of adequate randomization in published trial reports may be associated with more positive estimates of intervention effects. The influence of double-blinding and follow-up is less clear. Several studies have found a significant association between funding sources and pro-industry conclusions. However, the methodological studies also show that bias is difficult to detect and appraise. The extent of bias in individual trials is unpredictable. A-priori exclusion of trials with certain characteristics is not recommended. Appraising bias control in individual trials is necessary to avoid making incorrect conclusions about intervention effects.
                Bookmark

                Author and article information

                Contributors
                Role: senior statistician
                Role: director
                Role: director
                Role: head of division
                Role: senior scientist
                Role: senior researcher
                Role: postdoctoral fellow
                Role: vice president
                Role: research associate
                Role: professor of medical statistics and epidemiology
                Journal
                BMJ
                bmj
                BMJ : British Medical Journal
                BMJ Publishing Group Ltd.
                0959-8138
                1468-5833
                2011
                2011
                18 October 2011
                : 343
                : d5928
                Affiliations
                [1 ]MRC Biostatistics Unit, Institute of Public Health, Cambridge CB2 0SR, UK
                [2 ]Centre for Statistics in Medicine, University of Oxford, Oxford, UK
                [3 ]The Nordic Cochrane Centre, Rigshospitalet and University of Copenhagen, Denmark
                [4 ]Institute of Social and Preventive Medicine, University of Bern, Switzerland
                [5 ]Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
                [6 ]Department of Epidemiology and Community Medicine, Faculty of Medicine, University of Ottawa, Canada
                [7 ]Preventive and International Health Care Unit, Norwegian Knowledge Centre for the Health Services, Oslo, Norway
                [8 ]Department of Social Medicine, University of Bristol, Bristol, UK
                [9 ]FHI, Research Triangle Park, North Carolina, USA
                Author notes
                Correspondence to: J P T Higgins julian.higgins@ 123456mrc-bsu.cam.ac.uk .
                Article
                higj860676
                10.1136/bmj.d5928
                3196245
                22008217
                2f4dc86a-ca60-4c3f-9f4b-582955dcdcc7
                © Higgins et al 2011

                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.

                History
                : 22 July 2011
                Categories
                Research Methods & Reporting

                Medicine
                Medicine

                Comments

                Comment on this article