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The CONSORT statement: revised recommendations for improving the quality of reports of parallel group randomized trials

, 1 , , 2 , , 3

BMC Medical Research Methodology

BioMed Central

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      To comprehend the results of a randomized controlled trial (RCT), readers must understand its design, conduct, analysis and interpretation. That goal can only be achieved through complete transparency from authors. Despite several decades of educational efforts, the reporting of RCTs needs improvement. Investigators and editors developed the original CONSORT (Consolidated Standards of Reporting Trials) statement to help authors improve reporting by using a checklist and flow diagram. The revised CONSORT statement presented in this paper incorporates new evidence and addresses some criticisms of the original statement.The checklist items pertain to the content of the Title, Abstract, Introduction, Methods, Results and Discussion. The revised checklist includes 22-items selected because empirical evidence indicates that not reporting the information is associated with biasedestimates of treatment effect or the information is essential to judge the reliability or relevance of the findings. We intended the flow diagram to depict the passage of participants through an RCT. The revised flow diagram depicts information from four stages of a trial (enrolment, intervention allocation, follow-up, and analysis). The diagram explicitly includes the number of participants, for each intervention group, included in the primary data analysis. Inclusion of these numbers allows the reader to judge whether the authors have performed an intention-to-treat analysis.In sum, the CONSORT statement is intended to improve the reporting of an RCT, enabling readers to understand a trial's conduct and to assess the validity of its results.

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      Most cited references 31

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      Meta-analysis of Observational Studies in EpidemiologyA Proposal for Reporting

       Donna Stroup (2000)
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        The revised CONSORT statement for reporting randomized trials: explanation and elaboration.

        Overwhelming evidence now indicates that the quality of reporting of randomized, controlled trials (RCTs) is less than optimal. Recent methodologic analyses indicate that inadequate reporting and design are associated with biased estimates of treatment effects. Such systematic error is seriously damaging to RCTs, which boast the elimination of systematic error as their primary hallmark. Systematic error in RCTs reflects poor science, and poor science threatens proper ethical standards. A group of scientists and editors developed the CONSORT (Con solidated S tandards o f R eporting T rials) statement to improve the quality of reporting of RCTs. The statement consists of a checklist and flow diagram that authors can use for reporting an RCT. Many leading medical journals and major international editorial groups have adopted the CONSORT statement. The CONSORT statement facilitates critical appraisal and interpretation of RCTs by providing guidance to authors about how to improve the reporting of their trials. This explanatory and elaboration document is intended to enhance the use, understanding, and dissemination of the CONSORT statement. The meaning and rationale for each checklist item are presented. For most items, at least one published example of good reporting and, where possible, references to relevant empirical studies are provided. Several examples of flow diagrams are included. The CONSORT statement, this explanatory and elaboration document, and the associated Web site ( ) should be helpful resources to improve reporting of randomized trials. Throughout the text, terms marked with an asterisk are defined at end of text.
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          Does quality of reports of randomised trials affect estimates of intervention efficacy reported in meta-analyses?

          Few meta-analyses of randomised trials assess the quality of the studies included. Yet there is increasing evidence that trial quality can affect estimates of intervention efficacy. We investigated whether different methods of quality assessment provide different estimates of intervention efficacy evaluated in randomised controlled trials (RCTs). We randomly selected 11 meta-analyses that involved 127 RCTs on the efficacy of interventions used for circulatory and digestive diseases, mental health, and pregnancy and childbirth. We replicated all the meta-analyses using published data from the primary studies. The quality of reporting of all 127 clinical trials was assessed by means of component and scale approaches. To explore the effects of quality on the quantitative results, we examined the effects of different methods of incorporating quality scores (sensitivity analysis and quality weights) on the results of the meta-analyses. The quality of trials was low. Masked assessments provided significantly higher scores than unmasked assessments (mean 2.74 [SD 1.10] vs 2.55 [1.20]). Low-quality trials (score 2), were associated with an increased estimate of benefit of 34% (ratio of odds ratios [ROR] 0.66 [95% CI 0.52-0.83]). Trials that used inadequate allocation concealment, compared with those that used adequate methods, were also associated with an increased estimate of benefit (37%; ROR=0.63 [0.45-0.88]). The average treatment benefit was 39% (odds ratio [OR] 0.61 [0.57-0.65]) for all trials, 52% (OR 0.48 [0.43-0.54]) for low-quality trials, and 29% (OR 0.71 [0.65-0.77]) for high-quality trials. Use of all the trial scores as quality weights reduced the effects to 35% (OR 0.65 [0.59-0.71]) and resulted in the least statistical heterogeneity. Studies of low methodological quality in which the estimate of quality is incorporated into the meta-analyses can alter the interpretation of the benefit of intervention, whether a scale or component approach is used in the assessment of trial quality.

            Author and article information

            [1 ]University of Ottawa, Thomas C. Chalmers Centre for Systematic Reviews, Ottawa, Canada
            [2 ]Family Health International and Dept. of Obstetrics and Gynecology, School of Medicine, University of North Carolina at Chapel Hill, North Carolina, USA
            [3 ]ICRF Medical Statistics Group and Centre for Statistics in Medicine, Institute of Health Sciences, Oxford, UK for the CONSORT Group
            BMC Med Res Methodol
            BMC Medical Research Methodology
            BioMed Central (London )
            20 April 2001
            : 1
            : 2
            Copyright © 2001 Moher et al; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL.
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