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      Guidance for Developers of Health Research Reporting Guidelines

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          Abstract

          David Moher and colleagues from the EQUATOR network offer guidance and recommended steps for developing health research reporting guidelines.

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          Most cited references28

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

          K Schulz, I. Chalmers, R Hayes … (1995)
          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 Review of the Empirical Evidence of Study Publication Bias and Outcome Reporting Bias

            Kerry Dwan, Douglas G. Altman, Juan A. Arnaiz … (2008)
            Background The increased use of meta-analysis in systematic reviews of healthcare interventions has highlighted several types of bias that can arise during the completion of a randomised controlled trial. Study publication bias has been recognised as a potential threat to the validity of meta-analysis and can make the readily available evidence unreliable for decision making. Until recently, outcome reporting bias has received less attention. Methodology/Principal Findings We review and summarise the evidence from a series of cohort studies that have assessed study publication bias and outcome reporting bias in randomised controlled trials. Sixteen studies were eligible of which only two followed the cohort all the way through from protocol approval to information regarding publication of outcomes. Eleven of the studies investigated study publication bias and five investigated outcome reporting bias. Three studies have found that statistically significant outcomes had a higher odds of being fully reported compared to non-significant outcomes (range of odds ratios: 2.2 to 4.7). In comparing trial publications to protocols, we found that 40–62% of studies had at least one primary outcome that was changed, introduced, or omitted. We decided not to undertake meta-analysis due to the differences between studies. Conclusions Recent work provides direct empirical evidence for the existence of study publication bias and outcome reporting bias. There is strong evidence of an association between significant results and publication; studies that report positive or significant results are more likely to be published and outcomes that are statistically significant have higher odds of being fully reported. Publications have been found to be inconsistent with their protocols. Researchers need to be aware of the problems of both types of bias and efforts should be concentrated on improving the reporting of trials.
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              The CONSORT statement: revised recommendations for improving the quality of reports of parallel-group randomised trials.

              Michael Altman, Thomas K F Schulz, D Moher … (2001)
              To comprehend the results of a randomised controlled trial (RCT), readers must understand its design, conduct, analysis, and interpretation. That goal can be achieved only through total 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 use of a checklist and flow diagram. The revised CONSORT statement presented here 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 this information is associated with biased estimates of treatment effect, or because 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 (enrollment, intervention allocation, follow-up, and analysis). The diagram explicitly shows 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 done 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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                Author and article information

                Journal
                Journal ID (nlm-ta): PLoS Med
                Journal ID (publisher-id): PLoS
                Journal ID (pmc): plosmed
                Title: PLoS Medicine
                Publisher: Public Library of Science (San Francisco, USA )
                ISSN (Print): 1549-1277
                ISSN (Electronic): 1549-1676
                Publication date Collection: February 2010
                Publication date (Print): February 2010
                Publication date (Electronic): 16 February 2010
                Volume: 7
                Issue: 2
                Electronic Location Identifier: e1000217
                Affiliations
                [1 ]Ottawa Methods Centre, Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
                [2 ]Department of Epidemiology and Community Medicine, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
                [3 ]Family Health International, Research Triangle Park, North Carolina, United States of America
                [4 ]Centre for Statistics in Medicine, University of Oxford, Oxford, United Kingdom
                Author notes

                ICMJE criteria for authorship read and met: DM KFS IS DGA. Wrote the first draft of the paper: DM. Contributed to the writing of the paper: KFS IS DGA.

                Article
                Publisher ID: 09-PLME-GG-1754R2
                DOI: 10.1371/journal.pmed.1000217
                PMC ID: 2821895
                PubMed ID: 20169112
                SO-VID: ded044e8-3ba2-4c22-9aea-c4b3dc61600b
                Copyright © Moher et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                Page count
                Pages: 9
                Categories
                Subject: Guidelines and Guidance
                Subject: Evidence-Based Healthcare/Statistical Methodologies and Health Informatics
                Subject: Science Policy

                ScienceOpen disciplines: Medicine
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                ScienceOpen disciplines: Medicine

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