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      The COMET Handbook: version 1.0

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          The selection of appropriate outcomes is crucial when designing clinical trials in order to compare the effects of different interventions directly. For the findings to influence policy and practice, the outcomes need to be relevant and important to key stakeholders including patients and the public, health care professionals and others making decisions about health care. It is now widely acknowledged that insufficient attention has been paid to the choice of outcomes measured in clinical trials. Researchers are increasingly addressing this issue through the development and use of a core outcome set, an agreed standardised collection of outcomes which should be measured and reported, as a minimum, in all trials for a specific clinical area.

          Accumulating work in this area has identified the need for guidance on the development, implementation, evaluation and updating of core outcome sets. This Handbook, developed by the COMET Initiative, brings together current thinking and methodological research regarding those issues. We recommend a four-step process to develop a core outcome set. The aim is to update the contents of the Handbook as further research is identified.

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          The online version of this article (doi:10.1186/s13063-017-1978-4) contains supplementary material, which is available to authorized users.

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          Most cited references 139

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          Reporting results of cancer treatment.

          On the initiative of the World Health Organization, two meetings on the Standardization of Reporting Results of Cancer Treatment have been held with representatives and members of several organizations. Recommendations have been developed for standardized approaches to the recording of baseline data relating to the patient, the tumor, laboratory and radiologic data, the reporting of treatment, grading of acute and subacute toxicity, reporting of response, recurrence and disease-free interval, and reporting results of therapy. These recommendations, already endorsed by a number of organizations, are proposed for international acceptance and use to make it possible for investigators to compare validly their results with those of others.
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            Systematic Review of the Empirical Evidence of Study Publication Bias and Outcome Reporting Bias

            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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              Defining and classifying clinical indicators for quality improvement.

               J Mainz (2003)
              This paper provides a brief review of definitions, characteristics, and categories of clinical indicators for quality improvement in health care. Clinical indicators assess particular health structures, processes, and outcomes. They can be rate- or mean-based, providing a quantitative basis for quality improvement, or sentinel, identifying incidents of care that trigger further investigation. They can assess aspects of the structure, process, or outcome of health care. Furthermore, indicators can be generic measures that are relevant for most patients or disease-specific, expressing the quality of care for patients with specific diagnoses. Monitoring health care quality is impossible without the use of clinical indicators. They create the basis for quality improvement and prioritization in the health care system. To ensure that reliable and valid clinical indicators are used, they must be designed, defined, and implemented with scientific rigour.

                Author and article information

                +44 (0) 151 794 9758 , ,
                BioMed Central (London )
                20 June 2017
                20 June 2017
                : 18
                Issue : Suppl 3 Issue sponsor : Publication of this supplement was funded by the Medical Research Council. The article has undergone the journal's standard peer review process for supplements. The Supplement Editor declares that they have no competing interests.
                [1 ]ISNI 0000 0004 1936 8470, GRID grid.10025.36, MRC North West Hub for Trials Methodology Research, Department of Biostatistics, , University of Liverpool, ; Block F Waterhouse Building, 1-5 Brownlow Street, Liverpool, L69 3GL UK
                [2 ]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, , University of Oxford, ; Oxford, UK
                [3 ]ISNI 0000 0004 1936 7603, GRID grid.5337.2, MRC ConDuCT II Hub for Trials Methodology Research, School of Social and Community Medicine, , University of Bristol, ; Bristol, UK
                [4 ]ISNI 0000 0004 0374 7521, GRID grid.4777.3, Centre for Public Health, , Queen’s University Belfast, ; Belfast, UK
                [5 ]ISNI 0000 0004 0488 0789, GRID grid.6142.1, , National University of Ireland Galway and HRB Trials Methodology Research Network, ; Galway, Ireland
                [6 ]ISNI 0000 0004 0435 165X, GRID grid.16872.3a, Department of Epidemiology and Biostatistics, EMGO+ Institute for Health and Care Research, , VU University Medical Center, ; Amsterdam, The Netherlands
                [7 ]ISNI 0000 0001 2111 7257, GRID grid.4488.0, Center for Evidence-based Healthcare, Medizinische Fakultät, , Technische Univesität Dresden, ; Dresden, Germany
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

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                patients and the public, comet initiative, clinical trial, core outcome set


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