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      Reproducible Research Practices and Transparency across the Biomedical Literature

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          Abstract

          There is a growing movement to encourage reproducibility and transparency practices in the scientific community, including public access to raw data and protocols, the conduct of replication studies, systematic integration of evidence in systematic reviews, and the documentation of funding and potential conflicts of interest. In this survey, we assessed the current status of reproducibility and transparency addressing these indicators in a random sample of 441 biomedical journal articles published in 2000–2014. Only one study provided a full protocol and none made all raw data directly available. Replication studies were rare ( n = 4), and only 16 studies had their data included in a subsequent systematic review or meta-analysis. The majority of studies did not mention anything about funding or conflicts of interest. The percentage of articles with no statement of conflict decreased substantially between 2000 and 2014 (94.4% in 2000 to 34.6% in 2014); the percentage of articles reporting statements of conflicts (0% in 2000, 15.4% in 2014) or no conflicts (5.6% in 2000, 50.0% in 2014) increased. Articles published in journals in the clinical medicine category versus other fields were almost twice as likely to not include any information on funding and to have private funding. This study provides baseline data to compare future progress in improving these indicators in the scientific literature.

          Abstract

          Examination of recent trends in reproducibility and transparency practices in biomedical research reveals an ongoing lack of access to full datasets and detailed protocols for both clinical and non-clinical studies.

          Author Summary

          There is increasing interest in the scientific community about whether published research is transparent and reproducible. Lack of replication and non-transparency decreases the value of research. Several biomedical journals have started to encourage or require authors to submit detailed protocols, full datasets, and disclose information on funding and potential conflicts of interest. In this study, we investigate the reproducibility and transparency practices across the full spectrum of published biomedical literature from 2000–2014. We identify an ongoing lack of access to full datasets and detailed protocols for both clinical and non-clinical biomedical investigation. We also map the availability of information on funding and conflicts of interest in this literature. The results from this study provide baseline data to compare future progress in improving these indicators in the scientific literature. We believe that this information may be essential to sensitize stakeholders in science about the need for improving reproducibility and transparency practices.

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          Most cited references27

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          Pharmaceutical industry sponsorship and research outcome and quality: systematic review.

          To investigate whether funding of drug studies by the pharmaceutical industry is associated with outcomes that are favourable to the funder and whether the methods of trials funded by pharmaceutical companies differ from the methods in trials with other sources of support. Medline (January 1966 to December 2002) and Embase (January 1980 to December 2002) searches were supplemented with material identified in the references and in the authors' personal files. Data were independently abstracted by three of the authors and disagreements were resolved by consensus. 30 studies were included. Research funded by drug companies was less likely to be published than research funded by other sources. Studies sponsored by pharmaceutical companies were more likely to have outcomes favouring the sponsor than were studies with other sponsors (odds ratio 4.05; 95% confidence interval 2.98 to 5.51; 18 comparisons). None of the 13 studies that analysed methods reported that studies funded by industry was of poorer quality. Systematic bias favours products which are made by the company funding the research. Explanations include the selection of an inappropriate comparator to the product being investigated and publication bias.
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            A call for transparent reporting to optimize the predictive value of preclinical research.

            The US National Institute of Neurological Disorders and Stroke convened major stakeholders in June 2012 to discuss how to improve the methodological reporting of animal studies in grant applications and publications. The main workshop recommendation is that at a minimum studies should report on sample-size estimation, whether and how animals were randomized, whether investigators were blind to the treatment, and the handling of data. We recognize that achieving a meaningful improvement in the quality of reporting will require a concerted effort by investigators, reviewers, funding agencies and journal editors. Requiring better reporting of animal studies will raise awareness of the importance of rigorous study design to accelerate scientific progress.
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              Reproducible research in computational science.

              Roger Peng (2011)
              Computational science has led to exciting new developments, but the nature of the work has exposed limitations in our ability to evaluate published findings. Reproducibility has the potential to serve as a minimum standard for judging scientific claims when full independent replication of a study is not possible.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Biol
                PLoS Biol
                plos
                plosbiol
                PLoS Biology
                Public Library of Science (San Francisco, CA USA )
                1544-9173
                1545-7885
                4 January 2016
                January 2016
                : 14
                : 1
                : e1002333
                Affiliations
                [1 ]Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
                [2 ]Department of Health Research and Policy, Stanford School of Medicine, Palo Alto, California, United States of America
                [3 ]Meta-Research Innovation Center at Stanford, Stanford University, Stanford, California, United States of America
                [4 ]Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
                [5 ]Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
                [6 ]Stanford Prevention Research Center, Department of Medicine, Stanford University, Stanford, California, United States of America
                [7 ]Department of Statistics, Stanford University School of Humanities and Sciences, Stanford, California, United States of America
                Walter and Eliza Hall Institute of Medical Research, AUSTRALIA
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: JPAI MJK SAI JDW SDS. Performed the experiments: SAI JDW JPAI. Analyzed the data: SAI JDW JPAI. Contributed reagents/materials/analysis tools: SAI JDW. Wrote the paper: SAI JDW JPAI. Wrote the protocol: JPAI SAI JDW. Further elaborated the protocol: MJK SDS. Data extraction and statistical analysis: SAI JDW. Extraction arbitration: JPAI. Interpretation of data and analyses: JPAI SAI JDW. Wrote first draft of manuscript: SAI JDW JPAI. Manuscript comments and revisions: JPAI SAI JDW MJK SDS.

                Article
                PBIOLOGY-D-15-02900
                10.1371/journal.pbio.1002333
                4699702
                26726926
                ecfb596c-c53e-4f6c-ab1b-579708bbbb1b

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication

                History
                : 13 October 2015
                : 19 November 2015
                Page count
                Figures: 2, Tables: 2, Pages: 13
                Funding
                The authors received no specific funding for this work. The Meta-Research Innovation Center at Stanford (METRICS) is supported by a grant from the Laura and John Arnold Foundation.
                Categories
                Meta-Research Article
                Custom metadata
                All relevant data are within the paper and its Supporting Information files. All authors had full access to all of the data (including statistical reports and tables) in the study and can take responsibility for the integrity of the data and accuracy of the data analysis.

                Life sciences
                Life sciences

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