Research techniques made simple: workflow for searching databases to reduce evidence selection bias in systematic reviews
Clinical trials and basic science studies without statistically significant results are less likely to be published than studies with statistically significant results. Systematic reviews and meta-analyses that omit unpublished data are at high risk of distorted conclusions. Here, we describe method...
| Main Authors: | , , , , |
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| Format: | Article |
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Nature Publishing Group
2016
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| Online Access: | https://eprints.nottingham.ac.uk/39661/ |
| _version_ | 1848795886116667392 |
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| author | Le Cleach, Laurence Doney, Elizabeth Katz, Kenneth A. Williams, Hywel C. Trinquart, Ludovic |
| author_facet | Le Cleach, Laurence Doney, Elizabeth Katz, Kenneth A. Williams, Hywel C. Trinquart, Ludovic |
| author_sort | Le Cleach, Laurence |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Clinical trials and basic science studies without statistically significant results are less likely to be published than studies with statistically significant results. Systematic reviews and meta-analyses that omit unpublished data are at high risk of distorted conclusions. Here, we describe methods to search beyond bibliographical databases to reduce evidence selection bias in systematic reviews. Unpublished studies may be identified by searching conference proceedings. Moreover, clinical trial registries—databases of planned and ongoing trials—and regulatory agency websites such as the European Medicine Agency (EMA) and the United States Food and Drug Administration (FDA) may provide summaries of efficacy and safety data. Primary and secondary outcomes are prespecified in trial registries, thus allowing the assessment of outcome reporting bias by comparison with the trial report. The sources of trial data and documents are still evolving, with ongoing initiatives promoting broader access to clinical study reports and individual patient data. There is currently no established methodology to ensure that the multiple sources of information are incorporated. Nonetheless, systematic reviews must adapt to these improvements and cover the new sources in their search strategies. |
| first_indexed | 2025-11-14T19:39:12Z |
| format | Article |
| id | nottingham-39661 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:39:12Z |
| publishDate | 2016 |
| publisher | Nature Publishing Group |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-396612020-05-04T18:23:37Z https://eprints.nottingham.ac.uk/39661/ Research techniques made simple: workflow for searching databases to reduce evidence selection bias in systematic reviews Le Cleach, Laurence Doney, Elizabeth Katz, Kenneth A. Williams, Hywel C. Trinquart, Ludovic Clinical trials and basic science studies without statistically significant results are less likely to be published than studies with statistically significant results. Systematic reviews and meta-analyses that omit unpublished data are at high risk of distorted conclusions. Here, we describe methods to search beyond bibliographical databases to reduce evidence selection bias in systematic reviews. Unpublished studies may be identified by searching conference proceedings. Moreover, clinical trial registries—databases of planned and ongoing trials—and regulatory agency websites such as the European Medicine Agency (EMA) and the United States Food and Drug Administration (FDA) may provide summaries of efficacy and safety data. Primary and secondary outcomes are prespecified in trial registries, thus allowing the assessment of outcome reporting bias by comparison with the trial report. The sources of trial data and documents are still evolving, with ongoing initiatives promoting broader access to clinical study reports and individual patient data. There is currently no established methodology to ensure that the multiple sources of information are incorporated. Nonetheless, systematic reviews must adapt to these improvements and cover the new sources in their search strategies. Nature Publishing Group 2016-12-31 Article PeerReviewed Le Cleach, Laurence, Doney, Elizabeth, Katz, Kenneth A., Williams, Hywel C. and Trinquart, Ludovic (2016) Research techniques made simple: workflow for searching databases to reduce evidence selection bias in systematic reviews. Journal of Investigative Dermatology, 136 (12). e125-e129. ISSN 1523-1747 http://dx.doi.org/10.1016/j.jid.2016.09.019 doi:10.1016/j.jid.2016.09.019 doi:10.1016/j.jid.2016.09.019 |
| spellingShingle | Le Cleach, Laurence Doney, Elizabeth Katz, Kenneth A. Williams, Hywel C. Trinquart, Ludovic Research techniques made simple: workflow for searching databases to reduce evidence selection bias in systematic reviews |
| title | Research techniques made simple: workflow for searching databases to reduce evidence selection bias in systematic reviews |
| title_full | Research techniques made simple: workflow for searching databases to reduce evidence selection bias in systematic reviews |
| title_fullStr | Research techniques made simple: workflow for searching databases to reduce evidence selection bias in systematic reviews |
| title_full_unstemmed | Research techniques made simple: workflow for searching databases to reduce evidence selection bias in systematic reviews |
| title_short | Research techniques made simple: workflow for searching databases to reduce evidence selection bias in systematic reviews |
| title_sort | research techniques made simple: workflow for searching databases to reduce evidence selection bias in systematic reviews |
| url | https://eprints.nottingham.ac.uk/39661/ https://eprints.nottingham.ac.uk/39661/ https://eprints.nottingham.ac.uk/39661/ |