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Previously unidentified duplicate registrations of clinical trials: an exploratory analysis of registry data worldwide
BACKGROUND: Trial registries were established to combat publication bias by creating a comprehensive and unambiguous record of initiated clinical trials. However, the proliferation of registries and registration policies means that a single trial may be registered multiple times (i.e., “duplicates”)...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4946209/ https://www.ncbi.nlm.nih.gov/pubmed/27422636 http://dx.doi.org/10.1186/s13643-016-0283-8 |
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author | van Valkenhoef, Gert Loane, Russell F. Zarin, Deborah A. |
author_facet | van Valkenhoef, Gert Loane, Russell F. Zarin, Deborah A. |
author_sort | van Valkenhoef, Gert |
collection | PubMed |
description | BACKGROUND: Trial registries were established to combat publication bias by creating a comprehensive and unambiguous record of initiated clinical trials. However, the proliferation of registries and registration policies means that a single trial may be registered multiple times (i.e., “duplicates”). Because unidentified duplicates threaten our ability to identify trials unambiguously, we investigate to what degree duplicates have been identified across registries globally. METHODS: We retrieved all records from the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) search portal and made a list of all records identified as duplicates by the ICTRP. To investigate how to discriminate duplicates from non-duplicates, we applied text-based similarity scoring to various registration fields of both ICTRP-identified duplicates and arbitrary pairs of trials. We then used the best similarity measure to identify the most similar pairs of records and manually assessed a random sample of pairs not identified as duplicates by the ICTRP to estimate the number of previously unidentified (or “hidden”) duplicates. RESULTS: Two hundred eighty-five thousand unique records, or 271 thousand unique trials after accounting for known duplicates, were retrieved from the ICTRP portal in April 2015. We found that the title field best discriminated duplicates from non-duplicates. Out of 41 billion total pair-wise comparisons, we identified the 474,000 pairs of titles with the highest similarity scores (>0.5). After manually assessing a random sample of 434 pairs, we estimated that 45 % of all duplicate registrations currently go undetected and remain to be identified and confirmed as duplicates. Thus, the actual number of unique trials represented in this dataset is estimated to be approximately 258,000 (5 % less). CONCLUSIONS: The ICTRP portal does not currently enable the unambiguous identification of trials across registries. Further research is needed to identify and verify the duplicates that currently go undetected. Sponsors, registries, and the ICTRP should consider actions to ensure duplicate registrations are easily identifiable. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13643-016-0283-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4946209 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-49462092016-07-16 Previously unidentified duplicate registrations of clinical trials: an exploratory analysis of registry data worldwide van Valkenhoef, Gert Loane, Russell F. Zarin, Deborah A. Syst Rev Research BACKGROUND: Trial registries were established to combat publication bias by creating a comprehensive and unambiguous record of initiated clinical trials. However, the proliferation of registries and registration policies means that a single trial may be registered multiple times (i.e., “duplicates”). Because unidentified duplicates threaten our ability to identify trials unambiguously, we investigate to what degree duplicates have been identified across registries globally. METHODS: We retrieved all records from the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) search portal and made a list of all records identified as duplicates by the ICTRP. To investigate how to discriminate duplicates from non-duplicates, we applied text-based similarity scoring to various registration fields of both ICTRP-identified duplicates and arbitrary pairs of trials. We then used the best similarity measure to identify the most similar pairs of records and manually assessed a random sample of pairs not identified as duplicates by the ICTRP to estimate the number of previously unidentified (or “hidden”) duplicates. RESULTS: Two hundred eighty-five thousand unique records, or 271 thousand unique trials after accounting for known duplicates, were retrieved from the ICTRP portal in April 2015. We found that the title field best discriminated duplicates from non-duplicates. Out of 41 billion total pair-wise comparisons, we identified the 474,000 pairs of titles with the highest similarity scores (>0.5). After manually assessing a random sample of 434 pairs, we estimated that 45 % of all duplicate registrations currently go undetected and remain to be identified and confirmed as duplicates. Thus, the actual number of unique trials represented in this dataset is estimated to be approximately 258,000 (5 % less). CONCLUSIONS: The ICTRP portal does not currently enable the unambiguous identification of trials across registries. Further research is needed to identify and verify the duplicates that currently go undetected. Sponsors, registries, and the ICTRP should consider actions to ensure duplicate registrations are easily identifiable. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13643-016-0283-8) contains supplementary material, which is available to authorized users. BioMed Central 2016-07-15 /pmc/articles/PMC4946209/ /pubmed/27422636 http://dx.doi.org/10.1186/s13643-016-0283-8 Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), 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 (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research van Valkenhoef, Gert Loane, Russell F. Zarin, Deborah A. Previously unidentified duplicate registrations of clinical trials: an exploratory analysis of registry data worldwide |
title | Previously unidentified duplicate registrations of clinical trials: an exploratory analysis of registry data worldwide |
title_full | Previously unidentified duplicate registrations of clinical trials: an exploratory analysis of registry data worldwide |
title_fullStr | Previously unidentified duplicate registrations of clinical trials: an exploratory analysis of registry data worldwide |
title_full_unstemmed | Previously unidentified duplicate registrations of clinical trials: an exploratory analysis of registry data worldwide |
title_short | Previously unidentified duplicate registrations of clinical trials: an exploratory analysis of registry data worldwide |
title_sort | previously unidentified duplicate registrations of clinical trials: an exploratory analysis of registry data worldwide |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4946209/ https://www.ncbi.nlm.nih.gov/pubmed/27422636 http://dx.doi.org/10.1186/s13643-016-0283-8 |
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