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Previously unidentified duplicate registrations of clinical trials: an exploratory analysis of registry data worldwide.

ABSTRACT: 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.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.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).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.

SUBMITTER: van Valkenhoef G

PROVIDER: S-EPMC4946209 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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Previously unidentified duplicate registrations of clinical trials: an exploratory analysis of registry data worldwide.

van Valkenhoef Gert G Loane Russell F RF Zarin Deborah A DA

Systematic reviews 20160715 1

<h4>Background</h4>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.<h4>Methods</h4 ...[more]

PMID: 27422636

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Project description:ImportanceDuplicate publications of randomized clinical trials are prevalent in the health-related literature. To date, few studies have assessed the interaction between duplicate publication and the language of the original publication.ObjectiveTo assess the existence of duplicate publication and the extent to which duplicate publication is associated with the language of the original publication.Design, setting, and participantsIn this retrospective cohort study, eligible randomized clinical trials were retrieved from trial registries, and bibliographic databases were searched to determine their publication status. Eligible randomized clinical trials were for drug interventions from January 1, 2008, to December 31, 2014. The search and analysis were conducted from March 1 to August 31, 2019. The trial registries were either primary registries recognized by the World Health Organization or the Drug Clinical Trial Registry Platform sponsored by the China Food and Drug Administration.ExposuresIndividual randomized clinical trials with positive vs negative results.Main outcomes and measuresJournal articles were classified as main articles (determined by largest sample size and longest follow-up among all journal articles derived from that randomized clinical trial) and duplicates. The duplicates were classified into 4 types: (1) unreferenced subgroup analysis (article did not disclose itself as a subgroup analysis or reference its main article); (2) unreferenced republication (article did not disclose itself as a replicate of the main article or reference it); (3) unreferenced interim analysis (article did not disclose itself as an interim analysis or reference its main article); and (4) partial duplicate (article did not disclose its sharing a subset of participants with other articles or reference them).ResultsAmong 470 randomized clinical trials published by August 2019 as journal articles, 55 (11.7%) had 75 duplicates, of which 53 (70.7%) were cross-language duplicates. Of the 75 duplicates, 33 (44.0%) were unreferenced republications, 25 (33.3%) unreferenced subgroup analyses, 15 (20.0%) unreferenced interim analyses, and 2 (2.7%) partial duplicates. When the main article of a randomized clinical trial was published in Chinese, those with positive findings were 2.48 (95% CI, 1.08-5.71) times more likely to have subsequent duplicate publication than those with negative findings.Conclusions and relevanceIn this study, most duplicates were cross-language duplicates and the most common type was unreferenced republication of the main article. Duplicate publication bias exists when the main articles of randomized clinical trials were published in Chinese, potentially misleading readers and compromising journals and evidence synthesis.

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Project description:BackgroundClinical Trials Registry - India (CTRI) was established in July 2007 and today hosts thousands of trials, a significant fraction of them registered in the last couple of years. We wished to undertake an up-to-date analysis of specific fields of the registered trials. In doing so we discovered problems with the quality of the data, which we describe in this paper.MethodsWe downloaded CTRI records and reformatted the data into an SQLite database, which we then queried. We also accessed ClinicalTrials.gov records as needed.ResultsWe discovered various categories of problems with the data in the CTRI database, including (1) a lack of clarity in the classification of Types of Study, (2) internal inconsistencies, (3) incomplete or non-standard information, (4) missing data, (5) variations in names or classification, and (6) incomplete or incorrect details of ethics committees. For most of these problems, error rates have been calculated, over time. Most were found to be in single digits, although others were significantly higher. We suggest how data quality in future editions of CTRI could be improved, including (1) a more elaborate and structured way of classifying the Type of Study, (2) the use of logic rules to prevent internal inconsistencies, (3) less use of free text fields and greater use of drop-down menus, (4) more fields to be made compulsory, (5) the pre-registration of individuals' and organizations' names and their subsequent selection from drop-down menus while registering a trial, and (6) more information about each ethics committee, including (a) its address and (b) linking the name of the trial site to the relevant ethics committee. As we discuss problems with the data of specific fields, we also examine - where possible - the quality of the data in the corresponding fields in ClinicalTrials.gov, the largest clinical trial registry in the world.ConclusionsIt is a scientific and ethical obligation to correctly record all information pertaining to each trial run in India. CTRI is a valuable database that has proved its worth in terms of improving the record of trials in the country. The suggestions made herein would improve it further.

Dataset Information

Previously unidentified duplicate registrations of clinical trials: an exploratory analysis of registry data worldwide.

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Previously unidentified duplicate registrations of clinical trials: an exploratory analysis of registry data worldwide.

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