1. Data quality assessment of interventional trials in public trial databases.
- Author
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Iken AR, Poolman RW, and Gademan MGJ
- Subjects
- Humans, Registries standards, Registries statistics & numerical data, Research Design standards, Data Accuracy, Arthroplasty, Replacement, Knee statistics & numerical data, Arthroplasty, Replacement, Knee standards, Clinical Trials as Topic standards, Databases, Factual standards
- Abstract
Objective: High-quality data entry in clinical trial databases is crucial to the usefulness, validity, and replicability of research findings, as it influences evidence-based medical practice and future research. Our aim is to assess the quality of self-reported data in trial registries and present practical and systematic methods for identifying and evaluating data quality., Study Design and Setting: We searched ClinicalTrials.Gov (CTG) for interventional total knee arthroplasty (TKA) trials between 2000 and 2015. We extracted required and optional trial information elements and used the CTG's variables' definitions. We performed a literature review on data quality reporting on frameworks, checklists, and overviews of irregularities in healthcare databases. We identified and assessed data quality attributes as follows: consistency, accuracy, completeness, and timeliness., Results: We included 816 interventional TKA trials. Data irregularities varied widely: 0%-100%. Inconsistency ranged from 0% to 36%, and most often nonrandomized labeled allocation was combined with a "single-group" assignment trial design. Inaccuracy ranged from 0% to 100%. Incompleteness ranged from 0% to 61%; 61% of finished TKA trials did not report their outcome. With regard to irregularities in timeliness, 49% of the trials were registered more than 3 months after the start date., Conclusion: We found significant variations in the data quality of registered clinical TKA trials. Trial sponsors should be committed to ensuring that the information they provide is reliable, consistent, up-to-date, transparent, and accurate. CTG's users need to be critical when drawing conclusions based on the registered data. We believe this awareness will increase well-informed decisions about published articles and treatment protocols, including replicating and improving trial designs., Competing Interests: Declaration of competing interest There are no competing interests for all the authors., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)
- Published
- 2024
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