Obstacles to the reuse of study metadata in ClinicalTrials.gov. Miron, L., Gonçalves, R. S., & Musen, M. A. Scientific Data, 7(1):443, December, 2020. ![Obstacles to the reuse of study metadata in ClinicalTrials.gov [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Abstract Metadata that are structured using principled schemas and that use terms from ontologies are essential to making biomedical data findable and reusable for downstream analyses. The largest source of metadata that describes the experimental protocol, funding, and scientific leadership of clinical studies is ClinicalTrials.gov. We evaluated whether values in 302,091 trial records adhere to expected data types and use terms from biomedical ontologies, whether records contain fields required by government regulations, and whether structured elements could replace free-text elements. Contact information, outcome measures, and study design are frequently missing or underspecified. Important fields for search, such as c ondition and intervention , are not restricted to ontologies, and almost half of the conditions are not denoted by MeSH terms, as recommended. Eligibility criteria are stored as semi-structured free text. Enforcing the presence of all required elements, requiring values for certain fields to be drawn from ontologies, and creating a structured eligibility criteria element would improve the reusability of data from ClinicalTrials.gov in systematic reviews, metanalyses, and matching of eligible patients to trials.
@article{miron_obstacles_2020,
title = {Obstacles to the reuse of study metadata in {ClinicalTrials}.gov},
volume = {7},
issn = {2052-4463},
url = {http://www.nature.com/articles/s41597-020-00780-z},
doi = {10.1038/s41597-020-00780-z},
abstract = {Abstract
Metadata that are structured using principled schemas and that use terms from ontologies are essential to making biomedical data findable and reusable for downstream analyses. The largest source of metadata that describes the experimental protocol, funding, and scientific leadership of clinical studies is ClinicalTrials.gov. We evaluated whether values in 302,091 trial records adhere to expected data types and use terms from biomedical ontologies, whether records contain fields required by government regulations, and whether structured elements could replace free-text elements. Contact information, outcome measures, and study design are frequently missing or underspecified. Important fields for search, such as c
ondition
and
intervention
, are not restricted to ontologies, and almost half of the
conditions
are not denoted by MeSH terms, as recommended. Eligibility criteria are stored as semi-structured free text. Enforcing the presence of all required elements, requiring values for certain fields to be drawn from ontologies, and creating a structured
eligibility criteria
element would improve the reusability of data from ClinicalTrials.gov in systematic reviews, metanalyses, and matching of eligible patients to trials.},
language = {en},
number = {1},
urldate = {2022-05-27},
journal = {Scientific Data},
author = {Miron, Laura and Gonçalves, Rafael S. and Musen, Mark A.},
month = dec,
year = {2020},
keywords = {Clinical Trials as Topic, Databases, Factual, Metadata},
pages = {443},
}
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