Presenting and sharing clinical data using the eTRIKS Standards Master Tree for tranSMART. Barbosa-Silva, A., Bratfalean, D., Gu, W., Satagopam, V., Houston, P., Becnel, L. B., Eifes, S., Richard, F., Tielmann, A., Herzinger, S., Rege, K., Balling, R., Peeters, P., & Schneider, R. Bioinformatics (Oxford, England), 35(9):1562–1565, May, 2019.
doi  abstract   bibtex   
MOTIVATION: Standardization and semantic alignment have been considered one of the major challenges for data integration in clinical research. The inclusion of the CDISC SDTM clinical data standard into the tranSMART i2b2 via a guiding master ontology tree positively impacts and supports the efficacy of data sharing, visualization and exploration across datasets. RESULTS: We present here a schema for the organization of SDTM variables into the tranSMART i2b2 tree along with a script and test dataset to exemplify the mapping strategy. The eTRIKS master tree concept is demonstrated by making use of fictitious data generated for four patients, including 16 SDTM clinical domains. We describe how the usage of correct visit names and data labels can help to integrate multiple readouts per patient and avoid ETL crashes when running a tranSMART loading routine. AVAILABILITY AND IMPLEMENTATION: The eTRIKS Master Tree package and test datasets are publicly available at https://doi.org/10.5281/zenodo.1009098 and a functional demo installation at https://public.etriks.org/transmart/datasetExplorer/ under eTRIKS-Master Tree branch, where the discussed examples can be visualized.
@article{barbosa-silva_presenting_2019,
	title = {Presenting and sharing clinical data using the {eTRIKS} {Standards} {Master} {Tree} for {tranSMART}.},
	volume = {35},
	copyright = {© The Author(s) 2018. Published by Oxford University Press.},
	issn = {1367-4811 1367-4803},
	doi = {10.1093/bioinformatics/bty809},
	abstract = {MOTIVATION: Standardization and semantic alignment have been considered one of the major challenges for data integration in clinical research. The inclusion of the  CDISC SDTM clinical data standard into the tranSMART i2b2 via a guiding master  ontology tree positively impacts and supports the efficacy of data sharing,  visualization and exploration across datasets. RESULTS: We present here a schema for  the organization of SDTM variables into the tranSMART i2b2 tree along with a script  and test dataset to exemplify the mapping strategy. The eTRIKS master tree concept  is demonstrated by making use of fictitious data generated for four patients,  including 16 SDTM clinical domains. We describe how the usage of correct visit names  and data labels can help to integrate multiple readouts per patient and avoid ETL  crashes when running a tranSMART loading routine. AVAILABILITY AND IMPLEMENTATION:  The eTRIKS Master Tree package and test datasets are publicly available at  https://doi.org/10.5281/zenodo.1009098 and a functional demo installation at  https://public.etriks.org/transmart/datasetExplorer/ under eTRIKS-Master Tree  branch, where the discussed examples can be visualized.},
	language = {eng},
	number = {9},
	journal = {Bioinformatics (Oxford, England)},
	author = {Barbosa-Silva, Adriano and Bratfalean, Dorina and Gu, Wei and Satagopam, Venkata and Houston, Paul and Becnel, Lauren B. and Eifes, Serge and Richard, Fabien and Tielmann, Andreas and Herzinger, Sascha and Rege, Kavita and Balling, Rudi and Peeters, Paul and Schneider, Reinhard},
	month = may,
	year = {2019},
	pmid = {30256906},
	pmcid = {PMC6499239},
	keywords = {*Information Storage and Retrieval, Data Accuracy, Data Collection, Humans, Information Dissemination},
	pages = {1562--1565},
}

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