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Linking MedDRA®-Coded Clinical Phenotypes to Biological Mechanisms by the Ontology of Adverse Events: A Pilot Study on Tyrosine Kinase Inhibitors

Overview of attention for article published in Drug Safety, March 2016
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Title
Linking MedDRA®-Coded Clinical Phenotypes to Biological Mechanisms by the Ontology of Adverse Events: A Pilot Study on Tyrosine Kinase Inhibitors
Published in
Drug Safety, March 2016
DOI 10.1007/s40264-016-0414-0
Pubmed ID
Authors

Sirarat Sarntivijai, Shelley Zhang, Desikan G. Jagannathan, Shadia Zaman, Keith K. Burkhart, Gilbert S. Omenn, Yongqun He, Brian D. Athey, Darrell R. Abernethy

Abstract

A translational bioinformatics challenge exists in connecting population and individual clinical phenotypes in various formats to biological mechanisms. The Medical Dictionary for Regulatory Activities (MedDRA(®)) is the default dictionary for adverse event (AE) reporting in the US Food and Drug Administration Adverse Event Reporting System (FAERS). The ontology of adverse events (OAE) represents AEs as pathological processes occurring after drug exposures. The aim of this work was to establish a semantic framework to link biological mechanisms to phenotypes of AEs by combining OAE with MedDRA(®) in FAERS data analysis. We investigated the AEs associated with tyrosine kinase inhibitors (TKIs) and monoclonal antibodies (mAbs) targeting tyrosine kinases. The five selected TKIs/mAbs (i.e., dasatinib, imatinib, lapatinib, cetuximab, and trastuzumab) are known to induce impaired ventricular function (non-QT) cardiotoxicity. Statistical analysis of FAERS data identified 1053 distinct MedDRA(®) terms significantly associated with TKIs/mAbs, where 884 did not have corresponding OAE terms. We manually annotated these terms, added them to OAE by the standard OAE development strategy, and mapped them to MedDRA(®). The data integration to provide insights into molecular mechanisms of drug-associated AEs was performed by including linkages in OAE for all related AE terms to MedDRA(®) and the existing ontologies, including the human phenotype ontology (HP), Uber anatomy ontology (UBERON), and gene ontology (GO). Sixteen AEs were shared by all five TKIs/mAbs, and each of 17 cardiotoxicity AEs was associated with at least one TKI/mAb. As an example, we analyzed "cardiac failure" using the relations established in OAE with other ontologies and demonstrated that one of the biological processes associated with cardiac failure maps to the genes associated with heart contraction. By expanding the existing OAE ontological design, our TKI use case demonstrated that the combination of OAE and MedDRA(®) provides a semantic framework to link clinical phenotypes of adverse drug events to biological mechanisms.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Netherlands 1 2%
Unknown 39 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 27%
Student > Ph. D. Student 8 20%
Student > Master 5 12%
Student > Doctoral Student 5 12%
Student > Bachelor 3 7%
Other 3 7%
Unknown 6 15%
Readers by discipline Count As %
Computer Science 9 22%
Medicine and Dentistry 7 17%
Pharmacology, Toxicology and Pharmaceutical Science 6 15%
Biochemistry, Genetics and Molecular Biology 3 7%
Agricultural and Biological Sciences 2 5%
Other 7 17%
Unknown 7 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 March 2016.
All research outputs
#15,365,885
of 22,858,915 outputs
Outputs from Drug Safety
#1,398
of 1,697 outputs
Outputs of similar age
#179,976
of 300,114 outputs
Outputs of similar age from Drug Safety
#24
of 25 outputs
Altmetric has tracked 22,858,915 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,697 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one is in the 11th percentile – i.e., 11% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 300,114 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.