Evidence map›Paper›PMID 31074377›Full record

ArticleBMC bioinformatics2019

ODAE: Ontology-based systematic representation and analysis of drug adverse events and its usage in study of adverse events given different patient age and disease conditions.

Hong Yu, Solomiya Nysak, Noemi Garg, Edison Ong, Xianwei Ye, Xiangyan Zhang, Yongqun He

Abstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Article
  3. An ontology-based tool for modeling and documenting events in neurosurgery.BMC medical informatics and decision making · 2024
    Article
  4. Review
  5. Article
  6. Article
  7. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Hong YuDepartment of Pulmonary and Critical Care Medicine, Guizhou Provincial People's Hospital, Guiyang, 550002, Guizhou, China. yuhong20040416@sina.com.
Solomiya NysakCollege of Literature, Science, and the Arts, University of Michigan, Ann Arbor, MI, 48109, USA.
Noemi GargCollege of Pharmacy, University of Michigan, Ann Arbor, MI, 48109, USA.
Edison OngDepartment of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, 48109, USA.
Xianwei YeDepartment of Pulmonary and Critical Care Medicine, Guizhou Provincial People's Hospital, Guiyang, 550002, Guizhou, China.
Xiangyan ZhangDepartment of Pulmonary and Critical Care Medicine, Guizhou Provincial People's Hospital, Guiyang, 550002, Guizhou, China.
Yongqun HeUnit for Laboratory Animal Medicine, Department of Microbiology and Immunology, Center for Computational Medicine and Bioinformatics, and Comprehensive Cancer Center, University of Michigan Medical School, Ann Arbor, MI, 48109, USA. yongqunh@med.umich.edu.

Funding

Ontology-based Information Network to Support Vaccine ResearchR01AI081062 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI HE, YONGQUN · 2009 to 2012
$1.1M
NIAID NIH HHS R01 AI081062
6 · The paper itself

Abstract

backgroundDrug adverse events (AEs), or called adverse drug events (ADEs), are ranked one of the leading causes of mortality. The Ontology of Adverse Events (OAE) has been widely used for adverse event AE representation, standardization, and analysis. OAE-based ADE-specific ontologies, including ODNAE for drug-associated neuropathy-inducing AEs and OCVDAE for cardiovascular drug AEs, have also been developed and used. However, these ADE-specific ontologies do not consider the effects of other factors (e.g., age and drug-treated disease) on the outcomes of ADEs. With more ontological studies of ADEs, it is also critical to develop a general purpose ontology for representing ADEs for various types of drugs.

resultsOur survey of FDA drug package insert documents and other resources for 224 neuropathy-inducing drugs discovered that many drugs (e.g., sirolimus and linezolid) cause different AEs given patients' age or the diseases treated by the drugs. To logically represent the complex relations among drug, drug ingredient and mechanism of action, AE, age, disease, and other related factors, an ontology design pattern was developed and applied to generate a community-driven open-source Ontology of Drug Adverse Events (ODAE). The ODAE development follows the OBO Foundry ontology development principles (e.g., openness and collaboration). Built on a generalizable ODAE design pattern and extending the OAE and NDF-RT ontology, ODAE has represented various AEs associated with the over 200 neuropathy-inducing drugs given different age and disease conditions. ODAE is now deposited in the Ontobee for browsing and queries. As a demonstration of usage, a SPARQL query of the ODAE knowledge base was developed to identify all the drugs having the mechanisms of ion channel interactions, the diseases treated with the drugs, and AEs after the treatment in adult patients. AE-specific drug class effects were also explored using ODAE and SPARQL.

conclusionODAE provides a general representation of ADEs given different conditions and can be used for querying scientific questions. ODAE is also a robust knowledge base and platform for semantic and logic representation and study of ADEs of more drugs in the future.

Indexed as

SoftwareAdultAdverse Drug Reaction Reporting SystemsAge FactorsAnti-Bacterial AgentsAntibiotics, AntineoplasticDrug-Related Side Effects and Adverse ReactionsHumansLinezolidNervous System DiseasesPharmaceutical PreparationsSirolimusAnti-Bacterial AgentsAntibiotics, AntineoplasticLinezolidPharmaceutical PreparationsSirolimusBioinformaticsDrugDrug adverse eventODAEOntologyOntology of drug adverse events

Identifiers

PMID31074377
PMCPMC6509876

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.