期刊论文详细信息
Journal of Biomedical Semantics
OAE: The Ontology of Adverse Events
Barry Smith4  Cui Tao1  Luca Toldo3  Desikan Jagannathan5  Shelley Zhang5  Abra Guo5  Zuoshuang Xiang5  Yu Lin5  Sirarat Sarntivijai2  Yongqun He5 
[1] University at Texas Health Science Center at Houston, Houston, TX, USA;US Food and Drug Administration, Silver Spring, MD, USA;Merck KGaA, Darmstadt, Germany;University at Buffalo, Buffalo, NY, USA;University of Michigan, Ann Arbor, MI, USA
关键词: Design pattern;    Drug adverse event;    VAERS;    Vaccine adverse event;    Drug;    Vaccine;    Ontology;    Adverse event;    OAE;    Ontology of Adverse Events;   
Others  :  1135943
DOI  :  10.1186/2041-1480-5-29
 received in 2013-06-22, accepted in 2014-06-27,  发布年份 2014
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【 摘 要 】

Background

A medical intervention is a medical procedure or application intended to relieve or prevent illness or injury. Examples of medical interventions include vaccination and drug administration. After a medical intervention, adverse events (AEs) may occur which lie outside the intended consequences of the intervention. The representation and analysis of AEs are critical to the improvement of public health.

Description

The Ontology of Adverse Events (OAE), previously named Adverse Event Ontology (AEO), is a community-driven ontology developed to standardize and integrate data relating to AEs arising subsequent to medical interventions, as well as to support computer-assisted reasoning. OAE has over 3,000 terms with unique identifiers, including terms imported from existing ontologies and more than 1,800 OAE-specific terms. In OAE, the term ‘adverse event’ denotes a pathological bodily process in a patient that occurs after a medical intervention. Causal adverse events are defined by OAE as those events that are causal consequences of a medical intervention. OAE represents various adverse events based on patient anatomic regions and clinical outcomes, including symptoms, signs, and abnormal processes. OAE has been used in the analysis of several different sorts of vaccine and drug adverse event data. For example, using the data extracted from the Vaccine Adverse Event Reporting System (VAERS), OAE was used to analyse vaccine adverse events associated with the administrations of different types of influenza vaccines. OAE has also been used to represent and classify the vaccine adverse events cited in package inserts of FDA-licensed human vaccines in the USA.

Conclusion

OAE is a biomedical ontology that logically defines and classifies various adverse events occurring after medical interventions. OAE has successfully been applied in several adverse event studies. The OAE ontological framework provides a platform for systematic representation and analysis of adverse events and of the factors (e.g., vaccinee age) important for determining their clinical outcomes.

【 授权许可】

   
2014 He et al.; licensee BioMed Central Ltd.

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【 参考文献 】
  • [1]Scheuermann RH, Ceusters W, Smith B: Toward an Ontological Treatment of Disease and Diagnosis. Proceedings of the 2009 AMIA Summit on Translational Bioinformatics 2009, 116-120.
  • [2]Varricchio F, Iskander J, Destefano F, Ball R, Pless R, Braun MM, Chen RT: Understanding vaccine safety information from the Vaccine Adverse Event Reporting System. Pediatr Infect Dis J 2004, 23(4):287-294.
  • [3]FDA U: FDA Adverse Event Reporting System (FAERS) (formerly AERS). 2013. URL: http://www.fda.gov/Drugs/GuidanceComplianceRegulatoryInformation/Surveillance/AdverseDrugEffects/default.htm webcite, accessed on June 21, 2013
  • [4]Brown EG, Wood L, Wood S: The medical dictionary for regulatory activities (MedDRA). Drug Saf 1999, 20(2):109-117.
  • [5]NCI Common Terminology Criteria for Adverse Events (CTCAE) http://ctep.cancer.gov/reporting/ctc.html webcite. Accessed on May 15, 2013
  • [6]WHO’s Adverse Reaction Terminology (WHO-ART) http://www.nlm.nih.gov/research/umls/sourcereleasedocs/current/WHO/ webcite. Accessed on March 17, 2013
  • [7]Brown EG: Methods and pitfalls in searching drug safety databases utilising the Medical Dictionary for Regulatory Activities (MedDRA). Drug Saf 2003, 26(3):145-158.
  • [8]Sarntivijai S, Xiang Z, Shedden KA, Markel H, Omenn GS, Athey BD, He Y: Ontology-based combinatorial comparative analysis of adverse events associated with killed and live influenza vaccines. PLoS One 2012, 7(11):e49941.
  • [9]He Y, Cowell L, Diehl AD, Mobley HL, Peters B, Ruttenberg A, Scheuermann RH, Brinkman RR, Courtot M, Mungall C, Xiang Z, Chen F, Todd T, Colby LA, Rush H, Whetzel T, Musen MA, Athey BD, Omenn GS, Smith B: VO: Vaccine Ontology. In The 1st International Conference on Biomedical Ontology (ICBO-2009): July 24–26 2009. Buffalo, NY, USA: Nature Precedings; 2009. http://precedings.nature.com/documents/3552/version/1 webcite
  • [10]Lin Y, He Y: Ontology representation and analysis of vaccine formulation and administration and their effects on vaccine immune responses. J Biomed Semantics 2012, 3(1):17.
  • [11]Ceusters W, Capolupo M, de Moor G, Devlies J, Smith B: An evolutionary approach to realism-based adverse event representations. Methods Inf Med 2011, 50(1):62-73.
  • [12]He Y, Xiang Z, Sarntivijai S, Toldo L, Ceusters W: AEO: a realism-based biomedical ontology for the representation of adverse events. In Adverse Event Representation Workshop, International Conference on Biomedical Ontologies (ICBO-2011): July 26–30 2011. Buffalo, NY, USA: CEUR Workshop Proceedings; 2011:309-315. http://ceur-ws.org/Vol-833/paper359.pdf webcite
  • [13]Courtot M, Brinkman RR, Ruttenberg A: The logic of surveillance guidelines: an analysis of vaccine adverse event reports from an ontological perspective. PLoS One 2014, 9(3):e92632.
  • [14]Hur J, Ozgur A, Xiang Z, He Y: Identification of fever and vaccine-associated gene interaction networks using ontology-based literature mining. J Biomed Semantics 2012, 3(1):18.
  • [15]Gurulingappa H, Mateen-Rajput A, Toldo L: Extraction of potential adverse drug events from medical case reports. J Biomed Semantics 2012, 3(1):15.
  • [16]Gurulingappa H, Rajput AM, Roberts A, Fluck J, Hofmann-Apitius M, Toldo L: Development of a benchmark corpus to support the automatic extraction of drug-related adverse effects from medical case reports. J Biomed Inform 2012, 45(5):885-892.
  • [17]Gurulingappa H, Toldo L, Rajput AM, Kors JA, Taweel A, Tayrouz Y: Automatic detection of adverse events to predict drug label changes using text and data mining techniques. Pharmacoepidemiol Drug Saf 2013, 22(11):1189-1194.
  • [18]Smith B, Ashburner M, Rosse C, Bard J, Bug W, Ceusters W, Goldberg LJ, Eilbeck K, Ireland A, Mungall CJ, Leontis N, Rocca-Serra P, Ruttenberg A, Sansone SA, Scheuermann RH, Shah N, Whetzel PL, Lewis S: The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol 2007, 25(11):1251-1255.
  • [19]Courtot M, Goldfain A, He Y, Ruttenberg A: Adverse Event Representation Workshop. International Conference on Biomedical Ontologies 2011 (ICBO 2011) 2011; University at Buffalo, NY 2011. http://icbo.buffalo.edu/2011/workshop/adverse-events webcite
  • [20]He Y, Toldo L, Burns G, Tao C, Abernethy DR: A 2012 Workshop: Vaccine and Drug Ontology in the Study of Mechanism and Effect (VDOSME 2012). J Biomed Semantics 2012, 3(1):12.
  • [21]Tao C, He Y, Arabandi S: A 2013 Workshop: Vaccine and Drug Ontology Studies (VDOS 2013). J Biomed Semantics 2014, 5(1):16.
  • [22]Zhou W, Pool V, Iskander JK, English-Bullard R, Ball R, Wise RP, Haber P, Pless RP, Mootrey G, Ellenberg SS, Braun MM, Chen RT: Surveillance for safety after immunization: Vaccine Adverse Event Reporting System (VAERS)–United States, 1991–2001. MMWR Surveill Summ 2003, 52(1):1-24.
  • [23]Burnstead B, Furlan G: Unifying drug safety and clinical databases. Curr Drug Saf 2013, 8(1):56-62.
  • [24]Smith B, Ceusters W: Ontological realism: A methodology for coordinated evolution of scientific ontologies. Appl Ontol 2010, 5:139-188.
  • [25]Xiang Z, Courtot M, Brinkman RR, Ruttenberg A, He Y: OntoFox: web-based support for ontology reuse. BMC Res Notes 2010, 3:175.
  • [26]Grenon P, Smith B: SNAP and SPAN: Towards Dynamic Spatial Ontology. Spat Cogn Comput 2004, 4(1):69-103.
  • [27]MacKenzie SH, Clark AC: Death by caspase dimerization. Adv Exp Med Biol 2012, 747:55-73.
  • [28]Marcos E, Zhao B, He Y: The Ontology of Vaccine Adverse Events (OVAE) and its usage in representing and analyzing adverse events associated with US-licensed human vaccines. J Biomed Semantics 2013, 4:40.
  • [29]Mungall CJ, Torniai C, Gkoutos GV, Lewis SE, Haendel MA: Uberon, an integrative multi-species anatomy ontology. Genome Biol 2012, 13(1):R5.
  • [30]Rosse C, Mejino JL Jr: A reference ontology for biomedical informatics: the Foundational Model of Anatomy. J Biomed Inform 2003, 36(6):478-500.
  • [31]NCBI Taxonomy ontology http://www.obofoundry.org/cgi-bin/detail.cgi?id=ncbi_taxonomy webcite. Accessed on March 17, 2013
  • [32]Naranjo CA, Busto U, Sellers EM, Sandor P, Ruiz I, Roberts EA, Janecek E, Domecq C, Greenblatt DJ: A method for estimating the probability of adverse drug reactions. Clin Pharmacol Ther 1981, 30(2):239-245.
  • [33]Evans SJ, Waller PC, Davis S: Use of proportional reporting ratios (PRRs) for signal generation from spontaneous adverse drug reaction reports. Pharmacoepidemiol Drug Saf 2001, 10(6):483-486.
  • [34]Heaney RP, Kopecky S, Maki KC, Hathcock J, Mackay D, Wallace TC: A review of calcium supplements and cardiovascular disease risk. Advances in nutrition 2012, 3(6):763-771.
  • [35]Pearl J: Causality (2nd edition). Cambridge University Press; 2009.
  • [36]Tao C, He Y, Yang H, Gregory PA, Chute CG: Ontology-based time information representation of vaccine adverse events in VAERS for temporal analysis. J Biomed Semantics 2012, 3(1):13.
  • [37]Lin Y, He Y: The Ontology of Genetic Susceptibility Factors (OGSF) and its application in modeling genetic susceptibility to vaccine adverse events. J Biomed Semantics 2014, 5:19.
  • [38]The protege ontology editor http://protege.stanford.edu/ webcite
  • [39]Tao C, Wei WQ, Solbrig HR, Savova G, Chute CG: CNTRO: A Semantic Web Ontology for Temporal Relation Inferencing in Clinical Narratives. AMIA Annu Symp Proc 2010, 2010:787-791.
  • [40]U.S. Food and Drug Administration: Vaccines Licensed for Immunization and Distribution in the US with Supporting Documents. URL: http://www.fda.gov/BiologicsBloodVaccines/Vaccines/ApprovedProducts/UCM093830.htm webcite, accessed on April 3, 2013
  • [41]US FDA Afluria package insert information URL: http://www.fda.gov/downloads/BiologicsBloodVaccines/Vaccines/ApprovedProducts/UCM263239.pdf webcite. Accessed on April 18, 2014
  • [42]Vrethem M, Malmgren K, Lindh J: A patient with both narcolepsy and multiple sclerosis in association with Pandemrix vaccination. J Neurol Sci 2012, 321(1–2):89-91.
  • [43]Reif DM, McKinney BA, Motsinger AA, Chanock SJ, Edwards KM, Rock MT, Moore JH, Crowe JE: Genetic basis for adverse events after smallpox vaccination. J Infect Dis 2008, 198(1):16-22.
  • [44]He Y: Updates on the development of the Ontology of Adverse Events (OAE) and its applications. In The 2012 Vaccine and Drug Oontology in the Study of Mechanism and Effect (VDOSME) workshop. Graz, Austria; 2012. http://kr-med.org/icbofois2012/vdosme/docs/presentations/OAE_VDOSME2012_He.pdf webcite
  • [45]Abernethy DR, Woodcock J, Lesko LJ: Pharmacological mechanism-based drug safety assessment and prediction. Clin Pharmacol Ther 2011, 89(6):793-797.
  • [46]Bai JP, Abernethy DR: Systems pharmacology to predict drug toxicity: integration across levels of biological organization. Annu Rev Pharmacol Toxicol 2013, 53:451-473.
  • [47]Sarntivijai S, Lin Y, Blair E, Burkhart KK, He Y, Omenn GS, Athey BD, Abernethy DR: The ontology representation of adverse events with composite symptoms: expanding Ontology of Adverse Events to describe drug-induced cardiotoxicity. In American Society for Clinical Pharmacology and Therapeutics 2014 Annual Meeting (ASCPT-2014). Atlanta, Georgia; 2014. http://www.ascpt.org/Portals/8/docs/Meetings/2014%2020Annual%2020Meeting/Speaker%2020Presentations/Thursday/TKI_Sirarat%2020Sarntivijai.pdf webcite
  • [48]Sarntivijai S, Hur J, Ozgur A, Burkhart KK, He Y, Omenn GS, Athey BD, Abernethy DR: Predicting gene interactions of tyrosine kinase inhibitor-induced cardiotoxicity with ontology of adverse events-assisted bioinformatics. In American Society for Clinical Pharmacology and Therapeutics 2014 Annual Meeting (ASCPT-2014). Atlanta, Georgia; 2014.
  • [49]Bousquet C, Henegar C, Louet AL, Degoulet P, Jaulent MC: Implementation of automated signal generation in pharmacovigilance using a knowledge-based approach. Int J Med Inform 2005, 74(7–8):563-571.
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