ArticleDrug safety2016
Evidence of Misclassification of Drug-Event Associations Classified as Gold Standard 'Negative Controls' by the Observational Medical Outcomes Partnership (OMOP).
Article in Drug safety, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
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- Exploring the impact of design criteria for reference sets on performance evaluation of signal detection algorithms: The case of drug-drug interactions.Pharmacoepidemiology and drug safety · 2023Article
- A Data-Driven Reference Standard for Adverse Drug Reaction (RS-ADR) Signal Assessment: Development and Validation.Journal of medical Internet research · 2022Article
- Detecting early safety signals of infliximab using machine learning algorithms in the Korea adverse event reporting system.Scientific reports · 2022Article
- Using computable knowledge mined from the literature to elucidate confounders for EHR-based pharmacovigilance.Journal of biomedical informatics · 2021Article
- Leveraging the Variability of Pharmacovigilance Disproportionality Analyses to Improve Signal Detection Performances.Frontiers in pharmacology · 2021Article
- Machine Learning for Detection of Safety Signals From Spontaneous Reporting System Data: Example of Nivolumab and Docetaxel.Frontiers in pharmacology · 2020Article
- Web-Based Signal Detection Using Medical Forums Data in France: Comparative Analysis.Journal of medical Internet research · 2018Article
- An MCEM Framework for Drug Safety Signal Detection and Combination from Heterogeneous Real World Evidence.Scientific reports · 2018Article
- Toward multimodal signal detection of adverse drug reactions.Journal of biomedical informatics · 2017Article
- Accuracy of an automated knowledge base for identifying drug adverse reactions.Journal of biomedical informatics · 2017Article
- Revisiting the reported signal of acute pancreatitis with rasburicase: an object lesson in pharmacovigilance.Therapeutic advances in drug safety · 2016Article
- Measuring Signal Detection Performance: Can We Trust Negative Controls and Do We Need Them?Drug safety · 2016Review
- Data-Driven Prediction of Beneficial Drug Combinations in Spontaneous Reporting Systems.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016Article
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3 authors.
Funding
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Abstract
introductionPharmacovigilance includes analysis of large databases of information on drugs and events using algorithms that detect disproportional frequencies of associations. In order to test such algorithms, attempts have been made to provide canonical reference lists of so-called 'positive controls' and 'negative controls'. Reference sets with even modest levels of misclassification may result in under- or overstatement of the performance of algorithms.
aimWe sought to determine the extent to which 'negative control' drug-event pairs in the Observational Medical Outcomes Partnership (OMOP) database are misclassified
methodsWe searched the medical literature for evidence of associations between drugs and events listed by OMOP as negative controls.
resultsThe criteria used in OMOP to classify positive and negative controls are asymmetric; drug-event associations published only as case series or case reports are classified as positive controls if they are cited in Drug-Induced Diseases by Tisdale and Miller, but as negative controls if case series or case reports exist but are not cited in Tisdale and Miller. Of 233 drug-event pairs classified in the 2013 version of OMOP as negative controls, 21 failed to meet pre-specified OMOP adjudication criteria; in another 19 cases we found case reports, case series, or observational evidence that the drug and event are associated. Overall, OMOP misclassified, or may have misclassified, 40 (17 %) of all 'negative controls.'
conclusionsResults from studies of the performance of signal-detection algorithms based on the OMOP gold standard should be viewed with circumspection, because imperfect gold standards may lead to under/overstatement of absolute and relative signal detection algorithm performance. Improvements to OMOP would include omitting misclassified drug-event pairs, assigning more specific event labels, and using more extensive sources of information.
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