Toward multimodal signal detection of adverse drug reactions

Autor: Nigam H. Shah, Ryen W. White, William DuMouchel, Anna Ripple, Carol Friedman, Martijn J. Schuemie, Rainer Winnenburg, Alfred Sorbello, Eric Horvitz, Olivier Bodenreider, Rave Harpaz
Rok vydání: 2017
Předmět:
Zdroj: J Biomed Inform
ISSN: 1532-0480
Popis: Display Omitted Improving signal detection is key to strengthening drug safety surveillance.Multimodal signal detection (MSD) is based on jointly analyzing multiple data sources.This manuscript broadens evaluations of MSD done in prior studies.The results provide support for MSD, but its ultimate utility cannot currently be proven.Further research is needed to determine the ultimate utility of MSD. ObjectiveImproving mechanisms to detect adverse drug reactions (ADRs) is key to strengthening post-marketing drug safety surveillance. Signal detection is presently unimodal, relying on a single information source. Multimodal signal detection is based on jointly analyzing multiple information sources. Building on, and expanding the work done in prior studies, the aim of the article is to further research on multimodal signal detection, explore its potential benefits, and propose methods for its construction and evaluation. Material and methodsFour data sources are investigated; FDAs adverse event reporting system, insurance claims, the MEDLINE citation database, and the logs of major Web search engines. Published methods are used to generate and combine signals from each data source. Two distinct reference benchmarks corresponding to well-established and recently labeled ADRs respectively are used to evaluate the performance of multimodal signal detection in terms of area under the ROC curve (AUC) and lead-time-to-detection, with the latter relative to labeling revision dates. ResultsLimited to our reference benchmarks, multimodal signal detection provides AUC improvements ranging from 0.04 to 0.09 based on a widely used evaluation benchmark, and a comparative added lead-time of 722 months relative to labeling revision dates from a time-indexed benchmark. ConclusionsThe results support the notion that utilizing and jointly analyzing multiple data sources may lead to improved signal detection. Given certain data and benchmark limitations, the early stage of development, and the complexity of ADRs, it is currently not possible to make definitive statements about the ultimate utility of the concept. Continued development of multimodal signal detection requires a deeper understanding the data sources used, additional benchmarks, and further research on methods to generate and synthesize signals.
Databáze: OpenAIRE
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