A Novel Semisupervised Algorithm for Rare Prescription Side Effect Discovery

Reps, J.M., Garibaldi, J.M., Aickelin, U., Soria, D., Gibson, J.E. and Hubbard, R.B. 2014. A Novel Semisupervised Algorithm for Rare Prescription Side Effect Discovery. IEEE Journal of Biomedical and Health Informatics. 18 (2), pp. 537-547. https://doi.org/10.1109/JBHI.2013.2281505

TitleA Novel Semisupervised Algorithm for Rare Prescription Side Effect Discovery
AuthorsReps, J.M., Garibaldi, J.M., Aickelin, U., Soria, D., Gibson, J.E. and Hubbard, R.B.
Abstract

Drugs are frequently prescribed to patients with the aim of improving each patient's medical state, but an unfortunate consequence of most prescription drugs is the occurrence of undesirable side effects. Side effects that occur in more than one in a thousand patients are likely to be signaled efficiently by current drug surveillance methods, however, these same methods may take decades before generating signals for rarer side effects, risking medical morbidity or mortality in patients prescribed the drug while the rare side effect is undiscovered. In this paper, we propose a novel computational metaanalysis framework for signaling rare side effects that integrates existing methods, knowledge from the web, metric learning, and semisupervised clustering. The novel framework was able to signal many known rare and serious side effects for the selection of drugs investigated, such as tendon rupture when prescribed Ciprofloxacin or Levofloxacin, renal failure with Naproxen and depression associated with Rimonabant. Furthermore, for the majority of the drugs investigated it generated signals for rare side effects at a more stringent signaling threshold than existing methods and shows the potential to become a fundamental part of post marketing surveillance to detect rare side effects.

JournalIEEE Journal of Biomedical and Health Informatics
Journal citation18 (2), pp. 537-547
ISSN2168-2194
Year2014
PublisherIEEE
Digital Object Identifier (DOI)https://doi.org/10.1109/JBHI.2013.2281505
Publication dates
Published online11 Sep 2013
Published in printMar 2014

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