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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 signalled 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 meta-analysis framework for signalling rare side effects that integrates existing methods, knowledge from the web, metric learning and semi-supervised 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 drug investigated it generated signals for rare side effects at a more stringent signalling threshold than existing methods and shows the potential to become a fundamental part of post marketing surveillance to detect rare side effects.
Highlights
Negative side effects caused by prescribed medication currently present a huge burden for the healthcare service in terms of causing both patient morbidity or mortality and costing large sums of money [1] [2] [3]
As Electronic Healthcare Database (EHD) do not contain links between drugs and suspected Adverse Drug Reaction (ADR) these are often inferred by investigating medical events that occur within some time period around a drug, but many of these medical events are linked to the cause of taking the drug and these ‘therapeutically related’ medical events present a major issue with the majority of the existing methods
The focus of this paper is to develop a method for detecting rare ADRs that occur shortly after prescription, so we can restrict our attention to the medical events that occur around the time of the drug prescription
Summary
Negative side effects caused by prescribed medication currently present a huge burden for the healthcare service in terms of causing both patient morbidity or mortality and costing large sums of money [1] [2] [3]. Investigations have shown that the rate of unwanted side effects has been increasing annually [4] [5] Possible reasons for this are an increase in the number of annual prescriptions due to an aging population or an increase in polypharmacy, when numerous drugs are prescribed at the same time [6]. A study conducted in the UK between November 2001 to April 2002 indicated that 6.5% of admissions to hospital were due to ADRs, with the mortality rate for an ADR patient of 2.3% [7]. It highlighted that a significant factor for developing an ADR was polypharmacy [8], when patients are prescribed multiple drugs
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