Signal Detection from Spontaneous Reports

  • KUBOTA Kiyoshi
    Department of Pharmacoepidemiology, Faculty of Medicine, University of Tokyo

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Other Title
  • 自発報告からのシグナル検出
  • Signal detection from spontaneous reports - new Methods in MCA in the UK, FDA in the US and WHO
  • New Methods in MCA in the UK, FDA in the US and WHO
  • 英国MCA, 米国FDA, WHOの新しい方法

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Description

Objective : To outline new methods developed in Medicines Control Agency (MCA) in the UK, Food and Drug Administration (FDA) in the USA and WHO Uppsala Monitoring Centre (UMC) to detect signals from spontaneous reports on suspected drug reactions.<BR>Methods : Presentations in the Signal Generation Symposium (Southampton, UK, June 2001) and related articles identified by hand searching were examined.<BR>Results : All of the 3 methods compare the number or probability of reports on a particular drug-event combination with the expected number or probability for the combination. For example, in the MCA's method, the expected number is estimated as (the total number of reports on a drug) × (the fraction of an event among all spontaneous reports). A signal is detected when Proportional Reporting Ratio (PRR) defined as the ratio of observed/expected numbers>2 and the corresponding chi-square value> 4. In the FDA's method, the observed number of a drug-event combination is supposed to have a Poisson distribution with a mean of μ and the signal score is defined as the expected value of a random variable λ=μ/E where E is the expected number of reports on that combination. A signal is detected when signal score>2. The “Information Component” (IC) in the UMC's methods is estimated from the ratio of posterior to prior probabilities for a particular drug-event combination. A signal is detected when the 95% confidence interval for the IC is positive and does not include 0.<BR>Conclusion : New methods outlined in this article require further theoretical development and its application to the analysis of spontaneous reports.

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Details 詳細情報について

  • CRID
    1390001204483686144
  • NII Article ID
    130004345379
  • DOI
    10.3820/jjpe1996.6.101
  • ISSN
    1882790X
    13420445
    http://id.crossref.org/issn/13420445
  • Data Source
    • JaLC
    • Crossref
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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