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Automated Analysis of Dynamic Ca2+ Signals in Image Sequences
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An evaluation of three signal-detection algorithms using a highly inclusive reference event database.

Alan M Hochberg1, Manfred Hauben, Ronald K Pearson

  • 1ProSanos Corporation, Harrisburg, Pennsylvania 17102, USA. alan.hochberg@prosanos.com

Drug Safety
|May 23, 2009
PubMed
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Data-mining algorithms (DMAs) for pharmacovigilance generate many false positives. This study evaluated three DMAs, finding significant differences in their detection rates and the scientific validity of their signals of disproportionate reporting (SDRs).

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Area of Science:

  • Pharmacovigilance and Drug Safety
  • Computational Toxicology
  • Biostatistics

Background:

  • Pharmacovigilance data-mining algorithms (DMAs) frequently produce false-positive signals of disproportionate reporting (SDRs).
  • Defining true and false positives varies across different DMAs.
  • Evaluating the scientific validity of detected SDRs is crucial for effective drug safety monitoring.

Purpose of the Study:

  • To create an inclusive reference database of adverse events for selected drugs.
  • To assess the performance of three DMAs (urn model, Gamma Poisson Shrinker (GPS), proportional reporting ratio (PRR)) using this database.
  • To determine the false-positive rates and overlap of SDRs generated by each DMA.

Main Methods:

  • Compiled a reference event database for 35 US FDA-approved drugs using prescribing information, literature, regulatory actions, and the British National Formulary.
  • Assigned evidence levels to each reported adverse event.
  • Applied three DMAs to FDA adverse event reporting system data (2002-2005) to identify SDRs.
  • Compared SDRs against the reference database to ascertain validity and calculated overlap among methods.

Main Results:

  • The Gamma Poisson Shrinker (GPS) algorithm yielded the fewest SDRs (763) with the highest match rate to the reference database (11.7%).
  • The urn model yielded more SDRs (1562) with a similar match rate (11.2%).
  • Proportional reporting ratio (PRR) detected the most SDRs (3616) but had the lowest match rate (8.2%). PRR also uniquely detected the most SDRs.

Conclusions:

  • The three evaluated DMAs exhibit distinct trade-offs between the volume of SDRs detected and their scientific support.
  • Algorithm design and detection thresholds significantly influence DMA performance.
  • A substantial proportion of identified SDRs lack external supporting evidence, even with comprehensive searches.