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Related Experiment Videos

Algorithms used in adverse drug event reports: a comparative study

P A Frick1, L G Cohen, J P Rovers

  • 1School of Pharmacy, University of Washington, Seattle, USA.

The Annals of Pharmacotherapy
|February 1, 1997
PubMed
Summary

The Kramer and Karch algorithms show some differences in assessing adverse drug events (ADEs), with Kramer more often finding possible ADEs and Karch finding unlikely ADEs. Both can be used to evaluate published ADE reports.

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Area of Science:

  • Pharmacovigilance
  • Drug Safety Evaluation
  • Clinical Pharmacology

Background:

  • Assessing the causality of adverse drug events (ADEs) from published literature is crucial for drug safety.
  • Standardized algorithms aid in the objective evaluation of potential ADEs.

Purpose of the Study:

  • To compare the Kramer and Karch algorithms in their probability assignments for published ADE cases.
  • To evaluate the utility of these algorithms for assessing reported ADEs.

Main Methods:

  • An open, single-rater comparison of the Karch and Kramer algorithms was performed.
  • The algorithms were applied to 200 published reports of suspected adverse drug events.

Main Results:

  • No significant differences were found between the algorithms in classifying cases as definite or probable ADEs.

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  • The Kramer algorithm was more likely to assign a 'possible' ADE risk (p=0.0001), while the Karch algorithm favored 'unlikely' (p=0.0001).
  • The algorithms achieved agreement in 41% of cases.

    • Conclusions:

    • The Karch and Kramer algorithms may yield different probability assessments for potential ADEs.
    • Discrepancies may arise from variations in algorithm application and inherent structural differences.
    • Both algorithms demonstrate potential utility in assessing published ADEs.