Data mining for signals in spontaneous reporting databases: proceed with caution

Authors

  • Wendy P. Stephenson MD, MS, MPH,

    Corresponding author
    1. Wendy Stephenson & Associates LLC, Maple Glen, PA, USA
    2. Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA
    • Wendy Stephenson & Associates LLC, Expertise in Pharmaceutical Safety, 1816 Carmel Place, Maple Glen, PA 19002, USA.
    Search for more papers by this author
  • Manfred Hauben MD, MPH

    1. Risk Management Strategy, Pfizer Inc., New York, NY, USA
    2. Department of Medicine, New York University School of Medicine, NY, USA
    3. Departments of Pharmacology and Community And Preventive Medicine, New York Medical College, Valhalla, NY, USA
    Search for more papers by this author

  • No conflict of interest was declared.

Abstract

Purpose

To provide commentary and points of caution to consider before incorporating data mining as a routine component of any Pharmacovigilance program, and to stimulate further research aimed at better defining the predictive value of these new tools as well as their incremental value as an adjunct to traditional methods of post-marketing surveillance.

Methods/Results

Commentary includes review of current data mining methodologies employed and their limitations, caveats to consider in the use of spontaneous reporting databases and caution against over-confidence in the results of data mining.

Conclusions

Future research should focus on more clearly delineating the limitations of the various quantitative approaches as well as the incremental value that they bring to traditional methods of pharmacovigilance. Copyright © 2006 John Wiley & Sons, Ltd.

Ancillary