In this chapter we have concentrated on the use of the BCPNN, partly because it is the most examined system used at present.
COMPARISON OF METHODS
In
this chapter we have concentrated on the use of the BCPNN, partly because it is
the most examined system used at present. As mentioned above, in vari-ous
centres, different measures are used to quantify the extent to which a certain
adverse drug reaction (ADR) is reported in a disproportionate relationship to a
certain drug compared to the generality of the database that is standing out
from the background of all reports.
There
have been a few studies (Kubota, Koide and Hirai, 2004; van Puijenbroek et al., 2002) comparing the BCPNN with
other methods. In the van Puijen-broek comparative study, the level of
concordance was measured of the various estimates to the measures produced from
the BCPNN. The investigation was performed on the data set of the Netherlands
Pharma-covigilance Foundation (Lareb), which maintains the spontaneous adverse
drug reaction reporting system in the Netherlands on behalf of the Dutch
Medicines Evaluation Board. In essence all the other methods highlighted the
same combinations as the BCPNN, and indeed more with lower numbers of cases.
When the ‘disproportionality’ was based on relationships with four or more
reports (about 11% of the Lareb database), all the methods were comparable. It
was only at low count values where any difference could be detected.
The
above finding is significant. The precise method used for data mining should be
based upon the benefits and drawbacks of each. Crucial to the Bayesian method
is the initial setting of the a priori
probability. How this is set determines the perfor-mance of the BCPNN at low
counter values. At the UMC we chose an a
priori probability of indepen-dence which is consistent with the WHO
definition of a signal and the previous publication (Edwards et al., 1990), suggesting that normally
more than one report would be needed
to trigger an expert to think that they had found a signal, unless there was
some-thing exceptional qualitatively
about a report (such as a case with proven, true re-challenge). Moreover the WHO
database has many more incident reports than the Lareb database so that as
greater numbers of reports are submitted, little time will be lost in find-ing
the signal even though the BCPNN requires about three or more reports to
trigger.
It
is clear that the other methods may be just as suitable as the BCPNN for
routine use to identify cases on a continuous basis which deserve follow-up for
more information. The trade-off between sensi-tivity and specificity of the
other methods, however, needs to be investigated further for predictive value
at a practical signal detection level. Table 21.2, taken from the comparisons
paper, gives a very good idea of some of the comparative benefits of the
methods.
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