All events are assessed by a physician using the same process as for reviewing ADR reports in the spontaneous reporting programme.
PROCESSING OF EVENTS
All
events are assessed by a physician using the same process as for reviewing ADR
reports in the spontaneous reporting programme. A ‘relationship’ is established
between the drug and the event following the protocol for causality assessment
recommended by the World Health Organisation Collaborating Centre for
International Drug Monitoring (Meyboom and Royer, 1992). The events are
classified according to system/organ class using the IMMP events dictio-nary,
which is a hierarchical terminology based on the WHO adverse reactions
terminology (WHOART). The hierarchy has five levels, and events can be sorted
at each level into their clinically related groupings or individually. There
are approximately 3000 event terms in the dictionary.
Each
drug-event relationship is coded as one of the following: definite, probable,
possible, unlikely or unclassified. These assessments are based mainly on duration
to onset of the event and the response to withdrawal and/or re-challenge. They
are not regarded as ‘causality’ assessments and are made without prej-udice.
Judgements on causality for many of the events can only come later when
epidemiological evidence using aggregated IMMP and other available data can be
considered along with biases and confounders and pharmacological plausibility.
With this back-ground thinking, and to facilitate further evaluation, the
assessed events are divided into two categories: those events with a
relationship of certain, probable or possible are classified as ‘reactions’ and
those with a relationship of unlikely are called ‘incidents’ (because they are
likely to be incidental to the use of the drug and represent the background
noise of the condition being treated or community morbidity). These two groups
are then evaluated for signals of previously unidentified adverse reactions.
This is largely under-taken by observation of the nature and pattern of events
being reported, examining comparative rates controlled for age, gender,
indication and severity of disease as appropriate and differences in profiles.
Signals arising from this process may be investigated further by special
studies.
Unless
the incident group contains unrecognized adverse reactions, it should represent
the background noise, and this should be generally similar for drugs of similar
indication. If the incident rates are simi-lar for comparator drugs, then it
can be assumed that reporting bias is not present. If there are statistically
significant differences between the incident profiles of comparator drugs, then
this may be because of the presence of an unrecognized adverse reaction or
confounding, e.g. by indication or reporting bias. Any such differences are
therefore investigated.
Incidents
are also used as within-drug controls for characterizing adverse reactions. The
variables associ-ated with, respectively, the reactions and incidents for a
drug and also the patient characteristics are compared, and should there be
differences these may indicate risk factors – e.g. a gender or dose difference
– for the reaction under study. An example of the use of inci-dents as
within-drug controls is as follows. The rates of adverse reactions were higher
in women than men for moclobemide [relative risk (RR) 1.7; 95% confidence
interval (95% CI) 1.4–2.0] and fluoxetine (RR 1.7; 95% CI 1.3–2.2). There was
no significant gender differ-ence seen in the incident rates. It would appear
there-fore that the gender difference seen for the reactions is a true risk
factor and not because of reporting bias.
For
these two drugs, which were monitored concur-rently, the incidents were also
used as between-drug controls. The reaction rate for fluoxetine was 50% higher
than that for moclobemide (RR 1.5; 95% CI 1.2–1.7). There was no significant
difference between the incident rates, suggesting an absence of reporting bias
and strengthening the finding of greater risk with fluoxetine (Coulter, 1996).
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