for data analyses
|under-reporting||In several jurisdictations health care professionals are not legally bound to file adverse events. Overlooking adverse events or non-reporting because of heavy workload often lead to under-reporting which is estimated to range between 1:10 to 1:100.||Absolute numbers of cases might
range 10-100 times higher. Cases for rarely used drugs might be missing.
||The act of reporting and the
choice of a primary and secondary suspected drug causing an event is
dependent how important and plausible this issue appears to a
physicians or patient. Different overview of literature could skew the
number of reports per drug or per adverse event.
More extensivly used drugs have higher total numbers of records.
|Queries should not always rely
on the item that specifies which drugs are suspected to cause the
reaction (DRUG.ROLE_COD in the AERS database). This is particulary
important for signal detection which aims to discover relations hereto
||The total amount of use for a
drug (e.g., defined daily dose (DDD) or total number of applications)
not gathered in traditional pharmacovigilance data. Any normalizations
relations to the real world (e.g., odds ratio, risks) are complicated
||A rough estimate of drug usage
and therefore substitute of DDD might be the total number of reports
which include this drug.
||Reporters might accidentally use
wrong formfields for items or mix up cases.
||Sanitizing the data might catch
some of these cases.
||Reporters might not have all
necessary data available or they cannot afford the time of entering all
avilable data due to their workload.
Some important data (e.g., magnesium level on Torsades de pointes onset) are not gathered in traditional pharmacovigilance data.
|These records with missing data
can be filtered out or some kind of extrapolation might be applied.
|duplicate or multiplicate records
||A report might be reported by
the sponsor of a trial, the affected participant and his general
Reports might be sent to a domestic and a foreign database and consequently be reported in duplicate to larger multi-national databases (e.g., VigiBase).
|Checks for records with
different case numbers but the same age, sex, date of onset of adverse
event and other database items
can catch these kind of multipicates.
||Besides formal inconsistency
(e.g., the gas xenon cannot be applied by intravenous route), the
mechanism needs to be explained (e.g., some licensed lipid lowering
drugs (e.g., orlistat) are connected to pharmacologically unexplainable
adverse reactions (i.e., influenza)).
||Health care professionals should
browse the list of case reports and manually correct inplausibilities
and inconsistencies. This implies that any statistical findings cannot
be used in legal proceedings.