The EU-ADR project: preliminary results and perspective.
The EU-ADR project aims to exploit different European electronic healthcare records (EHR) databases for drug safety signal detection. In this paper we describe the project framework and the preliminary results.


METHODS
As first step we created a ranked list of the events that are deemed to be important in pharmacovigilance as mining on all possible events was considered to unduly increase the number of spurious signals. All the drugs that are potentially associated to these events will be detected via data mining techniques. Data sources are eight 8 databases in four countries (Denmark, Italy, the Netherlands, and the United Kingdom) that are virtually linked through harmonisation of input data followed by local elaboration of input data through custom-built software (Jerboa). All the identified drug-event associations (signals) will be thereafter biologically substantiated and epidemiologically validated. To date, only Upper gastrointestinal bleeding (UGIB) event has been used to test the ability of the system in signal detection.


RESULTS
An initial ranked list comprising 23 adverse events was identified. The top-ranking events were: cutaneous bullous eruptions, acute renal failure, acute myocardial infarction, anaphylactic shock, and rhabdomyolysis. Regarding the UGIB test, a total of 48,016 first-ever episodes were identified. The age-standardized incidence rates of UGIB varied between 40-100/100,000 person-years depending on country and type of healthcare database. A statistically significant association between use of NSAIDs and UGIB was detected in all of the databases.


CONCLUSIONS
a dynamic ranked list of 23 adverse drug events judged as important in pharmacovigilance was created to permit focused data mining. Preliminary results on the UGIB event detection demonstrate the feasibility of harmonizing various health care databases in different European countries through a distributed network approach.
Trifiro
Gianluca
G
Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands. trifirog@unime.it
Fourrier-Reglat
Annie
A
Sturkenboom
Miriam C J M
MC
Díaz Acedo
Carlos
C
Van Der Lei
Johan
J
D057225:Data Mining; D064420:Drug-Related Side Effects and Adverse Reactions / Q000150:complications / Q000175:diagnosis* / Q000517:prevention & control; D057286:Electronic Health Records / Q000458:organization & administration; D005060:Europe; D005260:Female; D006801:Humans; D008297:Male; D016730:Program Development; D015397:Program Evaluation; D017751:Safety Management / Q000458:organization & administration