title: Pharmacological prioritisation of signals of disproportionate reporting: proposal of an algorithm and pilot evaluation.
abstract: OBJECTIVE
  Data mining in spontaneous reporting databases generates large numbers of signals of disproportionate reporting (SDRs) that need to be prioritised for assessment. The pharmacological relevance of drug-event associations is not considered in SDR prioritisation algorithms. This aimed to propose and test a pharmacological score for SDR prioritisation.
  
  
  METHODS
  The Pharmacological Score for SDRs Prioritisation (PS-SP) was developed using a Delphi approach. An expert group agreed that PS-SP should include general criteria concerning SDRs and criteria concerning pharmacological relevance, and that criteria should be weighted for their risk representation. Once defined, the PS-SP was tested for prioritisation of SDRs for extrapyramidal syndrome in the French Pharmacovigilance database; the SDR classification was compared to that obtained using a traditional disproportionality approach.
  
  
  RESULTS
  For a given drug, the general criteria retained were the reporting rate of the adverse drug reaction (ADR) and value of the 95% confidence interval (CI) lower boundary of the Reporting Odds Ratio (ROR). Pharmacological criteria consisted of the ADR reporting rate without concomitant at-risk drugs or those indicated for ADR treatment, and the value of the ROR 95% CI lower boundary as estimated in the subset of reports concerning drugs from the same therapeutic and then pharmacological class. Compared with traditional disproportionality, PS-SP prioritised specific drugs within congeners: metoclopramide, indoramin, and trimetazidine appeared as outliers within their classes; conventional antipsychotics had higher prioritisation than atypical antipsychotics.
  
  
  CONCLUSIONS
  The pilot evaluation of PS-SP performed in extrapyramidal syndrome advocates for the use of pharmacological criteria in SDR prioritisation algorithms.
authors.affiliation: Univ Bordeaux, U657, F33000, Bordeaux, France, francesco.salvo@u-bordeaux.fr.
authors.forename: Francesco
authors.initials: F
authors.lastname: Salvo
authors.forename: Emanuel
authors.initials: E
authors.lastname: Raschi
authors.forename: Ugo
authors.initials: U
authors.lastname: Moretti
authors.forename: Anita
authors.initials: A
authors.lastname: Chiarolanza
authors.forename: Annie
authors.initials: A
authors.lastname: Fourrier-Réglat
authors.forename: Nicholas
authors.initials: N
authors.lastname: Moore
authors.forename: Miriam
authors.initials: M
authors.lastname: Sturkemboom
authors.forename: Fabrizio
authors.initials: F
authors.lastname: De Ponti
authors.forename: Elisabetta
authors.initials: E
authors.lastname: Poluzzi
authors.forename: Antoine
authors.initials: A
authors.lastname: Pariente
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems / Q000458:organization & administration / Q000706:statistics & numerical data*; D000465:Algorithms; D057225:Data Mining / Q000379:methods* / Q000706:statistics & numerical data; D016208:Databases, Factual; D064420:Drug-Related Side Effects and Adverse Reactions / Q000453:epidemiology*; D006801:Humans; D008492:Medical Informatics Computing; D016017:Odds Ratio; D010865:Pilot Projects