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Autor(en) / Beteiligte
Titel
An Empirical Approach to Explore the Relationship Between Measures of Disproportionate Reporting and Relative Risks from Analytical Studies
Ist Teil von
  • Drug safety, 2016-01, Vol.39 (1), p.29-43
Ort / Verlag
Cham: Springer International Publishing
Erscheinungsjahr
2016
Quelle
MEDLINE
Beschreibungen/Notizen
  • Introduction Although it seems reasonable to suppose that a drug that increases the risk of an adverse event might tend to show increased disproportionality statistics in spontaneous reporting databases, that relationship is not clear. Therefore, an empirical approach was taken to investigate the relationship between proportional reporting ratios (PRRs) and relative risk (RR) estimates from formal studies in a set of known adverse drug reactions (ADRs). Methods Drug-event pairs that were the subject of pharmacovigilance-driven European regulatory actions from 2007 to 2010 were selected. Only pairs having RR derived from formal studies and where it was considered that there was well-established evidence supporting the actions were included. A best estimate of the RR for each ADR was chosen based on pre-specified rules. PRRs were then calculated in Eudravigilance using only those cases reported before the date of first recognition of the ADR in the medical community. An additional analysis was carried out in FEDRA, the Spanish spontaneous reports database. A descriptive analysis and an orthogonal regression model were performed. Results From an initial dataset of 78 drug-event pairs, 15 were selected. The regression model (ln RR = 0.203 + 0.463 × ln PRR) showed a significant ( p  < 0.001) correlation between RR and PRR in Eudravigilance. None of the ADR-related variables analysed modified the relationship. Exploratory results in FEDRA went in the same direction. Conclusions Disproportionality measures should not replace formal studies but could provide an initial indication of the likely clinical importance of an ADR, should the signal be confirmed subsequently. Whether the same conclusions can be applied to other datasets should be further studied.

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