Adverse Drug Reaction Risk Measures: A Comparison of Estimates from Drug Surveillance and Randomised Trials

Raphaelle Beau-Lejdstrom, Sarah Crook, Alessandra Spanu, Tsung Yu, Milo A. Puhan

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Background: Most drug regulatory agencies and pharmaceutical companies hold databases of spontaneous reports of suspected adverse drug reactions (ADRs). Detection systems for ADR signals have been created by specialists to analyse such reports, based on the concept of disproportionality, in order to support safety decision making. However, these measures are often misinterpreted by non-specialists in pharmacovigilance. Objectives: Our aim was to assess agreement between estimates of risk from spontaneous reports of suspected ADRs and estimates of risks of ADRs from randomised controlled trials (RCTs). Methods: From 150 drugs randomly selected from the US Food and Drug Administration’s Adverse Event Reporting System (FAERS), we identified drugs where FAERS provided reporting odds ratios (RORs) and corresponding systematic reviews from the Cochrane database gave (pooled) odds ratios (ORs) for the same drugs and adverse reactions. We assessed agreement between (ln) RORs and (ln) ORs using the Pearson correlation coefficient and the Bland–Altman agreement method, and performed sensitivity analyses. Results: We identified 6 drugs and 125 ADRs. Overall, there was a weak correlation (r = 0.20) between RORs (FAERS) and ORs (RCTs). However, we observed a stronger correlation (r = 0.78) between RORs and ORs for one drug (roflumilast) that received market approval relatively recently (2011). Conclusions: Spontaneous reporting of suspected ADRs is an important tool for regulatory agencies and pharmaceutical companies in making decisions and detecting drug safety signals. Although there was moderate-to-strong agreement between ADR risk estimates from drug surveillance and RCTs for one drug, this study illustrates the current recommendations not to use disproportionality measures as valid proxies for risk estimates.

Original languageEnglish
Pages (from-to)331-339
Number of pages9
JournalPharmaceutical Medicine
Volume33
Issue number4
DOIs
Publication statusPublished - 2019 Aug 1

All Science Journal Classification (ASJC) codes

  • Pharmacology
  • Pharmacology (medical)

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