Evolving Roles of Spontaneous Reporting Systems to Assess and Monitor Drug Safety

Abstract

This chapter aims to describe current and emerging roles of spontaneous reporting systems (SRSs) for assessing and monitoring drug safety. Moreover, it offers a perspective on the near future, which entails the so-called era of Big Data, keeping in mind both regulator and researcher viewpoints. After a panorama on key data sources and analyses of post-marketing data of adverse drug reactions, a critical appraisal of methodological issues and debated future applications of SRSs will be presented, including the exploitation and challenges in evidence integration (i.e., merging and combining heterogeneous sources of data into a unique indicator of risk) and patient's reporting via social media. Finally, a call for a responsible use of these studies is offered, with a proposal on a set of minimum requirements to assess the quality of disproportionality analysis in terms of study conception, performing and reporting.

Ototoxic Adverse Drug Reactions: A Disproportionality Analysis Using the Italian Spontaneous Reporting Database

“…The main strength is that we conducted the first overview of all drug-induced ototoxicity from an SRS database. ROR computing does not allow a quantification of the true risk of ototoxicity, and it is often calculated on a limited number of cases; it only suggests a statistically significant disproportionality of specific drug–ADR pairs, which should be further investigated for signal validation (Raschi et al, 2019). We believe that our findings reflect real differences in the relative ototoxicity of these drugs in the real world compared to pre-marketing authorization studies.…”

Lessons to be Learnt from Real-World Studies on Immune-Related Adverse Events with Checkpoint Inhibitors: A Clinical Perspective from Pharmacovigilance

“… Link adverse event reporting to drug consumption (prescription/dispensation data) in order to calculate a reporting rate. This measure, accounting for empirical estimation of the underreporting, might allow to calculate a minimum incidence rate from postmarketing real-world evidence, and may also provide a safety comparison [ 10 ]. Address missing information on management (including outcomes after drug interruption and rechallenge) and describe the long-term consequences of irAEs.…”

“…Therefore, when approaching DA in oncology, the existence of specific biases and relevant minimization strategies should be considered ( Table 1). For a systematic discussion of all technical aspects in study concept, design, conduction, presentation, and discussion of results, the reader may refer to dedicated book chapters [10,24] and expert documents such as the article on Good Signal Detection Practices [30].…”

“…adverse event reporting system, spontaneous reporting system, pharmacovigilance database, FAERS, Vigibase, Eudravigilance) yielded 3283 articles (search performed on 15 January 2020), of which 1445 were published in the last 5 years (390 in 2019). This scenario may be attributable to multifold reasons, including the increased awareness by clinicians regarding the importance of pharmacovigilance (namely postmarketing surveillance) and relevant commitment of submitting AEs for regulatory purposes, public availability of large SRSs, and open-access tools to independently analyze international databases [10].…”

Gender Differences in Adverse Drug Events of Hydroxychloroquine: Analysis of Spontaneous Reports Submitted to FAERS

“…We acknowledge inherent limitations of our study: by de nition, FAERS data cannot be used to calculate the incidence of an ADE, because of the under-reporting phenomenon, the lack of solid data on population exposure and the absence of certainty that the drug is actually responsible for the reported event [32]. ROR computing does not allow a quanti cation of the true risk of ADE for different gender, it only suggests a statistically signi cant disproportionality of speci c drug-event pair of interest, which should be further investigated for signal validation [33]. In addition, various biases such as over-reporting, duplicates, missing data, the possibility effect of diseases and drug interaction on signal detect should be taken into account when interpreting the results obtained from spontaneous report analysis [34].…”