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ENCePP Guide on Methodological Standards in Pharmacoepidemiology


8.4. Spontaneous reports


Note: Chapter 8.4. (formerly 7.4.) has not been updated for Revision 11 of the Guide, as contents remain up-to-date.


Spontaneous reports of suspected adverse drug reactions remain a cornerstone of pharmacovigilance and are collected from a variety of sources, including healthcare providers, national authorities, pharmaceutical companies, medical literature, and directly from patients.


EudraVigilance is the European Union data processing network and management system for reporting and evaluating suspected adverse drug reactions (ADRs). Other major systems for collections of spontaneous reports are the FDA's Adverse Event Reporting System (FAERS), the FDA’s Vaccine Adverse Event Reporting System (VAERS) and the WHO global database of individual case safety reports, VigiBase, that pools reports from the members of the WHO programme for international drug monitoring. These systems deal with the electronic exchange of Individual Case Safety Reports (ICSRs), the early detection of possible safety signals and the continuous monitoring and evaluation of potential safety issues in relation to reported ADRs. Spontaneous case reports represent the first line of evidence and the majority of safety signals is based on them, as described in A description of signals during the first 18 months of the EMA pharmacovigilance risk assessment committee (Drug Saf. 2014;37(12):1059-66).


The main strengths of spontaneous reporting systems are:


i) they cover all types of authorised medicines used in any setting (primary, secondary and specialised healthcare) and all reasons for use including authorised indications, off-label, misuse and abuse;

ii) they are built to obtain information specifically to evaluate the likelihood that a particular treatment is the cause of an observed adverse event. The data collection concentrates on variables relevant to this objective directing reporters towards careful coding and communication of the main aspects of an ADR (e.g., event dates, medical history and co-morbidities, concomitant treatments, etc.);

iii) they are designed to collect and make the information on suspected ADRs rapidly available for analysis.

The application of knowledge discovery in databases to post-marketing drug safety: example of the WHO database (Fundam Clin Pharmacol. 2008;22(2):127-40) describes known limitations of spontaneous ADR reporting systems, which can be grouped into four main categories:

i) factors influencing reporting dynamics, whereby known or unknown factors, such as workload of healthcare professionals or increased media coverage and public awareness, may influence the reporting rate, leading respectively to under-reporting or to a comparative increase in the reporting rate affecting the reliability of estimates of signals of disproportionate reporting;

ii) insufficient clinical information reported, not allowing a satisfactory case evaluation and/or the identification of possible risk factors, which is crucial to establish the likely causal relationship between exposure to the product and occurrence of the adverse drug reaction;

iii) misclassification of diagnosis is closely related to the factors influencing reporting dynamics, where extensive media coverage and public awareness not only stimulates reporting, but may influence the interpretation of symptoms, such that symptoms similar to the ones of the disorder in the media coverage, are likely to be reported as suspected cases of that disorder to the detriment of other disorders with similar symptoms, potentially leading to a misclassification of diagnosis;

iv) lack of collection of control information, as these databases are case-only databases and thus cannot provide actual medicinal product exposure information nor information on the disease incidence.


Another challenge of spontaneous reporting databases is the quality of the information provided and adherence to reporting rules; for this reason, comprehensive and multi-faceted quality activities are often an integral part of these systems (see Detailed guide regarding the EudraVigilance data management activities by the European Medicines Agency Rev 1 for an example). One aspect of the data quality activities regards report duplication. Duplicates are separate and unlinked records that refer to one and the same case of a suspected ADR and may mislead signal assessment or distort statistical screening. They are generally detected by individual case review of all reports or by computerised duplicate detection algorithms. In Performance of probabilistic method to detect duplicate individual case safety reports (Drug Saf. 2014;37(4):249-58) a probabilistic method applied to VigiBase highlighted duplicates that had been missed by a rule-based method and also improved the accuracy of manual review. In the study, however, a demonstration of the performance of de-duplication methods to improve signal detection is lacking. The EMA and FDA have also implemented probabilistic duplicate detection in their databases.


More recently, there have been attempts to boost the computerised detection of duplicates using Natural Language Processing (NLP) techniques to identify similarities on the narrative of reports, as demonstrated in Using Probabilistic Record Linkage of Structured and Unstructured Data to Identify Duplicate Cases in Spontaneous Adverse Event Reporting Systems (Drug Saf. 2017;40(7):571–82).


For the above reasons, it is advised that the cases underlying a potential safety signal from spontaneous reports should be verified from a clinical perspective and preferably supported by pharmacological information before further investigation. Anecdotes that provide definitive evidence (BMJ. 2006;333(7581):1267-9) describes uncommon examples where this is not necessary, where strong and well documented spontaneous reports can be convincing to support the existence of a signal.


Patient reporting is an important source of suspected adverse drug reactions. Factors affecting patient reporting of adverse drug reactions: a systematic review (Br J Clin Pharmacol. 2017;83(4):875-83) describes the practical difficulties with patient reporting and highlights the patients’ motivation to make their ADRs known to prevent similar suffering in other patients. The value of patient reporting to the pharmacovigilance system: a systematic review (Br J Clin Pharmacol. 2017;83(2):227-46) concludes that patient reporting adds new information and perspective about ADRs in a way otherwise unavailable, and this can contribute to better regulatory decision-making. Patient Reporting in the EU: Analysis of EudraVigilance Data (Drug Saf. 2017;40(7):629-45) also concludes that patient reporting complements reporting by health care professionals and that patients are motivated to report especially those ADRs that affect their quality of life.


The information collected in spontaneous reports is a reflection of a clinical event that has been attributed to the use of one or more suspected medicinal products. Although the majority of information provided in the ICSRs is coded, the description of the clinical event, as well as the interpretation of the reporter, contains valuable information for signal detection purposes. Examples are the description of timing and course of the reactions, of the presence or absence of additional risk factors and of the medical history of the patient. Knowledge of the local healthcare system, its corresponding guidelines and the possibilities to follow-up for more detailed information are considered important during this review.


Since only part of this information is coded and can be used in statistical analyses, it remains important to review the underlying cases for signal detection purposes.


The increase in systematic collection of ICSRs in large electronic databases has allowed the application of data mining and statistical techniques for the detection of safety signals (see Chapter 11). Validation of statistical signal detection procedures in EudraVigilance post-authorisation data: a retrospective evaluation of the potential for earlier signalling (Drug Saf. 2010;33(6): 475-87) shows that the statistical methods applied in EudraVigilance can provide significantly early warning in a large proportion of drug safety concerns. Nonetheless, this approach should supplement, rather than replace, other pharmacovigilance methods.


The report ‘Characterisation of Databases (DBs) Used for Signal Detection (SD): Results of a Survey of IMI PROTECT Work Package (WP) 3 Participants’ (Pharmacoepidemiol Drug Saf. 2012;21(Suppl.3): abstract no. 496 pp 233) shows the heterogeneity of spontaneous databases and the lack of comparability of signal detection methods employed.


Chapters IV and V of the Report of the CIOMS Working Group VIII ‘Practical aspects of Signal detection in Pharmacovigilance’ present sources and limitations of spontaneously-reported drug-safety information and databases that support signal detection. Appendix 3 of the report provides a list of international and national spontaneous reporting system databases.


Finally, in EudraVigilance Medicines Safety Database: Publicly Accessible Data for Research and Public Health Protection (Drug Saf. 2018;41(7):665-75), the authors describe how these databases, focusing on EudraVigilance, have been made more easily accessible for external stakeholders. This has allowed to provide better access to information on suspected adverse reactions for healthcare professionals and patients, and opportunities for health research for academic institutions.



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