Conducting and interpreting disproportionality analyses derived from spontaneous reporting systems

Abstract

Spontaneous reporting systems remain pivotal for post-marketing surveillance and disproportionality analysis (DA) represents a recognized approach for early signal detection. Although DAs cannot be used per se as a standalone approach to assess a drug-related risk and cannot replace clinical judgment in the individual patient, their role remain irreplaceable for rapid detection of rare and unpredictable adverse drug reactions with strong drug-attributable component (e.g., designated medical events), especially when developed by a multidisciplinary team and combined with a careful case-by-case analysis (individual inspection of reports for causality assessment or to uncover reporting patterns and clinical features). In the recent past, a remarkable increase in publications of pharmacovigilance studies using DAs was observed, albeit the quality was debated: several publications contained “spin”, namely, misinterpretation of results to infer causality, calculate incidence, or provide risk stratification, which may ultimately result in unjustified alarm. The development of dedicated Guidelines by the international READUS-PV project (https://readus-statement.org/) will allow reproducible and transparent publication of accurate DAs, thus supporting their real transferability and exploitation by regulators and clinicians. This review offered a perspective on methodological aspects (and understanding) of DAs, their rationale, design, reporting, and interpretation.

Safety of Dual Orexin Receptor Antagonist Daridorexant: A Disproportionality Analysis of Publicly Available FAERS Data

“…Disproportionality analyses are commonly affected by biases such as the notoriety bias and confounding by indication [ 43 ]. As far as notoriety bias is concerned, its impact on our analysis cannot be underestimated.…”

Peer Review in Pharmacovigilance: Lens on Disproportionality Analysis

“…These challenges are amplified in the field of pharmacovigilance, and specifically when dealing with disproportionality analysis (DA) of individual case safety report (ICSR) systems, a consolidated statistical approach to detect higher-than-expected adverse event reporting [3]. The key goal of DA remains early detection of rare but serious suspected adverse drug reactions (including those from drug interactions) that cannot be detected or fully appreciated from clinical trials or healthcare databases [4]. In recent years, we have witnessed an exponential increase in the number of publications on DA, mostly from academia [5].…”

“…In other words, DAs cannot be used per se as a standalone approach to assess a drug-related risk (they do not provide risk quantification and ranking) and cannot replace clinical judgement at the individual level. DAs should be complemented by a careful case-by-case analysis as the first step within the signal management process, including pharmacological plausibility, and further assessed in conjunction with an appraisal of available evidence [4].…”

Meta-analyzing Results From Disproportionality Analysis of Individual Case Safety Reports

“…Although the reporting odds ratio (ROR) used in disproportionality analysis on ICSRs databases and the odds ratio used in the case-control design on claims databases share the same statistical formula, the ROR is not a risk measure. 11 Instead, it primarily reflects (when achieving statistical significance) an imbalance in the frequency of reporting an event with a drug compared with other drugs in the database, known as a signal of disproportionate reporting warranting further investigation. 12 This statistical association should be cautiously interpreted due to inherent limitations: the actual population of exposed patients is not available, underreporting cannot be precisely estimated, the ability to account for relevant confounders is limited, and the selection of the comparator is debated and not standardized.…”

“…There are key differences in the nature of data between ICSRs and administrative/claims databases. Although the reporting odds ratio (ROR) used in disproportionality analysis on ICSRs databases and the odds ratio used in the case-control design on claims databases share the same statistical formula, the ROR is not a risk measure 11 . Instead, it primarily reflects (when achieving statistical significance) an imbalance in the frequency of reporting an event with a drug compared with other drugs in the database, known as a signal of disproportionate reporting warranting further investigation 12 .…”