ArticleDrug safety2025
Are Causal Statements Reported in Pharmacovigilance Disproportionality Analyses Using Individual Case Safety Reports Exaggerated in Related Citations? A Meta-epidemiological Study.
Article in Drug safety, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Analytic Misjudgment of Drug Safety Evidence and Causality: From the Prosecutor's Fallacy and Simpson's Paradox to Artificial Intelligence.Drug safety · 2026Review
- Disproportionality analysis to investigate fatal adverse events with immune checkpoint inhibitors: Proceed with extreme caution.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Causal Inference Tools for Pharmacovigilance: Using Causal Graphs to Identify and Address Biases in Disproportionality Analysis.Drug safety · 2026Article
- Safety profile of entrectinib in NSCLC: Multi-source pharmacovigilance analysis using FAERS and JADER.PloS one · 2026Article
- Exploring the complexities of disproportionality analysis in pharmacovigilance: reflections on the READUS-PV guideline and a call to action.Frontiers in pharmacology · 2025Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPrevious meta-epidemiological surveys have found considerable misinterpretation of results of disproportionality analyses. We aim to explore the relationship between the strength of causal statements used in title and abstract conclusions of pharmacovigilance disproportionality analyses and the strength of causal language used in citing studies.
methodsOn March 30, 2022, we selected the 30 disproportionality studies with the highest Altmetric Attention Scores. For each article, we extracted all citing studies using the Dimension database (n = 1434). In parallel, two authors assessed the strength of causal statements in the title and abstract conclusions of source articles and in the paragraph of citing studies. Based on previous studies, the strength of causal language was quantified based on a four-level scale (1-appropriate interpretation; 2-ambiguous interpretation; 3-conditionally causal; 4-unconditionally causal). Discrepancies were solved by discussion until consensus among the team. We assessed the association between the strength of causal statements in source articles and citing studies, separately for the title and abstract conclusions, through multinomial regression models.
resultsOverall, 27% (n = 8) of source studies used unconditionally causal statements in their title, 30% (n = 9) in their abstract conclusion, and 17% (n = 5) in both. Only 20% (n = 6) used appropriate statements in their title and in their abstract's conclusions. Among the 622 citing studies analyzed, 285 (45.8%) used unconditionally causal statements when referring to the findings from disproportionality analysis, and only 164 (26.4%) used appropriate language. Multinomial models found that the strength of causal statements in citing studies was positively associated with the strength of causal language used in abstract conclusions of source articles (Likelihood Ratio Test (LogLRT) p < 0.00001) but not in the titles. In particular, among studies citing source articles with appropriate interpretation, 30.2% (95% confidence interval [CI] 22.8-37.6) contained unconditionally causal statements in their abstract conclusions, versus 56.4% (95% CI 48.7-64.2) for studies citing source articles with unconditionally causal statements.
conclusionsNearly half of the studies citing pharmacovigilance disproportionality analyses results used causal claims, particularly when the causal language used in the source article was stronger. There is a need for higher caution when writing, interpreting, and citing disproportionality studies.
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