Are Causal Statements Reported in Pharmacovigilance Disproportionality Analyses Using Individual Case Safety Reports Exaggerated in Related Citations? A Meta-epidemiological Study

Claire Bernardeau, Bruno Revol, Francesco Salvo, Michele Fusaroli, Emanuel Raschi, Jean-Luc Cracowski, Matthieu Roustit and Charles Khouri ()
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Claire Bernardeau: Grenoble Alpes University Hospital, University Grenoble Alpes
Bruno Revol: Grenoble Alpes University Hospital, University Grenoble Alpes
Francesco Salvo: Université de Bordeaux, INSERM, BPH, Team AHeaD, U1219
Michele Fusaroli: University of Bologna
Emanuel Raschi: University of Bologna
Jean-Luc Cracowski: Grenoble Alpes University Hospital, University Grenoble Alpes
Matthieu Roustit: University Grenoble Alpes, Inserm U1300, HP2
Charles Khouri: Grenoble Alpes University Hospital, University Grenoble Alpes

Drug Safety, 2025, vol. 48, issue 6, No 7, 679-688

Abstract: Abstract Background Previous 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. Methods On 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. Results Overall, 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

Date: 2025
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DOI: 10.1007/s40264-025-01524-x

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