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Objectives: To review and appraise methods and reporting characteristics of pharmacovigilance disproportionality analyses., Study Design and Setting: We randomly selected 100 disproportionality analyses indexed in Medline found during a systematic literature search. We then extracted and synthetized methodological and reporting characteristics using seven key items: (1) title transparency; (2) protocol pre-registration; (3) date of data extraction and analysis; (4) outcome, population, exposure and comparator definitions; (5) adjustment and stratification of results; (6) method and threshold for signal detection; (7) secondary and sensitivity analyses., Results: We found that methods used to generate disproportionality signals were extremely heterogeneous; there were nearly as many unique analyses as studies. The authors used various populations, methods, signal detection thresholds, adjustment or stratification variables, generally without justification for their choice or pre-specification in protocols. Moreover, 78% of studies failed to report methods for case, adverse drug reactions or comparator selection and 32 studies did not define the threshold for signal generation., Conclusion: Our survey raises major concerns regarding all aspects of disproportionality analyses that could lead to misleading results and generate unjustified alarms. We advocate for a strong and transparent rationale for variable selection, choice of population and comparators pre-specified in a protocol and assessed by sensitivity analyses., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Objective: To systematically review and appraise misinterpretation of pharmacovigilance disproportionality analysis results in published studies., Study Design and Setting: We randomly selected 100 studies that performed disproportionality analyses and indexed in Medline identified during a systematic literature search. Titles, abstracts and main texts (results, discussion and conclusion) were evaluated for spin independently by two reviewers. Spin in pharmacovigilance studies was classified according to three main categories: inappropriate interpretation, inappropriate extrapolations and misleading reporting., Results: Of the 100 studies evaluated, we found that 63%, 56% and 51% had at least one type of spin in their abstract, main text or conclusion respectively, and 40% used causal language to interpret their results in the abstract or conclusion. Spin in titles and results were exclusively represented by inappropriate interpretations of findings (12% and 21% respectively), with terms such as "risk of" or "risks associated with" or results erroneously presented as regular Odds Ratios. Spin in discussion sections mostly concerned inappropriate interpretations (38%)and misleading reporting (12%). Misleading reporting, notably failing to acknowledge the limitations of disproportionality analyses, was the most frequent type of spin in abstracts (55%) and conclusion sections (37%)., Conclusion: We found that spin is frequent in publications of pharmacovigilance disproportionality analyses, notably in abstracts. This consisted notably in an over-interpretation of the results suggesting a proven causative link between a drug use and the risk of an event., (Copyright © 2021. Published by Elsevier Inc.)

Objective: We aimed at testing if a correlation between adverse drug reactions relative risks estimated from meta-analyses and disproportionality analyses calculated from pharmacovigilance spontaneous reporting systems databases exist, and if methodological choices modify this correlation., Study Design: We extracted adverse drug reactions (ADR) odds ratios (ORs) from meta-analyses used as reference and calculated corresponding Reporting Odds Ratios (RORs) from the WHO pharmacovigilance database according to five different designs. We also calculated the relative bias and agreement of ROR compared to ORs., Results: We selected five meta-analyses which displayed a panel of 13 ADRs. A significant correlation for 7 out of the 13 ADRs studied in the primary analysis was found. The methods for ROR calculation impacted the results but none systematically improved the correlations. Whereas correlation was found between OR and ROR, agreement was poor and relative bias was important., Conclusion: Despite the large variation in disproportionality analyses results due to design specification, this study provides further evidence that relative risks obtained from meta-analyses and from disproportionality analyses correlate in most cases, in particular for objective ADR not associated with the underlying pathology., (Copyright © 2021 Elsevier Inc. All rights reserved.)

The pathophysiology of pulmonary arterial hypertension (PAH) induced by protein kinase inhibitors (PKIs) remains unclear. To gain knowledge into this rare and severe pathology we performed a study combining a pharmacovigilance approach and the pharmacodynamic properties of PKIs.A disproportionality analysis on the World Health Organization pharmacovigilance database VigiBase using the reporting odds ratio (ROR) and 95% confidence interval was first performed. Then, we identified the most relevant cellular targets of interest through a systematic literature review and correlated the pharmacovigilance signals with the affinity for the different PKIs. We further performed a hierarchical cluster analysis to assess patterns of binding affinity.A positive disproportionality signal was found for dasatinib, bosutinib, ponatinib, ruxolitinib and nilotinib. Five non-receptor protein kinases significantly correlate with disproportionality signals: c-Src (r=0.79, p=0.00027), c-Yes (r=0.82, p=0.00015), Lck (r=0.81, p=0.00046) and Lyn (r=0.80, p=0.00036), all belonging to the Src protein kinase family, and TEC (r=0.85, p=0.00006). Kinases of the bone morphogenetic protein signalling pathway also seem to play a role in the pathophysiology of PKI-induced PAH. Interestingly, the dasatinib affinity profile seems to be different from that of other PKIs in the cluster analysis.The study highlights the potential role of the Src protein kinase family and TEC in PAH induced by PKIs. This approach combining pharmacovigilance and pharmacodynamics data allowed us to generate some hypotheses about the pathophysiology of the disease; however, the results have to be confirmed by further studies., Competing Interests: Conflict of interest: L. Cornet has nothing to disclose. Conflict of interest: C. Khouri has nothing to disclose. Conflict of interest: M. Roustit reports grants from United Therapeutics outside the submitted work. Conflict of interest: C. Guignabert has nothing to disclose. Conflict of interest: M-C. Chaumais reports nonfinancial support from Bayer and personal fees from Actelion, outside the submitted work. Conflict of interest: M. Humbert reports personal fees from Actelion, Bayer, GSK, Merck and United Therapeutics, during the conduct of the study. Conflict of interest: B. Revol has nothing to disclose. Conflict of interest: F. Despas has nothing to disclose. Conflict of interest: D. Montani reports grants and personal fees from Actelion and Bayer, and personal fees from BMS, GSK, MSD and Pfizer, outside the submitted work. Conflict of interest: J-L. Cracowski reports grants from Bioprojet and Topadur, outside the submitted work., (Copyright ©ERS 2019.)