Julien Mahé1, Emilie Patras de Campaigno2,3, Anne-Laure Chené4, Jean-Louis Montastruc2,3,5,6, Fabien Despas2,3,5,7, Pascale Jolliet1,8. 1. Service de Pharmacologie Clinique, CHU de Nantes, Nantes, France. 2. Service de Pharmacologie Médicale et Clinique, CHU de Toulouse, Toulouse, France. 3. UMR1027, Inserm, Université Paul Sabatier, Toulouse, France. 4. Institut du thorax, hôpital CHU de Nantes, Nantes, France. 5. Service de Pharmacologie Médicale et Clinique, Faculté de Médecine, Université Paul Sabatier, Toulouse, France. 6. Centre Midi-Pyrénées de Pharmacovigilance, de Pharmacoépidémiologie et d'Informations sur le Médicament, CHU de Toulouse, Toulouse, France. 7. INSERM CIC 1436 Toulouse, Centre d'Investigation Clinique de Toulouse, CHU de Toulouse, France. 8. UMR INSERM 1246 - SPHERE MethodS in Patients-centered outcomes and HEalth ResEarch.
Abstract
AIMS: To evaluate the risk of pleural disorders (PD) associated with 33 protein kinase (PK) inhibitors (PKIs) through a disproportionality analysis and to identify which PKs and pathways are involved in PKI-induced PD. METHODS: To evaluate the risk of PD, reporting odds ratios (RORs) were calculated for 33 PKIs through data registered in the World Health Organization safety report database (VigiBase). We undertook a literature review to identify PKs that were possibly involved in PD caused by PKIs. Pearson correlation coefficients (r) between RORs and affinity data of 19 PKIs were calculated to identify the cellular target most likely to be involved in PKI-induced PD. RESULTS: A total of 235 110 individual case safety reports were extracted from the database for 33 available PKIs. Among these reports, 5001 concerned PD (2.1%). Significant and positive disproportionality for PD was found for 29 of 33 PKI included in our study with top values for dasatinib [ROR = 115.3; 95% confidence interval (CI): 110.1-120.8], bosutinib (ROR = 20.4; 95% CI: 15.8-26.4) and ponatinib (ROR = 12; 95% CI: 9.2-15.6). Correlation analyses between the product of dissociation constant and ROR highlighted possibly Lyn involvement in PD with PKI (r = 0.73, P = 0.0004). CONCLUSIONS: Our study showed that 28 of the 33 tested PKIs were associated with PD. Besides, the study highlighted the role of Lyn in PD caused by PKIs through an immune-mediated process.
AIMS: To evaluate the risk of pleural disorders (PD) associated with 33 protein kinase (PK) inhibitors (PKIs) through a disproportionality analysis and to identify which PKs and pathways are involved in PKI-induced PD. METHODS: To evaluate the risk of PD, reporting odds ratios (RORs) were calculated for 33 PKIs through data registered in the World Health Organization safety report database (VigiBase). We undertook a literature review to identify PKs that were possibly involved in PD caused by PKIs. Pearson correlation coefficients (r) between RORs and affinity data of 19 PKIs were calculated to identify the cellular target most likely to be involved in PKI-induced PD. RESULTS: A total of 235 110 individual case safety reports were extracted from the database for 33 available PKIs. Among these reports, 5001 concerned PD (2.1%). Significant and positive disproportionality for PD was found for 29 of 33 PKI included in our study with top values for dasatinib [ROR = 115.3; 95% confidence interval (CI): 110.1-120.8], bosutinib (ROR = 20.4; 95% CI: 15.8-26.4) and ponatinib (ROR = 12; 95% CI: 9.2-15.6). Correlation analyses between the product of dissociation constant and ROR highlighted possibly Lyn involvement in PD with PKI (r = 0.73, P = 0.0004). CONCLUSIONS: Our study showed that 28 of the 33 tested PKIs were associated with PD. Besides, the study highlighted the role of Lyn in PD caused by PKIs through an immune-mediated process.
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