Adverse Drug Reactions to acetaminophen and ibuprofen in the paediatric population: analysis of the Italian spontaneous reporting database

Background: Acetaminophen and ibuprofen are the only antipyretics drugs approved in children, and are considered safe and well tolerated. However, data regarding the adverse drug reaction (ADR) profile of these drugs in children are scattered. Aim: The aim of our study is to evaluate the ADRs of acetaminophen and ibuprofen through an observational study over a period of 15 years (January 2005-April 2020). Reports of suspected ADRs to the active substances ‘acetaminophen’ and ‘ibuprofen’ are listed and accessible through the Italian spontaneous reporting database (RAM system) by AIFA (Pharmacovigilance of the Italian Drug Agency). Methods: Acetaminophen ADRs in paediatric populations were 15% of cases, with more frequent involvement of skin and soft tissue (54.36%) and gastrointestinal apparatus (44.09%); liver dysfunction accounts for 5.67%. Results: Ibuprofen paediatric ADRs were 26%: skin and soft tissues in 63.16% of cases, gastrointestinal tract in 47.75%, hematemesis and melena in 6.38%; kidney injury in 2.25% of cases. Conclusion: Children aged 2 to 11 are more frequently affected by ADRs than infants and adolescents. The risk of gastrointestinal and renal side effects is significantly higher with ibuprofen. Hepatobiliary side effects are more frequently linked to acetaminophen. Potentially fatal ADRs have been reported sporadically for both drugs.

Identifying and Characterizing Serious Adverse Drug Reactions Associated With Drug-Drug Interactions in a Spontaneous Reporting Database

Background: Drug-drug interactions (DDIs) are an important cause of adverse drug reactions (ADRs). In literature most of studies focus only on potential DDIs, while detailed data on serious ADRs associated with DDIs are limited. Our aim is to identify and characterize serious ADRs caused by DDIs using a spontaneous reporting database.Methods: All serious ADR reports, not related to vaccines and with a “definite”, “probable” or “possible” causality assessment, inserted into the National Pharmacovigilance database from Veneto Region (January 1, 2015 to May 31, 2020) were analyzed. A list of drug pairs was created by selecting the reports containing at least two suspected or concomitant drugs. We verified which drug pairs potentially interacted according to the online version of DRUGDEX® system. For each potential DDI we controlled whether the ADR description in the report corresponded to the interaction effect as described in Micromedex. A detailed characterization of all serious reports containing an occurring DDI was performed.Results: In the study period a total of 31,604 reports of suspected ADRs from the Veneto Region were identified, of which 2,195 serious reports (6.9% of all ADR reports) containing at least two suspected or concomitant drugs were analyzed. We identified 1,208 ADR reports with at least one potential DDI (55.0% of 2,195) and 381 reports (17.4% of 2,195 reports) with an occurring ADR associated with a DDI. The median age of patients and the number of contraindicated or major DDIs were significantly higher in reports with an occurring DDI. Warfarin was the most frequently reported interacting drug and the most common ADRs were gastrointestinal or cerebral hemorrhagic events. The proton pump inhibitors/warfarin, followed by platelet aggregation inhibitors/warfarin were the drug-drug combinations most frequently involved in ADRs caused by DDIs. The highest proportion of fatal reports was observed with platelet aggregation inhibitors/warfarin and antidepressants/warfarin.Conclusion: Our findings showed that about one-third of patients exposed to a potential DDI actually experienced a serious ADR. Furthermore, our study confirms that a spontaneous reporting database could be a valuable resource for identifying and characterizing ADRs caused by DDIs and the drugs leading to serious ADRs and deaths.

Safety Surveillance of Pneumococcal Vaccine Using Three Algorithms: Disproportionality Methods, Empirical Bayes Geometric Mean, and Tree-Based Scan Statistic

Introduction: Diverse algorithms for signal detection exist. However, inconsistent results are often encountered among the algorithms due to different levels of specificity used in defining the adverse events (AEs) and signal threshold. We aimed to explore potential safety signals for two pneumococcal vaccines in a spontaneous reporting database and compare the results and performances among the algorithms. Methods: Safety surveillance was conducted using the Korea national spontaneous reporting database from 1988 to 2017. Safety signals for pneumococcal vaccine and its subtypes were detected using the following the algorithms: disproportionality methods comprising of proportional reporting ratio (PRR), reporting odds ratio (ROR), and information component (IC); empirical Bayes geometric mean (EBGM); and tree-based scan statistics (TSS). Moreover, the performances of these algorithms were measured by comparing detected signals with the known AEs or pneumococcal vaccines (reference standard). Results: Among 10,380 vaccine-related AEs, 1135 reports and 101 AE terms were reported following pneumococcal vaccine. IC generated the most safety signals for pneumococcal vaccine (40/101), followed by PRR and ROR (19/101 each), TSS (15/101), and EBGM (1/101). Similar results were observed for its subtypes. Cellulitis was the only AE detected by all algorithms for pneumococcal vaccine. TSS showed the best balance in the performance: the highest in accuracy, negative predictive value, and area under the curve (70.3%, 67.4%, and 64.2%). Conclusion: Discrepancy in the number of detected signals was observed between algorithms. EBGM and TSS calibrated noise better than disproportionality methods, and TSS showed balanced performance. Nonetheless, these results should be interpreted with caution due to a lack of a gold standard for signal detection.

Pharmacovigilance Assessment of Drug-Induced Acute Pancreatitis Using a Spontaneous Reporting Database

Background: Acute pancreatitis (AP) is associated with risks of morbidity and mortality. The incidence of AP recently increased compared to that traditionally reported in the literature. Objective: The purpose of this study was to evaluate the possible association between AP and drugs using the Japanese Adverse Drug Event Report (JADER) database, which is a spontaneous reporting database of adverse drug events. Methods: Adverse event reports submitted to the JADER database between 2004 and 2017 were analyzed. Disproportionality analysis was performed by calculating the reporting odds ratio (ROR) with 95% confidence intervals for signal detection. Results: A total of 3,443 reports (0.17% of all adverse events) were identified as drug-induced AP, in which 431 different drugs were involved. Acute pancreatitis was frequently reported in men (58.5%) in their 60s (19.1%); 40.6% developed AP within 4 weeks after the treatment. Among the most frequently reported drugs, signals were detected for prednisolone, ribavirin, sitagliptin, mesalazine, tacrolimus, and l-asparaginase, which are well-known causes of AP. Telaprevir, donepezil, and ustekinumab also generated signals. As for drugs with high RORs, l-asparaginase and alogliptin were noteworthy. Conclusion: Most of the identified drugs were already known to induce AP, but the likelihood of the reporting of AP varied among the drugs. Our results should raise physicians’ awareness of drugs associated with AP, but further investigation of these medications is warranted.