Novel Adverse Events of Iloperidone: A Disproportionality Analysis in US Food and Drug Administration Adverse Event Reporting System (FAERS) Database.

The signal is defined as "reported information on a possible causal relationship between an adverse event and a drug, of which the relationship is unknown or incompletely documented previously". To detect novel adverse events of iloperidone by disproportionality analysis in FDA database of Adverse Event Reporting System (FAERS) using Data Mining Algorithms (DMAs). The US FAERS database consists of 1028 iloperidone associated Drug Event Combinations (DECs) which were reported from 2010 Q1 to 2016 Q3. We consider DECs for disproportionality analysis only if a minimum of ten reports are present in database for the given adverse event and which were not detected earlier (in clinical trials). Two data mining algorithms, namely, Reporting Odds Ratio (ROR) and Information Component (IC) were applied retrospectively in the aforementioned time period. A value of ROR-1.96SE>1 and IC- 2SD>0 were considered as the threshold for positive signal. The mean age of the patients of iloperidone associated events was found to be 44years [95% CI: 36-51], nevertheless age was not mentioned in twenty-one reports. The data mining algorithms exhibited positive signal for akathisia (ROR-1.96SE=43.15, IC-2SD=2.99), dyskinesia (21.24, 3.06), peripheral oedema (6.67,1.08), priapism (425.7,9.09) and sexual dysfunction (26.6-1.5) upon analysis as those were well above the pre-set threshold. Iloperidone associated five potential signals were generated by data mining in the FDA AERS database. The result requires an integration of further clinical surveillance for the quantification and validation of possible risks for the adverse events reported of iloperidone.

Subeesh V ，Maheswari E ，Singh H ，Beulah TE ，Swaroop AM ... -  《-》

Drug-Associated Acute Kidney Injury Identified in the United States Food and Drug Administration Adverse Event Reporting System Database.

Acute kidney injury (AKI) is a common condition associated with both short-term and long-term consequences including dialysis, chronic kidney disease, and mortality. Although the United States Food and Drug Administration Adverse Event Reporting System (FAERS) database is a powerful tool to examine drug-associated events, to our knowledge, no study has analyzed this database to identify the most common drugs reported with AKI. The objective of this study was to analyze AKI reports and associated medications in the FAERS database. Retrospective pharmacovigilance disproportionality analysis. Food and Drug Administration Adverse Event Reporting System database. We queried the FAERS database for reports of AKI from 2004 quarter 1 through 2015 quarter 3. Extracted drugs were assessed using published references and categorized as known, possible, or new potential nephrotoxins. The reporting odds ratio (ROR), a measure of reporting disproportionality, was calculated for the 20 most frequently reported drugs in each category. We retrieved 7,241,385 adverse event reports, of which 193,996 (2.7%) included a report of AKI. Of the AKI reports, 16.5% were known nephrotoxins, 18.6% were possible nephrotoxins, and 64.8% were new potential nephrotoxins. Among the most commonly reported drugs, those with the highest AKI ROR were aprotinin (7614 reports; ROR 115.70, 95% confidence interval [CI] 110.63-121.01), sodium phosphate (1687 reports; ROR 55.81, 95% CI 51.78-60.17), furosemide (1743 reports; ROR 12.61, 95% CI 11.94-13.32), vancomycin (1270 reports, ROR 12.19, 95% CI 11.45-12.99), and metformin (4701 reports; ROR 10.65, 95% CI 10.31-11.00). The combined RORs for the 20 most frequently reported drugs with each nephrotoxin classification were 3.71 (95% CI 3.66-3.76) for known nephrotoxins, 2.09 (95% CI 2.06-2.12) for possible nephrotoxins, and 1.55 (95% CI 1.53-1.57) for new potential nephrotoxins. Acute kidney injury was a common reason for adverse event reporting in the FAERS. Most AKI reports were generated for medications not recognized as nephrotoxic according to our classification system. This report provides data on medications needing further research to determine the risk of AKI with these new potential nephrotoxins.

Welch HK ，Kellum JA ，Kane-Gill SL 《-》

Pantoprazole associated dyspepsia hypocalcemia and hyponatremia: A disproportionality analysis in FDA adverse event reporting system (FAERS) database.

The study was designed to detect novel Adverse Events (AEs) of pantoprazole by disproportionality analysis in the FDA (Food and Drug Administration) database of Adverse Event Reporting System (FAERS) using Data Mining Algorithms (DMAs). Pantoprazole, the most commonly over-utilized Over The Counter (OTC) medication, was selected to assess any short-term or long-term AEs. The study aimed to analyze the novel adverse events of pantoprazole using the FAERS database. A retrospective case/non-case disproportionality analysis was performed in the FAERS database. This study was based on AEs reported to FAERS from 2006Q1-2021Q3. Openvigil 2.1 was used for data extraction. Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), and Information Component (IC) were applied to measure the disproportionality in reporting. A value of ROR-1.96SE > 1, PRR ≥ 2, and IC-2SD > 0 were considered as the threshold for a positive signal. A total of 1050 reports of dyspepsia, 7248 reports of hypocalcemia and 995 reports of hyponatremia were identified. A potential positive signal for dyspepsia (ROR-1.96SE = 2.231, PRR = 2.359, IC-2SD = 1.13), hypocalcemia (4.961, 5.45, 2.23) and hyponatremia (3.948, 4.179, 1.92) were identified for pantoprazole. Data mining in the FAERS database produced three potential signals associated with pantoprazole. As a result, further clinical surveillance is needed to quantify and validate potential hazards associated with pantoprazole-related adverse events.

Nair HP ，Kulkarni AR ，Eswaran M ，Subeesh V ... -  《-》

Novel adverse events of vortioxetine: A disproportionality analysis in USFDA adverse event reporting system database.

Signal detection is one of the most advanced and emerging field in pharmacovigilance. It is a modern method of detecting new reaction (which can be desired or undesired) of a drug. It facilitates early adverse drug reaction detection which enables health professionals to identify adverse events that may not have been identified in pre-marketing clinical trials. Vortioxetine, the first mixed serotonergic antidepressant was initially approved by the US Food and Drug Administration (USFDA) on September 30, 2013 for the treatment of adults with Major Depressive Disorder (MDD). This study was to identify the signal strength for vortioxetine associated ADRs using data mining technique in USFDA Adverse Event Reporting System (AERS) database. Most commonly used three data mining algorithms, Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR) and Information Component (IC) were selected for the study and they were applied retrospectively in USFDA AERS database from 2015Q1 to 2016Q3. A value of ROR-1.96SE >1, PRR≥2, IC- 2SD>0 were considered as the positive signal. A study population of 61,22,000 were reported all over the world. Among which 3481 reactions were associated with vortioxetine which comprised of 632 unique events encompassed with 27 clinically relevant reactions. ROR, PRR and IC showed positive signal for weight loss, agitation, anger, ketoacidosis, insomnia and abnormal dreams. The present study suggests that vortioxetine may result in these adverse events. Further pharmacoepidemiologic studies are necessary to confirm this conclusion and to improve the precision of the prevalence and/or the risk factors of this ADRs.

Subeesh V ，Singh H ，Maheswari E ，Beulah E ... -  《-》

Triptans and serious adverse vascular events: data mining of the FDA Adverse Event Reporting System database.

Roberto G ，Piccinni C ，D'Alessandro R ，Poluzzi E ... -  《-》