Data Mining Techniques in Pharmacovigilance: Analysis of the Publicly Accessible FDA Adverse Event Reporting System (AERS)

Abstract

Background: Acute kidney injury (AKI) is associated with signi cant increases in short-and long-term morbidity and mortality. Drug-induced AKI is a major concern in the present healthcare system. Our spontaneous reporting system (SRS) analysis assessed links between AKIs, along with patients' age, as healthcare-associated risks and administered anti-infectives. We also generated anti-infectives-related AKI-onset pro les. Method: We calculated adjusted reporting odds ratios (RORs) for reports of anti-infectives-related AKIs (per Medical Dictionary for Regulatory Activities) in the Japanese Adverse Drug Event Report database and evaluated associations between anti-infectives and age by association rule mining. We evaluated time-to-onset data and hazard types using the Weibull parameter. Results: Among 534,688 reports (submission period: April 2004-June 2018), there were 21,727 AKI events. Anti-infective treatments including glycopeptide antibacterials, uoroquinolones, third-generation cephalosporins, triazole derivatives, and carbapenems were associated with 596, 494, 341, 315, and 313 AKI incidences, respectively. Adjusted RORs of anti-infectives-related AKIs increased among older patients and were higher in anti-infective combination therapies [anti-infectives, ≥ 2; ROR, 2.75 (2.56-2.95)] than in monotherapies [ROR, 1.52 (1.45-1.61)]. In association rule mining, the number of anti-infectives and age were associated with anti-infectives-related AKI lift values (as consequent). Moreover, 48.1% of AKIs occurred within 5 days (median, 5.0 days) of anti-infective therapy initiation. Conclusion: Thus, adjusted RORs derived from our new SRS analysis indicate potential AKI risks linked to age and number of administered anti-infectives.

Assessing liver injury associated with antimycotics: Concise literature review and clues from data mining of the FAERS database

“…Data processing and management (e.g., duplicate detection and removal, handling of missing data) were performed according to previous methodology, extensively described in a dedicated book chapter [43] . In this study, main selection criteria regards the role code assigned to the drug (i.e., only "Primary Suspect", "Secondary Suspect" or "Interacting", whereas cases where antimycotics were reported as "Concomitant" were not included) and information on age and gender (records with missing of mild, asymptomatic, reversible elevations in serum transaminases has been estimated to be 5%-10% [29] .…”

Macrolides and Torsadogenic Risk: Emerging Issues from the FDA Pharmacovigilance Database

“…Before performing the analysis, several technical issues were handled with. This is the case for the drug mapping, duplicate removal and management of missing data [13]. Data of interest for the 2004-2011 period were collected from "DEMO" (demographic information), "DRUG", "REACTION" (adverse events coded according to the Medical Dictionary for Regulatory Activities terminology, MedDRA version 13.0) and "OUTCOME" files [14].…”

Evaluation of Drug-Induced Photosensitivity Using the Japanese Adverse Drug Event Report (JADER) Database

“…We examined the AE profiles for DIP using several established indices for pharmacovigilance analysis. 9,10) SRSs can be used to evaluate drug-associated AEs through disproportionality analysis, which usually involves the crude reporting odds ratio (ROR) for the signal detection of rare and severe AEs. In general, the crude ROR is unsuitable for inferring the comparative strength of causal relationships between drugs and AEs, and only offers a rough indication of the signal strength (i.e., generating hypotheses to search for unknown potential AEs).…”

“…In general, the crude ROR is unsuitable for inferring the comparative strength of causal relationships between drugs and AEs, and only offers a rough indication of the signal strength (i.e., generating hypotheses to search for unknown potential AEs). 9,11) It might be acceptable to compare crude RORs of a particular event within a particular context to examine the possibility of an interaction between the drug and AE. 9,11) In addition, the crude ROR can be used as a technique that allows for adjustments through logistic regression analyses to mitigate the effects of confounding factors.…”

“…Therefore, the obtained ROR does not provide sufficient evidence on causality and should be considered exploratory in the context of signal detection. 9) Furthermore, cases reported in the JADER database do not always contain sufficient information regarding patient background and dose response, among others, to allow for proper evaluation. Thus, since PTR is related and PAR is not related to a drug concentration, 3) it is tempting to speculate that a possible association has been found between the dose response and DIP onset profile.…”