Abstract

One of the largest spontaneous adverse events reporting databases in the world is the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). Unfortunately, researchers face many obstacles in analyzing data from the FAERS database. One of the major obstacles is the unstructured entry of drug names into the FAERS, as reporters might use generic names or trade names with different naming structures from all over the world and, in some cases, with typographical errors. Moreover, report duplication is a known problem in spontaneous adverse event-reporting systems, including the FAERS database. Hence, thorough text processing for database entries, especially drug name entries, coupled with a practical case-deduplication logic, is a prerequisite to analyze the database, which is a time- and resource-consuming procedure. In this study, we provide a clean, deduplicated, and ready-to-import dataset into any relational database management software of the FAERS database up to September 2021. Drug names are standardized to the RxNorm vocabulary and normalized to the single active ingredient level. Moreover, a pre-calculated disproportionate analysis is provided, which includes the reporting odds ratio (ROR), proportional reporting ratio (PRR), Chi-squared analysis with Yates correction (), and information component (IC) for each drug-adverse event pair in the database.

Highlights

  • Drug post-marketing surveillance programs aim to minimize the risk of drug harm in clinical and pharmacy practices

  • It basically relies on spontaneous adverse event reporting systems

  • Case report duplication is a known issue in spontaneous adverse event reporting databases [11], including the FDA Adverse Event Reporting System (FAERS)/LAERS database, due to the uncontrolled inputs of reports from different sources, which means the same case report can be reported multiple times from different sources

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Summary

Introduction

Drug post-marketing surveillance programs aim to minimize the risk of drug harm in clinical and pharmacy practices It basically relies on spontaneous adverse event reporting systems. Spontaneous adverse event reports can effectively detect serious adverse drug reactions resulting from drug–drug interactions [6] It is common practice in each country to have a designated official entity responsible for supervising drug post-marketing surveillance activities [4]. Case report duplication is a known issue in spontaneous adverse event reporting databases [11], including the FAERS/LAERS database, due to the uncontrolled inputs of reports from different sources (i.e., healthcare professionals, patients, or manufacturing companies), which means the same case report can be reported multiple times from different sources. Many new drugs have emerged in the market as well as millions of new case reports have been added to the FAERS database

Design
Downloading Source Files
Case Reports Deduplication
RxNorm
Drug Names Normalization
Creating Drug-Adverse Reaction Contingency Table
Data Mining
Dataset Validation
Results

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