The Weber Effect and the United States Food and Drug Administration’s Adverse Event Reporting System (FAERS): Analysis of Sixty-Two Drugs Approved from 2006 to 2010

Abstract

BackgroundThe United States Food and Drug Administration’s (FDA) Adverse Event Reporting System (FAERS) consists of adverse event (AE) reports linked to approved drugs. The database is widely used to support post-marketing safety surveillance programs. Sometimes cited as a limitation to the usefulness of FAERS, however, is the ‘Weber effect,’ which is often summarized by stating that AE reporting peaks at the end of the second year after a regulatory authority approves a drug. Weber described this effect in 1984 based upon a single class of medications prescribed in the United Kingdom. Since that time, the FDA has made a concerted effort to improve both reporting and the database itself. Both volume and quality of AE reporting has dramatically improved since Weber’s report, with an estimated 800,000 yearly reports now being logged into FAERS.ObjectiveThe aim of this study was to determine if current FAERS reporting follows the trend described by Weber.MethodsSixty-two drugs approved by the FDA between 2006 and 2010 were included in this analysis. Publicly available FAERS data were used to assess the ‘primary suspect’ AE reporting pattern for up to a 4-year period following each drug’s approval date.ResultsA total of 334,984 AE reports were logged into FAERS for the 62 drugs analyzed here. While a few of the drugs demonstrated what could be considered ‘Weber effect’ curves, a majority of the drugs showed little evidence for the effect. In fact, the general AE reporting pattern observed in this study appears to consist simply of increasing case counts over the first three quarters after approval followed by relatively constant counts thereafter.ConclusionsOur results suggest that most of the modern adverse event reporting into FAERS does not follow the pattern described by Weber. Factors that may have contributed to this finding include large increases in the volume of AE reports since the Weber effect was described, as well as a concerted effort by the FDA to increase awareness regarding the utility of post-marketing AE reporting.Electronic supplementary materialThe online version of this article (doi:10.1007/s40264-014-0150-2) contains supplementary material, which is available to authorized users.

Post-marketing Drug Safety Evaluation Using Data Mining Based on FAERS

“…Similar works for comparing multiple drugs are based solely on the counts of events for each drug or only one specific AE such as bleeding, while our work is designed for all the AEs combined and specifically for the FAERS data. [16,17]…”

Comparison of Hemorrhagic Risk between Prasugrel and Clopidogrel: a Retrospective Study using Adverse Drug Event Reporting Databases

“…Most importantly, SRS is a passive reporting system, and is, therefore, subject to many biases, such as under-reporting and overreporting [14]. In addition, SRS is subjected to the "Weber effect," which refers to an increase in adverse event reporting over the initial 2 years after a drug is approved, followed by a rapid decline in reporting rates [15]. However, no such effect was evident in our database; the number of reports of total hemorrhage due to prasugrel in JADER was 130 (2014 Q2-2016 Q1) and 173 (2016 Q2-2017 Q2) and that in FAERS was 227 (the fourth quarter [Q4] of 2009 -the third quarter [Q3] of 2011) and 305 (2011 Q4-2013 Q3).…”

Cyclo‐oxygenase selectivity and chemical groups of nonsteroidal anti‐inflammatory drugs and the frequency of reporting hypersensitivity reactions: a case/noncase study in VigiBase

“…To minimize the effect of underreporting of ADRs, we considered time after market approval of a NSAID in the analyses. Even though the Weber effect is described as ADR reports that peak at the second year after drug approval, other studies showed that ADR reports still increase up to 5 years . We calculated RORs in three strata of 5 years after market approval to ensure that time after market approval did indeed contribute to ROR differences.…”