Evidence map›Paper›PMID 24178291›Full record

ArticleDrug safety2013

Profiling cumulative proportional reporting ratios of drug-induced liver injury in the FDA Adverse Event Reporting System (FAERS) database.

Allen D Brinker, Jenna Lyndly, Joseph Tonning, David Moeny, Jonathan G Levine, Mark I Avigan

Abstract read
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In one paragraph

Article in Drug safety, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.1field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 36 citations in OpenAlex.

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  9. Drug-induced liver injury: Do we know everything?World journal of hepatology · 2017
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 2 countries.

Allen D BrinkerOffice of Surveillance and Epidemiology, Center for Drug Evaluation and Research, Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD, 20993, USA, allen.brinker@fda.hhs.gov.
Jenna Lyndly
Joseph Tonning
David Moeny
Jonathan G Levine
Mark I Avigan
Food and Drug Administration · THCenter for Drug Evaluation and Research · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEarly prediction and accurate characterization of risk for serious liver injury associated with newly marketed drugs remains an important challenge for clinicians, the pharmaceutical industry, and regulators. To date, a biomarker that specifically indicates exposure to a drug as the etiologic cause of liver injury has not been identified.

objectivesUsing cumulative proportional reporting ratios (PRRs), we investigated 'real-time' profiles of a set of pharmaceuticals, over the first 3 years of US marketing, for the signaling of clinically serious drug-induced liver injury (DILI) in a large spontaneous-reporting database.

methodsUsing report counts of hepatic failure or clinically serious liver injury obtained from the FDA Adverse Events Reporting System (FAERS) database, PRRs of adverse drug event terms were calculated by division of counts of domestic reports of these events by counts of all serious adverse events for each of 13 selected drugs associated with a broad range of hepatotoxic risk (including three linked to only rare instances of clinically apparent liver injury) with reference to all other drugs in the database. Drug-specific cumulative PRRs were measured at successive intervals (calendar quarters) using cumulative tallies of FAERS reports to generate time-based profiles over the initial 3 years of US marketing.

resultsIn the set of drugs analyzed, those with no known hepatotoxic risk demonstrated time-based cumulative PRR profiles that approximate the background rates of hepatic failure and serious liver injury reported in the entire FAERS database. In contrast, those that were removed from marketing or subjected to marketing restrictions due to their potential to cause liver injury were associated with profiles of rapidly rising cumulative PRRs that were greater than 5 within the first 10 million domestic prescriptions or the first four quarters of US marketing. The systematic tracking and identification of rising PRRs for DILI associated with newly marketed pharmaceutical and biological agents is a valuable tool for identification of safety signals within the FAERS database. LIMITATIONS: Disproportionality profiling of spontaneous reports in FAERS (e.g., cumulative PRR measurements), which signals an association between a recently marketed drug and liver injury, is not a method to quantitatively measure drug-related risk. Regulatory actions in response to emerging drug safety concerns often depend on an accurate assessment of risks using multiple sources of data and the consideration of overall benefits and risks of the agent. Causality must be determined through analysis of individual cases to exclude other etiologies of liver injury.

conclusionThe FAERS database can be used to advance empiric hepatotoxicity time-trending reporting levels for newly marketed agents in order to rapidly identify recently launched potential hepatotoxic agents and initiate further evaluation.

Indexed as

Adverse Drug Reaction Reporting SystemsChemical and Drug Induced Liver InjuryDatabases, FactualDrug-Related Side Effects and Adverse ReactionsHumansUnited StatesUnited States Food and Drug Administration

Identifiers

PMID24178291
OpenAlexW2091819473

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.