Evidence map›Paper›PMID 32720297›Full record

ArticleTherapeutic innovation & regulatory science2021

Exploring Completeness of Adverse Event Reports as a Tool for Signal Detection in Pharmacovigilance.

Inyoung Lee, Jeremy D Jokinen, Stephanie Y Crawford, Gregory S Calip, Ryan D Kilpatrick, Todd A Lee

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Article in Therapeutic innovation & regulatory science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 50% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

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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 1 country.

Inyoung LeeDepartment of Pharmacy Systems, Outcomes and Policy, College of Pharmacy, University of Illinois at Chicago, 833 South Wood Street MC 871, Chicago, IL, 60612, USA. ilee37@uic.edu.ORCID 0000-0001-5436-2013
Jeremy D JokinenDepartment of Pharmacy Systems, Outcomes and Policy, College of Pharmacy, University of Illinois at Chicago, 833 South Wood Street MC 871, Chicago, IL, 60612, USA.ORCID 0000-0001-8484-5788
Stephanie Y CrawfordDepartment of Pharmacy Systems, Outcomes and Policy, College of Pharmacy, University of Illinois at Chicago, 833 South Wood Street MC 871, Chicago, IL, 60612, USA.ORCID 0000-0002-0228-337X
Gregory S CalipDepartment of Pharmacy Systems, Outcomes and Policy, College of Pharmacy, University of Illinois at Chicago, 833 South Wood Street MC 871, Chicago, IL, 60612, USA.ORCID 0000-0002-7744-3518
Ryan D KilpatrickAbbVie Inc., North Chicago, IL, USA.
Todd A LeeDepartment of Pharmacy Systems, Outcomes and Policy, College of Pharmacy, University of Illinois at Chicago, 833 South Wood Street MC 871, Chicago, IL, 60612, USA.ORCID 0000-0003-3619-5367
University of Illinois Chicago · USAbbVie (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCompleteness of adverse event (AE) reports is an important component of quality for good pharmacovigilance practices. We aimed to evaluate the impact of incorporating a measure of completeness of AE reports on quantitative signal detection.

methodsAn internal safety database from a global pharmaceutical company was used in the analysis. vigiGrade, an index score of completeness, was derived for each AE report. Data from various patient support programs (PSPs) were categorized based on average vigiGrade score per PSP. Performance of signal detection was compared between: (1) weighting and not weighting by vigiGrade score; and, (2) well documented and poorly documented PSPs using sensitivity, specificity, area under the receiver operating characteristics curve (AUC) and time-to-signal detection.

resultsThe ability to detect signals did not differ significantly when weighting by vigiGrade score [sensitivity (50% vs. 45%, p = 1), specificity (82.8% vs. 82.8%, p = 1), AUC (0.66 vs. 0.63, p = 0.051) or time-to-signal detection (HR 0.81, p = 0.63)] compared to not weighting. Well documented PSPs were better at detecting signals than poorly documented PSPs (AUC 0.66 vs. 0.52; p = 0.041) but time-to-signal detection did not differ significantly (HR 1.54, p = 0.42).

conclusionCompleteness of AE reports did not significantly impact the ability to detect signals when weighting by vigiGrade score or restricting the database based on the level of completeness. While the vigiGrade helps provide quality assessments of AE reports and prioritize cases for review, our findings indicate the tool might not be useful for quantitative signal detection when used by itself.

Indexed as

PharmacovigilanceAdverse Drug Reaction Reporting SystemsDatabases, FactualDrug-Related Side Effects and Adverse ReactionsHumansCompletenessPatient support programPharmacovigilancevigiGradeWeightingWell documented

Identifiers

PMID32720297
OpenAlexW3045649770

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.