Evidence map›Paper›PMID 39664518›Full record

ArticleFrontiers in pharmacology2024

The reporting of disproportionality analysis in pharmacovigilance: spotlight on the READUS-PV guideline.

Michele Fusaroli, Francesco Salvo, Charles Khouri, Emanuel Raschi

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
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

15 citing papers in PubMed.

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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

4 authors.

Michele FusaroliDepartment of Medical and Surgical Sciences, Alma Mater Studiorum - University of Bologna, Bologna, Italy.
Francesco SalvoUniversité de Bordeaux, INSERM, BPH, Team AHeaD, U1219, Bordeaux, France.
Charles KhouriUniversity Grenoble Alpes, Pharmacovigilance Unit, Grenoble Alpes University Hospital, Grenoble, France.
Emanuel RaschiDepartment of Medical and Surgical Sciences, Alma Mater Studiorum - University of Bologna, Bologna, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Disproportionality analyses are the most-commonly used study design used in the post-marketing phase to detect suspected adverse drug reactions in individual case safety reports. Recent years have witnessed an exponential increase in published articles on disproportionality analyses, thanks to publicly accessible databases. Unfortunately, this trend was accompanied by concerns on lack of transparency and misinterpretation of results, both generating unjustified alarm and diluting true signals into overwhelming noise. The READUS-PV guideline for reporting disproportionality analysis was developed to tackle this emerging issue. In this perspective article, we describe the rationale behind the development of the READUS-PV guideline, the first collaborative initiative to harmonize the reporting of disproportionality analyses. The adoption of the checklists will assist researchers, regulators, and reviewers in the reporting, assessment, and publication of disproportionality analyses. Acknowledging the challenges ahead of effective implementation, we advocate for a global endorsement by Pharmacology Journals. A wide dissemination of the READUS-PV guideline is crucial to foster transparency and reproducibility of pharmacovigilance research, supporting an effective exploitation of disproportionality analysis among other irreplaceable post-marketing research tools to ensure drug safety.

Indexed as

adverse drug reactionsdisproportionality analysisindividual case safety reportspharmacovigilancesignal detection

Identifiers

PMID39664518
PMCPMC11632231

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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.