Evidence map›Paper›PMID 37990902›Full record

ArticleCurrent drug safety2024

Identification of Novel Signals Associated with US-FDA Approved Drugs (2013) Using Disproportionality Analysis.

Sourabh Raghuvanshi, Mohammad Akhlaquer Rahman, Mahesh Kumar Posa, Anoop Kumar

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Article in Current drug safety, 2024. 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
–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

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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.

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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.

Sourabh RaghuvanshiDepartment of Clinical Research, Delhi Pharmaceutical Science and Research University (DPSRU), New Delhi, 110017, India.
Mohammad Akhlaquer RahmanDepartment of Pharmaceutics and Industrial Pharmacy, College of Pharmacy, Taif University, Taif, 21944, Kingdom of Saudi Arabia.
Mahesh Kumar PosaSchool of Pharmacy and Technology Management, SVKM'S NMIMS, Polepally SEZ, Jadcherla, Hyderabad, 509301, India.
Anoop KumarDepartment of Pharmacology, Delhi Pharmaceutical Sciences and Research University (DPSRU), New Delhi, 110017, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDrugs are related with various adverse drug reactions (ADRs), however, many unexpected ADRs of drugs are reported through post-marketing surveillance.

aimThe current study's goal is to uncover potential signals connected with FDA-approved medications in the United States (2013).

methodsOpen Vigil 2.1-MedDRA-v24 (data 20004Q1-2021Q3) was used as a tool to query the FAERS data. To find possible signals, disproportionality measures such as Proportional Reporting Ratio (PRR 2) with associated Chi-square value, Reporting Odds Ratio (ROR 2) with 95% confidence interval, and case count (3) were calculated.

resultsA total of eight potential signals were identified with five drugs. Positive signals were found with pomalidomide, canagliflozin, dolutegravir sodium, macitentan and ibrutinib.

conclusionHowever, further causality assessment is required to confirm the association of these drugs with identified potential signals.

Indexed as

Adverse Drug Reaction Reporting SystemsDrug-Related Side Effects and Adverse ReactionsUnited States Food and Drug AdministrationAdenineCanagliflozinDolutegravirDrug ApprovalHeterocyclic Compounds, 3-RingHumansOxazinesPiperazinesPiperidinesProduct Surveillance, PostmarketingPyrazolesPyridonesPyrimidinesAdenineCanagliflozinDolutegravirHeterocyclic Compounds, 3-RingibrutinibOxazinesPiperazinesPiperidinesPyrazolesPyridonesPyrimidinesThalidomidedisproportionality analysisFAERSopenvigil 2.1sensitivity analysis.signal detectionUS-FDA approved drugs

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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 Socratic graph.