Evidence map›Paper›PMID 39764463›Full record

ArticleFrontiers in pharmacology2024

An exploratory study evaluated the 30 most commonly reported medications in the United States food and drug administration's adverse event reporting system that are associated with the occurrence of kidney stones.

Erhao Bao, Yang Yang, Binglei Jiang, Ben Wang, Ying Liu, Lin Yang, Long Xia, Pingyu Zhu

Abstract read
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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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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

8 authors.

Erhao Bao *Urology Department, Sichuan Provincial People's Hospital East Sichuan Hospital and Dazhou First People's Hospital, Dazhou, China.
Yang Yang *Traditional Chinese Medicine department, Sichuan Provincial People's Hospital East Sichuan Hospital and Dazhou First People's Hospital, Dazhou, China.
Binglei Jiang *Department of Ultrasound, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
Ben Wang *Department of Urology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
Ying LiuDepartment of Urology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
Lin YangDepartment of Urology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
Long XiaDepartment of Urology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
Pingyu ZhuDepartment of Urology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This research project aimed to identify and analyze the top 30 drugs most commonly associated with kidney stone formation using data from the U.S. Food and Drug Administration's Adverse Event Reporting System (FAERS) database. The study will focus on determining the reported Odds ratio (ROR) and Proportional Report ratio (PRR) of each identified drug to assess its potential risk of contributing to the development of kidney stones in order to effectively manage and reduce the overall burden of kidney stones worldwide. Background: Kidney stones are a common urinary system disease, and their formation is influenced by multiple factors, including medications, metabolic syndrome, environmental factors, genetic susceptibility, urinary tract abnormalities, and obstructive pathology. Among these factors, medications are an important and clearly defined cause of kidney stone formation. Currently, drug-induced kidney stones account for 1%-2% of all cases of kidney stones. Although the proportion may appears modest, its contribution to the overall prevalence of kidney stones should not be overlooked. The high incidence and frequent recurrence of kidney stones pose significant challenges to prevention efforts. Therefore, a thorough understanding of which medications may trigger stone formation is crucial for effectively managing and reducing the burden of this global health issue. Method: This study utilized the FDA Adverse Event Reporting System (FAERS) database maintained by the U.S. Food and Drug Administration to extract raw data from 1 January 2010, to 31 March 2024. Duplicate data was removed following the FDA-recommended method. Subsequently, data related to drug-induced kidney stones was extracted by linking the DEMO table, DRUG table, and REAC table using specific primaryid numbers, resulting in a total of 37,781 drug records and 37,027 demographic records. The data was sorted based on the frequency of drug-induced kidney stones, and the top 30 drugs associated with kidney stone formation were selected for analysis. The primary analytical methods employed were disproportionality analyses, calculating the Reporting Odds Ratio (ROR) with its 95% Confidence Interval (CI) and Proportional Reporting Ratio (PRR) to reveal the association between drugs and adverse kidney stone events. Results: We ranked the 30 most common drugs based on their ROR and PRR values. The three drugs most commonly associated with kidney stones were Atazanavir (ROR 46.35, 95% CI 43-50, PRR 44.9), Topamax (ROR 19.44, 95% CI 17.66-21.40, PRR 19.19), and Prevacid (ROR 12.67, 95% CI 11.62-13.82, PRR 12.57). Drug categories most commonly associated with kidney stones were antiretroviral drugs, proton pump inhibitors, and antiepileptic drugs. Conclusion: Our research has summarized a list of potential drug categories associated with kidney stones. Clear understanding of the risk and frequency of drug-induced kidney stones caused by specific medications can reduce the likelihood of patients developing the condition. Clinical doctors should keep vigilant during diagnosis and treatment processes, and communicate relevant risk information to patients.

Indexed as

exploratory studyFAERSFDAkidney stonesmedications

Identifiers

PMID39764463
PMCPMC11701592

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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.