Evidence map›Paper›PMID 42182858›Full record

ArticleTherapeutic advances in drug safety2026

Adverse events associated with statin co-use in breast cancer patients: a disproportionality analysis based on the FDA Adverse Event Reporting System.

Yunnan Zhang, Wenxing Peng, Wei Yang, Yang Gao, Yannan Fan, Qianqian Guo

Abstract read
In one paragraph

Article in Therapeutic advances in drug safety, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Yunnan ZhangDepartment of Pharmacy, Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.ORCID https://orcid.org/0000-0002-3515-200X
Wenxing PengDepartment of Pharmacy, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.
Wei YangDepartment of Pharmacy, Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.
Yang GaoDepartment of Pharmacy, Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.
Yannan FanDepartment of Pharmacy, Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.
Qianqian GuoDepartment of Pharmacy, Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: An increasing number of breast cancer patients are using statins concomitantly. However, there are relatively few safety studies on the association between statins and adverse events (AEs) during breast cancer treatment. Objective: This study aims to systematically evaluate the disproportionality signals associated with statin use and the reporting of AEs across different system organ classes (SOCs) in breast cancer patients. Design: This is a pharmacovigilance disproportionality analysis based on the U.S. Food and Drug Administration's (FDA) Adverse Event Reporting System database. Methods: All AE reports related to breast cancer from the 2004 Q1 to 2024 Q3 were extracted. Disproportionality analysis was performed using reporting odds ratios (RORs) to detect potential safety signals associated with statin use. Multivariate logistic regression model was used as a secondary analysis to adjust for potential confounders, including age, gender, and therapeutic drugs. Results: A total of 237,868 breast cancer-related AE reports were identified, of which 8,223 involved concomitant statin use. Statin use was associated with lower RORs of hepatobiliary (ROR: 0.60, 95% CI: 0.52-0.68), and blood and lymphatic system disorders (ROR: 0.62, 95% CI: 0.57-0.67). In contrast, higher RORs were observed for skin and subcutaneous tissue (ROR: 1.75, 95% CI: 1.67-1.84), psychiatric (ROR: 1.95, 95% CI: 1.82-2.08), renal and urinary (ROR: 2.03, 95% CI: 1.85-2.22), musculoskeletal and connective tissue (ROR: 1.48, 95% CI: 1.40-1.58), infections and infestations (ROR: 1.25, 95% CI: 1.18-1.34), metabolism and nutrition (ROR: 1.25, 95% CI: 1.16-1.35), gastrointestinal (ROR: 1.10, 95% CI: 1.05-1.16), vascular (ROR: 1.26, 95% CI: 1.16-1.37), nervous system (ROR: 1.20, 95% CI: 1.13-1.27), respiratory, thoracic and mediastinal disorders (ROR: 1.07, 95% CI: 1.00-1.14). Conclusion: In breast cancer patients receiving statins concomitantly, specific disproportionality signals were observed across multiple SOCs. These findings highlight the need for individualized monitoring strategies and further mechanistic studies to clarify the underlying pathways and optimize clinical risk management.

Indexed as

adverse eventsbreast cancerdisproportionality analysisFAERSstatins

Identifiers

PMID42182858
PMCPMC13195224

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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.