Evidence map›Paper›PMID 42723825›Full record

ArticleFrontiers in medicine2026

Real-world safety profile of alectinib: a 10-year pharmacovigilance study based on the FDA adverse event reporting system.

Le Zhang, DanDan Li, ChenJing Luo, Li Fan, Min Hu, Fei Ye, Peng Gu

Abstract read
In one paragraph

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

0numbers the graph read from it
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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Le ZhangDepartment of Pharmacy, The Second Affiliated Hospital of Army Medical University, Chongqing, China.
DanDan LiDepartment of Pharmacy, The Second Affiliated Hospital of Army Medical University, Chongqing, China.
ChenJing LuoDepartment of Pharmacy, The Second Affiliated Hospital of Army Medical University, Chongqing, China.
Li FanDepartment of Pharmacy, The Second Affiliated Hospital of Army Medical University, Chongqing, China.
Min HuDepartment of Pharmacy, The Second Affiliated Hospital of Army Medical University, Chongqing, China.
Fei YeDepartment of Pharmacy, The Second Affiliated Hospital of Army Medical University, Chongqing, China.
Peng GuDepartment of Pharmacy, The Second Affiliated Hospital of Army Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Alectinib is the standard first-line therapy for treatment-naïve ALK-positive non-small cell lung cancer (NSCLC). Given its increasing clinical utilization, a comprehensive pharmacovigilance evaluation of its adverse events (AEs) is warranted. Methods: We assessed alectinib-associated AEs using the FDA Adverse Event Reporting System (FAERS) database from Q4 2015 to Q3 2025. AEs were categorized per MedDRA, and four disproportionality analysis algorithms were used to detect potential safety signals. Results: A total of 8,602 reports with alectinib as the primary suspect drug were included. Overall, 51.1% were serious adverse events (SAEs). Median AE onset was 120 days (IQR: 27-428), with 27.4% within 30 days and 28.9% after 360 days. All algorithms identified 108 preferred terms meeting positive safety signal criteria. Besides well-recognized AEs, novel signals emerged: hypertriglyceridemia, hypercholesterolemia, pericardial effusion, erythema multiforme, muscle fatigue, and myositis. Multivariate regression showed male sex and age ≥65 years were independently linked to higher SAE risk. Conclusion: Leveraging a large pharmacovigilance database, this study comprehensively characterized alectinib's safety profile. It confirmed established signals and uncovered novel potential AEs needing further prospective research. Subgroup disparities and key monitoring windows were identified, deepening mechanistic understanding and supporting optimized clinical risk mitigation strategies. It should be noted that disproportionality analysis is used to detect potential safety signals rather than establishing causal relationships, and all identified signals require further clinical evaluation.

Indexed as

adverse eventsAlectinibdisproportionality analysisFAERS databasepharmacovigilance

Identifiers

PMID42723825
PMCPMC13557985

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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.