Evidence map›Paper›PMID 41298739›Full record

ArticleScientific reports2025

Post marketing safety surveillance of atezolizumab based on a retrospective analysis of the FDA adverse events reporting system (FAERS).

Gan Zhang, Danfeng Yu, Huan Pan, Jiong Liu, Ruling Wang, Yunyan Wan, Wuhua Zhou, Huaxiang Wang

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Gan ZhangDepartment of Hepatobiliary and Pancreatic Surgery, Taihe Hospital, Affiliated Hospital of Hubei University of Medicine, Shiyan, 442000, Hubei Province, China.
Danfeng YuDepartment of Neurocritical Medicine, Taihe Hospital, Affiliated Hospital of Hubei University of Medicine, Shiyan, 442000, Hubei Province, China.
Huan PanDepartment of Pediatrics, Taihe Hospital, Affiliated Hospital of Hubei University of Medicine, Shiyan, 42000, Hubei Province, China.
Jiong LiuDepartment of Hepatobiliary and Pancreatic Surgery, Taihe Hospital, Affiliated Hospital of Hubei University of Medicine, Shiyan, 442000, Hubei Province, China.
Ruling WangDepartment of Hepatobiliary and Pancreatic Surgery, Taihe Hospital, Affiliated Hospital of Hubei University of Medicine, Shiyan, 442000, Hubei Province, China.
Yunyan WanDepartment of Hepatobiliary and Pancreatic Surgery, Taihe Hospital, Affiliated Hospital of Hubei University of Medicine, Shiyan, 442000, Hubei Province, China.
Wuhua ZhouDepartment of Hepatobiliary and Pancreatic Surgery, Taihe Hospital, Affiliated Hospital of Hubei University of Medicine, Shiyan, 442000, Hubei Province, China. ministerwuhua@163.com.
Huaxiang WangDepartment of Hepatobiliary and Pancreatic Surgery, Taihe Hospital, Affiliated Hospital of Hubei University of Medicine, Shiyan, 442000, Hubei Province, China. whx@taihehospital.com.

Funding

Natural Science Foundation of Hubei Province of China 2025AFB368
6 · The paper itself

Abstract

Atezolizumab has been widely used for the immunotherapy of various cancers. This study aims to analyze the adverse events (AEs) associated with Atezolizumab post-marketing using the FDA Adverse Event Reporting System (FAERS). We conducted a retrospective analysis of the FAERS database, focusing on reports associated with atezolizumab from the first quarter of 2016 to the third quarter of 2024. The ADRs were stratified by demographics, event types, and reported outcomes. We performed a disproportionality analysis using the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN), and the empirical Bayesian geometric mean (EBGM) to assess the statistical association between atezolizumab use and specific AEs. Among the 18,310,937 non-duplicated reports collected from the FAERS database, 21,162 reports identified Atezolizumab as the "primary suspect (PS)," leading to the identification of 52,348 atezolizumab-induced AEs. The majority of AE reports (59.66%) occurred within the first 360 days of treatment, with most cases reported between 30 and 180 days of administration. A total of 494 Preferred Terms (PTs) were identified as significant across all four disproportionality-based pharmacovigilance signal assessment algorithms. The three system organ classes (SOCs) with the highest signal frequencies in AE reports were Gastrointestinal System Disorders (11.54%), Infectious and Invasive Disorders (10.12%), and Benign, Malignant, and Undetermined Tumors (including cystic and polypoid) (9.92%). The top five PTs with the strongest risk signals based on frequency screening were death, disease progression, pyrexia, anemia, and infectious pneumonia. Additionally, unexpected significant AEs were identified, including homicidal ideation, encephalitis, pancreatitis, disseminated intravascular coagulation, and Guillain- Barré syndrome. Atezolizumab treatment may be associated with a range of AEs. Further studies and continued pharmacovigilance efforts are essential to better understand the long-term safety of atezolizumab and to improve patient management strategies.

Indexed as

Adverse Drug Reaction Reporting SystemsAntibodies, Monoclonal, HumanizedProduct Surveillance, PostmarketingAlgorithmsAntineoplastic AgentsDatabases, FactualDrug-Related Side Effects and Adverse ReactionsFemaleHumansImmune Checkpoint InhibitorsMaleNeoplasmsNeural Networks, ComputerPharmacovigilanceRetrospective StudiesUnited StatesAntibodies, Monoclonal, HumanizedAntineoplastic AgentsatezolizumabImmune Checkpoint InhibitorsAdverse eventsAtezolizumabFAERSPharmacovigilanceSafety profile

Identifiers

PMID41298739
PMCPMC12658018

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

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.