Evidence map›Paper›PMID 36313675›Full record

ArticleFrontiers in oncology2022

Peripheral absolute eosinophil count identifies the risk of serious immune-related adverse events in non-small cell lung cancer.

Yan Wu, Dapeng Li, Mengyao Wu, Ying Yang, Meng Shen, Kai Chen

Abstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
–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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

6 authors.

Yan WuDepartment of Oncology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Dapeng LiDepartment of Oncology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Mengyao WuDepartment of Oncology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Ying YangDepartment of Oncology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Meng ShenDepartment of Oncology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Kai ChenDepartment of Oncology, The First Affiliated Hospital of Soochow University, Suzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Immune-related adverse events (irAEs) have drawn a lot of attention lately as a result of the predominance of immunotherapy in advanced non-small cell lung cancer (NSCLC). However, the clinical evidence for irAEs in real life is limited. In this paper, the occurrence of irAEs in Chinese NSCLC patients was examined, and possible risk factors for the emergence of severe irAEs were discovered. Methods: Our retrospective investigation assessed the occurrence of adverse events (AEs) and prognosis of 213 patients who received immunotherapy for NSCLC. Using univariate and multivariate logistic regression models, the association between clinicopathological traits and the incidence of severe irAEs was investigated. To assess the prognostic impact of irAEs, survival data was analyzed. Results: Among the 213 NSCLC patients, 122 (57.3%) had irAEs of any grade, and 38 (17.8%) had high-grade (grade 3-5) AEs. Baseline peripheral absolute eosinophil count (AEC) (HR 6.58, 95% CI: 1.5-28.8, P=0.012) was found to be an independent predictor of high-grade irAEs by multivariate analysis. The survival analysis revealed that patients with severe irAEs had worse OS (15.7 vs. 20.8 months, 95% CI: 11.6-19.8 vs. 16.0-25.5, P=0.026). Conclusion: According to our findings, the peripheral absolute eosinophil count (AEC) is a reliable indicator of severe irAEs in NSCLC. Serious irAEs that occur in patients often reflect poor prognoses. In the future, high-grade irAEs should receive more attention.

Indexed as

high-gradeimmune-related adverse eventsnon-small cell lung cancerpredictorprognosisreal-world evidence

Identifiers

PMID36313675
PMCPMC9608122

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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.