Evidence map›Paper›PMID 42311240›Full record

ArticleFrontiers in oncology2026

Clinicopathological characteristics of alveolar adenoma.

Jing Chen, Zhengjin Liu, Wei Zheng, Huiling Chen, Zeyang Lin, Zhe Li

Abstract read
In one paragraph

Article in Frontiers in oncology, 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
0cells of the map it votes in
0citing 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

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

6 authors.

Jing Chen *Department of Pathology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Zhengjin Liu *Department of Pathology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Wei Zheng *Department of Pathology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Huiling ChenDepartment of Pathology, The People's Hospital of Guangxi Zhuang Autonomous Region (Guangxi Academy of Medical Sciences), Nanning, China.
Zeyang LinDepartment of Pathology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Zhe LiDepartment of Thoracic Surgery, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Alveolar adenoma is an uncommon benign lung tumor that typically appears as a well-defined nodule on imaging and pathological examination. Currently, there is limited research on alveolar adenoma. This article aims to present this rare tumor by describing three cases. Methods: We reviewed and analyzed the morphological and immunohistochemical characteristics of three cases using hematoxylin and eosin (HE) staining and immunohistochemistry (IHC). Results: The alveolar adenomas exhibited well-defined tumors composed of well-differentiated cuboidal or flattened alveolar epithelial cells that formed glandular or cystic structures of varying sizes, accompanied by well-differentiated spindle cell stroma. Immunohistochemical analysis showed consistently strong and widespread CD34 expression in the stromal cells in all cases. Additionally, CD10 was diffusely positive in stromal cells in about two-thirds of the cases, with focal positivity observed in the remaining case. Discussion: While previous research has not identified specific immunohistochemical markers, our findings are interesting, and we suggest that these markers could be useful in diagnosing alveolar adenoma.

Indexed as

alveolar adenomaCD10CD34diagnosisdifferential diagnosis

Identifiers

PMID42311240
PMCPMC13268956

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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.