Evidence map›Paper›PMID 38919222›Full record

ArticleCureus2024

Elevated Levels of the Cancer Marker Neuron-Specific Enolase in a Patient With Coexisting Silicosis and Sarcoidosis.

Khishigtogtokh Davaajav, Dolgormaa Dagva, Ichinnorov Dashtseren, Yoshimitsu Takahashi, Takeo Nakayama

Abstract readCase Reports
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Khishigtogtokh DavaajavHealth Informatics, Kyoto University, Graduate School of Medicine, Kyoto, JPN.
Dolgormaa DagvaForensic Medicine, National Forensic Agency of Mongolia, Ulaanbaatar, MNG.
Ichinnorov DashtserenPulmonology and Allergology, Mongolian National University of Medical Sciences, School of Medicine, Ulaanbaatar, MNG.
Yoshimitsu TakahashiHealth Informatics, Kyoto University, Graduate School of Medicine, Kyoto, JPN.
Takeo NakayamaHealth Informatics, Kyoto University, Graduate School of Medicine, Kyoto, JPN.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In a periodical medical checkup, a 39-year-old Mongolian underground miner was diagnosed with silicosis based on chest radiography, computed tomography (CT), and work history. Chest radiography showed diffuse bilateral rounded nodules in both lung fields, with upper lobe dominance and large opacities in the right upper zone. Chest CT presented conglomerated massive changes in the right upper lobe and the coalescence of small nodules in the left upper lung. In the blood test, serum levels of the lung cancer marker neuron-specific enolase (NSE) were elevated (24.58 ng/mL). Carcinoembryonic antigen (CEA) and cytokeratin 19 fragment (CYFRA 21-1) levels were within the reference range. Subsequent to the suspicion of a tumour in the right upper lobe, a right upper lobectomy was performed. The histopathological examination of the lung specimen revealed the coalescence of numerous silica nodules, accompanied by indications of associated sarcoidosis. The histological features suggested the presence of two concurrent pathological processes: silicosis and sarcoidosis. This case demonstrated the combination of three clinical conditions diagnosed in one patient, including complicated silicosis associated with sarcoidosis and elevated serum NSE levels. This case report may serve as a foundation for future investigations exploring the potential of NSE as a marker for silicosis.

Indexed as

cancer markerlung cancersoccupational exposure to silicapulmonary sarcoidosissilicosis

Identifiers

PMID38919222
PMCPMC11198998

What OpenQuestion holds

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Registered trials

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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.