Evidence map›Paper›PMID 38549716›Full record

ArticleDisease markers2024

Determination of Tumor Marker Screening for Lung Cancer Using ROC Curves.

Xiaofeng Dou, Jiachen Lu, Yingying Yu, Yaohui Yi, Ling Zhou

Open access · hybridAbstract read
In one paragraph

Article in Disease markers, 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
0.8field-weighted citation impact, top 25% of its field
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, 3 citations in OpenAlex.

  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 at 1 institution in 1 country.

Xiaofeng DouSchool of Public Health, Dalian Medical University, Dalian 116044, Liaoning, China.ORCID https://orcid.org/0009-0005-6070-6894
Jiachen LuSchool of Public Health, Dalian Medical University, Dalian 116044, Liaoning, China.ORCID https://orcid.org/0009-0009-7359-531X
Yingying YuSchool of Public Health, Dalian Medical University, Dalian 116044, Liaoning, China.ORCID https://orcid.org/0009-0006-8446-1999
Yaohui YiSchool of Public Health, Dalian Medical University, Dalian 116044, Liaoning, China.ORCID https://orcid.org/0009-0004-3802-5024
Ling ZhouSchool of Public Health, Dalian Medical University, Dalian 116044, Liaoning, China.ORCID https://orcid.org/0009-0003-4692-2772
Dalian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Lung cancer ranks first among malignant tumors worldwide and is a leading cause of cancer-related mortality in both men and women. Combining tumor marker testing is a strategy to screen individuals at high risk of pulmonary cancer and minimize pulmonary cancer mortality. Therefore, tumor marker screening is crucial. In this study, we analyzed combinations of tumor markers for lung cancer screening using receiver operating characteristic (ROC) curve analysis. Methods: A retrospective descriptive study was conducted on patients diagnosed with lung cancer, as well as healthy and benign lung diseases, using data from the China Huludao Central Hospital database between January 2016 and July 2022. The Results: In this study, 267 healthy participants, 385 patients with benign lesions, and 296 patients with lung cancer underwent tumor marker screening. The sensitivity of five tumor markers-CEA, CYFRA21-1, NSE, pro-GRP, and CA125-was found to be <55%. This study revealed that a single tumor marker had limited value in lung cancer screening. However, combining two or more markers yielded varying area under the curves (AUC), with no significant impact on screening accuracy. The combination of CEA + CA125 demonstrated the highest accuracy for lung cancer screening in healthy participants. At a cutoff of 0.447 for CEA + CA125, the combination showed a sensitivity of 0.676 and specificity of 0.846 for lung cancer screening. Conversely, for patients with benign lung lesions, the optimal combination was CEA + NSE, with a cutoff of 0.393, yielding a sensitivity of 0.645 and specificity of 0.766 for lung cancer screening. Conclusion: The five tumor markers-CEA, CA125, CY211, NSE, GRP-show promising results in screening healthy individuals and patients with lung cancer. However, only CEA, NSE, and GRP effectively differentiate patients with benign lung lesions from those with lung cancer. A single tumor marker has limited utility in detecting and screening for lung cancer and should be combined with other tumor markers. CEA + CA125 emerges as a superior tumor marker for distinguishing healthy individuals from those with lung cancer, whereas the CEA + NSE combination is more effective in identifying tumor markers in patients with benign lung lesions and lung cancer.

Indexed as

Lung NeoplasmsAntigens, NeoplasmBiomarkers, TumorCarcinoembryonic AntigenEarly Detection of CancerFemaleHumansKeratin-19MaleRetrospective StudiesROC Curveantigen CYFRA21.1Antigens, NeoplasmBiomarkers, TumorCarcinoembryonic AntigenKeratin-19

Identifiers

PMID38549716
PMCPMC10978075
OpenAlexW4393029958

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.