Evidence map›Paper›PMID 40847031›Full record

ArticleScientific reports2025

A prediction model based on cfDNA concentration and cfDNA methylation biomarkers for lung cancer detection.

Li Ke, Xiang Huang, Wenting Liu, Bo Hong, Hongzhi Wang, Jian Qi, Yannan Chu

Abstract read
PubMed Full text at PMC Publisher
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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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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

7 authors.

Li KeUniversity of Science and Technology of China, Hefei, China.
Xiang HuangUniversity of Science and Technology of China, Hefei, China.
Wenting LiuUniversity of Science and Technology of China, Hefei, China.
Bo HongUniversity of Science and Technology of China, Hefei, China.
Hongzhi WangUniversity of Science and Technology of China, Hefei, China. wanghz@hfcas.ac.cn.
Jian QiUniversity of Science and Technology of China, Hefei, China. qijian@mail.ustc.edu.cn.
Yannan ChuUniversity of Science and Technology of China, Hefei, China. ychu@aiofm.ac.cn.

Funding

the National Natural Science Foundation of China 21876176the President Foundation of Hefei Institute of Physical Sciences YZJJZX202009
6 · The paper itself

Abstract

Early detection plays a critical role in reducing lung cancer mortality. DNA methylation biomarker assay based on cell-free DNA (cfDNA) is a promising method for early detection of lung cancer. In this study, we aimed to develop a prediction model based on cfDNA methylation biomarkers and cfDNA concentration for early detection of lung cancer. We recruited 179 lung cancer patients and 82 healthy controls, and assessed the methylation level of four DNA methylation biomarkers (PTGER4, RASSF1A, SHOX2, and H4C6) and cfDNA concentration. The LASSO and Boruta algorithms were then used to select the best performing variables, and a lung cancer prediction model was constructed using the generalized linear models (GLMs) algorithm. The model was then validated in an independent set. Finally, the AUC for this model in the training and validation cohorts was 0.8012 and 0.8436, respectively. The accuracy of the model was significantly higher than the individual biomarkers. These results demonstrated that this panel based on four methylation markers and cfDNA concentration was effective in lung cancer detection, and may provide clinical utility in combination with current lung cancer detection techniques to improve the diagnosis of lung cancer.

Indexed as

Biomarkers, TumorCell-Free Nucleic AcidsDNA MethylationLung NeoplasmsAgedAlgorithmsCase-Control StudiesEarly Detection of CancerFemaleHumansMaleMiddle AgedTumor Suppressor ProteinsBiomarkers, TumorCell-Free Nucleic AcidsRASSF1 protein, humanTumor Suppressor ProteinsCell-free DNAEarly detectionLung cancerMethylation biomarker

Identifiers

PMID40847031
PMCPMC12373927

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