Evidence map›Paper›PMID 40804569›Full record

ArticleAnnals of surgical oncology2026

Establishing Clinically Significant Prostate Cancer Diagnosis Models Based on Serum Methylation Levels of Four Genes.

Jinyan Xu, Ya Wu, Wei Ma, Rui He, Daoyuan Yue, Zhen Kang, Xuguang Liu, Jun Zhou, Shaogang Wang, Bo Shu and 2 more

Abstract read
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Article in Annals of surgical oncology, 2026. 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

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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.

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4 · The record

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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

12 authors.

Jinyan Xu *Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Ya Wu *Wuhan BGI Clinical Laboratory Co., Ltd, Wuhan, China.
Wei Ma *Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Rui HeDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Daoyuan YueDepartment of Clinical Laboratory, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China.
Zhen KangDepartment of Radiology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Xuguang LiuDepartment of Pathology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Jun ZhouDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Shaogang WangDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Bo ShuDepartment of Urology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. 2015103030020@whu.edu.cn.
Xiong WangDepartment of Clinical Laboratory, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China. wangxiong@tjh.tjmu.edu.cn.
Chunguang YangDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. cgyang-hust@hotmail.com.

Funding

Chunguang Yang Hubei key R&D project (2023DJC160)
6 · The paper itself

Abstract

backgroundProstate cancer is the most common malignant tumor of the male reproductive system. Improving the ability of noninvasive diagnosis of prostate cancer is an urgent clinical problem to be solved and has broad research prospects. Our explores the application value of serum DNA methylation indicators and models in the diagnosis of clinically significant prostate cancer (csPCa), including its diagnostic efficiency and application in unnecessary biopsy.

methodsThis study retrospectively enrolled 223 Chinese patients and recorded patients' clinical information. Five serum gene promoter methylation levels were detected before operation and then established various logistic regression models based on serum methylation levels and clinical information. The diagnostic efficacy of each model for csPCa was analyzed and compared.

resultsIn our research, the area under the receiver operating curve of serum methylation regression model (abbreviated as GRP) was significantly higher than that of traditional models based on prostate specific antigen model (p < 0.05). When the sensitivity of the model was 95.0% or greater, and the rate of unnecessary biopsy was increased by 33.1%, the rate of missed diagnosis was only 5.8% (3/56). The net clinical benefit of GRP model was also much higher than that of the other two models in the decision curve analysis.

conclusionsThe diagnostic capacity of the serum methylation regression model is superior to the traditional model. Compared with traditional model, it can reduce the number of unnecessary prostate biopsy by 16.5% to 21.6%, and the rate of missed diagnosis is not significantly improved.

Indexed as

Biomarkers, TumorDNA MethylationProstatic NeoplasmsAgedFollow-Up StudiesHumansMaleMiddle AgedNeoplasm GradingNeoplasm StagingPrognosisPromoter Regions, GeneticProstate-Specific AntigenRetrospective StudiesROC CurveBiomarkers, TumorProstate-Specific Antigen

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Registered trials

None linked

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 Socratic graph.