Evidence map›Paper›PMID 41951831›Full record

ArticleNPJ precision oncology2026

Identification of biomarkers for non-invasive diagnosis and risk stratification in prostate cancer using NMR-based metabolomics and machine learning.

Xi Zhang, Minjiang Chen, Binbin Xia, Binrui Liu, Xiaoya Lin, Hanyang Tao, He Wang, Tengfei Gu, Jie Li, Baijun Dong and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ precision 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

11 authors.

Xi Zhang *School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, China.
Minjiang Chen *Department of Urology, Lishui Central Hospital, Lishui, China.
Binbin Xia *Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Binrui LiuSchool of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, China.
Xiaoya LinSchool of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, China.
Hanyang TaoDepartment of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
He WangSchool of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, China.
Tengfei GuDepartment of Urology, Lishui Central Hospital, Lishui, China.
Jie LiDepartment of Urology, Lishui Central Hospital, Lishui, China.
Baijun DongDepartment of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. dongbaijun@renji.com.
Hongchang GaoSchool of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, China. gaohc27@wmu.edu.cn.ORCID http://orcid.org/0000-0003-3462-1879

Funding

Key Research and Development Program of Zhejiang Province 2019C03030National Natural Science Foundation of China 32400047Natural Science Foundation of Zhejiang Province LQ23H020010
6 · The paper itself

Abstract

The non-invasive diagnosis and risk stratification of prostate cancer (PCa) remain clinically challenging due to the limited specificity of prostate-specific antigen (PSA). In this retrospective study, we applied a comparative machine learning (ML) framework to rank and select biomarkers from serum

Identifiers

PMID41951831
PMCPMC13237143

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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.