Evidence map›Paper›PMID 40235907›Full record

ArticleWorld journal of gastrointestinal oncology2025

Precision medicine in the prediction of metachronous liver metastasis in rectal cancer: Applications and challenges.

Xu-Xing Ye, Hui-Heng Qu, Chao Yang, Wei-Jun Teng, Yan-Ping Chen, Jun-Mei Lin, Xiao-Bo Wang

Abstract readEditorial
PubMed Full text at PMC Publisher
In one paragraph

Article in World journal of gastrointestinal oncology, 2025. 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

7 authors.

Xu-Xing YeDepartment of Traditional Chinese Medicine, Jinhua Municipal Central Hospital, Jinhua 321000, Zhejiang Province, China.
Hui-Heng QuDepartment of General Surgery, Wuxi No. 2 people's Hospital, Wuxi 214002, Jiangsu Province, China.
Chao YangThe Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou 310000, Zhejiang Province, China.
Wei-Jun TengDepartment of Gastroenterology, Jinhua Municipal Central Hospital, Jinhua 321000, Zhejiang Province, China.
Yan-Ping ChenDepartment of Gastroenterology, Jinhua Municipal Central Hospital, Jinhua 321000, Zhejiang Province, China.
Jun-Mei LinDepartment of Traditional Chinese Medicine, Jinhua Municipal Central Hospital, Jinhua 321000, Zhejiang Province, China.
Xiao-Bo WangThe Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou 310000, Zhejiang Province, China. wxb2310@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rectal cancer is a major global health concern, and metachronous liver metastasis (MLM) significantly worsens patient prognosis. Advances in imaging and machine learning have led to the development of radiomics models, particularly those utilizing multiparametric magnetic resonance imaging, which are highly valuable in predicting MLM. These models analyze imaging features to provide insights that can aid clinical decision-making and potentially improve treatment outcomes and survival rates. However, realizing the full potential of radiomics models faces challenges in terms of accuracy, generalizability, and data dependency. This editorial comments on a study regarding radiomics prediction models for rectal cancer MLM published recently in the

Indexed as

Magnetic resonance imagingMetachronous liver metastasisPredictive modelingRadiomicsRectal cancer

Identifiers

PMID40235907
PMCPMC11995326

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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.