Evidence map›Paper›PMID 42215721›Full record

ArticleLangenbeck's archives of surgery2026

A predictive model for metastatic colorectal cancer based on immune cells and tumor markers.

Chentong Mao, Zhongyuan Bai, Hongling Zhang, Shuzhe Yang, Jianghong Guo, Jiayi Wu, Yanfeng Xi

Abstract read
In one paragraph

Article in Langenbeck's archives of surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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.

Chentong MaoThe Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China.
Zhongyuan BaiThe Fifth Affiliated Hospital of Shanxi Medical University, Taiyuan, China.
Hongling ZhangThe Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China.
Shuzhe YangThe Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China.
Jianghong GuoPathology Department, Shanxi Province Cancer Hospital/ Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Taiyuan, China.
Jiayi WuThe Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China.
Yanfeng XiThe Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China. xiyanfeng1998@163.com.

Funding

Natural Science Foundation of China 82172659
6 · The paper itself

Abstract

objectiveThis study aims to investigate the relationship between immune cell levels, tumor markers, and metastatic colorectal cancer (mCRC), evaluate their predictive efficacy, and construct a predictive model.

methodRetrospectively selected patients diagnosed with colorectal cancer (CRC) through pathological examination at Shanxi Cancer Hospital between January 2016 and December 2018. T-tests and chi-square tests were used to identify clinical and pathological characteristics associated with mCRC. Evaluate predictive performance using the ROC curve. A risk factor scoring system is constructed based on immune cell levels and tumor markers, categorizing patients into low-risk and high-risk groups according to their scores. Single-factor and multi-factor logistic regression analyses were employed to identify independent predictors and construct a nomogram.

resultsA total of 270 patients with CRC were included, including 45 cases of mCRC. Statistical analysis results indicate that peripheral blood laboratory indicators associated with mCRC include immune cell levels (Th, Tc, Th/Tc) and tumor markers (CEA, CA199, CA242, CA724, CA50). The risk factor scoring system revealed that the incidence of distant metastasis was significantly higher in the high-risk group than in the low-risk group (P < 0.001). Furthermore, logistic regression analysis results indicate that the risk factor score is an independent predictor of distant metastasis in CRC.

conclusionA risk factor scoring system based on immune cell levels (Th, Tc, Th/Tc) and tumor markers (CEA, CA199, CA242, CA724, CA50) effectively predicts the occurrence of mCRC. This approach holds promise as a non-invasive tool for dynamic monitoring of distant metastasis risk in clinical practice.

Indexed as

Biomarkers, TumorColorectal NeoplasmsAgedFemaleHumansMaleMiddle AgedNeoplasm MetastasisNomogramsPredictive Value of TestsPrognosisRetrospective StudiesRisk FactorsBiomarkers, TumorColorectal cancerDistant metastasisImmune cell levelsTumor markers

Identifiers

PMID42215721
PMCPMC13396018

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.