Evidence map›Paper›PMID 40248373›Full record

ArticleWorld journal of gastroenterology2025

Prognostic scoring system using inflammation- and nutrition-related biomarkers to predict prognosis in stage I-III colorectal cancer patients.

Ke-Jin Li, Zi-Yi Zhang, Kuan Wang, Subinur Sulayman, Xiang-Yue Zeng, Juan Liu, Yi Chen, Ze-Liang Zhao

Abstract readValidation Study
In one paragraph

Article in World journal of gastroenterology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
–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

31 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

8 authors.

Ke-Jin LiDepartment of Gastrointestinal Surgery, The Affiliated Cancer Hospital of Xinjiang Medical University, Urumqi 830000, Xinjiang Uygur Autonomous Region, China.
Zi-Yi ZhangDepartment of Gastrointestinal Surgery, The Affiliated Cancer Hospital of Xinjiang Medical University, Urumqi 830000, Xinjiang Uygur Autonomous Region, China.
Kuan WangDepartment of Gastrointestinal Surgery, The Affiliated Cancer Hospital of Xinjiang Medical University, Urumqi 830000, Xinjiang Uygur Autonomous Region, China.
Subinur SulaymanDepartment of Gastrointestinal Surgery, The Affiliated Cancer Hospital of Xinjiang Medical University, Urumqi 830000, Xinjiang Uygur Autonomous Region, China.
Xiang-Yue ZengDepartment of Gastrointestinal Surgery, The Affiliated Cancer Hospital of Xinjiang Medical University, Urumqi 830000, Xinjiang Uygur Autonomous Region, China.
Juan LiuDepartment of Gastrointestinal Surgery, The Affiliated Cancer Hospital of Xinjiang Medical University, Urumqi 830000, Xinjiang Uygur Autonomous Region, China.
Yi ChenDepartment of Breast and Thyroid Surgery, The Affiliated Cancer Hospital of Xinjiang Medical University, Xinjiang Key Laboratory of Oncology, Urumqi 830000, Xinjiang Uygur Autonomous Region, China.
Ze-Liang ZhaoDepartment of Gastrointestinal Surgery, The Affiliated Cancer Hospital of Xinjiang Medical University, Urumqi 830000, Xinjiang Uygur Autonomous Region, China. zlzhao71@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundColorectal cancer (CRC) is a common malignancy that has become a global burden. The prognostic prediction of CRC patients on the basis of inflammatory biomarkers and nutritional biomarkers has shown some potential but has not been fully explored.

aimTo develop and validate a prognostic model for CRC based on inflammation and nutrition-related biomarkers and to evaluate its predictive value for patient outcomes.

methodsPatients were randomized at a 3:2 ratio into a training cohort (

resultsIn the training cohort, univariate analysis of all the inflammatory and nutritional biomarkers demonstrated some predictive value. A LASSO-Cox analysis included four biomarkers and constructed an RS. Through ROC analysis, the area under the prognostic curve was 0.795. K-M survival curve analyses revealed that the five-year OS was significantly greater in the Low-RS group than in the High-RS group (

conclusionThis study developed a nomogram based on the RS to predict the OS of CRC patients. This nomogram can guide treatment decisions and enable the formulation of personalized follow-up strategies on the basis of predicted recurrence risk, aiming to improve long-term prognosis.

Indexed as

Biomarkers, TumorColorectal NeoplasmsInflammationAdultAgedFemaleHumansKaplan-Meier EstimateMaleMiddle AgedNeoplasm StagingNomogramsNutritional StatusPredictive Value of TestsPrognosisProportional Hazards ModelsBiomarkers, TumorColorectal cancerInflammationNutritionOverall survivalPrognosis

Identifiers

PMID40248373
PMCPMC12001188

What Socratic holds

Textmetadata
LicenceCC BY-NC
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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.