Evidence map›Paper›PMID 42249647›Full record

ArticleCancer medicine2026

Development and Validation of a Predictive Nomogram for Diagnosing Colorectal Cancer Based on Immune-Nutritional Score.

Xiaofan Liu, Liuqun Shan, Wei Liang, Lin Fu, Rong Wu, Linzhu Zhang, Qian Lv, Wei Shi, Fei Fei

Abstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer medicine, 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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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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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Xiaofan LiuDepartment of Oncology, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.ORCID https://orcid.org/0009-0004-5594-1219
Liuqun ShanDepartment of General Surgery, The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, People's Republic of China.
Wei LiangDepartment of Oncology, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.
Lin FuInformation Statistics Center, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.
Rong WuDepartment of Scientific and Technology, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.
Linzhu ZhangDepartment of Oncology, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.ORCID https://orcid.org/0009-0002-7527-1983
Qian LvDepartment of Pathology, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.
Wei ShiState Key Laboratory of Natural Medicines, Center of Drug Discovery, China Pharmaceutical University, Nanjing, Jiangsu, People's Republic of China.
Fei FeiDepartment of Oncology, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.ORCID https://orcid.org/0000-0002-6815-7931

Funding

China Postdoctoral Science Foundation 2024M763658Foundation for Innovative Research Groups of the National Natural Science Foundation of China 82203182Project of Future Technology Star of Nanjing First Hospital
6 · The paper itself

Abstract

backgroundEarly diagnosis of colorectal cancer (CRC) can significantly improve prognosis, but currently there is a lack of simple and effective screening methods in clinical practice.

methodsThis single-center retrospective study included patients with CRC and benign colorectal polyps (BCP) diagnosed at our hospital between December 2020 and December 2023, as well as healthy controls (HCs). Eligible participants were randomly assigned to a training cohort and an internal validation cohort in a 7:3 ratio. Univariable and multivariable logistic regression analyses were performed in the training cohort to identify independent diagnostic predictors of CRC. A diagnostic nomogram was then constructed based on these predictors and internally validated.

resultsSix hundred forty seven CRC, 365 BCP, and 400 HC were ultimately included in the study. Univariate and multivariate analysis showed that sex, HB, CEA, CA19-9, CONUT score, and HALP score were independent diagnostic predictors associated with CRC. The internal validation results indicated that the predictive ability of the nomogram (AUC

conclusionThis study integrated multiple independent diagnostic predictors of CRC and developed an internally validated diagnostic nomogram with good discrimination and calibration in this single-center retrospective cohort.

Indexed as

Colorectal NeoplasmsEarly Detection of CancerNomogramsAgedFemaleHumansMaleMiddle AgedPrognosisRetrospective Studiescolorectal cancerdiagnosisimmune‐nutritional scorenomogram

Identifiers

PMID42249647
PMCPMC13241691

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