ArticleFrontiers in oncology2021
Preoperative Predictors of Lymph Node Metastasis in Colon Cancer.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 13 citations in OpenAlex.
- AI-Guided Ferroptosis Biomarker Discovery and Routine Laboratory-Based Machine Learning for Predicting Nodal Metastasis in Colon Cancer.Metabolites · 2026Article
- Nomogram for preoperative prediction of lymph node metastasis in patients with early submucosal right-sided colon cancer: a dual-center retrospective cohort study.Surgical endoscopy · 2026Article
- Article
- Pretreatment intravoxel incoherent motion histogram metrics and clinical characteristics for prediction of perineural invasion status and survival in patients with rectal cancer.Insights into imaging · 2025Article
- Prediction of lymph node metastasis in stage I-III colon cancer patients younger than 40 years.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Article
- Association of clinicopathological factor with lymph node metastasis in rectal cancer patients: a retrospective cohort study.BMC gastroenterology · 2025Article
- Predicting the risk of lymph node metastasis in colon cancer: development and validation of an online dynamic nomogram based on multiple preoperative data.BMC gastroenterology · 2025Article
- F-18 FDG PET/CT based Preoperative Machine Learning Prediction Models for Evaluating Regional Lymph Node Metastasis Status of Patients with Colon Cancer.Asian Pacific journal of cancer prevention : APJCP · 2025Article
- Predicting lymph node metastasis in colorectal cancer patients: development and validation of a column chart model.Updates in surgery · 2024Article
- Histogram analysis based on intravoxel incoherent motion diffusion-weighted imaging for determining the perineural invasion status of rectal cancer.Quantitative imaging in medicine and surgery · 2024Article
- A prediction nomogram for perineural invasion in colorectal cancer patients: a retrospective study.BMC surgery · 2024Article
- D-dimer to lymphocyte ratio can serve as a potential predictive and prognostic value in colorectal cancer patients with liver metastases.BMC surgery · 2023Article
- A novel potential inflammation-nutrition biomarker for predicting lymph node metastasis in clinically node-negative colon cancer.Frontiers in oncology · 2023Article
- Development and validation of a survival prediction model for 113,239 patients with colon cancer: a retrospective cohort study.Journal of gastrointestinal oncology · 2022Article
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9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLymph node metastasis (LNM) is a well-established prognostic factor for colon cancer. Preoperative LNM evaluation is relevant for planning colon cancer treatment. The aim of this study was to construct and evaluate a nomogram for predicting LNM in primary colon cancer according to pathological features. PATIENTS AND
methodsSix-hundred patients with clinicopathologically confirmed colon cancer (481 cases in the training set and 119 cases in the validation set) were enrolled in the Affiliated Cancer Hospital of Guangxi Medical University from January 2010 to December 2019. The expression of molecular markers (p53 and β-catenin) was determined by immunohistochemistry. Multivariate logistic regression was used to screen out independent risk factors, and a nomogram was established. The accuracy and discriminability of the nomogram were evaluated by consistency index and calibration curve.
resultsUnivariate logistic analysis revealed that LNM in colon cancer is significantly correlated (P <0.05) with tumor size, grading, stage, preoperative carcinoembryonic antigen (CEA) level, and peripheral nerve infiltration (PNI). Multivariate logistic regression analysis confirmed that CEA, grading, and PNI were independent prognostic factors of LNM (P <0.05). The nomogram for predicting LNM risk showed acceptable consistency and calibration capability in the training and validation sets.
conclusionsPreoperative CEA level, grading, and PNI were independent risk factor for LNM. Based on the present parameters, the constructed prediction model of LNM has potential application value.
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