ArticleClinical and translational medicine2020
Development and external validation of a predictive scoring system associated with metastasis of T1-2 colorectal tumors to lymph nodes.
Article in Clinical and translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Nomogram Development for Predicting Synchronous Lung Metastasis in Patients with T1 Colorectal Cancer: An SEER-Based Analysis.Medicina (Kaunas, Lithuania) · 2026Article
- Machine learning to develop and validate a model for predicting the risk of lymph node metastasis in colorectal cancer patients.Frontiers in oncology · 2026Article
- Mendelian Randomization-Based Discovery of Novel Protein Biomarkers and Drug Targets in Colorectal Cancer: Validation Through Prognostic Modeling, Single-Cell Analysis, and In Vitro Cell Experiments.Applied biochemistry and biotechnology · 2025Article
- Somatic mutation correlation with lymph node metastasis and prognosis in T1/2 stage colorectal cancer patients: A propensity score matching analysis.Clinical and translational medicine · 2025Article
- Germline polymorphisms of the NOD2 pathway may predict the effectiveness of radioiodine in differentiated thyroid cancer treatment.Journal of endocrinological investigation · 2024Article
- Unveiling the best predictive models for early‑onset metastatic cancer: Insights and innovations (Review).Oncology reports · 2024Review
- Perineural invasion in colorectal cancer: mechanisms of action and clinical relevance.Cellular oncology (Dordrecht, Netherlands) · 2024Review
- LC-MS/MS analysis reveals plasma protein signatures associated with lymph node metastasis in colorectal cancer.Frontiers in immunology · 2024Article
- Predictors of early colorectal cancer metastasis to lymph nodes: providing rationale for therapy decisions.Frontiers in oncology · 2024Review
- Development and Validation of Risk Prediction Models for Colorectal Cancer in Patients with Symptoms.Journal of personalized medicine · 2023Article
- Prediction of lymph node metastasis in stage T1-2 rectal cancers with MRI-based deep learning.European radiology · 2023Article
- Diagnostic performance of synthetic magnetic resonance imaging in the prognostic evaluation of rectal cancer.Quantitative imaging in medicine and surgery · 2022Article
- Nerve Dependence in Colorectal Cancer.Frontiers in cell and developmental biology · 2022Review
- FOLFIRI (folinic acid, fluorouracil, and irinotecan) increases not efficacy but toxicity compared with single-agent irinotecan as a second-line treatment in metastatic colorectal cancer patients: a randomized clinical trial.Therapeutic advances in medical oncology · 2022Article
- Establishment of a Dynamic Nomogram for Predicting the Risk of Lymph Node Metastasis in T1 Stage Colorectal Cancer.Frontiers in surgery · 2022Article
- Development and validation of a nomogram for further decision of radical surgery in pT1 colorectal cancer after local resection.International journal of colorectal disease · 2021Article
- Development and Validation of the Individualized Prognostic Nomograms in Patients With Right- and Left-Sided Colon Cancer.Frontiers in oncology · 2021Article
- Development and external validation of a predictive scoring system associated with metastasis of T1-2 colorectal tumors to lymph nodes.Clinical and translational medicine · 2020Article
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Authors and funding
10 authors.
Funding
Abstract
backgroundIt is critical for determining the optimum therapeutic solutions for T1-2 colorectal cancer (CRC) to accurately predict lymph node metastasis (LNM) status. The purpose of the present study is to establish and verify a nomogram to predict LNM status in T1-2 CRCs.
methodsA total of 16 600 T1-2 CRC patients were enrolled and classified into the training, internal validation, and external validation cohorts. The independent predictive parameters were determined by univariate and multivariate analyses to develop a nomogram to predict the probability of LNM status. The calibration curve, the area under the receiver operating characteristic curve (AUROC), and decision curve analysis (DCA) were used to evaluate the performance of the nomogram, and an external verification cohort was to verify the applicability of the nomogram.
resultsSeven independent predictors of LNM in T1-2 CRC were identified in the multivariable analysis, including age, tumor site, tumor grade, perineural invasion, preoperative carcinoembryonic antigen, clinical assessment of LNM, and T stage. A nomogram incorporating the seven predictors was constructed. The nomogram yielded good discrimination and calibration, with AUROCs of 0.72 (95% confidence interval [CI]: 0.70-0.75), 0.70 (95% CI: 0.67-0.74), and 0.74 (95% CI: 0.71-0.79) in the training, internal validation, and external validation cohorts, respectively. DCA showed that the predictive scoring system had high clinical application value.
conclusionsWe proposed a novel predictive model for LNM in T1-2 CRC patients to assist physicians in making treatment decisions. The nomogram is advantageous for tailoring therapy in T1-2 CRC patients.
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