ArticleJournal of translational medicine2019
Novel nomograms to predict lymph node metastasis and liver metastasis in patients with early colon carcinoma.
Article in Journal of translational medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- [Construction and evaluation of an artificial intelligence-based risk prediction model for death in patients with nasopharyngeal cancer].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2023Trial
- Trial
- A web-based prediction model for overall survival of elderly patients with early renal cell carcinoma: a population-based study.Journal of translational medicine · 2022Trial
- A Web-Based Prediction Model for Cancer-Specific Survival of Middle-Aged Patients With Non-metastatic Renal Cell Carcinoma: A Population-Based Study.Frontiers in public health · 2022Trial
- A Web-Based Prediction Model for Overall Survival of Elderly Patients With Malignant Bone Tumors: A Population-Based Study.Frontiers in public health · 2021Trial
- Development and external validation of a nomogram for overall survival in oral tongue squamous cell carcinoma using machine learning-assisted feature selection.Scientific reports · 2026Article
- Machine learning based prognostic model for oral squamous cell carcinoma using SEER data and external validation.iScience · 2026Article
- [Development and validation of a multicenter nomogram predicting the risk of liver metastasis after curative resection of colorectal cancer].Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2026Article
- Elevated fibrosis‑4 index is associated with 30-day mortality in adult hemophagocytic lymphohistiocytosis patients.Annals of hematology · 2025Article
- Deep learning models based on multiparametric magnetic resonance imaging and clinical parameters for identifying synchronous liver metastases from rectal cancer.BMC medical imaging · 2025Article
- Risk factors of surgical compliance and impact on survival in patients with kidney cancer: a population-based, propensity score matching study.Langenbeck's archives of surgery · 2024Article
- Unveiling the best predictive models for early‑onset metastatic cancer: Insights and innovations (Review).Oncology reports · 2024Review
- Predictive modeling algorithms for liver metastasis in colorectal cancer: A systematic review of the current literature.Annals of hepato-biliary-pancreatic surgery · 2024Review
- Predictors of early colorectal cancer metastasis to lymph nodes: providing rationale for therapy decisions.Frontiers in oncology · 2024Review
- Article
- A New Online Dynamic Nomogram: Construction and Validation of a Predictive Model for Distant Metastasis Risk and Prognosis in Patients with Gastrointestinal Stromal Tumors.Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract · 2023Review
- Construction and validation of a nomogram of risk factors and cancer-specific survival prognosis for combined lymphatic metastases in patients with early-onset colorectal cancer.International journal of colorectal disease · 2023Article
- LncRNA LINC01232 Enhances Proliferation, Angiogenesis, Migration and Invasion of Colon Adenocarcinoma Cells by Downregulating miR-181a-5p.Journal of microbiology and biotechnology · 2023Article
- A novel potential inflammation-nutrition biomarker for predicting lymph node metastasis in clinically node-negative colon cancer.Frontiers in oncology · 2023Article
- Development and external validation of prognostic nomograms for liver disease-free and overall survival in locally advanced rectal cancer with neoadjuvant therapy: a post cohort study based on the FOWARC trial.Annals of translational medicine · 2022Article
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9 authors.
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Abstract
backgroundLymph node status and liver metastasis (LIM) are important in determining the prognosis of early colon carcinoma. We attempted to develop and validate nomograms to predict lymph node metastasis (LNM) and LIM in patients with early colon carcinoma.
methodsA total of 32,819 patients who underwent surgery for pT1 or pT2 colon carcinoma were enrolled in the study based on their records in the SEER database. Risk factors for LNM and LIM were assessed based on univariate and multivariate binary logistic regression. The C-index and calibration plots were used to evaluate LNM and LIM model discrimination. The predictive accuracy and clinical values of the nomograms were measured by decision curve analysis. The predictive nomograms were further validated in the internal testing set.
resultsThe LNM nomogram, consisting of seven features, achieved the same favorable prediction efficacy as the five-feature LIM nomogram. The calibration curves showed perfect agreement between nomogram predictions and actual observations. The decision curves indicated the clinical usefulness of the prediction nomograms. Receiver operating characteristic curves indicated good discrimination in the training set (area under the curve [AUC] = 0.667, 95% CI 0.661-0.673) and the testing set (AUC = 0.658, 95% CI 0.649-0.667) for the LNM nomogram and encouraging performance in the training set (AUC = 0.766, 95% CI 0.760-0.771) and the testing set (AUC = 0.825, 95% CI 0.818-0.832) for the LIM nomogram.
conclusionNovel validated nomograms for patients with early colon carcinoma can effectively predict the individualized risk of LNM and LIM, and this predictive power may help doctors formulate suitable individual treatments.
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