ArticleChinese journal of cancer research = Chung-kuo yen cheng yen chiu2015
Nomogram for predicting lymph node metastasis rate of submucosal gastric cancer by analyzing clinicopathological characteristics associated with lymph node metastasis.
Article in Chinese journal of cancer research = Chung-kuo yen cheng yen chiu, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 3 of them syntheses that pooled it.
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7 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Risk prediction models for lymph node metastasis in early gastric cancer patients: a systematic review and meta-analysis.BMC gastroenterology · 2025Pooled it
- Relationship between histological mixed-type early gastric cancer and lymph node metastasis: A systematic review and meta-analysis.PloS one · 2022Pooled it
- Machine learning for lymph node metastasis prediction of in patients with gastric cancer: A systematic review and meta-analysis.Frontiers in oncology · 2022Pooled it
- Prediction Model of Lymph Node Metastasis Risk in Elderly Patients with Early Gastric Cancer before Endoscopic Resection: A Retrospective Analysis Based on International Multicenter Data.Journal of Cancer · 2021Article
- Construction and external validation of a nomogram that predicts lymph node metastasis in early gastric cancer patients using preoperative parameters.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2018Article
- A nomogram to predict adjuvant chemotherapy recommendation in breast cancer patients with intermediate recurrence score.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2018Article
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9 authors.
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Abstract
backgroundTo combine clinicopathological characteristics associated with lymph node metastasis for submucosal gastric cancer into a nomogram.
methodsWe retrospectively analyzed 262 patients with submucosal gastric cancer who underwent D2 gastrectomy between 1996 and 2012. The relationship between lymph node metastasis and clinicopathological features was statistically analyzed. With multivariate logistic regression analysis, we made a nomogram to predict the possibility of lymph node metastasis. Receiver operating characteristic (ROC) analysis was also performed to assess the predictive value of the model. Discrimination and calibration were performed using internal validation.
resultsA total number of 48 (18.3%) patients with submucosal gastric cancer have pathologically lymph node metastasis. For submucosal gastric carcinoma, lymph node metastasis was associated with age, tumor location, macroscopic type, size, differentiation, histology, the existence of ulcer and lymphovascular invasion in univariate analysis (all P<0.05). The multivariate logistic regression analysis identified that age ≤50 years old, macroscopic type III or mixed, undifferentiated type, and presence of lymphovascular invasion were independent risk factors of lymph node metastasis in submucosal gastric cancer (all P<0.05). We constructed a predicting nomogram with all these factors for lymph node metastasis in submucosal gastric cancer with good discrimination [area under the curve (AUC) =0.844]. Internal validation demonstrated a good discrimination power that the actual probability corresponds closely with the predicted probability.
conclusionsWe developed a nomogram to predict the rate of lymph node metastasis for submucosal gastric cancer. With good discrimination and internal validation, the nomogram improved individualized predictions for assisting clinicians to make appropriated treatment decision for submucosal gastric cancer patients.
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