Jianfeng Mu1, Zhifang Jia2, Weikai Yao3, Jiaxing Song4, Xueyuan Cao1, Jing Jiang2, Quan Wang1. 1. Department of Gastric & Colorectal Surgery, The First Hospital of Jilin University, Changchun 130021, PR China. 2. Division of Clinical Research, The First Hospital of Jilin University, Changchun 130021, PR China. 3. Department of Pathology, The First Hospital of Jilin University, Changchun 130021, PR China. 4. Clinical Laboratory, The First Hospital of Jilin University, Changchun 130021, PR China.
Abstract
Aim: To develop and validate a model to predict possibility of lymph node metastasis (LNM) in early gastric cancer. Materials & methods: An LNM prediction model was developed by logistic regression based on the demographics or characteristics of the tumor (N = 746) and then internally and externally validated (N = 126). Results: Four variables, lymphovascular invasion, differentiated types, diameter of tumor and T stage were screened into the model. The area under the receiver-operating characteristic curve of the model was 0.861 (95% CI: 0.851-0.864) in internal validation and 0.911 (95% CI: 0.848-0.974) in the validation set. Conclusion: The model shows excellent discrimination and calibration performance, and is potential to be a useful clinical model to predict the risk of LNM in early gastric cancer.
Aim: To develop and validate a model to predict possibility of lymph node metastasis (LNM) in early gastric cancer. Materials & methods: An LNM prediction model was developed by logistic regression based on the demographics or characteristics of the tumor (N = 746) and then internally and externally validated (N = 126). Results: Four variables, lymphovascular invasion, differentiated types, diameter of tumor and T stage were screened into the model. The area under the receiver-operating characteristic curve of the model was 0.861 (95% CI: 0.851-0.864) in internal validation and 0.911 (95% CI: 0.848-0.974) in the validation set. Conclusion: The model shows excellent discrimination and calibration performance, and is potential to be a useful clinical model to predict the risk of LNM in early gastric cancer.
Entities:
Keywords:
early gastric cancer; lymph node metastasis; nomogram; predictive model