A Clinicopathological Feature-Based Nomogram for Predicting the Likelihood of D3 Lymph Node Metastasis In Right-Sided Colon Cancer Patients

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Chenyan Long ◽  
Mingyuan Feng ◽  
Shijie Wang ◽  
Hongli Ji ◽  
Zhiming Li ◽  
...  
2020 ◽  
Author(s):  
Xiangjian Zheng ◽  
Xiaodong Chen ◽  
Min Li ◽  
Chunmeng Li ◽  
Xian Shen

Abstract Background: Surgery combined with chemo-radiotherapy is a recognized model for the treatment of gastric and colon cancers. Lymph node metastasis determines the patient's surgical or comprehensive treatment plan. This analytical study aims to compare preoperative prediction scores to better predict lymph node metastasis in gastric and colon cancer patients.Methods: This study comprised 768 patients, which included 312 patients with gastric cancer and 462 with colon cancer. Preoperative clinical tumor characteristics, serum markers, and immune indices were evaluated using single-factor analysis. Logistic analysis was designed to recognize independent predictors of lymph node metastasis in these patients. The independent risk factors were integrated into preoperative prediction scores, which were accurately assessed using receiver operating characteristic (ROC) curves.Results: Results showed that serum markers (CA125, hemoglobin, albumin), immune indices (S100, CD31, d2–40), and tumor characteristics (pathological type, size) were independent risk factors for lymph node metastasis in patients with gastric and colon cancer. The preoperative prediction scores reliably predicted lymph node metastasis in gastric and colon cancer patients with a higher area under the ROC curve (0.901). The area was 0.923 and 0.870 in gastric cancer and colon cancer, respectively. Based on the ROC curve, the ideal cutoff value of preoperative prediction scores to predict lymph node metastasis was established to be 287. Conclusion: The preoperative prediction scores is a useful indicator that can be applied to predict lymph node metastasis in gastric and colon cancer patients.


2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Aydin Eresen ◽  
Yu Li ◽  
Jia Yang ◽  
Junjie Shangguan ◽  
Yury Velichko ◽  
...  

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