Volume 22 Issue 3
Mar.  2024
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Article Navigation >  Chinese Journal of General Practice  > 2024  >  22(3): 372-375
WANG Yu, CHEN Fangfang, WANG Chao, GUO Han, WANG Suhang, LIU Mulin. Value of c-MYC expression in a lymph node metastasis risk prediction model for colon cancer[J]. Chinese Journal of General Practice, 2024, 22(3): 372-375. doi: 10.16766/j.cnki.issn.1674-4152.003405
Citation: WANG Yu, CHEN Fangfang, WANG Chao, GUO Han, WANG Suhang, LIU Mulin. Value of c-MYC expression in a lymph node metastasis risk prediction model for colon cancer[J]. Chinese Journal of General Practice, 2024, 22(3): 372-375. doi: 10.16766/j.cnki.issn.1674-4152.003405
shu

Value of c-MYC expression in a lymph node metastasis risk prediction model for colon cancer

doi: 10.16766/j.cnki.issn.1674-4152.003405

  • Department of General Surgery, the First Affiliated Hospital of Bengbu Medical University, Bengbu, Anhui 233004, China

Funds:

 2108085MH291

 20220133

  • Received Date: 2023-03-28
    Available Online: 2024-05-27
    Abstract
  •   Objective  To examine the correlation between the expression of cellular-myelocytomatosis viral oncogene (c-MYC) and lymph node metastasis risk in colon cancer, develop a risk prediction model and evaluate its significance.  Methods  The medical records of 304 patients who underwent radical colon cancer surgery at the First Affiliated Hospital of Bengbu Medical University from January 2020 to December 2022 were collected. The patients were randomly divided into a model group and a validation group, each comprising 152 cases. We analyzed the factors influencing lymph node metastasis and identified the risk variables for input into the prediction model. The characteristics of colon cancer lymph node metastasis were then analyzed using an artificial intelligence system through deep learning. Finally, we assessed the effectiveness of the model.  Results  Univariate analysis showed that the neutrophil-to-lymphocyte ratio (NLR), c-MYC expression, tumor morphology, vascular cancer thrombus, tumor length, and tumor differentiation degree of 152 colon cancer patients in the model group were related to their lymph node metastasis. Further multivariate analysis identified the neutrophil-lymphocyte ratio, c-MYC expression, tumor morphology, vascular cancer thrombus, tumor length and diameter, and tumor differentiation degree as significant risk relevant variables for lymph node metastasis in colon cancer. The ROC curve based on the prediction model showed an AUC of 0.745 (95% CI: 0.712-0.803) in the validation group and 0.832 (95% CI: 0.796-0.875) in the model group, suggesting the effective predictive capability of the risk prediction model for lymph node metastasis in colon cancer patients.  Conclusion  The NLR, c-MYC expression, tumor morphology, vascular cancer thrombus, tumor length, and tumor differentiation were significant risk variables affecting lymph node metastasis in colon cancer. The risk prediction model constructed in this study demonstrates accurate identification of lymph node metastasis risk in colon cancer patients, holding promising clinical applications.

     

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