Analysis of Associated Factors, Construction, and Application of a Predictive Model for Lymph Node Metastasis in Colorectal Cancer.
| Autor: | Yang D, Wu B, Liu J, Li W, Wang R, Shi Y |
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| Jazyk: | angličtina |
| Zdroj: | Alternative therapies in health and medicine [Altern Ther Health Med] 2024 Apr 05. Date of Electronic Publication: 2024 Apr 05. |
| Abstrakt: | Background: In colorectal cancer (CRC), understanding lymph node metastasis (LNM) is critical for effective treatment. Better approaches are required for identifying and assessing the risk contributions of factors influencing lymph node metastasis in colorectal cancer. Objective: This study aims to analyze factors associated with LNM in CRC and develop a risk prediction model. Methods: A retrospective cohort study was conducted and a total of 181 CRC patients admitted between March 2020 and April 2023 were selected as research participants. Among them, 47 patients developed LNM, while the remaining 134 did not. Clinical data, including age, sex, pathological stages, were collected. Logistic regression was employed to identify factors influencing LNM in CRC, forming the basis for constructing a risk model. The diagnostic efficiency of this model was assessed through receiver operating characteristic (ROC) curves. Results: Tumor nodules and histological types showed no correlation with LNM in CRC (P > .05). However, pathological staging, vascular and neural invasion, use of VEGF inhibitors, and preoperative CEA were identified as independent risk factors for LNM in CRC (P < .05). The established model demonstrated a good fit with the observations. ROC curve analysis indicated an area under the curve (AUC) of 0.884 for predicting LNM in CRC, signifying excellent predictive performance. Conclusions: The risk model, formulated on factors associated with LNM in CRC, serves as a efficient tool in assessing the probability of LNM. It provides invaluable insights that can significantly enhance clinical approaches to the diagnosis and treatment of CRC in the future. |
| Databáze: | MEDLINE |
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