Published online Jul 15, 2024. doi: 10.4251/wjgo.v16.i7.2960
Revised: May 9, 2024
Accepted: May 28, 2024
Published online: July 15, 2024
Processing time: 93 Days and 2.6 Hours
Lymph node metastasis (LNM) significantly impacts the treatment and prognosis of early gastric cancer (EGC). Consequently, the precise prediction of LNM risk in EGC patients is essential to guide the selection of appropriate surgical approaches in clinical settings.
To develop a novel nomogram risk model for predicting LNM in EGC patients, utilizing preoperative clinicopathological data.
Univariate and multivariate logistic regression analyses were performed to examine the correlation between clinicopathological factors and LNM in EGC patients. Additionally, univariate Kaplan-Meier and multivariate Cox regression analyses were used to assess the influence of clinical factors on EGC prognosis. A predictive model in the form of a nomogram was developed, and its discrimination ability and calibration were also assessed.
The incidence of LNM in the study cohort was 19.6%. Multivariate logistic regression identified tumor size, location, degree of differentiation, and path
A clinical prediction model was constructed (using tumor size, low differentiation, location in the middle-lower region, and signet ring cell carcinoma), with its score being a significant prognosis indicator.
Core Tip: Early gastric cancer (EGC) refers to adenocarcinoma in which the cancer tissue is limited to the gastric mucosa or submucosa, regardless of tumor size and lymph node metastasis (LNM). It is very important to accurately predict the risk of LNM, and understanding the metastatic status of lymph nodes in EGC is conducive to selecting the appropriate surgical method and improving the overall efficacy of treatment.