Abstract:

Objective To explore the preoperative predictors of lymphovascular invasion (LVI) in patients with advanced gastric cancer, and establish the corresponding nomogram prediction model and conduct internal validation. Methods A total of 246 cases of advanced gastric cancer who underwent surgical resection in the Department of Gastrointestinal Surgery of Hengshui People's Hospital from January 2018 to December 2021 were selected. Patients were divided into the LVI positive group and the LVI negative group according to postoperative pathological diagnosis. The age, gender, tumor differentiation, tumor size, tumor site, Borrmann classification, Lauren's classification, cT stage, cN stage and systemic immune-inflammation index (SII) of patients were collected and compared between the two groups. The predictors that were statistically different between the two groups were subjected to multivariate Logistic regression and further developed into a visual prediction model. Bootstrap method was applied for internal validation of the prediction efficiency of the model. Results The differences of tumor size, Borrmann classification, tumor differentiation, Lauren classification, cT staging, cN staging and SII were statistically significant between the two groups ( P<0.05). Multivariate Logistic regression analysis showed that tumor size (OR=2.184, 95%CI:1.224-3.898), Borrmann classification (OR=2.517, 95%CI: 1.294-4.896), cT staging (OR=1.860, 95%CI: 1.045-3.308), cN staging (OR=1.816, 95%CI: 1.004-3.285) and SII (OR=1.001, 95%CI: 1.000-1.002) were independent predictors of LVI in advanced gastric cancer. A preoperative nomogram prediction model for advanced gastric cancer LVI was developed based on results of multivariate analysis. By internal validation, the area under curve (AUC) value of the subject operating characteristic (ROC) curve of the nomogram was 0.735, which was higher than that of tumor size (0.599), Borrmann staging (0.564), cT staging (0.604), cN staging (0.582) and SII (0.615), respectively. The calibration curve showed that the probability of predicted LVI by the nomogram was in a good agreement with the probability of actual LVI occurrence. The Hosmer-Lemeshow test showed good model fit (χ²=4.387, P=0.821). Conclusion The established nomogram prediction model can help to predict the probability of LVI in advanced gastric cancer preoperatively, which can provide a guideline for clinical individualized treatment.

Key words: gastric neoplasms, risk factors, nomograms, advanced, lymphovascular invasion, predictive model