Abstract
Background: Most lymph node metastasis (LNM) models for early gastric cancer (EGC) include lymphovascular invasion (LVI) as a predictor. However, LVI must be confirmed by postoperative pathology. In this study, we aimed to develop a model for predicting the risk of LNM/LVI in EGC using preoperative factors. Methods: EGC patients who underwent radical gastrectomy at Fujian Medical University Union Hospital and Sun Yat-sen University Cancer Center (n = 1460) were selected as the training set. The risk factors of LNM/LVI were investigated. Data from the International study group on Minimally Invasive surgery for GASTRIc Cancer trial (n = 172) were selected as the validation set. Results: In the training set, the incidence of LNM/LVI was 21.6%. The 5-year cancer-specific survival rates of patients with and without LNM/LVI were 92.4 and 95.0%, respectively, with significant difference (P = 0.030). Multivariable logistic regression analysis showed that the four independent risk factors for LNM/LVI were female, tumor larger than 20 mm, submucosal invasion and undifferentiated tumor histological type (all P < 0.05); the area under the curve (AUC) was 0.694 (95% confidence interval [CI]: 0.659-0.730). Patients were divided into low-risk, intermediate-risk, high-risk and extremely high-risk groups by recursive partitioning analysis; the incidences of LNM/LVI were 5.4, 12.6, 24.2 and 37.8%, respectively (P < 0.001). The AUC of the validation set was 0.796 (95%CI, 0.662-0.851) and the predictive performance of the LNM/LVI risk in the validation set was consistent with that in the training set. Conclusions: The risk of LNM/LVI in differentiated mucosal EGC is low, which indicated that endoscopic resection is a treatment option. The risk of LNM/LVI in undifferentiated mucosal EGC and submucosa EGC are high and gastrectomy with lymph node dissection is suggested.
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Lin, J. X., Wang, Z. K., Wang, W., Desiderio, J., Xie, J. W., Wang, J. B., … Huang, C. M. (2019). Risk factors of lymph node metastasis or lymphovascular invasion for early gastric cancer: A practical and effective predictive model based on international multicenter data. BMC Cancer, 19(1). https://doi.org/10.1186/s12885-019-6147-6
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