Analysis of Factors Influencing Early Recurrence of Lauren Type Gastric Cancer after Radical Resection
HUANG Qing-feng,YANG Li-cheng,WU Jian-jun
General Surgery Department, Liyang People’s Hospital, Liyang 213300, China
Abstract:
Objective To investigate the clinic pathological features of patients with different Lauren types of gastric cancer and the independent risk factors of early recurrence after radical resection. Methods 236 patients with gastric cancer who underwent radical resection in our hospital from January 2016 to April 2019 were selected. The clinical data were collected to compare the clinical characteristics of patients with different Lauren types of gastric cancer. The patients were followed up for two years. According to the recurrence during the follow-up period, they were divided into no recurrence group and recurrence group. The independent risk factors of early recurrence after radical gastrectomy were analyzed by univariate and logistic multivariate regression, and the nomogram prediction model was constructed and veri.ed. Results Intestinal gastric cancer was more common in men, with higher histological grade, longer postoperative adjuvant chemotherapy cycle and higher proportion of high expression of Ki-67 and HER-2 in cancer tissues (P<0.05). Diffuse gastric cancer is more common in women, and patients are more prone to vascular tumor emboli and peripheral nerve in.ltration. The proportion of tumor diameter ≥ 50 mm is higher, and the positive rate of lymph node is signi.cantly higher than that of patients with intestinal type (P<0.05). Tumor size, Lauren type, T stage, lymph node positive rate and postoperative adjuvant chemotherapy cycle were independent risk factors for early recurrence after radical resection of gastric cancer patients (P<0.05). The nomogram model was constructed according to independent risk factors. The consistency index was 0.745 (95%CI: 0.702~0.788) and the AUC of ROC curve was 0.726 (95%CI: 0.695~0.757), which had good discrimination. The evaluation results of calibration curve and model calibration curve showed that the prediction model was accurate. Conclusion The clinical characteristics of
