Abstract:Objective To study the levels of serum pepsinogen (PG), gastrin-17 (G-17) and Helicobacter pylori IgG antibody (Hp-IgG) before and after endoscopic submucosal dissection (ESD) in patients with early gastric cancer (EGC), and calculate the pepsinogen rate (PGR) and analyze the clinical significance.Methods 326 patients with EGC who underwent ESD treatment from February 2013 to February 2015 were selected as the research subjects, and 80 healthy people who underwent physical examination during the same period in the hospital were selected as control. The levels of serum PG I, PGⅡ, G-17 and Hp-IgG were detected. According to the follow-up results after ESD, the patients with EGC were divided into recurrence group and control group. The differences in detection results were compared among each group, and their effects and predictive value on tumor recurrence were analyzed.Results The G-17 level and Hp-IgG positive rate of patients with EGC were higher than those of healthy people while the levels of PGⅠ and PGR were lower than those of healthy people (P < 0.05). At 3 months after surgery, the levels of serum PGⅠ and PGR in recurrence group and control group were significantly increased (P < 0.05) while the G-17 level was significantly decreased (P < 0.05), and the Hp-IgG positive rate before and after surgery in recurrence group was higher than that in control group, and the levels of serum PGⅠ and PGR after surgery were lower than those in control group while the level of serum G-17 was higher than that in control group (P < 0.05). Binary Logistic regression analysis showed that PG I, Hp-IgG and PGR were important factors affecting postoperative recurrence in patients with EGC (P < 0.05). The areas under the curves (AUC) of PG I, Hp-IgG and PGR in predicting the postoperative recurrence of patients with EGC were 0.772, 0.612 and 0.835 (P > 0.05).Conclusion ESD is an effective method for the treatment of EGC. Monitoring the changes of PG, G-17 and Hp-IgG before and after surgery can provide reference information for predicting tumor recurrence.