Hye-Kyung Jung, Seung Joo Kang, Yong Chan Lee, Hyo-Joon Yang, Seon-Young Park, Cheol Min Shin, Sung Eun Kim, Hyun Chul Lim, Jie-Hyun Kim, Su Youn Nam, Woon Geon Shin, Jae Myung Park, Il Ju Choi, Jae Gyu Kim, and Miyoung Choi, Korean College of Helicobacter and Upper Gastrointesinal Research. Gut and Liver -0001;0:. https://doi.org/10.5009/gnl20288

Objective: The association between proton pump inhibitor (PPI) use and gastric cancer related to Helicobacter pylori eradication has not been fully investigated in geographical regions with high risk of gastric cancer. We aimed to evaluate the association between PPIs and gastric cancer in Korea. Design: This study analysed the original and common data model versions of the Korean National Health Insurance Service database from 2002 to 2013. We compared the incidence rates of gastric cancer after 1-year drug exposure, between new users of PPIs and other drugs excluding PPIs, by Cox proportional hazards model. We also analysed the incidence of gastric cancer among PPI users after H. pylori eradication. Results: The analysis included 11 741 patients in matched PPI and non-PPI cohorts after large-scale propensity score matching. During a median follow-up of 4.3 years, PPI use was associated with a 2.37-fold increased incidence of gastric cancer (PPI≥30 days vs non-PPI; 118/51 813 person-years vs 40/49 729 person-years; HR 2.37, 95% CI 1.56 to 3.68, p=0.001). The incidence rates of gastric cancer showed an increasing trend parallel to the duration of PPI use. In H. pylori -eradicated subjects, the incidence of gastric cancer was significantly associated with PPI use over 180 days compared with the non-PPI group (PPI≥180 days vs non-PPI; 30/12 470 person-years vs 9/7814 person-years; HR 2.22, 95% CI 1.05 to 4.67, p=0.036). Conclusion: PPI use was associated with gastric cancer, regardless of H. pylori eradication status. Long-term PPIs should be used with caution in high-risk regions for gastric cancer.

The greater occipital nerve (GON) block has been frequently used for different types of headache, but performed with rough estimates of anatomic landmarks. Our study presents the values of the anatomic parameters and estimates the effectiveness of the ultrasound-guided GON blockade. The GON was detected using ultrasound technique and distance from external occipital protuberance (EOP) to GON, from GON to occipital artery and depth from skin to GON was measured in volunteers. Patients with occipital headache were divided into two groups (ultrasound-guided block: group S, conventional blind block: group B) and GON block was performed. The same parameters were measured on group S and VAS scores were assessed at pretreatment, 1 week and 4 weeks after treatment on both groups. The GON had distance of 23.1 ± 3.4 mm (right) and 20.5 ± 2.8 mm (left) from EOP to GON. Its depth below the skin was 6.8 ± 1.5 mm (right) and 7.0 ± 1.3 mm (left). The distance from GON to occipital artery was 1.5 ± 0.6 mm (right) and 1.2 ± 0.6 mm (left) in volunteers. Initial VAS score of group S and group B patients were 6.4 ± 0.2 and 6.5 ± 0.2. VAS score of 4 weeks after injection were 2.3 ± 0.2 on group S and 3.8 ± 0.3 on group B (P = 0.0003). The parameters measured in this study should be useful for GON block and ultrasound-guided blockade is likely to be a more effective technique than blind blockade in occipital headache treatment.

SUMMARY: Background: Tegoprazan is a novel potassium‐competitive acid blocker used to treat acid‐related disorders.Aim: To compare tegoprazan 25 mg with lansoprazole 15 mg as maintenance therapy in healed erosive oesophagitis (EE)Methods: In this phase 3, double‐blind, multi‐centre study, patients with endoscopically confirmed healed EE were randomised 1:1 to receive tegoprazan 25 mg or lansoprazole 15 mg once daily for up to 24 weeks. The primary efficacy endpoint was the endoscopic remission rate after 24 weeks. The secondary efficacy endpoint was the endoscopic remission rate after 12 weeks. Safety endpoints included adverse events, clinical laboratory results and serum gastrin and pepsinogen I/II levels.Results: We randomised patients to tegoprazan 25 mg (n = 174) or lansoprazole 15 mg (n = 177). Most had mild EE (Los Angeles (LA) grade A: 57.3%, LA grade B: 37.3%). The endoscopic remission rate after 24 weeks was 90.6% with tegoprazan and 89.5% with lansoprazole. Tegoprazan was not inferior to lansoprazole for maintaining endoscopic remission at 24 weeks and 12 weeks. In subgroup analysis, tegoprazan 25 mg showed no significant difference in maintenance rate according to LA grade (p = 0.47). The maintenance effect of tegoprazan was consistent in CYP2C19 extensive metabolisers (p = 0.76). Increases in serum gastrin were not higher in tegoprazan‐treated than lansoprazole‐treated patients.Conclusions: Tegoprazan 25 mg was non‐inferior to lansoprazole 15 mg in maintenance of healing of mild EE. In this study, tegoprazan had a similar safety profile to lansoprazole.

Background: Undifferentiated type of early gastric cancer (U-EGC) is included among the expanded indications of endoscopic submucosal dissection (ESD); however, the rate of curative resection remains unsatisfactory. Endoscopists predict the probability of curative resection by considering the size and shape of the lesion and whether ulcers are present or not. The location of the lesion, indicating the likely technical difficulty, is also considered. Objective: The aim of this study was to establish machine learning (ML) models to better predict the possibility of curative resection in U-EGC prior to ESD. Methods: A nationwide cohort of 2703 U-EGCs treated by ESD or surgery were adopted for the training and internal validation cohorts. Separately, an independent data set of the Korean ESD registry (n=275) and an Asan medical center data set (n=127) treated by ESD were chosen for external validation. Eighteen ML classifiers were selected to establish prediction models of curative resection with the following variables: age; sex; location, size, and shape of the lesion; and whether ulcers were present or not. Results: Among the 18 models, the extreme gradient boosting classifier showed the best performance (internal validation accuracy 93.4%, 95% CI 90.4%-96.4%; precision 92.6%, 95% CI 89.5%-95.7%; recall 99.0%, 95% CI 97.8%-99.9%; and F1 score 95.7%, 95% CI 93.3%-98.1%). Attempts at external validation showed substantial accuracy (first external validation 81.5%, 95% CI 76.9%-86.1% and second external validation 89.8%, 95% CI 84.5%-95.1%). Lesion size was the most important feature in each explainable artificial intelligence analysis. Conclusions: We established an ML model capable of accurately predicting the curative resection of U-EGC before ESD by considering the morphological and ecological characteristics of the lesions.