Background/Aims: Diagnosis of Helicobacter pylori-naïve gastric cancer (HPNGC) is becoming increasingly important. This study aimed to explore the quality indicators for HPNGC detection. Methods: We conducted a cross-sectional, nationwide, web-based survey of gastrointestinal endoscopists in Japan. In addition to questions about the number of HPNGC cases detected in a year and basic information, the questionnaire also consisted of 28 questions: (1) 18 about HPNGC awareness, (2) six about diagnostic proactiveness, and (3) four about interest in HPNGC. Results: Valid responses were obtained from 712 endoscopists. The Japan Gastroenterological Endoscopy Society-certified endoscopists had a significantly higher HPNGC detection rate than the nonspecialists (0.42% vs. 0.32%, respectively; p=0.008). The results of the multiple regression analysis showed that Japan Gastroenterological Endoscopy Society certification and high awareness and interest scores were independent predictors of the HPNGC detection rate (p=0.012, p<0.001, p=0.024, respectively). Principal component analysis showed that the endoscopists who attended conferences for collecting information on HPNGC had a higher level of awareness. Conclusions To improve the detection of HPNGC, it is necessary to increase the awareness of the disease. It is hoped that relevant societies will play an important role in endoscopists’ education.

Although magnifying endoscopy with narrow-band imaging is the standard diagnostic test for gastric cancer, diagnosing gastric cancer using this technology requires considerable skill. Artificial intelligence has superior image recognition, and its usefulness in endoscopic image diagnosis has been reported in many cases. The diagnostic performance (accuracy, sensitivity, and specificity) of artificial intelligence using magnifying endoscopy with narrow band still images and videos for gastric cancer was higher than that of expert endoscopists, suggesting the usefulness of artificial intelligence in diagnosing gastric cancer. Histological diagnosis of gastric cancer using artificial intelligence is also promising. However, previous studies on the use of artificial intelligence to diagnose gastric cancer were small-scale; thus, large-scale studies are necessary to examine whether a high diagnostic performance can be achieved. In addition, the diagnosis of gastric cancer using artificial intelligence has not yet become widespread in clinical practice, and further research is necessary. Therefore, in the future, artificial intelligence must be further developed as an instrument, and its diagnostic performance is expected to improve with the accumulation of numerous cases nationwide.

Since the indications for endoscopic submucosal dissection have been expanded to include undifferentiated-type early gastric cancers, improvements in preoperative diagnostic ability have been an area of research. There are also concerns about the impact on the diagnosis of Helicobacter pylori infection. Based on our previous studies, in undifferentiated-type early gastric cancers, magnifying endoscopy with narrow-band imaging is useful for delineating the demarcation regardless of the tumor size. Additionally, inflammatory cell infiltration appears to be a cause of misdiagnosis, suggesting that the resolution of inflammation could contribute to the accurate diagnosis of demarcations. As such, the accuracy of demarcation in eradicated and uninfected cases is higher than that in non-eradicated cases. The common features of the endoscopic findings were discoloration under white-light imaging and a predominance of sites in the lower and middle regions. The uninfected group was characterized by smaller tumor size, flat type, more extended intervening parts in magnifying endoscopy with narrow-band imaging, and pure signet ring cell carcinoma. In contrast, the eradication and non-eradication groups were characterized by larger tumor size, depressed type, and wavy microvessels in magnifying endoscopy with narrow-band imaging. In this comprehensive review, as described above, we discuss the diagnosis of demarcation of undifferentiated-type early gastric cancers, undifferentiated-type early gastric cancers that developed following H. pylori eradication, and H. pylori-uninfected undifferentiatedtype early gastric cancers, with a focus on studies with self-examination and endoscopic findings and describe the future direction.

Objective: To evaluate the efficacy and safety of niraparib in Japanese women with heavily pretreated ovarian cancer. Methods: This Phase 2 open-label, single-arm study enrolled Japanese women with homologous recombination deficiency-positive relapsed, high-grade serous ovarian, fallopian tube, or primary peritoneal cancer who had completed 3–4 lines of therapy. The starting dose of niraparib was 300 mg administered once daily in continuous 28-day cycles until objective progressive disease, unacceptable toxicity, consent withdrawal or discontinuation. The primary endpoint, objective response rate (ORR), was assessed by the investigator using RECIST version 1.1. Safety evaluations included the incidence of treatment-emergent adverse events (TEAEs), including serious TEAEs. Results: Twenty women were enrolled and the confirmed ORR in the full analysis set (FAS) was 35.0% (7/20), consisting of 1 complete response and 6 partial responses. Disease control rate in the FAS was 90.0%. The most frequently reported TEAEs (>50%) were anemia, nausea, and platelet count decreased. One patient (5.0%) had TEAEs leading to discontinuation of niraparib whereas reductions or interruptions were reported in 14 (70.0%) and 15 (75.0%) patients, respectively. The median dose intensity (202.9 mg daily) corresponded to a relative dose intensity of 67.6%. Conclusion Efficacy and safety of niraparib in heavily pretreated Japanese women was comparable to that seen in an equivalent population of non-Japanese women. No new safety signals were identified.