Journal of Gastric Cancer最新文献

Purpose: Despite scientific evidence regarding laparoscopic gastrectomy (LG) for advanced gastric cancer treatment, its application in patients receiving neoadjuvant chemotherapy remains uncertain.

Materials and methods: We used the 2019 Korean Gastric Cancer Association nationwide survey database to extract data from 489 patients with primary gastric cancer who received neoadjuvant chemotherapy. After propensity score matching analysis, we compared the surgical outcomes of 97 patients who underwent LG and 97 patients who underwent open gastrectomy (OG). We investigated the risk factors for postoperative complications using multivariate analysis.

Results: The operative time was significantly shorter in the OG group. Patients in the LG group had significantly less blood loss than those in the OG group. Hospital stay and overall postoperative complications were similar between the two groups. The incidence of Clavien-Dindo grade ≥3 complications in the LG group was comparable with that in the OG group (1.03% vs. 4.12%, P=0.215). No statistically significant difference was observed in the number of harvested lymph nodes between the two groups (38.60 vs. 35.79, P=0.182). Multivariate analysis identified body mass index (odds ratio [OR], 1.824; 95% confidence interval [CI], 1.029-3.234; P=0.040) and extent of resection (OR, 3.154; 95% CI, 1.084-9.174; P=0.035) as independent risk factors for overall postoperative complications.

Conclusions: Using a large nationwide multicenter survey database, we demonstrated that LG and OG had comparable short-term outcomes in patients with gastric cancer who received neoadjuvant chemotherapy.

Purpose: This study aimed to analyze the incidence and risk factors of complications following gastric cancer surgery in Korea and to compare the correlation between hospital complications based on the annual number of gastrectomies performed.

Materials and methods: A retrospective analysis was conducted using data from 12,244 patients from 64 Korean institutions. Complications were classified using the Clavien-Dindo classification (CDC). Univariate and multivariate analyses were performed to identify the risk factors for severe complications.

Results: Postoperative complications occurred in 14% of the patients, severe complications (CDC IIIa or higher) in 4.9%, and postoperative death in 0.2%. The study found that age, stage, American Society of Anesthesiologists (ASA) score, Eastern Cooperative Oncology Group (ECOG) score, hospital stay, approach methods, and extent of gastric resection showed statistically significant differences depending on hospital volumes (P<0.05). In the univariate analysis, patient age, comorbidity, ASA score, ECOG score, approach methods, extent of gastric resection, tumor-node-metastasis (TNM) stage, and hospital volume were significant risk factors for severe complications. However, only age, sex, ASA score, ECOG score, extent of gastric resection, and TNM stage were statistically significant in the multivariate analysis (P<0.05). Hospital volume was not a significant risk factor in the multivariate analysis (P=0.152).

Conclusions: Hospital volume was not a significant risk factor for complications after gastric cancer surgery. The differences in the frequencies of complications based on hospital volumes may be attributed to larger hospitals treating patients with younger age, lower ASA scores, better general conditions, and earlier TNM stages.

Purpose: Endoscopic submucosal dissection (ESD) is an effective treatment for early gastrointestinal neoplasms. However, this is a time-consuming procedure requiring various devices. This study aimed to evaluate the efficacy and safety of the ClearCut™ Knife H-type, which is an integrated needle-tipped and insulated-tipped (IT) knife.

Materials and methods: Between July 2020 and September 2021, 99 patients with gastric epithelial neoplasms scheduled for ESD at three tertiary care hospitals were randomly assigned to H-knife (ClearCut™ Knife H-type) or IT-knife (conventional IT knife) groups. Procedure times, therapeutic outcomes, and adverse events were analyzed.

Results: A total of 98 patients (50 in the H-knife group and 48 in the IT-knife group) were analyzed. The median total procedure time was 11.9 minutes (range, 4.4-47.2 minutes) in the H-knife group and 12.7 minutes (range, 5.2-137.7 minutes) in the IT-knife group (P=0.209). Unlike the IT-knife group, which required additional devices in all cases, no additional devices were used in the H-knife group (P<0.001). En-bloc resection was performed for all lesions in both groups. The incidence of adverse events was not significantly different between groups (4.0% in the H-knife group vs. 8.3% in the IT-knife group; P=0.431).

Conclusions: The newly developed hybrid device, the ClearCut™ Knife H-type, had comparable efficacy to the conventional IT knife for gastric ESD.

Trial registration: Clinical Research Information Service Identifier: KCT0005164.

Purpose: Reduced port surgery (RPS) for gastric cancer has been frequently reported in distal gastrectomies but rarely in total gastrectomies. This study aimed to determine the feasibility of 3-port totally laparoscopic total gastrectomy (TLTG) with overlapping esophagojejunal (EJ) anastomosis.

Materials and methods: A total of 81 patients who underwent curative TLTG for gastric cancer (36 and 45 patients with 3-port and 5-port TLTG, respectively) were evaluated. All 3-port TLTG procedures were performed with the same method as 5-port TLTG, including EJ anastomosis with the intracorporeal overlap method using a linear stapler, except for the number of ports and assistants. Short-term outcomes, including the number of lymph nodes (LNs) harvested by station and postoperative complications, were analyzed retrospectively.

Results: Clinical characteristics were not significantly different among the groups, except that the 3-port TLTG group was younger and had a lower rate of pulmonary comorbidity. There were no cases of open conversion or additional port placement. All operative details and the number of harvested LNs did not differ between the groups, but the rate of suprapancreatic LN harvest was higher in the 3-port TLTG group. No significant differences were observed in the overall complication rates between the 2 groups.

Conclusions: Three-port TLTG with overlapping EJ anastomoses using a linear stapler is a feasible RPS procedure for total gastrectomy to treat gastric cancer.

Artificial intelligence (AI) has made significant progress in recent years, and many medical fields are attempting to introduce AI technology into clinical practice. Currently, much research is being conducted to evaluate that AI can be incorporated into surgical procedures to make them safer and more efficient, subsequently to obtain better outcomes for patients. In this paper, we review basic AI research regarding surgery and discuss the potential for implementing AI technology in gastric cancer surgery. At present, research and development is focused on AI technologies that assist the surgeon's understandings and judgment during surgery, such as anatomical navigation. AI systems are also being developed to recognize in which the surgical phase is ongoing. Such a surgical phase recognition systems is considered for effective storage of surgical videos and education, in the future, for use in systems to objectively evaluate the skill of surgeons. At this time, it is not considered practical to let AI make intraoperative decisions or move forceps automatically from an ethical standpoint, too. At present, AI research on surgery has various limitations, and it is desirable to develop practical systems that will truly benefit clinical practice in the future.

This meta-analysis examined the surgical management of older patients (>80 years) with gastric cancer, who were often excluded from randomized controlled trials. We analyzed 23 retrospective cohort studies involving 18,372 patients and found that older patients had a higher in-hospital mortality rate (relative risk [RR], 3.23; 95% confidence interval [CI], 1.46-7.17; P<0.01) and more post-operative complications (RR, 1.36; 95% CI, 1.19-1.56; P<0.01) than did younger patients. However, the surgical complications were similar between the two groups. Older patients were more likely to undergo less extensive lymph node dissection and longer hospital stays. Although older patients had statistically significant post-operative medical complications, they were not deprived of surgery for gastric cancer. The comorbidities and potential risks of post-operative complications should be carefully evaluated in older patients, highlighting the importance of careful patient selection. Overall, this meta-analysis provides recommendations for the surgical management of older patients with gastric cancer. Careful patient selection and evaluation of comorbidities should be performed to minimize the risk of post-operative complications in older patients, while recognizing that they should not be deprived of surgery for gastric cancer.

Purpose: The optimal tumor mutational burden (TMB) value for predicting treatment response to programmed cell death-1 (PD-1) checkpoint inhibitors in advanced gastric cancer (AGC) remains unclear. We aimed to investigate the optimal TMB cutoff value that could predict the efficacy of PD-1 checkpoint inhibitors in AGC.

Materials and methods: Patients with AGC who received pembrolizumab or nivolumab between October 1, 2020, and July 27, 2021, at Samsung Medical Center in Korea were retrospectively analyzed. The TMB levels were measured using a next-generation sequencing assay. Based on receiver operating characteristic curve analysis, the TMB cutoff value was determined.

Results: A total 53 patients were analyzed. The TMB cutoff value for predicting the overall response rate (ORR) to PD-1 checkpoint inhibitors was defined as 13.31 mutations per megabase (mt/Mb) with 56% sensitivity and 95% specificity. Based on this definition, 7 (13.2%) patients were TMB-high (TMB-H). The ORR differed between the TMB-low (TMB-L) and TMB-H (8.7% vs. 71.4%, P=0.001). The progression-free survival and overall survival (OS) for 53 patients were 1.93 (95% confidence interval [CI], 1.600-2.268) and 4.26 months (95% CI, 2.992-5.532). The median OS was longer in the TMB-H (20.8 months; 95% CI, 2.292-39.281) than in the TMB-L (3.31 months; 95% CI, 1.604-5.019; P=0.049).

Conclusions: The TMB cutoff value for predicting treatment response in AGC patients who received PD-1 checkpoint inhibitor monotherapy as salvage treatment was 13.31 mt/Mb. When applying the programmed death ligand-1 status to TMB-H, patients who would benefit from PD-1 checkpoint inhibitors can be selected.

Stomach cancer has a high annual mortality rate worldwide necessitating early detection and accurate treatment. Even experienced specialists can make erroneous judgments based on several factors. Artificial intelligence (AI) technologies are being developed rapidly to assist in this field. Here, we aimed to determine how AI technology is used in gastric cancer diagnosis and analyze how it helps patients and surgeons. Early detection and correct treatment of early gastric cancer (EGC) can greatly increase survival rates. To determine this, it is important to accurately determine the diagnosis and depth of the lesion and the presence or absence of metastasis to the lymph nodes, and suggest an appropriate treatment method. The deep learning algorithm, which has learned gastric lesion endoscopyimages, morphological characteristics, and patient clinical information, detects gastric lesions with high accuracy, sensitivity, and specificity, and predicts morphological characteristics. Through this, AI assists the judgment of specialists to help select the correct treatment method among endoscopic procedures and radical resections and helps to predict the resection margins of lesions. Additionally, AI technology has increased the diagnostic rate of both relatively inexperienced and skilled endoscopic diagnosticians. However, there were limitations in the data used for learning, such as the amount of quantitatively insufficient data, retrospective study design, single-center design, and cases of non-various lesions. Nevertheless, this assisted endoscopic diagnosis technology that incorporates deep learning technology is sufficiently practical and future-oriented and can play an important role in suggesting accurate treatment plans to surgeons for resection of lesions in the treatment of EGC.

Gastric cancer remains a significant global health concern, coercing the need for advancements in imaging techniques for ensuring accurate diagnosis and effective treatment planning. Artificial intelligence (AI) has emerged as a potent tool for gastric-cancer imaging, particularly for diagnostic imaging and body morphometry. This review article offers a comprehensive overview of the recent developments and applications of AI in gastric cancer imaging. We investigated the role of AI imaging in gastric cancer diagnosis and staging, showcasing its potential to enhance the accuracy and efficiency of these crucial aspects of patient management. Additionally, we explored the application of AI body morphometry specifically for assessing the clinical impact of gastrectomy. This aspect of AI utilization holds significant promise for understanding postoperative changes and optimizing patient outcomes. Furthermore, we examine the current state of AI techniques for the prognosis of patients with gastric cancer. These prognostic models leverage AI algorithms to predict long-term survival outcomes and assist clinicians in making informed treatment decisions. However, the implementation of AI techniques for gastric cancer imaging has several limitations. As AI continues to evolve, we hope to witness the translation of cutting-edge technologies into routine clinical practice, ultimately improving patient care and outcomes in the fight against gastric cancer.