Active clinical trials for "Stomach Neoplasms"

Recently, with the development of minimally invasive surgery and the development of instruments, laparoscopic and robotic surgery are increasing, and laparoscopic and robotic surgery are evolving. The association between the new surgical instruments used in each upper gastrointestinal surgery and the results has been traditionally analyzed through the learning curve, and in addition, the study aims to collect and analyze the utilization of the instrument and surgical results prospectively through surgical video analysis.

This study aims to test the hypothesis that the diagnosis for histological type, histological grade, LAUREN type, HER-2 expression, MSI/dMMR status, and EBV status in gastric cancer is at least as reliable when performed on endoscopic biopsy specimens as on surgical resection specimens.

This study learns if depression, anxiety, and catastrophizing (thought patterns that prompt people to expect the worst) are associated with chronic pain after surgery among patients who are scheduled to have cytoreductive surgery with intraoperative hyperthermic chemotherapy. Information from this study may improve the understanding of persistent and chronic postsurgical pain integrating multiple layers of biological and behavioral sciences.

The goal of the CAFÉ Study is to determine the cancer risks associated with germline CTNNA1 loss-of-function variants.

The early noninvasive screening of patients suitable for neoadjuvant chemotherapy (NCT) is essential for personalized treatment in locally advanced gastric cancer (LAGC). The aim of this study was to develop and visualized a radio-clinical biomarker from pretreatment oversampled CT images to predict the response and prognosis to NCT in LAGC patients.

The primary objectives of this study are: To identify clinical or histological factors associated with gastric cancer development in patients with IM and AG To establish a machine learning algorithm for prediction of future gastric cancer risks and individual risk stratification in patient with IM and AG

Adult patients undergoing elective non-cardiac surgery were enrolled. Anxiety before the operation was evaluated by The State Anxiety Inventory (S-AI). Logistics regression would be used for identifying the independent factors of preoperative anxiety and prediction model would be established.

The purpose of this study is to enable non-invasive early detection of gastric cancer in high-risk populations through the establishment of a multimodal machine learning model using plasma cell-free DNA fragmentomics. Plasma cell-free DNA from early stage gastric cancer patients and healthy individuals will be subjected to whole-genome sequencing. Features, such as cell-free DNA fragmentation, copy number variations and microbiome, will be assessed to generate this model.

discovery and validation of biomarker predicting gastric cancer chemotherapy response Analysis for expression level of mRNA using Next generation sequencing in gastric cancer tissue by chemotherapy response Analysis for expression level of miRNA using Next generation sequencing in gastric cancer tissue and blood by chemotherapy response Validation of mRNA and miRNA using qRT-PCR in multiple independent cohort Biological biomarkers-clinical factor combined prediction model of gastric cancer chemotherapy response

The purposes of this study are to collect and store samples including blood, normal and tumor tissue from patients with colorectal cancer or gastric cancer, to collect and store samples including blood and/or normal gastrointestinal tissue (if available) from patients with non-malignant disease (including, but not limited to, inflammatory bowel disease (IBD), gastric ulcer, hemorrhoids or hernia), and to create a database for the collected samples and allow access to relevant clinical information for current and future protocols.