[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"leadSponsorName\":\"Hebei Medical University\",\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:":86},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,3,0,[8,43,65],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":13,"acronym":4,"eligibilityCriteria":14,"healthyVolunteers":11,"sex":15,"minAge":16,"maxAge":17,"enrollmentInfo":18,"targetDuration":4,"studyType":21,"phases":22,"briefSummary":24,"conditions":25,"keywords":27,"overallStatus":31,"whyStopped":4,"lastUpdateSubmitDate":32,"lastUpdatePostDateStruct":33,"startDateStruct":36,"completionDateStruct":37,"leadSponsor":39,"locationsCount":42},"100616334","phase-2-a-prospective-phase-ii-clinical-study-of-hipec-combined-with-nips-and-tislelizumab-conversion-therapy-for-gastric-cancer-with-peritoneal-metastasis-with-positive-cytology-alone-or-pci-score-10-100616334",false,"NCT07304258","A Prospective, Phase II Clinical Study of HIPEC Combined With NIPS and Tislelizumab Conversion Therapy for Gastric Cancer With Peritoneal Metastasis With Positive Cytology Alone or PCI Score ≤10","Inclusion Criteria:\n\n1. Treatment-naïve patients who have not received chemotherapy, radiotherapy, or any other antitumor therapy prior to the start of the clinical trial;\n2. Age between 18 and 75 years;\n3. Male or non-pregnant, non-lactating female;\n4. Gastric or gastroesophageal junction adenocarcinoma confirmed by gastroscopy and pathological diagnosis;\n5. HER-2 negative by immunohistochemistry (IHC), and PD-L1 CPS ≥1;\n6. Laparoscopic exploration confirming either positive cytology alone (P0CY1) or peritoneal metastasis (PCI score ≤10);\n7. No other distant metastases;\n8. Hematological criteria: white blood cell count ≥3.5×10⁹\u002FL, neutrophils ≥1.5×10⁹\u002FL, platelet count ≥100×10⁹\u002FL, hemoglobin ≥90 g\u002FL;\n9. Biochemical criteria: ALT ≤2.5×ULN, AST ≤2.5×ULN, total bilirubin ≤1.5×ULN, serum creatinine ≤1.5×ULN;\n10. Left ventricular ejection fraction ≥50%;\n11. ECOG performance status 0-1;\n12. Ability to comply with the study protocol and voluntarily provide signed informed consent.\n\nExclusion Criteria:\n\n1. Inability to comply with the study protocol or procedures;\n2. Known HER2-positive status;\n3. Known diagnosis of squamous cell carcinoma, undifferentiated carcinoma, or other histological types of gastric cancer, or adenocarcinoma mixed with other histological types;\n4. Current conditions or diseases affecting drug absorption;\n5. Patients preoperatively confirmed as unsuitable for conversion therapy;\n6. Severe cardiovascular diseases, such as uncontrolled heart failure, coronary artery disease, arrhythmia, or uncontrolled hypertension;\n7. Symptomatic active central nervous system metastases (e.g., clinical symptoms, cerebral edema, spinal cord compression, carcinomatous meningitis, leptomeningeal disease, and\u002For progressive growth);\n8. Known allergy to the investigational drug(s);\n9. Prior treatment with anti-PD-1\u002FPD-L1 antibodies, anti-PD-L2 antibodies, anti-CD137 antibodies, anti-CTLA-4 antibodies, or other drugs\u002Fantibodies targeting T-cell co-stimulation or checkpoint pathways;\n10. Clinically uncontrolled active infections, such as acute pneumonia, active hepatitis B or C (HBV DNA ≥1×10⁴ copies\u002FmL or \\>2000 IU\u002FmL despite prior antiviral therapy); Known primary immunodeficiency or active tuberculosis; History of allogeneic organ transplantation or allogeneic hematopoietic stem cell transplantation; Known history of human immunodeficiency virus (HIV) infection (HIV antibody positive);\n11. Significant malnutrition (weight loss ≥5% within 1 month or \\>15% within 3 months prior to informed consent, or food intake reduced by ≥50% within 1 week), unless corrected for ≥4 weeks before the first dose of investigational drug;\n12. History of other primary malignancies, except:\n\n    * Malignancies in complete remission for at least 2 years prior to enrollment with no required treatment during the study;\n    * Adequately treated non-melanoma skin cancer or malignant lentigo with no evidence of recurrence;\n    * Adequately treated carcinoma in situ with no evidence of recurrence;\n13. Female patients who are pregnant or breastfeeding;\n14. Any concomitant illness that, in the investigator's judgment, seriously endangers patient safety or affects study completion;\n15. Patients deemed ineligible for the study by the investigator.","ALL","18 Years","75 Years",{"count":19,"type":20},30,"ESTIMATED","INTERVENTIONAL",[23],"PHASE2","This study aims to evaluate the efficacy and safety of HIPEC combined with NIPS and tislelizumab conversion therapy for gastric\u002Fgastroesophageal junction cancer with positive cytology alone (CY1P0) or a Peritoneal Carcinomatosis Index (PCI) ≤10",[26],"Gastric Cancer Peritoneal Metastases",[28,29,30],"HIPEC","NIPS","PD-1","NOT_YET_RECRUITING","2025-12-12",{"date":34,"type":35},"2025-12-26","ACTUAL",{"date":32,"type":20},{"date":38,"type":20},"2027-12-31",{"name":40,"class":41},"Hebei Medical University","OTHER",1,{"id":44,"slug":45,"hasResults":11,"nctId":46,"briefTitle":47,"officialTitle":47,"acronym":4,"eligibilityCriteria":48,"healthyVolunteers":11,"sex":15,"minAge":16,"maxAge":49,"enrollmentInfo":50,"targetDuration":4,"studyType":21,"phases":52,"briefSummary":54,"conditions":55,"keywords":4,"overallStatus":31,"whyStopped":4,"lastUpdateSubmitDate":57,"lastUpdatePostDateStruct":58,"startDateStruct":60,"completionDateStruct":62,"leadSponsor":64,"locationsCount":4},"100587933","clinical-study-of-double-endoscopic-combined-with-minimally-invasive-treatment-for-early-gastric-cancer-at-clinical-stage-t1b-100587933","NCT06934824","Clinical Study of Double-Endoscopic Combined With Minimally Invasive Treatment for Early Gastric Cancer at Clinical Stage T1b","Inclusion Criteria:\n\n1. Age 18-70 years old;\n2. Endoscopic pathological diagnosis: adenocarcinoma;\n3. Enhanced abdominal CT combined with endoscopic ultrasound clinical staging: T1bN0-1M0.\n4. Has not received other treatment;\n5. No other serious comorbidities;\n6. Agree to participate in the study and sign the informed consent form.\n\nExclusion Criteria:\n\n1. Pregnant or breastfeeding women\n2. History of previous abdominal surgery\n3. History of other previous malignancies\n4. Can patients with severe heart, lung, brain diseases tolerate surgical treatment","70 Years",{"count":51,"type":20},60,[53],"NA","For patients diagnosed with early gastric cancer involving submucosal invasion, super-ESD indications, or lymph node metastasis, a combination of preoperative endoscopic ultrasound and abdominal contrast-enhanced CT was utilized to ascertain the depth of tumor invasion and to identify any suspicious metastatic lymph nodes in the vicinity of the stomach. Subsequently, a local full-thickness resection, coupled with or followed by individualized precise lymph node dissection, was conducted to fulfill the following objectives: ① To investigate the safety, feasibility, and efficacy of local resection for patients meeting super-ESD criteria; ② To offer a clinical foundation for the individualized and precise lymph node dissection treatment of early gastric cancer.",[56],"Gastric Cancer Patients Undergoing Minimally Invasive Gastrectomy","2025-04-12",{"date":59,"type":35},"2025-04-18",{"date":61,"type":20},"2025-05-01",{"date":63,"type":20},"2027-01-01",{"name":40,"class":41},{"id":66,"slug":67,"hasResults":11,"nctId":68,"briefTitle":69,"officialTitle":40,"acronym":4,"eligibilityCriteria":70,"healthyVolunteers":11,"sex":15,"minAge":16,"maxAge":4,"enrollmentInfo":71,"targetDuration":4,"studyType":73,"phases":4,"briefSummary":74,"conditions":75,"keywords":4,"overallStatus":77,"whyStopped":4,"lastUpdateSubmitDate":78,"lastUpdatePostDateStruct":79,"startDateStruct":81,"completionDateStruct":83,"leadSponsor":85,"locationsCount":42},"100557184","development-and-application-of-an-artificial-intelligence-driven-accurate-identification-model-for-gastric-cancer-lymph-node-metastasis-100557184","NCT06534814","Development and Application of an Artificial Intelligence-driven Accurate Identification Model for Gastric Cancer Lymph Node Metastasis","Inclusion Criteria:\n\n1. Diagnosis of Gastric Cancer: Confirmed diagnosis of gastric cancer, either newly diagnosed or recurrent.\n2. Lymph Node Involvement: Suspected or confirmed involvement of lymph nodes, as indicated by imaging studies or pathology reports.\n3. Age: Patients aged 18 years or older.\n4. Performance Status: An Eastern Cooperative Oncology Group (ECOG) performance status of 0 to 2, indicating a functional status that allows participation in the study.\n5. Informed Consent: Ability to provide written informed consent to participate in the study.\n\nExclusion Criteria:\n\n1. Pregnancy or Lactation: Pregnant or lactating women, due to potential risks to the fetus or infant.\n2. Severe Comorbid Conditions: Presence of severe comorbid medical conditions that could interfere with the study or pose additional risks.\n3. Previous AI-Driven Diagnostic Intervention: Prior use of any AI-driven diagnostic models specifically for gastric cancer lymph node metastasis.\n4. Inability to Comply: Inability or unwillingness to comply with study procedures, including follow-up visits and data collection.\n5. Mental or Cognitive Impairment: Conditions that impair the ability to provide informed consent or participate effectively in the study.",{"count":72,"type":20},300,"OBSERVATIONAL","The clinical trial titled \"Development and Application of an Artificial Intelligence-Driven Accurate Identification Model for Gastric Cancer Lymph Node Metastasis\" aims to enhance the detection and treatment of gastric cancer through the utilization of cutting-edge artificial intelligence (AI) technology. This study will develop an AI-driven model designed to accurately identify lymph node metastasis in patients with gastric cancer, which is crucial for staging the disease and planning effective treatment strategies.\n\nThe trial will involve a multidisciplinary team of oncologists, radiologists, data scientists, and AI experts who will collaborate to create a robust and precise identification system. Participants will undergo standard diagnostic procedures, and the AI model will analyze imaging and pathological data to predict lymph node involvement.\n\nBy comparing the AI model's predictions with traditional diagnostic methods, the study seeks to validate the model's accuracy and efficiency. This approach is expected to improve early detection rates, reduce diagnostic errors, and ultimately lead to better clinical outcomes for patients with gastric cancer. The successful implementation of this AI-driven model could revolutionize the current standards of care and serve as a blueprint for integrating AI technologies in other cancer diagnoses and treatments.",[76],"The Primary Focus of This Study is on Gastric Cancer","RECRUITING","2024-08-01",{"date":80,"type":35},"2024-08-02",{"date":82,"type":35},"2024-07-01",{"date":84,"type":20},"2030-07-30",{"name":40,"class":41},""]