[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100522862":3},{"organization":4,"armGroups":7,"interventions":10,"overallOfficials":10,"centralContacts":10,"locations":13,"responsibleParty":32,"collaborators":10,"id":36,"slug":10,"hasResults":37,"nctId":38,"briefTitle":39,"officialTitle":40,"acronym":10,"eligibilityCriteria":41,"healthyVolunteers":37,"sex":42,"minAge":10,"maxAge":10,"enrollmentInfo":43,"targetDuration":10,"studyType":46,"phases":10,"briefSummary":47,"conditions":48,"keywords":10,"overallStatus":16,"whyStopped":10,"lastUpdateSubmitDate":52,"lastUpdatePostDateStruct":53,"startDateStruct":56,"completionDateStruct":58,"leadSponsor":60,"locationsCount":61},{"fullName":5,"class":6},"First Affiliated Hospital of Chongqing Medical University","OTHER",[8,11],{"label":9,"type":10,"description":10,"interventionNames":10},"Non-recurrence group",null,{"label":12,"type":10,"description":10,"interventionNames":10},"Recurrence group",[14],{"facility":15,"status":16,"city":17,"state":18,"zip":19,"country":20,"cosmosGeoPoint":21,"geoPoint":26,"contacts":27},"Yingjie Xv","RECRUITING","Chongqing","Chongqing Municipality","400016","China",{"type":22,"coordinates":23},"Point",[24,25],106.55771,29.56026,{"lat":25,"lon":24},[28],{"name":15,"role":29,"phone":30,"phoneExt":10,"email":31},"CONTACT","83-18725891425","xvyingjiecq@qq.com",{"type":33,"investigatorFullName":34,"investigatorTitle":35,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"SPONSOR_INVESTIGATOR","Mingzhao Xiao","Urology Department","100522862",false,"NCT06088134","Contrast-enhanced CT-based Deep Learning Model for Preoperative Prediction of Disease-free Survival (DFS) in Localized Clear Cell Renal Cell Carcinoma (ccRCC)","Urology Department of the First Affiliated Hospital of Chongqing Medical University","Inclusion Criteria:\n\n* underwent partial\u002Fradical nephrectomies\n* histologically diagnosed as ccRCC\n* with complete clinical data and preoperative CT image data\n\nExclusion Criteria:\n\n* with incomplete clinic-pathological data\n* lack of preoperative contrast-enhanced CT images or the image quality was unsuitable for analysis\n* who received pre-surgery neoadjuvant or adjuvant therapies\n* with multiple renal tumors or\u002Fand had synchronous metastasis","ALL",{"count":44,"type":45},800,"ESTIMATED","OBSERVATIONAL","This study aims to preoperatively predict DFS of patients with localised ccRCC using a deep learning prognostic model based on enhanced contrast CT images, validate it's predictive ability in multicentre data and compare it's predictive ability with traditional models.",[49,50,51],"Clear Cell Renal Cell Carcinoma","Prognostic Cancer Model","Recurrent Renal Cell Cancer","2025-05-27",{"date":54,"type":55},"2025-05-31","ACTUAL",{"date":57,"type":55},"2022-09-01",{"date":59,"type":45},"2025-08-01",{"name":34,"class":6},1]