[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100603454":3},{"organization":4,"armGroups":7,"interventions":19,"overallOfficials":24,"centralContacts":29,"locations":38,"responsibleParty":54,"collaborators":18,"id":56,"slug":57,"hasResults":58,"nctId":59,"briefTitle":60,"officialTitle":61,"acronym":62,"eligibilityCriteria":63,"healthyVolunteers":58,"sex":64,"minAge":65,"maxAge":18,"enrollmentInfo":66,"targetDuration":18,"studyType":69,"phases":70,"briefSummary":72,"conditions":73,"keywords":75,"overallStatus":79,"whyStopped":18,"lastUpdateSubmitDate":80,"lastUpdatePostDateStruct":81,"startDateStruct":84,"completionDateStruct":86,"leadSponsor":88,"locationsCount":89},{"fullName":5,"class":6},"The First Affiliated Hospital of Xinxiang Medical College","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"AI management unit","EXPERIMENTAL","For patients with comorbid pulmonary malignancies who have been included, the registration process is guided by the management platform. Researchers will use digital management throughout The platform carries out screening assessment and Comprehensive Evaluation of nutrition, exercise, psychology and symptoms of the subjects, and the system will be combined with the patient's disease and treatment Information, intelligent management of the whole project. The clinician can review the protocol in the light of the patient's disease status and give the full management instructions Case to patient side.",[13],"Other: AI-assisted comprehensive management system",{"label":15,"type":16,"description":17,"interventionNames":18},"Standard Clinical Management","NO_INTERVENTION","Patients who are not willing to accept the whole program will only be followed up, and will receive standard clinical management without AI-assisted digital platform support. Patients will receive conventional treatment. In the data analysis phase, subjects were stratified to explore the feasibility and effectiveness of digital whole-course management in patients with oncological comorbidities.",null,[20],{"type":6,"name":21,"description":22,"armGroupLabels":23,"otherNames":18},"AI-assisted comprehensive management system","Precision Risk Stratification and personalized treatment recommendation through AI models may improve the suitability of treatment regimens and thus reduce the incidence of antineoplastic therapy-related adverse effects (e.g. , reduction of chemotherapy toxicity through nutritional intervention) , and improve the efficacy of chemotherapy, and prolonged progression-free survival (PFS) and overall survival (OS)",[9],[25],{"name":26,"affiliation":27,"role":28},"Wei Shen Wei Shen, MD, Doctor of Medicine","First Affiliated Hospital of Xinjiang Medical University","STUDY_CHAIR",[30,34],{"name":26,"role":31,"phone":32,"phoneExt":18,"email":33},"CONTACT","+86 15638800873","swccvsw@126.com",{"name":35,"role":31,"phone":36,"phoneExt":18,"email":37},"Ping Lu Ping Lu, MD, Doctor of Medicine","+86 13598722864","lupingdoctor@126.com",[39],{"facility":40,"status":18,"city":41,"state":42,"zip":43,"country":44,"countryCode":45,"cosmosGeoPoint":46,"geoPoint":51,"contacts":52},"The First Affiliated Hospital of Xinxiang Medical University","Xinxiang","Henan","453000","China","CN",{"type":47,"coordinates":48},"Point",[49,50],113.80151,35.19033,{"lat":50,"lon":49},[53],{"name":35,"role":31,"phone":36,"phoneExt":18,"email":37},{"type":55,"investigatorFullName":18,"investigatorTitle":18,"investigatorAffiliation":18,"oldNameTitle":18,"oldOrganization":18},"SPONSOR","100603454","ai-assisted-comprehensive-management-for-cancer-patients-with-comorbidities-gcog-cg001-100603454",false,"NCT07136727","AI-Assisted Comprehensive Management for Cancer Patients With Comorbidities (GCOG-CG001)","The Impact of Multimodal Digital Fusion AI-Assisted Decision Support System-Based Comprehensive Management on Clinical Outcomes in County-Level Patients With Comorbid Cancer:A Prospective Non-randomized Controlled Interventional Study.","GCOG-CG001","Inclusion Criteria:\n\n* Patients with a definite diagnosis of malignancy by histopathology and\u002For cytology;\n* Age ≥18 years;\n* There is no gender limit\n* Plan to receive antineoplastic therapy within 2 weeks or are receiving standard antineoplastic care (surgery, radiation, chemotherapy, or targeted therapy) ;\n* Conscious and able to answer questions and use electronic devices autonomously;\n* Patients were able to understand the study and voluntarily sign an informed consent form;\n\nExclusion Criteria:\n\n* Having severe mental or cognitive impairments that prevent them from understanding the content of the study or implementing the programme;\n* With severe heart disease, acute respiratory failure, liver kidney failure and other critical illness;\n* Women during pregnancy or lactation；\n* Have participated in other interventional studies in the past 1 month or are currently participating;\n* Patients with ECOG ≥ 3 that do not respond to treatment;\n* Patients with an expected survival of \\\u003C 3 months that do not respond to treatment;\n* Cases deemed unsuitable for enrollment by the investigator.","ALL","18 Years",{"count":67,"type":68},5000,"ESTIMATED","INTERVENTIONAL",[71],"NA","Combined with the digital whole process management data pool, a multi-modal data fusion framework is developed, and an AI model is established to realize risk stratification and personalized treatment Recommendation and dynamic prognosis prediction; validation of whole-process management based on multimodal digital fusion AI-aided decision support system through prospective non-randomized controlled interventional study The effect on survival, complication control and utilization of medical resources in patients with comorbid malignant tumors.",[74],"Oncological Comorbidities (e. g. Hypertension, Diabetes, Malnutrition)",[76,77,78],"Malignant neoplasm","Comorbidity","Artificial intelligence","NOT_YET_RECRUITING","2025-08-20",{"date":82,"type":83},"2025-08-22","ACTUAL",{"date":85,"type":68},"2025-08-15",{"date":87,"type":68},"2031-05-01",{"name":5,"class":6},1]