[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100480587":3},{"organization":4,"armGroups":7,"interventions":10,"overallOfficials":10,"centralContacts":15,"locations":21,"responsibleParty":78,"collaborators":82,"id":92,"slug":93,"hasResults":94,"nctId":95,"briefTitle":96,"officialTitle":96,"acronym":10,"eligibilityCriteria":97,"healthyVolunteers":94,"sex":98,"minAge":99,"maxAge":10,"enrollmentInfo":100,"targetDuration":10,"studyType":103,"phases":10,"briefSummary":104,"conditions":105,"keywords":110,"overallStatus":24,"whyStopped":10,"lastUpdateSubmitDate":114,"lastUpdatePostDateStruct":115,"startDateStruct":118,"completionDateStruct":120,"leadSponsor":122,"locationsCount":123},{"fullName":5,"class":6},"Fondazione IRCCS Istituto Nazionale dei Tumori, Milano","OTHER",[8,12],{"label":9,"type":10,"description":11,"interventionNames":10},"Retrospective Cohort",null,"This cohort includes the analysis of a multicentric retrospective cohort of more than 2,000 patients. This cohort will be used to perform a preliminary knowledge extraction phase and to build a retrospective predictive model for IO (R-Model). All available clinical data will be collected. Also, CT and PET scans will be collected and a first radiomic signature.",{"label":13,"type":10,"description":14,"interventionNames":10},"Prospective Cohort","The prospective part of the project includes the collection and the analysis of multi-OMICs data from a multicentric prospective cohort of about 200 patients.",[16],{"name":17,"role":18,"phone":19,"phoneExt":10,"email":20},"Arsela Prelaj, MD","CONTACT","+39 022390 3647","arsela.prelaj@istitutotumori.mi.it",[22,39,52,65],{"facility":23,"status":24,"city":25,"state":26,"zip":27,"country":28,"countryCode":29,"cosmosGeoPoint":30,"geoPoint":35,"contacts":36},"University of Chicago","RECRUITING","Chicago","Illinois","60637","United States","US",{"type":31,"coordinates":32},"Point",[33,34],-87.65005,41.85003,{"lat":34,"lon":33},[37],{"name":38,"role":18,"phone":10,"phoneExt":10,"email":10},"Marina Garassino",{"facility":40,"status":24,"city":41,"state":10,"zip":10,"country":42,"countryCode":43,"cosmosGeoPoint":44,"geoPoint":48,"contacts":49},"Metropolitan Hospital","Athens","Greece","GR",{"type":31,"coordinates":45},[46,47],23.72784,37.98376,{"lat":47,"lon":46},[50],{"name":51,"role":18,"phone":10,"phoneExt":10,"email":10},"Elena Linardou",{"facility":53,"status":24,"city":54,"state":10,"zip":10,"country":55,"countryCode":56,"cosmosGeoPoint":57,"geoPoint":61,"contacts":62},"Shaare Zedek Medical Center","Jerusalem","Israel","IL",{"type":31,"coordinates":58},[59,60],35.21633,31.76904,{"lat":60,"lon":59},[63],{"name":64,"role":18,"phone":10,"phoneExt":10,"email":10},"Nir Peled",{"facility":66,"status":24,"city":67,"state":10,"zip":10,"country":68,"countryCode":69,"cosmosGeoPoint":70,"geoPoint":74,"contacts":75},"Vall D'Hebron Institute of Oncology","Barcelona","Spain","ES",{"type":31,"coordinates":71},[72,73],2.15899,41.38879,{"lat":73,"lon":72},[76],{"name":77,"role":18,"phone":10,"phoneExt":10,"email":10},"Enriqueta Felip",{"type":79,"investigatorFullName":80,"investigatorTitle":81,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"PRINCIPAL_INVESTIGATOR","Arsela Prelaj","Principal Investigator",[83,85,86,88,91],{"name":84,"class":6},"Vall d'Hebron Institute of Oncology",{"name":53,"class":6},{"name":87,"class":6},"LungenClinic Grosshansdorf",{"name":89,"class":90},"Metropolitan Hospital, Athens","UNKNOWN",{"name":23,"class":6},"100480587","i3lung-integrative-science-intelligent-data-platform-for-individualized-lung-cancer-care-with-immunotherapy-100480587",false,"NCT05537922","I3LUNG: Integrative Science, Intelligent Data Platform for Individualized LUNG Cancer Care With Immunotherapy","Inclusion Criteria:\n\n* Age \\>\u002F= 18 years.\n* Eastern Cooperative Oncology Group (ECOG) performance status \\\u003C\u002F= 2.\n* Histologically confirmed diagnosis of stage IIIB\u002FC-IV Non-Small-Cell Lung Cancer\n* Received any line immunotherapy (maintenance therapy with Durvalumab is allowed) for retrospective cohort; clinical indication for frontline treatment with immunotherapy as first line treatment for prospective cohort.\n* Patients with CNS metastasis are allowed\n* Patients with driver genomic alterations are allowed (only for retrospective cohort)\n* Evidence of a personally signed and dated ICF indicating that the patient has been informed of and understands all pertinent aspects of the study before enrolment (only for prospective cohort)\n* Availability of at least one FFPE block for -omics data generation (only for prospective cohort)\n\nExclusion Criteria:\n\n* Patients without minimal treatment information data to be included in the retrospective cohort\n* Prior treatment for advanced disease (only for prospective cohort)\n* Unavailability or inability to comply with the requested study procedures, including compilation of QoL questionnaires","ALL","18 Years",{"count":101,"type":102},2200,"ESTIMATED","OBSERVATIONAL","I3LUNG is an international project aiming to develop a medical device to predict immunotherapy efficacy for NSCLC patients using the integration of multisource data (real word and multi-omics data). This objective will be reached through a retrospective - setting up a transnational platform of available data from 2000 patients - and a prospective - multi-omics prospective data collection in 200 NSCLS patients - study phase.\n\nThe retrospective cohort will be used to perform a preliminary knowledge extraction phase and to build a retrospective predictive model for IO (R-Model), that will be used in the prospective study phase to create a first version of the PDSS tool, an AI-based tool to provide an easy and ready-to-use access to predictive models, increasing care appropriateness, reducing the negative impacts of prolonged and toxic treatments on wellbeing and healthcare costs.\n\nThe prospective part of the project includes the collection and the analysis of multi-OMICs data from a multicentric prospective cohort of about 200 patients. This cohort will be used to validate the results obtained from the retrospective model through the creation of a new model (P-Model), which will be used to create the final PDSS tool.",[106,107,108,109],"Non Small Cell Lung Cancer","Lung Cancer Metastatic","Lung Cancer, Nonsmall Cell","Lung Adenocarcinoma",[111,112,113],"NSCLC","Artificial Intelligence","Immunotherapy","2023-01-05",{"date":116,"type":117},"2023-01-06","ACTUAL",{"date":119,"type":117},"2022-10-01",{"date":121,"type":102},"2027-10-01",{"name":5,"class":6},4]