[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100564207":3},{"organization":4,"outcomesModule":7,"designInfo":18,"detailedDescription":26,"studyPopulation":17,"armGroups":27,"interventions":53,"overallOfficials":17,"centralContacts":88,"locations":95,"responsibleParty":113,"collaborators":17,"id":116,"slug":17,"hasResults":117,"nctId":118,"briefTitle":119,"officialTitle":120,"acronym":121,"eligibilityCriteria":122,"healthyVolunteers":123,"sex":124,"minAge":125,"maxAge":17,"enrollmentInfo":126,"targetDuration":17,"studyType":129,"phases":130,"briefSummary":132,"conditions":133,"keywords":136,"overallStatus":98,"whyStopped":17,"lastUpdateSubmitDate":141,"lastUpdatePostDateStruct":142,"startDateStruct":145,"completionDateStruct":146,"leadSponsor":148,"locationsCount":149},{"fullName":5,"class":6},"Scientific Institute San Raffaele","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":13,"otherOutcomes":17},[9],{"measure":10,"description":11,"timeFrame":12},"Creation of Artificial Intelligence (AI) algorithm","To train and validate a reliable and unbiased Artificial Intelligence (AI) algorithm that detects the presence of nodules and differentiates between malignant or benign tumor types.\n\nAUC (Area Under the Curve) values, expressed as mean and standard deviation (SD), comparing the ability in detecting the presence of nodules and differentiating the malignancy or benignity of a radiologist versus an AI algorithm, both trained on the same patient group.","from enrollment to 48 months",[14],{"measure":15,"description":16,"timeFrame":12},"Multimodal program","Develop a multimodal program to enhance the prevention and the early detection of multiple smoking-related diseases Presence and absence of lung nodules \\> 4 mm with computed tomography (CT) scan",null,{"allocation":19,"interventionModel":20,"interventionModelDescription":21,"primaryPurpose":22,"observationalModel":17,"timePerspective":17,"maskingInfo":23},"NON_RANDOMIZED","PARALLEL","In the study are considered 4 different cohorts. Lung cancer patients diagnosed outside screening and treated at San Raffaele Hospital; smokers and former smokers aged over 50 years old at high risk for lung cancer, cardiovascular diseases and chronic obstructive pulmonary disease (COPD); subjects enrolled in previous screening cohorts in this Institute, which presented a computed tomography (CT) with the presence of lung nodules \\>4 mm and to conclude, subjects enrolled in previous screening cohorts in this Institute, which presented a negative computed tomography (CT).","SCREENING",{"masking":24,"maskingDescription":25,"whoMasked":17},"NONE","No blinding in this study","Interventional pilot study, single-center with additional procedures, such as completion of EORTC-QLQ-LC29, EORTC-QLQ-C30 questionnaires, motivational test, Fagestrom test, anamnestic questionnaire, spirometry, measurement of carbon monoxide, Low-dose spiral computed tomography without contrast medium, peripheral venous blood sampling for a volume of 20 ml.\n\nThe study has the main objective of traininig and validate a reliable and unbiased Artificial Intelligence (AI) algorithm that detects the presence of nodules and differentiates between malignant or benign tumor types.\n\nThe study considers patients with suspected diagnosis or with a dignosis of lung cancer, smokers and former smokers over 50 years of age at high risk of lung cancer and subjects enrolled in previous screening cohorts at this Institute.",[28,40,44,48],{"label":29,"type":30,"description":31,"interventionNames":32},"High-risk screening subjects","EXPERIMENTAL","Ever and former male and female smokers aged over 50 years old at high risk for lung cancer, cardiovascular diseases and chronic obstructive pulmonary disease (COPD).\n\nAdditional procedures for this group:\n\n* Spirometry\n* Nurse evaluation\n* Epidemiological questionnaire, Quality of Life (QoL) questionnaires\n* Smoking cessation program\n* Cardiovascular primary prevention\n* measurement of carbon monoxide (CO)\n* Blood storage\n* Computed tomography (CT) scan low-dose",[33,34,35,36,37,38,39],"Diagnostic Test: Computed tomography (CT) scan low dose","Procedure: Blood sampling","Other: Spirometry","Other: Questionnaires","Other: Smoking cessation program","Other: Carbon monoxide measurment","Other: Cardiovascular primary prevention",{"label":41,"type":30,"description":42,"interventionNames":43},"Previous positive high-risk screening subjects","Subjects enrolled in previous screening cohorts in this Institute with the presence of lung nodules \\>4 mm. Additional procedure for this group: Computed tomography (CT) scan low-dose",[33,37],{"label":45,"type":46,"description":47,"interventionNames":17},"Previous negative high-risk screening subjects","NO_INTERVENTION","Subjects enrolled in previous screening cohorts in this Institute with negative computed tomography (CT) scan. No additional procedures for this group.",{"label":49,"type":30,"description":50,"interventionNames":51},"Lung cancer patients","Lung cancer patients diagnosed outside screening and treated at San Raffaele Hospital. Additional procedures for this group: biobank tissue and blood storage.",[34,52],"Procedure: Tissue sampling (lung)",[54,59,64,68,72,76,80,84],{"type":55,"name":56,"description":57,"armGroupLabels":58,"otherNames":17},"DIAGNOSTIC_TEST","Computed tomography (CT) scan low dose","The radiological investigation will be done with multi-detector-row (64 or more) computed tomography (CT) scanners at low-dose protocol. The low-dose spiral CT consists of a CT study of the chest, without the need for injection of contrast medium, characterized by less radio exposure than the standard CT of the chest with high sensitivity in detecting pulmonary nodules.",[29,41],{"type":60,"name":61,"description":62,"armGroupLabels":63,"otherNames":17},"PROCEDURE","Blood sampling","Peripheral venous blood sampling (20 ml)",[29,49],{"type":60,"name":65,"description":66,"armGroupLabels":67,"otherNames":17},"Tissue sampling (lung)","sampling of tumor and healthy tissue during surgery",[49],{"type":6,"name":69,"description":70,"armGroupLabels":71,"otherNames":17},"Spirometry","Spirometry measurement using spirometer",[29],{"type":6,"name":73,"description":74,"armGroupLabels":75,"otherNames":17},"Questionnaires","Compilation of epidemiological questionnaire, quality of life questionnaires",[29],{"type":6,"name":77,"description":78,"armGroupLabels":79,"otherNames":17},"Smoking cessation program","Study guarantee valid support for quitting smoking, which for a smoker is a more effective intervention to reduce the risk of developing lung cancer, myocardial infarction and other smoking-related diseases",[29,41],{"type":6,"name":81,"description":82,"armGroupLabels":83,"otherNames":17},"Carbon monoxide measurment","Measurment of Carbon monoxide (CO)",[29],{"type":6,"name":85,"description":86,"armGroupLabels":87,"otherNames":17},"Cardiovascular primary prevention","Intervention done in order to find the presence of coronary calcifications",[29],[89],{"name":90,"role":91,"phone":92,"phoneExt":93,"email":94},"Piergiorgio Muriana, MD","CONTACT","0226437232","+39","muriana.piergiorgio@hsr.it",[96],{"facility":97,"status":98,"city":99,"state":17,"zip":100,"country":101,"countryCode":102,"cosmosGeoPoint":103,"geoPoint":108,"contacts":109},"Scientific Institute Ospedale San Raffaele","RECRUITING","Milan","20132","Italy","IT",{"type":104,"coordinates":105},"Point",[106,107],9.18951,45.46427,{"lat":107,"lon":106},[110,111],{"name":90,"role":91,"phone":92,"phoneExt":93,"email":94},{"name":90,"role":112,"phone":17,"phoneExt":17,"email":17},"PRINCIPAL_INVESTIGATOR",{"type":112,"investigatorFullName":114,"investigatorTitle":115,"investigatorAffiliation":5,"oldNameTitle":17,"oldOrganization":17},"Muriana Piergiorgio","Medical Doctor","100564207",false,"NCT06626178","Development of an Artificial Intelligence Model for the Identification and Prevention of Smoking-related Diseases.","ARtificial Intelligence for heAlth and Prevention of Smoking-related Diseases","ARIA","High-risk screening subjects\n\nInclusion Criteria:\n\n* Age \\>= 50 years old\n* Active smokers\n* Former smokers (from no more than 15 years)\n* Pack\u002Fyear \\>20\n* Risk-prediction model from Prostate, Lung, Colorectal, and Ovarian study (PLCOm2012) \\>1.2%\n* Provision and signature of informed consent\n\nExclusion Criteria:\n\n* Previous or concurrent neoplastic disease, excluding skin cancers\n* Cognitive or other problems that could hinder the collection of informed consent\n* Severe pulmonary or extra pulmonary disease\n* Previous low-dose computed tomography (CT) scan in the past 12 months\n\nPrevious high-risk positive screening subjects\n\nInclusion Criteria:\n\n* Subjects enrolled in previous lung cancer screening with the presence of lung nodules \\>4 mm and candidate to additional computed tomography (CT)\n* Signed informed consent\n\nExclusion Criteria:\n\n\\- None\n\nPrevious high-risk negative screening subjects\n\nInclusion Criteria:\n\n* Subjects enrolled in previous lung cancer screening in this Institute with negative computed tomography (CT)\n* Signed informed consent\n\nExclusion Criteria:\n\n\\- None\n\nLung Cancer patients\n\nInclusion Criteria:\n\n* Patients with diagnosis or suspicious diagnosis of lung cancer candidate to surgical treatment or already submitted to it\n* Patients with diagnosis of lung cancer treated with surgical resection\n* Signed informed consent\n\nExclusion Criteria:\n\n* computed tomography (CT) scans not available at San Raffaele Hospital\n* Previous neoadjuvant treatment",true,"ALL","18 Years",{"count":127,"type":128},2840,"ESTIMATED","INTERVENTIONAL",[131],"NA","The study is an interventional pilot study. The study is designed to be monocentric and it presents additional procedues.",[134,135],"Lung Cancer Screening Program","Artificial Intelligence (AI)",[137,138,139,140],"CT scan low-dose","Artificial Intelligence","High-risk sucjects","Lung cancer","2024-10-01",{"date":143,"type":144},"2024-10-03","ACTUAL",{"date":141,"type":144},{"date":147,"type":128},"2028-11-01",{"name":5,"class":6},1]