[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100621850":3},{"organization":4,"outcomesModule":7,"designInfo":21,"detailedDescription":24,"studyPopulation":25,"armGroups":26,"interventions":20,"overallOfficials":20,"centralContacts":20,"locations":36,"responsibleParty":142,"collaborators":146,"id":154,"slug":20,"hasResults":155,"nctId":156,"briefTitle":157,"officialTitle":157,"acronym":20,"eligibilityCriteria":158,"healthyVolunteers":159,"sex":160,"minAge":161,"maxAge":162,"enrollmentInfo":163,"targetDuration":20,"studyType":166,"phases":20,"briefSummary":167,"conditions":168,"keywords":170,"overallStatus":174,"whyStopped":20,"lastUpdateSubmitDate":175,"lastUpdatePostDateStruct":176,"startDateStruct":179,"completionDateStruct":181,"leadSponsor":183,"locationsCount":184},{"fullName":5,"class":6},"Shanghai Pulmonary Hospital, Shanghai, China","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":13,"otherOutcomes":20},[9],{"measure":10,"description":11,"timeFrame":12},"The performance of mult-modal in lung cancer early detection","The sensitivity, specificity and AUC for lung cancer early detection in detecting cancer or non-cancer at 95% confidence interval","12 months",[14,17],{"measure":15,"description":16,"timeFrame":12},"The performance of multi-modal across subgroup analysis","Sensitivity and 95% confidence intervals of multimodal approach (imaging combined with blood-based methylation testing) across different stages, pathological subtypes, gender, age, and risk factor subgroups.",{"measure":18,"description":19,"timeFrame":12},"Comparing the performance of three different modals.","Comparison of sensitivity, specificity, and 95% confidence intervals among imaging modality, blood-based methylation testing modality, and multimodal approach (imaging combined with blood-based methylation testing) in lung cancer early screening.",null,{"allocation":20,"interventionModel":20,"interventionModelDescription":20,"primaryPurpose":20,"observationalModel":22,"timePerspective":23,"maskingInfo":20},"CASE_CONTROL","RETROSPECTIVE","This study aims to develop three modality -based models for lung cancer early screening, incuding a CT-based imaging model, a blood-based cfDNA methylation model, and a multimodal framework. First, 10,700 retrospective non-contrast CT scans will be collected to construct the CT imaging-based model. This model will extract multi- scale structural features through a hierarchical modeling framework, enabling the learning of interpretable spatial representations. Second, cfDNA methylation data from lung cancer patients and healthy individuals enrolled in the ProFound study (NCT06217900) wll be used to develop the blood-based model. Third, subjects with paired CT imaging and cfDNA methylation data from the ProFound study will be included to construct a multimodal model by integrating information across modalities. The performance of models based on different modalities will be systematically compared to evaluate their respective and complementary contributions to lung cancer early screening.","lung cancers or healthy individuals who can provide imaging data meeting the inclusion and exclusion criteria",[27,30,33],{"label":28,"type":20,"description":29,"interventionNames":20},"CT cohort","Lung cancer patients or healthy individuals who can provide CT scan",{"label":31,"type":20,"description":32,"interventionNames":20},"Blood-based cohort","Blood based cfDNA methylation information retrieved from Profound study",{"label":34,"type":20,"description":35,"interventionNames":20},"Multi-modal cohort","Retrospective collect paired CT and blood based cfDNA methylation information from Profound study",[37,56,71,86,101,116,127],{"facility":38,"status":20,"city":39,"state":40,"zip":41,"country":42,"countryCode":43,"cosmosGeoPoint":44,"geoPoint":49,"contacts":50},"Shijiazhuang People's Hospital","Shijiazhuang","Hebei","050026","China","CN",{"type":45,"coordinates":46},"Point",[47,48],114.47861,38.04139,{"lat":48,"lon":47},[51],{"name":52,"role":53,"phone":54,"phoneExt":20,"email":55},"Tianlong Huo","CONTACT","86-18600682228","huotianlong@bjmu.edu.cn",{"facility":57,"status":20,"city":58,"state":59,"zip":60,"country":42,"countryCode":43,"cosmosGeoPoint":61,"geoPoint":65,"contacts":66},"The First Affiliated Hospital of Zhengzhou University","Zhengzhou","Henan","450052",{"type":45,"coordinates":62},[63,64],113.64861,34.75778,{"lat":64,"lon":63},[67],{"name":68,"role":53,"phone":69,"phoneExt":20,"email":70},"Xiangnan Li, PhD","86+13592502553","lxn-2000@163.com",{"facility":72,"status":20,"city":73,"state":74,"zip":75,"country":42,"countryCode":43,"cosmosGeoPoint":76,"geoPoint":80,"contacts":81},"The First Hospital of Ji Lin University","Changchun","Jilin","130021",{"type":45,"coordinates":77},[78,79],125.32278,43.88,{"lat":79,"lon":78},[82],{"name":83,"role":53,"phone":84,"phoneExt":20,"email":85},"Dan Tong","86-15843073226","tongdan@jlu.edu.cn",{"facility":87,"status":20,"city":88,"state":89,"zip":90,"country":42,"countryCode":43,"cosmosGeoPoint":91,"geoPoint":95,"contacts":96},"Liaoning Cancer Hospital & Institute","Shenyang","Liaoning","110801",{"type":45,"coordinates":92},[93,94],123.43278,41.79222,{"lat":94,"lon":93},[97],{"name":98,"role":53,"phone":99,"phoneExt":20,"email":100},"Hongxu Liu, PhD","86-18040097698","hongxuliu@qq.com",{"facility":102,"status":20,"city":103,"state":104,"zip":105,"country":42,"countryCode":43,"cosmosGeoPoint":106,"geoPoint":110,"contacts":111},"Shanghai Pulmonary Hospital","Shanghai","Shanghai Municipality","200000",{"type":45,"coordinates":107},[108,109],121.45806,31.22222,{"lat":109,"lon":108},[112],{"name":113,"role":53,"phone":114,"phoneExt":20,"email":115},"Chang Chen, MD,PhD","86+13816869003","chenthoracic@163.com",{"facility":117,"status":20,"city":103,"state":104,"zip":118,"country":42,"countryCode":43,"cosmosGeoPoint":119,"geoPoint":121,"contacts":122},"Shanghai Chest Hospital","200030",{"type":45,"coordinates":120},[108,109],{"lat":109,"lon":108},[123],{"name":124,"role":53,"phone":125,"phoneExt":20,"email":126},"Zhigang Li, PhD","86-18930619260","zhigang.li@shchest.org",{"facility":128,"status":20,"city":129,"state":130,"zip":131,"country":42,"countryCode":43,"cosmosGeoPoint":132,"geoPoint":136,"contacts":137},"Yunnan Cancer Hospital","Kunming","Yunnan","650100",{"type":45,"coordinates":133},[134,135],102.71833,25.03889,{"lat":135,"lon":134},[138],{"name":139,"role":53,"phone":140,"phoneExt":20,"email":141},"Xudong Xiang, M.D.","86-13108519813","xxd9813@163.com",{"type":143,"investigatorFullName":144,"investigatorTitle":145,"investigatorAffiliation":5,"oldNameTitle":20,"oldOrganization":20},"PRINCIPAL_INVESTIGATOR","Chang Chen","Chief Physician",[147,148,149,150,151,152],{"name":117,"class":6},{"name":87,"class":6},{"name":57,"class":6},{"name":128,"class":6},{"name":38,"class":6},{"name":153,"class":6},"The First Hospital of Jilin University","100621850",false,"NCT07375979","A Multi-modal Integrating Imaging and Cell-free DNA Methylation in Lung Cancer Early Detection (CMe-Lung): a Multi-center, Observational Study","Inclusion Criteria:\n\n* 40-74 years old\n* Clinically and\u002For pathologically diagnosed cancer\n* No prior or undergoing any systemic or local antitumor therapy, including but not limited to surgical resection, radiochemotherapy, endocrinotherapy, targeted therapy, immunotherapy, interventional therapy, etc.\n* Able to provide a written informed consent and willing to comply with all part of the protocol procedures\n\nExclusion Criteria:\n\n* Pregnancy or lactating women\n* Known prior or current diagnosis of other types of malignancies comorbidities\n* Severe acute infection (e.g. severe or critical COVID-19, sepsis, etc.) or febrile illness (body temperature of ≥ 38.5 °C) within 14 days prior to screen\n* Recipients of organ transplant or prior bone marrow transplant or stem cell transplant\n* Recipients of blood transfusion within 30 days prior to screen\n* Recipients of therapy in past 14 days prior to screen, including oral or IV antibiotics, glucocorticoid, azacitidine, decitabine, procainamide, hydrazine, arsenic trioxide\n* Unsuitable for this trial determined by the researchers\n* Low-quality samples: images only partially showing the lungs or in lateral decubitus position, unreadable due to severe motion artifacts\u002Fmetal artifacts, or with missing critical metadata\n\nInclusion Criteria for Control Arm Participants:\n\n* 40-74 years old\n* Without confirmed cancer diagnosis\n* Able to provide a written informed consent and willing to comply with all part of the protocol procedures\n\nExclusion Criteria for Control Arm Participants:\n\n* Pregnancy or lactating women\n* Known prior or current diagnosis of other types of malignancies comorbidities\n* Severe acute infection (e.g. severe or critical COVID-19, sepsis, etc.) or febrile illness (body temperature of ≥ 38.5 °C) within 14 days prior to screen\n* Recipients of organ transplant or prior bone marrow transplant or stem cell transplant\n* Recipients of blood transfusion within 30 days prior to screen\n* Recipients of therapy in the past 14 days prior to screen, including oral or IV antibiotics, glucocorticoid, azacitidine, decitabine, procainamide, hydrazine, arsenic trioxide\n* Unsuitable for this trial determined by the researchers\n* Low-quality samples: images only partially showing the lungs or in lateral decubitus position, unreadable due to severe motion artifacts\u002Fmetal artifacts, or with missing critical metadata",true,"ALL","40 Years","74 Years",{"count":164,"type":165},14300,"ESTIMATED","OBSERVATIONAL","This study is a multi-center, observational study aiming to develop an early screening multi-model for detecting lung cancer signals through the integration of imaging (non-contrast CT) and blood testing (cfDNA methylation).",[169],"Lung Cancer",[171,172,173],"multi-modal","CT and cfDNA methylation","lung cancer early detection","NOT_YET_RECRUITING","2026-01-21",{"date":177,"type":178},"2026-01-29","ACTUAL",{"date":180,"type":165},"2026-02-05",{"date":182,"type":165},"2026-09-01",{"name":5,"class":6},7]